This paper aims to present a smart high speed battery charger, powered by a photovoltaic module array, for a LiFePO4 battery as a solar energy storage device. With a battery charging strategy, the presented battery charger involves a Buck converter as the core equipped with a simple maximum power point (MPP) tracker. Considering complexity reduction and easy hardware implementation, a constant voltage MPP tracking approach is adopted such that the maximum amount of output power can be delivered to the load in response to an arbitrary change in the solar radiation. A smart two-stage charging strategy, with a constant current mode followed by a constant voltage mode, is employed in such a way that the battery charge process can be accelerated largely, while the damage caused by overcharging can be prevented. In the end, the performance of this proposal is validated experimentally.

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for AA7050-T7451 by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of cutting variables such as, feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error, material removal rate and power consumption the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is proved that the most significant factor is cutting speed, followed by feed rate, radial depth of cut. Finally, confirmation tests were performed to make a comparison between the experimental results. Experimental results have shown that machining performance in precision turn-boring process can be improved effectively through this approach

The rapid industrial growth in solar energy is gaining increasing interest in renewable power from smart grids and plants. Anomaly detection in photovoltaic (PV) systems is a demanding task. In this sense, it is vital to utilize recent advances in machine learning to accurately and timely detect different anomalies and condition monitoring. This paper addresses this issue by evaluating different machine learning techniques and schemes and showing how to apply these approaches to solve anomaly detection and detect faults on photovoltaic components. For this, we apply distinct state-of-the-art machine learning techniques (AutoEncoder Long Short-Term Memory (AE-LSTM), Facebook-Prophet, and Isolation Forest) to detect faults/anomalies and evaluate their performance. These models shall identify the PV system's healthy and abnormal actual behaviors. Our results provide clear insights to make an informed decision, especially with experimental trade-offs for such complex solution space.

In this paper, a recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of soft open points (SOPs) and renewable distributed generators allocation along with new network reconfiguration methodology under different loading conditions to minimize the total power loss in balanced distribution systems. Multi-scenario studies, which aim to improve the investigation of the overall performance of the strategies, are conducted on IEEE 33-node and 83-node balanced distribution systems. The contributions of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to the system, are investigated to determine the real benefits gained from their allocation. The results obtained validate, with proper justifications, the effectiveness of allocating both SOPs and renewable distributed generators with the proposed network reconfiguration methodology to provide the best operation of distribution networks with minimum losses and enhanced power quality performance. It was also shown that SOPs successfully assist the growing integration plans of the renewable distributed generators units and can address issues related to voltage violations and network losses efficiently.

The matrix converter converts the input line voltage into a variable voltage with an unrestricted output frequency without using an intermediate circuit, dc link circuit. A pure sine in and pure sine out is the unique feature of the matrix converter. This research paper also analyzes the basic operating principle and the simulation modeling of the direct matrix converter, which is controlled by the Space Vector Pulse Width Modulation technique by using the software which is known as MATLAB/Simulink. The most desirable features in the power frequency changes can be fulfilled by using the matrix converters, and this is the reason for the tremendous interest in the topology. Since the power electronic circuits which is known as the motor drives are used to operate the AC motors at the frequencies other than that of the supply.

Due to its spatio-temporal variability, the mismatch between the weather and demand patterns challenges the design of highly renewable energy systems. A principal component analysis is applied to a simplified networked European electricity system with a high share of wind and solar power generation. It reveals a small number of important mismatch patterns, which explain most of the system's required backup and transmission infrastructure. Whereas the first principal component is already able to reproduce most of the temporal mismatch variability for a solar dominated system, a few more principal components are needed for a wind dominated system. Due to its monopole structure the first principal component causes most of the system's backup infrastructure. The next few principal components have a dipole structure and dominate the transmission infrastructure of the renewable electricity network.

Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA), including expert system (EPS), artificial neural network (ANN), fuzzy theory, rough sets theory (RST), grey system theory (GST), swarm intelligence (SI) algorithms, data mining technology, machine learning (ML), and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as well as references and guidance for researchers to choose optimal approach to achieve DGA-based fault diagnosis and decision of the large oil-immersed power transformers in preventive electrical tests.

The contamination on the insulators may increase its surface conductivity and, as a consequence, electrical discharges occur more frequently, which can lead to interruptions in the power supply. To maintain reliability in the electrical distribution power system, components that have lost their insulating properties must be replaced. Identifying the components that need maintenance, is a difficult task as there are several levels of contamination that are hardly noticed during inspections. To improve the quality of inspections, this paper proposes to use the k-nearest neighbours (k-NN) to classify the levels of insulator contamination, based on the image of insulators at various levels of contamination simulated in the laboratory. Using computer vision features such as mean, variance, asymmetry, kurtosis, energy, and entropy are used for training the k-NN. To assess the robustness of the proposed approach, statistical analysis and a comparative assessment with well-consolidated algorithms such as decision tree, ensemble subspace, and support vector machine models are presented. The k-NN showed results of up to 85.17 % accuracy using the k-fold cross-validation method, with an average accuracy higher than 82 % for multi-classification of the contamination of the insulators, being superior to the compared models.

In this paper a microstrip Wilkinson power divider with a 90^° phase delay at one output port is proposed to obtain circular polarization to feed a dual port RFID antenna. The 90^° phase delay was obtained by embedding an extra quarter wavelength at one port of the Wilkinson power divider. The feeding circuit is then mounted on the ground plane of the microstrip antenna feeding the radiating patch directly through the ground plane and dielectric layer thus reducing any fringing effect and resulting a mechanically compact unit. The proposed feeding method offers better expectation of antenna performance with minimal attenuation and coupling losses. The design process generalizes geometric pa- rameters of the Wilkinson power divider for variable port distances. The paper considers both UK and US RFID center frequencies, 870 MHz and 915 MHz respectively. Numeri- cally computed values for geometric design parameters for both frequencies are tabled as future design tools for port distances varying from 18 mm up to 34 mm at 870 MHz and 17 mm up to 32 mm at 915 MHz. Simulation results indicate a return loss (S11) of -20 dB and -26 dB at 870 MHz and 915 MHz operational frequencies respectively at 270^° angled quarter wavelength.

The VLSI industry is facing parasitic effects that trouble development in the nanoscale domain. However, instead of replacing the traditional MOSFET design, it would be more advantageous to apply different doping profiles and discerning which deal with specific parasitic effects the best. With a review of Gaussian doping, Uniform doping, and Delta doping profiles and analysis of the FET technology characteristics that use these doping profiles, a comparison can be made among them for integrated circuit design engineers. These doping profiles are compared based on how well they perform against non-ideal and ideal environments. Also, both digital and analog performance are measured to ensure the uniqueness of each doping profile that is present. After getting a list of benefits from each doping profile, it is derived to determine which doping profile works best against a host of parasitic effects and what type of application do these doping profiles have

Power quality is a major concern in electrical power systems. The power quality disturbances such as sags, swells, harmonic distortion and other interruptions have impact on the electrical devices and machines and in severe cases can cause serious damages. Therefore it is required to recognize and compensate all types of disturbances at an earliest to ensure normal and efficient operation of the power system. To solve these problems, many types of power devices are used. At the present time, one of those devices, Dynamic Voltage Restorer (DVR) is the most efficient and effective device used in power distribution system. In this paper, design and modeling of a new structure of multifunctional DVR for voltage correction is presented. The performance of the device under different conditions such as voltage swell, voltage sag due to symmetrical and unsymmetrical short circuit, starting of motors, and voltage distortion are described. Simulation result shows the superior capability of proposed DVR to improve power quality under different operating conditions. The proposed new DVR controller is able to detect the voltage disturbances and control the converter to inject appropriate voltages independently for each phase and compensate to load voltage through three single- phase transformers.

Rural electrification rate (RER) in Africa is still low to date. Several countries in Sub-Saharan Africa have tried to address this problem using conventional single-phase two-wire or three-phase three-wire systems, however at large costs due to the nature of dispersed rural load centers, low load demand, and low population density. Another solution of off-grid generation creates associated health problems. Therefore, this paper undertakes a review of a single wire earth return (SWER) network as a RER improvement solution. The paper undertakes intensive literature review to elucidate challenges and solutions to the implementation of SWER technology. Advantages of SWER technology discussed make it the choice for RER improvement in Sub-Saharan African countries. After that, a case study is selected in rural Tanzania, and a preliminary SWER network design is undertaken.

Three-phase AC electric arc furnace (EAF) is a typical non-linear load, causing many power quality problems. Most of the researches on the voltage problems of EAF mainly focus on the voltage fluctuation, and less on the transient voltage problems caused by EAF short circuit and open circuit. In this paper, the relationship between voltage and current of EAF is obtained by combining hyperbolic function and exponential function, then the white noise and chaotic circuit are added to establish the EAF model which is suitable for the study of voltage fluctuation and transient voltage. This paper analyzes the causes of the transient voltage problem of the EAF, calculates the short-circuit current, reactive impact and the influence on voltage at the point of common coupling (PCC) in the three-phase short-circuit of the EAF, and compares the calculation results with the simulation results to prove the accuracy of this model. The results show that the reactive impact of three-phase short circuit is about twice as much as that of normal operation of EAF, resulting in about 30% voltage sag at the PCC, which is very unfavorable to the power grid. This paper provides reference for transient power quality evaluation and dynamic reactive power compensation of EAF.

Accurate forecasting of wind power generation plays a key role in improving the operation and management of a power system network and thereby its reliability and security. However, predicting wind power is complex due to the existence of high non-linearity in wind speed that eventually relies on prevailing weather conditions. In this paper, a novel hybrid deep learning model is proposed to improve the prediction accuracy of very short-term wind power generation for the Bodangora Wind Farm located in New South Wales, Australia. The hybrid model consists of convolutional layers, gated recurrent unit (GRU) layers and a fully connected neural network. The convolutional layers have the ability to automatically learn complex features from raw data while the GRU layers are capable of directly learning multiple parallel sequences of input data. The data sets of five-minute intervals from the wind farm are used in case studies to demonstrate the effectiveness of the proposed model against other advanced existing models, including long short-term memory (LSTM), GRU, autoregressive integrated moving average (ARIMA) and support vector machine (SVM), which are tuned to optimise outcome. It is observed that the hybrid deep learning model exhibits superior performance over other forecasting models to improve the accuracy of wind power forecasting, numerically, up to 1.59 per cent in mean absolute error, 3.73 per cent in root mean square error and 8.13 per cent in mean absolute percentage error.

In this paper, a new approach is proposed for designing ultra-low-power FFT (Fast Fourier Transform) system suitable for use in energy harvesting powered sensors. Bit-serial architecture is adopted to reduce the power consumption of butterfly operation. Simulation results show that, compared with state-of-the-art bit-serial and conventional parallel processors, the proposed technique is superior in terms of silicon area, power consumption, dynamic energy use due to variable precision arithmetic. A sample design of a 64-point FFT shows that the implementation can save about 40% area and 36% leakage power compared with a conventional parallel counterpart, accordingly achieving significant power benefits at a low sample rate and low voltage domain. The dynamic variation of the arithmetic precision can be achieved through a simple modification of the controller with hardware area overhead of 10% gate count.

With a relatively small population, Russia accesses huge oil, natural gas, coal and uranium resources, and hosts advanced nuclear energy, oil and natural gas industries. However, the combined effect of today’s low cost electricity generation via photovoltaic modules, water and wind turbines and similarly low cost storage in Li-ion battery and solar hydrogen obtained via water electrolysis will have a profound impact on Russia’s energy and automotive industries.

The environmental issues we are currently facing require long-term prospective efforts for sustainable growth. Renewable energy sources seem to be one of the most practical and efficient alternatives in this regard. Understanding a nation's pattern of energy use and renewable energy production is crucial for developing strategic plans. No previous study has been performed to explore the dynamics of power consumption with the change in renewable energy production on a country-wide scale. In contrast, a number of deep learning algorithms demonstrated acceptable performance while handling sequential data in the era of data-driven predictions. In this study, we developed a scheme to investigate and predict total power consumption and renewable energy production time series for eleven years of data using a Recurrent Neural Network (RNN). The dynamics of the interaction between the total annual power consumption and renewable energy production are investigated through extensive Exploratory Data Analysis (EDA) and a feature engineering framework. The performance of the model is found satisfactory through the comparison of the predicted data with the observed data, visualization of the distribution of the errors and Root Mean Squared Error (RMSE) value of 0.084. Higher performance is achieved through the increase in the number of epochs and hyperparameter tuning. The proposed framework can be used and transferred to investigate the trend of renewable energy production and power consumption and predict the future scenarios for different communities. Incorporation of the cloud-based platform into the proposed pipeline may lead to real-time forecasting.

Abstract Due to the relatively low efficiency of thermoelectric (TE) generators, they have mostly been used in niche applications where the unique properties of TE generators outweigh their lack of efficiency, or conditions where it is more reasonable to base the optimal design on maximum generated power rather than maximum efficiency. The aim of this work is to investigate how the different fundamental transport properties (Seebeck coefficient, thermal conductivity and electrical resistivity) in materials with equal figure of merit (ZT) impact TE module design and maximum power output. Further, we discuss and review the strategies to enhance material properties and the latest studies on the TE module performance. It is shown, that by increasing the power factor by a factor of 15 and decreasing the thermal conductivity by 13.33 in order to maintain ZT=1, power output is increased by 45%. This effect is stronger in lower module fill factor and thermal resistance of the heat source and heat sink.

Uniform illumination is a key requirement in different research fields. However, this requirement is often difficult to achieve when high intensity is required at the same time. Recent advancements in LED lamps allow nowadays for compact and economical solutions. In this work we present a suitable solution for various laboratory purposes requiring stable, uniform and high intensity illumination. The system is composed of four identical high power white LED arrays of 30 mm diameter each, placed on a supporting and cooling structure having a minimum volume of 26 cm x 26 cm x 8 cm. A numerical model has been developed, based on a ray tracing software, in order to simulate the performances. These have then been experimentally validated with measurements of the power density map, carried out with a 1% uncertainty pyranometer. Data show that the built system is very stable over time and provides an illumination uniformity higher than 98%, on a surface of 50 mm radius, which reduces to 95% on a surface of 75 mm radius. The power density can be adjusted in the 390-1360 W m-2 range, not affecting uniformity.

To show that underlying Schmitt's account of fascist politics lies a Gnostic-like metaphysical dualism separating the realms of value and power. Contrary to the normative political tradition of the West, which defends an ethical politics, Schmitt - jurist and theorist of the Nazis - aligns himself with Machiavelli and Hobbes to defend realpolitik: where sovereignty is ultimately a function of the Dictator's will alone. This paper shows the contradiction within such a position, which criticizes values in politics but by its advocacy, and its defense of the Dictator's willing, relies on valuation, choice, and hence the ethical.

This paper presents findings of a study on continuous feed-in management and continuous synthetic inertia contribution with wind turbines. A realistic case study, based on real measurements, is outlined. A wind turbine feeds into a weak feeder, such that its power has to be adapted to the permissible loading of this feeder. At the same time the wind turbine is to provide inertia to the grid by applying the previously published variable inertia constant controller. It is discussed that optimal grid utilisation and simultaneous inertia contribution are mandatory for the frequency control in power systems that are heavily penetrated with renewable energies. The study shows that continuous feed-in management can be combined well with continuous inertia provision. There are hardly any negative consequences for the wind turbine. The benefits for the grid are convincing, both in terms of increased system utilisation and in terms of provided inertia. It is concluded that wind turbines can enhance angular stability in a power system to a larger extent than conventional power plants.

Supply chain management requires regular updates of the location of assets, which can be enabled by low power wide area networks, such as Sigfox. While it is useful to localize a device simply by its communication signals, this is very difficult to do with Sigfox because of wide area and ultra narrowband nature. On the other hand, installing a satellite localization element on the device greatly increases its power consumption. We investigated using information about nearby Wi-Fi access points as a way to localize the asset over the Sigfox network, so without connecting to those Wi-Fi networks. This paper reports the location error that can be achieved by this type of outdoor localization. By using a combination of two databases, we could localize the device on all 36 test locations with a median location error of 39 m. This shows that the localization accuracy of this method is promising enough to warrant further study, most specifically the minimal power consumption.

The operation of electricity and natural gas transmission networks in the U.S. are increasingly interdependent, due to the growing number of installations of gas fired generators and the penetration of renewable energy sources. This development suggests the need for closer communication and coordination between gas and power transmission system operators in order to improve the efficiency and reliability of the combined energy system. In this paper, we present a co-simulation platform for examining the interdependence between natural gas and electricity transmission networks based on a direct current unit-commitment and economic dispatch model for the power system and a transient hydraulic gas model for the gas system. We analyze the value of day-ahead coordination of power and natural gas network operations and show the importance of considering gas system constraints when analyzing power systems operation with high penetration of gas generators and renewable energy sources. Results show that day-ahead coordination contributes to a reduction in curtailed gas during high stress periods (e.g., large gas offtake ramps) and a reduction in energy consumption of gas compressor stations.

The incorporation of renewable energy into power systems poses serious challenges to the transmission and distribution power system operators (TSOs and DSOs). To fully leverage these resources there is a need for a new market design with improved coordination between TSOs and DSOs. In this paper we propose two coordination schemes between TSOs and DSOs: one centralised and another decentralised that facilitate the integration of distributed based generation; minimise operational cost; relieve congestion; and promote a sustainable system. To this end, we approximate the power equations with linearised equations so that the resulting optimal power flows (OPFs) in both the TSO and DSO become convex optimisation problems. In the resulting decentralised scheme, the TSO and DSO collaborate to optimally allocate all resources in the system. In particular, we propose an iterative bi-level optimisation technique where the upper level is the TSO that solves its own OPF and determines the locational marginal prices at substations. We demonstrate numerically that the algorithm converges to a near optimal solution. We study the interaction of TSOs and DSOs and the existence of any conflicting objectives with the centralised scheme. More specifically, we approximate the Pareto front of the multi-objective optimal power flow problem where the entire system, i.e., transmission and distribution systems, is modelled. The proposed ideas are illustrated through a five bus transmission system connected with distribution systems, represented by the IEEE 33 and 69 bus feeders.

We study on the sums of powers of consequtive integers and alternating sums of power of consequtive integers. We derive many identities and correlations including Bernoulli, Euler and Genocchi polynomials and numbers.

This study aims to determine the optimal configuration (position and operation duration) for wall mounted mechanical mixers based on the comparison of three-dimensional computational fluid dynamics (CFD) modelling results and physical data collected from the treatment plant. A three-dimensional model of anoxic zone 1, 2 and 3 of Northern Wastewater Treatment Plant (WWTP) located at Cairns Regional Council, Cairns, Queensland, Australia was developed and validated. The model was used to simulate the flow pattern of the WWTP and the simulation results are in good agreement with the physical data varying between 0% to 15% in key locations. The anoxic zones were subject to velocities less than the desired 0.3 metres per second however results for suspended solids concentration indicate that good mixing is being achieved. Results for suspended solids concentrations suggest that the anoxic zones are towards the upper limits recommended by literature for specific power dissipation. The duration for operation of mechanical mixers was investigated and identified that the duration could be reduced from 900 seconds down to 150 seconds. Alternative mixer positioning was also investigated and identified positioning which would increase the average flow velocity with decreased duration (150 seconds). The study identified that Council may achieve savings of $24,000 per year through optimisation of the mechanical mixers.

The main objective of this paper is to continue the development of activities of basic and applied research related to wind energy and to develop methods of optimal control to improve the performance and production of electrical energy from wind. A new control technique of Double fed induction generator for wind turbine is undertaken through a robust approach tagged nonlinear sliding mode control (SMC) with exponential reaching law control (ERL). The SMC with ERL proves to be capable of reducing the system chattering phenomenon as well as accelerating the approaching process. A nonlinear case numerical simulation test is employed to verify the superior performance of the ERL method over traditional power rate reaching strategy. Results obtained in Matlab/Simulink environment show that the SMC with ERL is more robust, prove excellent performance for the control unit by improving power quality and stability of wind turbine.

In manual maintenance inspections of large-scaled photovoltaic (PV) or rooftop PV systems, several days are required to survey the entire PV field. To improve reliability and shorten the amount of time involved, this study proposes an electrical examination based method for locating multiple faults in the PV array. The maximum power point tracking (MPPT) algorithm is used to estimate the maximum power of each PV panel; this is then compared with metering the output power of PV array. Power degradation indexes are parameterized to quantify the degradation between maximum power and metered output power. Bidirectional hetero-associative memory (BHAM) networks are then used to locate multiple faults within the entire PV field. For a rooftop PV system with two strings, as seen in Figure 1, experimental results demonstrate that the proposed model has computational efficiency for real-time applications and that its algorithm is easily implemented in a mobile intelligent vehicle.

This study examined the effects of incorporating 8 weeks of biweekly upper limb loaded plyometric training (elastic band) into the in-season regimen of handball players. Trial participants were assigned between control (n = 15, age: 18.1±0.5 years, body mass: 73.7±13.9 kg) and experimental (n = 14, age: 17.7±0.3 years, body mass: 76.8±10.7 kg) groups. Measures obtained pre- and post- included a cycle ergometer force-velocity test, ball throwing velocity in three types throw, 1-RM bench press and pull-over, and anthropometric estimates of upper limb muscle volumes. Gains in the experimental group relative to controls included absolute muscle power (W) (Δ23.3%; t-test p<0.01; d=0.083), relative muscle power (W.kg-1) (Δ22.3%; t-test p<0.01; d=0.091), and all 3 types of ball throw (Δ18.6%, t-test p<0.01, d=0.097 on jumping shot; Δ18.6%, t-test p<0.01; d=0.101 on 3-step running throw; and Δ19.1%, t-test p<0.01, d=0.072 on standing throw). Furthermore, a significant improvement by time interactions was observed in both groups on 1-RM bench press and pull-over performance. However, upper limb muscle volumes remained unchanged in both groups. We conclude that adding biweekly elastic band plyometric training to standard training improves measures important to game performance. Accordingly, such exercises can usefully be adopted as a part of handball training.

This paper aims to analyze the effects of Covid-19 on financial markets from the perspective of Complexity. The Covid-19 pandemic has caused turmoil in financial markets and is already one of the most important financial crises in history, causing a fall in several stock markets as well as great volatility. Unlike past crises, which in most cases were caused either by problems of fiscal deficits or in the financial system, this crisis has its origin in an epidemic disease, which occurred in Wuhan, China, and quickly spread across the globe affecting transport networks, commerce and finance, and will affect the public debt of many countries. This is a systemic situation in which there is a need to consider several interconnected systems, financial instability and high financial risk, something that econophysics and some complexity theorists already do. Therefore, this paper intends to show, theoretically, the systemic and complex character of the recent financial crisis caused by Covid-19.

This paper presents an optimal design for the inner current control loop of the continuous current conduction mode (CCM) power factor correction (PFC) stage, which it can be used as the front stage of the two stages alternating current-direct current (AC-DC) telecom power supply. Conventional single-phase CCM-PFC boost converter usually implemented with using of the proportional-integral (PI) controllers in both of the voltage and current control loops, to regulate the output DC voltage to the specified value, moreover to maintains the input current follows the input voltage which offers converter with high power factor (P.F) and low current total harmonic distortion (THD). However, due to the slow dynamic response of the PI controller at the zero-crossing point of the input supply current, input current can’t fully follow the input voltage which leads to high THD. Digitally controlled PFC converter with an optimal design of the inner current control loop using doubly control loops IP controller to reduce the THD and to offer input current with unity P.F was performed in this paper. Furthermore, for the economic design of the digitally control PFC converter, two isolated AC and DC voltage sensors are proposed and designed for the interfacing with the microcontroller unit (MCU). PSIM software was used to test the converter performance with using the proposed designed current controllers and isolated voltage sensors. High power density digitally controlled telecom PFC stage with P.F of about 99.93%, full load efficiency of about 98.70% and THD less 5.50% is achieved in this work.

In this paper, a multi-operator differential evolution algorithm (MODE) is proposed to solve the Optimal Power Flow (OPF) problem and is called MODE-OPF. The MODE-OPF utilizes the strengths of more than one differential evolution (DE) operator in a single algorithmic framework. Additionally, an adaptive method (AM) is proposed to update the number of solutions evolved by each DE operator based on both the diversity of population and quality of solutions. This adaptive method has the ability to maintain diversity at the early stages of the optimization process and boost convergence at the later ones. The performance of the proposed MODE-OPF is tested by solving OPF problems for both small and large IEEE bus systems (i.e., IEEE-30 and IEEE-118) while considering the intermittent solar and wind power generation. To prove the suitability of this proposed algorithm, its performance has been compared against several state-of-the-art optimization algorithms, where MODE-OPF outperforms other algorithms in all experimental results and thereby improving a network's performance with lower cost. MODE-OPF decreases the total generation cost up to 24.08%, the real power loss up to 6.80% and the total generation cost with emission up to 8.56%.

In this paper a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator. This new family of test statistics will be called Wald-type test statistics. The problem of testing a simple and a composite null hypothesis is considered and the robustness is studied on the basis of a simulation study. Previously, the composite minimum density power divergence estimator is introduced and its asymptotic properties are studied.

Purpose: The present study which addressed adults who stutter (AWS), has been an attempt to investigate power spectral dynamics in stuttering state through answering the written questions using quantitative electroencephalography (qEEG).Materials and Methods: A 64-channel EEG setup was used for data acquisition in 9 AWS. Since speech, and especially stuttering, causes significant noise in the EEG, the three conditions of speech preparation (SP), imagined speech (IS), and simulated speech (SS) in a 7-band format were chosen to source localize the signals using the standard low-resolution electromagnetic tomography (sLORETA) tool in fluent and disfluent states. Results: Having extracted enough fluent and disfluent utterances, significant differences were noted. Consistent with previous studies, the lack of beta suppression in SP, especially in beta2 and beta3 and somewhat in gamma band, was localized in supplementary motor area (SMA) and pre motor area in disfluent state. Delta band frequency was the best marker of stuttering shared in all 3 experimental conditions. Decreased delta power in SMA of both hemispheres and right premotor area through SP, in fronto-central and right angular gyrus through IS, and in SMA of both hemispheres through SS were a notable qEEG features of disfluent speech. Conclusion: The dynamics of beta and delta frequency bands may potentially explain the neural networks involved in stuttering. Based on the above, neurorehabilitation may better be formulated in the treatment of speech disfluency, namely stuttering.

new subsonic blower wind tunnel design has been studied both numerically and experimentally, it is also referred to as “blower” wind tunnel. This paper, is initially aimed to address each sequential stage of the wind tunnel design process. Rather than applying the standard method of modelling solely the flow in the test section, a large-scale CFD model of the whole wind tunnel was employed. The loss of every constituent element was calculated and then all the losses are added up to determine the power needed for the wind tunnel operation which is used as “intake fan” boundary conditions in the CFD model. Then, flow uniformity and turbulent intensity measurements in an empty test section using a Pitot-static tube and hot wire anemometer (HWA) were introduced to validate the CFD results. The results showed that flow quality was significantly affected by boundary layer controllers (honeycomb and mesh screens) in the settling chamber and wide-angle diffuser. Investigations were also conducted to evaluate the flow deficit in the wake area behind a convex hump model using HWA. This was additional experimental tests carried out to validate the suitability of the wind tunnel flow aerodynamic research.

Gas turbine engines are widely used in various industries such as aviation, power generation, and marine propulsion due to their high efficiency and reliability. The combustion chamber of a gas turbine engine design contains a number of elements, including as the chamber's size and form, the fuel injection system, the ignition system, and the cooling system and it plays a critical role in the performance and efficiency of the engine. This research discusses the fabrication of a combustion chamber model for a gas turbine engine. The aim of this research is to develop a combustion chamber that is cost-effective, easily available, and can be fabricated in less time. The research covers the different types of combustion chambers used in gas turbine engines and compares their advantages and disadvantages. It then selects the best type of combustion chamber for the gas turbine engine based on its cost, availability, and fabrication time, Efficiency and high power to fuel ratio. The report also describes the fabrication process involved, including the techniques and materials used, along with safety precautions and environmental protection measures. Lastly, the research suggests future improvements and potential applications for the fabricated combustion chamber model.

This paper reports a new control strategy to improve sharing of unbalanced currents in islanded LV microgrids. This technique provides fast and effective sharing of positive-, negative- and zero-sequence currents, and is the first example of zero-sequence current sharing in the literature. The controllers are designed in the stationary frame. The control structure consists of four loops; 1)~the current controller; 2)~the voltage controller; 3)~the droop controller and the 4)~negative and zero sequence current controllers. The output current is considered unknown for the controller and is added to the control system as a disturbance. The proposed controller features a high gain in fundamental and harmonic frequencies, hence a good voltage quality is obtained in the presence of unbalanced and nonlinear loads. To this aim, a proportional-resonant (PR) controller is adopted as the current controller. By using a multi-resonant controller as current controller, a unified control structure is obtained which is suitable for both grid-connected and islanded modes. The voltage controller is designed using a resonant controller so that the voltage can have low VUF and THD in the presence of unbalanced and nonlinear loads. Furthermore, in this paper droop method is applied to the control structure to share real and reactive powers. Simulation studies show that the conventional droop method cannot share the oscillatory part of the output power that is due to the presence of unbalanced loads in the microgrid. This paper relies on using zero and negative sequence virtual impedance controller to share the oscillatory part of output power. By using zero-sequence virtual impedance controller (ZSVIC) and negative-sequence virtual impedance controller (NSVIC), the zero and negative sequence currents in the microgrid are controlled and shared effectively. By compensating zero- and negative-sequence currents locally, the flow of these currents in the microgrid is minimized, and the overall power quality of the islanded LV microgrid is improved.

An optimal scheduling strategy for cooling, heating and power (CCHP) joint-power-supply system is proposed to improve energy utilization and minimize costs in this paper. Firstly, the mathematical model of CCHP system is established. Particle swarm optimization (PSO) is used to optimize the regularization coefficient C and the kernel parameter λ which can affect the prediction accuracy of KELM(PSO-KELM). Then PV generation and load prediction model are established by PSO-KELM. In order to jump out of local optimal solution, Cauchy variation is introduced in SFLA local update, and adaptive mutation operation is carried out on SFLA individuals. The predictions of PV generation and load power by PSO-KELM are imported into the objective function, and the microgrid dispatching model is solved by the improved SFLA algorithm. Compared with the traditional GA-KELM and KELM, PSO-KELM has faster convergence and prediction accuracy. Compared with the power supply division, the operation cost of the power grid is reduced by the proposed optimization dispatching strategy of CCHP micro-grid.

Increasing demand for electricity and modernization of power systems within competitive markets induce power systems to operate close to their stability limits. Therefore, a power system continuous monitoring and control by using voltage stability indices are known exigence. This is the first-ever effort, examined more than 40 voltage stability indices thorough an exhaustive study based in on their formulation, application, performance, and assessment measures. Which is conducted based on a logical and chronological order considering the most recent worldwide applied voltage stability indices. However, the generalizability of such an immense diversity of these indices in term of multivariable objectives subjects to a certain limitation to summate into a deciphered outcome. Despite all these obstacles, this study systematically reviews available indices in the literature within the past three decades to set out an integrated knowledge with an insight up-to-date exposition. That followed with a comparative analysis in term of their similarity, functionality, applicability, formulation, merit, demerit, and overall performances. Also, a broad categorization of voltage stability indices is addressed. This study with an immediate implication in practice as an exhaustive roadmap can be counted a planning and operation reference in the context of voltage stability for students, researchers, scholars, and practitioners.

The ecological background condition of the semi-arid steppe region (SASR) is extremely fragile. It is recognized that the development of coal and electricity power is a kind of strong human interference behavior for regional landscape ecology. Landscape ecological classification (LEC) is the premise of landscape ecology research of the mining area. The current research on the SASR and grassland LEC of coal-power base is relatively less, but still remains uncertainty concerning how to stratify and classify urban mining landscapes into units of ecological significance at spatial scales appropriate for management. This study is based on hierarchy theory, scale theory, landscape process, the patch-corridor-matrix model, the network, the theory of multiple planning integration and the principle of remote sensing. According to the comprehensive principle, principles of the combining of structure and function, principle of the combining human-ominated and natural landscape, principle of emphasis, and principle of combining qualitative analysis with quantitative research of LEC in large-scale coal-power base(LSCPB). On the basis of occurrence method land classification, fully consider the ecological attributes of the land, integration pattern, processes and function theory of the landscape ecology, the LEC system of the LSCPB in the SASR has been constructed by using top-down decomposition classification method. Empirical research of the Victory and Mindong No.1 mining areas of Shenhua Group shows that the classification system constructed in this paper can meet the requirements of LEC and fully reflect the status of landscape ecology of LSCPB in SASR. This study can provide theoretical guidance for the landscape ecology of LSCPB, while also supporting a theoretical reference for the LEC research.

The increasing variability in power plant load, in response to a wildly uncertain electricity market and the need to to mitigate CO₂ emissions, lead power plant operators to explore advanced options for efficiency optimization. Model-based, system-scale dynamic simulation and optimization are useful tools in this effort, and the subject of the work presented here. In prior work, a dynamic model validated against steady-state data from a 605 MW subcritical power plant was presented. This power plant model is used as a test-bed for dynamic simulations, in which the coal load is regulated to satisfy a varying power demand. Plant-level control regulates plant load to match an anticipated trajectory of the power demand. The efficiency of the power plant operating at varying load is optimized through a supervisory control architecture that performs set point optimization on the regulatory controllers. Dynamic optimization problems are formulated to search for optimal time-varying input trajectories that satisfy operability and safety constraints during the transition between plant states. An improvement in time-averaged efficiency of up to 1.8% points is shown feasible with corresponding savings in coal consumption of 184.8 tons/day and carbon footprint decrease of 0.035 kg/kWh.

The world is moving to the next phase of the energy transition with high penetrations of renewable energy. Flexible and scalable redox flow battery (RFB) technology is expected to play an important role in ensuring electricity network security and reliability. Continuous performance improvements will further enhance their value by reducing parasitic losses and maximizing available energy conversion over broader operating conditions. Concentration overpotentials from poor internal reactant distribution at high and low states of charge (SOC) limit power densities and are thus an important area of investigation. However, efforts to address these coupled electrochemical phenomena can compromise mechanical performance. Modelling and simulation of cell design innovations have shown it is possible to reduce losses from pump energy while increasing the availability of active species where required. The combination of wedge-shaped cells with static mixers investigated in this paper can reduce pressure drop and improve energy efficiency. Toroidal vanadium redox flow battery (VRB/VRFB) designs incorporating this innovation are presented for further development to improve community engagement with the technology.

The research sought to investigate the long term characteristics of wind in the Kisii region (elevation 1710m above sea level, 0.68^oS, 34.79^o E). Wind speeds were analyzed and characterized on short term (per month for a year) and then simulated for long term (ten years) measured hourly series data of daily wind speeds at a height of 10m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent; the mean wind speed, diurnal variations, daily variations as well as the monthly variations. The wind speed frequency distribution at the height 10 m was found to be 2.9ms^-1 with a standard deviation of 1.5. Based on the two month’s data that was extracted from the AcuRite 01024 Wireless Weather Stations with 5-in-1 Weather Sensor experiments set at three sites in the region, averages of wind speeds at hub heights of 10m and 13m were calculated and found to be 1.7m/s, 2.0m/s for Ikobe station, 2.4m/s, 2.8m/s for Kisii University stations, and 1.3m/s, 1.6m/s for Nyamecheo station respectively. Then extrapolation was done to determine average wind speeds at heights (20m, 30m, 50m, and 70m) which were found to be 85.55W/m², 181.75W/m², 470.4W/m² and 879.9W/m² respectively. The wind speed data was used statistically to model a Weibull probability density function and used to determine the power density for Kisii region.

In this manuscript, we present a high-fidelity physics-based truth model of a Single Machine Infinite Bus (SMIB) system. We also present reduced-order control-oriented nonlinear and linear models of a synchronous generator-turbine system connected to a power grid. The reduced-order control-oriented models are next used to design various control strategies such as: proportional-integral-derivative (PID), linear-quadratic regulator (LQR), pole placement-based state feedback, observer-based output feedback, loop transfer recovery (LTR)-based linear-quadratic-Gaussian (LQG), and nonlinear feedback-linearizing control for the SMIB system. The controllers developed are then validated on the high-fidelity physics-based truth model of the SMIB system. Finally, a comparison is made of the performance of the controllers at different operating points of the SMIB system.

Synthetic fuels play an important role in the defossilization of future aviation transport. To reduce the ecological impact of remote airports due to long range transportation of kerosene, a decentralized on-site-production of synthetic paraffinic kerosene is applicable, preferably as near-drop-in fuel or alternatively as blend. One possible solution for such a production of synthetic kerosene is the Power-to-Liquid process. The basic development of a simplified plant layout addressing the specific challenges of a decentralized kerosene production which differ from most current approaches for infrastructural well-connected regions is described. The decisive influence of the Fischer-Tropsch synthesis on the PtL process is shown by means of a steady-state reactor model which was developed in Python and serves as basis for further development of a modular environment able to represent entire process chains. The reactor model is based on reaction kinetics according current literature. The effects of adjustments of the main operation parameters on the reactor behavior are evaluated and the impacts on up- and downstream processes are described. The results prove the governing influence of the Fischer-Tropsch reactor on the PtL process and show its flexibility regarding the desired product fraction output, which makes it an appropriate solution for a decentralized kerosene production.

This paper presents a control algorithm for soft-switching series LC converters. The conventional voltage-to-voltage controller is split into a master and a slave controller. The master controller implements constant-current-constant-voltage (CCCV) control, required for demanding applications, i.e. lithium battery charging or laboratory power supplies. It defines the set-current for the open-loop current slave controller, which generates the PWM parameters. The power supply achieves fast large-signal responses, e.g. from 5 V to 24 V, where 95% of the target value is reached in less than 400 µs. The design is evaluated extensively in simulation and on a prototype. A consensus between simulation and measurement is achieved.

The work addresses the problem of Power Quality (PQ) metrics (or indexes) suitable for DC grids, encompassing Low and Medium Voltage applications, including electric transports, all-electric ships and aircrafts, electric vehicles, distributed generation and microgrids, modern data centers, etc. The two main pillars on which such PQ indexes are discussed and built are: i) the physical justification, so the electric phenomena affecting DC grids and components (PV panels, fuel cells, capacitors, batteries, etc.), causing e.g. stress of materials, ageing, distortion, grid instability; ii) the existing standardization framework, pointing out desirable coverage and extension, similarity with AC grids standards, but also inconsistencies. The first point is made more clear and usable by a graphical overview of the discussed phenomena. On this basis PQ is interpreted beyond the usual low-frequency range, including thus supraharmonics and common-mode disturbance, and filling the gap with the Electromagnetic Compatibility domain. However, phenomena typical of EMC and electrical safety (such as various types of overvoltages and fast transients) are excluded. Suitable PQ indexes are then reviewed, suggesting integrations and modifications, to cover the relevant phenomena and technological progress, and to better follow the normative exigencies.

The transition towards a renewable energy system is essential in order to reduce greenhouse gas emissions. The increase in the share of variable renewable energy sources (VRES), which mainly comprise wind and solar energy, necessitates storage technologies by which the intermittency of VRES can be compensated for. Although hydrogen has been envisioned to play a significant role as a promising alternative energy carrier in a future European VRES-based energy concept, the optimal design of this system remains uncertain. In this analysis, a hydrogen infrastructure is posited that would meet the electricity and hydrogen demand for a 100% renewable energy-based European energy system in the context of 2050. The overall system design is optimized by minimizing the total annual cost. Onshore and offshore wind energy, open-field photovoltaics (PV), rooftop PV and hydro energy, as well as biomass, are the technologies employed for electricity generation. The electricity generated is then either transmitted through the electrical grid or converted into hydrogen by means of electrolyzers and then distributed through hydrogen pipelines. Battery, hydrogen vessels and salt caverns are considered as potential storage technologies. In the case of a lull, stored hydrogen can be re-electrified to generate electricity to meet demand during that time period. For each location, eligible technologies are introduced, as well as their maximum capacity and hourly demand profiles, in order to build the optimization model. In addition, a generation time series for VRES has been exogenously derived for the model. The generation profiles of wind energy have been investigated in detail by considering future turbine designs with high spatial resolution. In terms of salt cavern storage, the technical potential for hydrogen storage is defined in the system as the maximum allowable capacity per region. Whether or not a technology is installed in a region, the hourly operation of these technologies, as well as the cost of each technology, are obtained within the optimization results. It is revealed that a 100 percent renewable energy system is feasible and would meet both electricity demand and hydrogen demand in Europe.

In this paper we review dynamics and roughness of bonds in proteins on example of albumin, that is important from the physiological point of view. We have performed computer simulations of albumin chain. Statistics were collected by performing many simulations realizations for each experimental setting. We concentrate on hydrogen bonds, cation-π and π- π interactions and NP contacts. Histograms of hydrogen bonds length are positively skewed in contrary to histograms of interactions and HP contacts that are negatively skewed. Scaling exponents of power spectra of energies of bonds / interactions /contacts are in range -0.2 to -0.5 and significantly differ between various hydrogen bonds or interactions. Varying scaling of such spectra can be used to classify between distinct bonds or contacts. Concerning particular amino-acids, largest amount of HBO H20 bonds are between Glutamate (GLU) amino-acids and water particle, while large amount of HBO bonds are formed with Lysine (LYS). For HP contacts the mayor role plays Phenylalanine (PHE) and Leucine (LEU) amino-acids. From decay curves HBO H2O bonds decays in fastest rate, while HBO bonds and HP contacts at slowest rate. We present as well decay curves of bonds formed by particular amino-acids, that gives interesting results.

Since large power transformers are custom-made, and their design process is a labor-intensive task, their design process is split into different parts. In tendering, the price calculation is based on the preliminary design of the transformer. Due to the complexity of this task, it belongs to the most general branch of discrete, non-linear mathematical optimization problems. Most of the published algorithms are using a copper filling factor based winding model to calculate the main dimensions of the transformer during this first, preliminary design step. Therefore, these cost optimization methods are not considering the detailed winding layout and the conductor dimensions. However, the knowledge of the exact conductor dimensions is essential to calculate the thermal behaviour of the windings and make a more accurate stray loss calculation. The paper presents a novel, evolutionary algorithm-based transformer optimization method which can determine the optimal conductor shape for the windings during this examined preliminary design stage. The accuracy of the presented FEM method was tested on an existing transformer design. Then the results of the proposed optimization method have been compared with a validated transformer design optimization algorithm.

Renewable energy sources (RES) will play a crucial role in future sustainable energy systems. In scenarios analyzing future energy system designs, a detailed spatial and temporal representation of renewable-based electricity generation is essential. For this, sufficiently representative weather data are required. Most analyses performed in this context use the historical data of either one specific reference year or an aggregation of multiple years. In contrast, this study analyzes the impact of different weather years based on historical weather data from 1980 through 2015 in accordance with the design of an exemplary future energy system. This exemplary energy system consists of on- and offshore wind energy for power-to-hydrogen via electrolysis, including hydrogen pipeline transport for most southwestern European countries. The assumed hydrogen demand for transportation needs represents a hypothetical future market penetration for fuel cell-electric vehicles of 75%. An optimization framework is used in order to evaluate the resulting system design with the objective function of minimizing the total annual cost (TAC) of the system. For each historical weather year, the applied optimization model determines the required capacities and operation of wind power plants, electrolyzers, storage technologies and hydrogen pipelines to meet the assumed future hydrogen demand in a highly spatially- and temporally-detailed manner, as well as the TAC of the system. Following that, the results of every individual year are compared in terms of installed capacities, overall electricity generation and connection to the transmission network, as well as the cost of these components within each region. The results reveal how sensitive the final design of the exemplary system is to the choice of the weather year. For example, the TAC of the system changes by up to 20% across two consecutive weather years. Furthermore, significant variation in the optimization results regarding installed capacities per region with respect to the choice of weather years can be observed.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus 13 voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ 14 constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources 15 on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar 16 PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed 17 using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of 18 simulation and statistical results of EO with other optimization techniques showed that EO is more effective 19 and superior.

This paper presents a complete control strategy of the active return-to-center (RTC) control for electric power steering (EPS) systems. We first establish the mathematical model of the EPS system and analyze the source and influence of the self-aligning torque (SAT). Second, based on the feedback signals of steering column torque and steering wheel angle, we give the trigger conditions of a state switch between the steering assist state and the RTC state. In order to avoid the sudden change of the output torque for the driving motor when the state switches frequently between the steering assist state and the RTC state, we design an undisturbed state switching logic algorithm. This state switching logic algorithm ensures that the output value of the RTC controller is set to an initial value and increases in given steps up to a maximum value after entering the RTC state, and the output value of the RTC controller will reduce in given steps down to zero when exiting the RTC state. This therefore ensures smooth switch control between the two states and improves the driver’s steering feeling. Third, we design the RTC controller, which depends upon the feedback signals of the steering wheel angle and the angular velocity. In addition, the controller increases the auxiliary control function of the RTC torque based on vehicle speed. The experimental results show that the active RTC control method does not affect the basic assist characteristics, which effectively reduces the residual angle of the steering wheel at low vehicle speed and improves the RTC performance of the vehicle.

A new method in which completely eliminated the negative value of the scattering power is proposed in this paper. Primarily, here are presented the Freeman-Durden decomposition of the scattering powers, which are computed by using the coherency matrix elements with rotation and without rotation. Secondly, this paper investigates the reasons of the occurrence of negative values of the scattering powers. Then using the modification like in algorithm proposed by Yamaguchi for G4U, it was applied for the algorithm of Freeman-Durden decomposition to eliminate negative values. In this research, Radarsat-2 radar remote sensing data were used, which are acquired for study area Yushu County, Qinghai province, China. At the end, the comparison results of Yamaguchi G4U and a modified Freeman-Durden decompositions were presented.

Fossil fuels are non-renewable sources of energy, used particularly in developing countries. There are insufficient fossil fuels and their availability is gradually declining. This leads to a steady increase in prices. Renewable energy is clean, cost-effective and limitless. The considerable population growth and industrial growth have made the construction of solar power plants essential in developing countries. The study used Boolean logical-AHP techniques to select a suitable site for solar power in Duhok Governorate. The result indicated that 68.5% of the area in the governorate of Duhok is available for solar power station construction, especially the most appropriate zone which has 132.2 sq. km and can provide more than 8000 megawatts of solar energy. Most of the appropriate areas are in the south and southwest regions of the governorate, located mostly in the districts of Bardarash, Shekhan and Semel, situated between the major cities of Mosul, Erbil and Duhok. These locations can supply a significant amount of clean, renewable energy for these areas.

This research paper is part of the wider project concerning the very first detailed mapping of the overall Taiwanese hydro-power plants that took place from 2013 up to 2015 and it is currently in evaluation and finalization stage. The case of Shanping hydro-power plant has been carefully studied, photographed, documented and mapped in situ. It was one of the isolated hydro-power plant projects originally built to supply the remote area with the specific designation. Shanping hydro-power plant, as well as the other units from the early hydro-power generation era in Taiwan, are considered to be the technological heritage of civil and mechanical engineering that reflects later in all the further projects up to nowadays modern Taiwanese hydro-power plants. Unfortunately, most of the hydro-power houses from the older periods were severely damaged or destroyed by natural causes which were also the case of Shanping unit. The research is trying to reconstruct the original location of the powerhouse and its supporting structures based on available historical documents, previous studies, comparative methodology, and the current on-site observation.

As on 31.03.2020, 55.4 % (205135 MW) of total installed capacity (370106 MW) in India is through coal and lignite based power plants. These plants, set up by central, state and private utilities with substantial capital investment are facing consistently reducing Plant Utilization Factor (known as Plant Load Factor, PLF, in India). In the year 2019-20 the national average thermal power PLF stood at 55.4%, down from 78.6 % in 2007-08. On the other hand, the electricity demand is consistently rising in the country and there exists a peak and energy shortage at national level. In 2019-20 energy shortage was 0.7 % and peak shortage was 0.5 %. A disturbing paradox therefore exists here. On one hand, the country is power deficit, and on the other hand, a large amount of coal based affordable power, ready to be generated by thermal power generators, remains grossly unused. Looking into the fact that considerable investment has gone into developing these thermal power generation assets in the country, the falling PLF is a matter of concern for all the key stakeholders including the power producers, lenders, regulators and consumers. This paper identifies seven major factors that are affecting PLF of thermal power plants and then makes an attempt to project future scenario of PLF so that critical stakeholders can intervene through appropriate actions. Primary research with responses from power professionals has been used to find out the major factors. Future projection of PLF has been done using Partial Least Square (PLS) regression. Projection shows that in the Business As Usual case (Factors increasing at the current CAGR rate), the thermal power plants will face very low level of PLF (14.76 %) by 2024-25. This will mean that many plants will be shut down and many will run for only few hours in a day that too at very low loads. If the future generation mix is kept as indicated by Central Electricity Authority (CEA), a Govt. of India in its report (Draft report on optimal generation capacity mix for 2029-30- CEA- Govt of India) then the thermal power plant average PLF can sustain above 68 % until 2024-25. If followed, this path can be a breather for the thermal power plants.

The calculation of power flow in power systems with the presence of harmonics has been properly studied in the scientific literature. However, power flow calculation considering interharmonic components is still an open question. Traditional methods based on the IEEE1459 standard have proven to be valid and accurate only for linear and sinusoidal systems, but have been criticized for non-linear and non-sinusoidal systems because they are not able to explain correctly the current and voltage interactions beyond the active power. This paper proposes the use of a novel mathematical framework called geometric algebra (GA) to study the power flow considering the interaction of current and voltage harmonics and interharmonics. The use of GA enables the precise determination of the direction and magnitude of the total and single active power flow for each component, as well as other power elements related to the non-active power due to cross interaction. Moreover, this paper makes a novel contribution to the definition of interharmonics in geometric algebra space that has not been done before. To test the validity of the method, both linear and non-linear circuits are proposed and solved by applying voltages and currents with harmonic and interharmonic components. The results obtained show that power flow can be analyzed under the prism of the principle of energy conservation (PoCoE) in a way that allows a better understanding of the power spectrum due to the interaction of harmonics and interharmonics of voltage and current.

This paper considers a hybrid relay network consisting of the source, the amplify-and-forward (AF) relay, the decode-and-forward (DF) relay, and the destination. We propose the optimal power allocation schemes between two different relays which maximize the achievable rate under a sum relay power constraint for given channel gains and transmit power from source. By solving the optimization problem to maximize the achievable rate for each relay network, the transmit power values in closed-form are derived. When the channel gains are the same, the optimal power allocation scheme for AF-DF relay network proves that a more power should be allocated at the first relay to maximize the achievable rate. In case of the DF-AF relay network, we derive the optimal power allocation scheme for the possible four cases. Under the same SNR condition at the first hop, we show that the achievable rate of AF-DF relay network is greater than that of DF-AF relay network when the channel gain between two relays is higher than that between the second relay and destination. Simulation results show that the proposed power allocation schemes provide a higher achievable rate than the equal power allocation schemes.

The decarbonization of the electrical energy sector is in progress for contrasting the climate changes, with a relevant increase of the Renewable Energy Sources (RES) power plants, mostly in Dispersed Generation (DG). The adequacy and the security of power systems, with a huge penetration of RES in DG is possible with a suitable integration of energy storage. In fact, energy storages are able to provide many different services for long-term adequacy and real time security. In this framework the present paper deals with a Thermal Energy Storage (TES) proposed for power system services. The technology presented is made up of modules containing a bed of fluidizable solid particles, which can store thermal energy from waste heat, process heat and/or from electricity. Stored thermal energy can be released, e.g. as superheated steam, for thermal uses or converted into electricity, by means of steam turbines. Some possible applications are then reported explaining advantages and limits.

Three-phase to single-phase matrix converter (TSMC) is used as the transmitter for transient electromagnetic method (TEM) instrument, instead of an AC-DC converter and an H-bridge inverter. The transmitter produces excitation current for primary field. The output current has a waveform with a bipolar square of half duty cycle, which is required by TEM. The space vector PWM based on input currents is discussed in detail. The control method of input power factor is proposed for TSMC. The simulation model of TSMC is established and the simulations of different conditions are completed. The simulation results show the controllability of the input power factor is illustrated.

Even though the current classic aerospace propulsion methods are greatly improved, some of the most modern methods have already been introduced, among which the propulsion with electric motors. Energy can be obtained from hydrogen burners, honeycomb burners to protect the burning of hydrogen that burns 10 times faster than conventional oil fuels or alcohols. Hydrogen storage is also done in honeycomb cell reservoirs. Getting solar photovoltaic power even during flight is not yet profitable or efficient, but it can be proposed in the future for lighter and/or spacecraft. A great desire is to dismantle water in hydrogen and oxygen directly on the aircraft, so the stored fuel is actually water and the one actually used is the hydrogen removed from the water. In this case, there is no need for hydrogen storage. And other modern methods of propulsion and energy acquisition are briefly presented in the paper.

A conventional electrical grid mostly depends on the electrical power generated from fossil fuels. However, the pollutants from fossil fuels are the key factors for adverse climate change. Most of the developed countries of the world have already recognized the fact that the energy mix requires to be diversified by incorporating renewable energy. This is especially relevant for many of the member countries of the Organization of Islamic Cooperation (OIC), consisting of 57 countries, whose abundance of fossil fuel reserve indicates that much of their electric power is still generated from fossil fuels. In order to integrate renewable energy sources into the hybrid energy mix, an existing conventional grid needs to undergo drastic changes. Alongside this, the population boom in the OIC member countries has caused higher demand for a steady supply of electricity that the conventional grids have long been struggling to cope with. With a view to solving this multifaceted problem, incorporation of the smart power management schemes is indispensable using a smart electrical grid, where information and communications technology is integrated into its major building blocks. This allows advanced applications of a grid, such as the formation of micro-grids, demand-side management, energy storage, high-tech power electronic converters, etc. As the smart grids are being adopted by many developed countries, it is high time for the OIC member countries to pay due attention to this development, if they have not already done so. This paper explains, with special focus on the OIC member countries, the various smart power management technologies, their operations and applications, and the benefits and challenges. Then it goes on to carry out the Strength-Weakness-Opportunity-Threat with Analytical-Heuristic-Procedure (SWOT-AHP) analysis to evaluate its feasibility of incorporation and the underlying strategies appropriate for its implementation. Furthermore, a Hybrid Multi-Criteria-Decision-Making (MCDM) analysis is performed to evaluate the sequence of the emphasis that should be given on each of the technologies from those available for the smart power management initiative. Finally, the study reinforces the stance by drawing parallels from the UN Sustainable Development Goals (SDG) and highlights the importance of the smart grid in line with the global vision of SDG. This paper aims at assisting the decision-makers in implementing smart power management schemes in the OIC member countries, in particular, and other countries of the world, in general.

This short communication makes use of the principle of singular perturbation to approximate the ordinary differential equation (ODE) of prompt neutron (in the point kinetics model) as an algebraic equation. This approximation is shown to yield a large gain in computational efficiency without compromising any significant accuracy in the numerical simulation of primary coolant system dynamics in a PWR nuclear power plant. The approximate (i.e., singularly perturbed) model has been validated with a numerical solution of the original set of neutron point-kinetic and thermal–hydraulic equations. Both models use variable-step Runge–Kutta numerical integration.

In this paper we discuss a problem of generalization of binomial distributed triangle, that is sequence A287326 in OEIS. The main property of A287326 that it returns a perfect cube n as sum of n-th row terms over k; 0 ≤ k ≤ n−1 or 1 ≤ k ≤ n, by means of its symmetry. In this paper we have derived a similar triangles in order to receive powers m = 5; 7 as row items sum and generalized obtained results in order to receive every odd-powered monomial n^2m+1; m ≥ 0 as sum of row terms of corresponding triangle. In other words, in this manuscript are found and discussed the polynomials D_m(n,k) and U_m(n,k), such that, when being summed up over k in some range with respect to m and n returns the monomial n^2m+1.

This contribution considers an improved control scheme for three-phase two-stage grid-tied photovoltaic (PV) power system based on integral sliding mode control (ISMC) theory. The proposed control scheme consists of maximum power point tracking (MPPT), DC-Link voltage regulation and grid currents synchronization. A modified voltage-oriented maximum power point tracking (VO-MPPT) method based on ISMC theory is proposed for design of an enhanced MPPT under irradiation changes. Moreover, a novel DC-Link voltage control based on ISMC theory is proposed in order to achieve good regulation of DC-Link voltage over its reference. To inject the generated PV power into the grid with high quality, a voltage oriented control based on space vector modulation (SVM) and ISMC (VOC-ISMC-SVM) has been developed to control the grid currents synchronization. Numerical simulations are performed in Matlab/SimulinkTM environment in order to evaluate the proposed control strategy. In comparison with conventional control scheme, the developed control strategy provides an accurate MPP tracking with less power oscillation as well as a fast and an accurate DC-Link regulation under climatic conditions variations. Moreover, the transfer of the extracted power into the grid is achieved with high quality.

This paper aims to propose a new approach of territorial competitiveness assessment revisited from the resource-based view, as the combination of location-specific resources and capabilities can improve the territorial socio-economic development. A territorial competitiveness index is calculated in order to assess the potential of renewable energy sources to improve the sustainable development in islands. Different sources of information and methodologies have been employed to measure the variables included in the model, thus ensuring a rigorous process in the index calculation. In order to quantify the basic resources, for example, a methodology based on a multicriteria analysis (MCA) with geographic information system (GIS) is suggested, with the objective of obtaining an indicator called index of available territorial resources. This index synthesizes the map information through a numerical value that allows integrating the territorial resource with other indicators of the model. The results of the study show that capability development is a key factor to better exploit the territorial resource endowment in order to achieve a competitive advantage.

While microcredits are, by the development practitioners, repeatedly hailed as a useful measure of development policy, this empirical research in Bangladesh arrives at different results: the governing and disciplinary measures are necessary to trigger the best possible repayment success. Based on interviews with the microfinance beneficiaries, loan officers, and microfinance experts in Bangladesh, I chart some of the most frequently used governing and disciplinary techniques including fictitious proximity of loan officers, their fields of visibility and surveillance processes. The “success” of credit delivery is a neoliberal stance that ensures the ceaseless debt repayment process using the intentional and planned conduct, capitalizing social capital and credit honour reputation, surveillance over business enterprises, use of equivocal language and different forms of deception. The development strategy through microfinance in Bangladesh is a development “dispositif” with a changing shift in its declared social missions.

To solve the problem of energy constraint and spectrum scarcity for cognitive radio wireless sensor networks (CR-WSNs), an underlay decode-and-forward relaying scheme is considered, where the energy constrained secondary source and relay nodes are capable of harvesting energy from a multi-antenna power beacon (PB) and using that harvested energy to forward the source information to the destination. Based on the time switching receiver architecture, three relaying protocols, namely, hybrid partial relay selection (H-PRS), conventional opportunistic relay selection (C-ORS), and best opportunistic relay selection (B-ORS) protocols are considered to enhance the end-to-end performance under the joint impact of maximal interference constraint and transceiver hardware impairments. For performance evaluation and comparison, we derive exact and asymptotic closed-form expressions of outage probability (OP) and throughput (TP) to provide significant insights into the impact of our proposed protocols on the system performance over Rayleigh fading channel. Finally, simulation results validate the theoretical results.

Chinese investors are easily affected by hot topics on the media and Internet and likely take irrational behavior. They tend to consume rationally and invest emotionally. This research aims to analyze the Baidu index’s effect on share price of solar power industry in China. Three main models are established to identify the correlation between Baidu index and stock price of solar industry. The media index and searching index of Baidu are chosen as an independent variable to measure the influence from media and Internet, and stock price as the dependent variable. To improve and complete the analysis, Hexun index is taken into consideration as mediator variable. This study applied Multiple Linear Regression Model and VAR (Vector auto-regression) Model. The research mainly uses the tools of SPSS, Eviews and Excel to conduct data analysis. The test is based on the theories of Granger Causality, unit root test, F-test, and t-test. The research proves the relationship between the close price of stock and Baidu index, and it also created a model for further forecasting.

A modular switched-capacitor (SC) DC-DC converter (MSCC) is introduced in this paper. It is designed to boost a low input voltage to a high voltage level and can be applied for photovoltaics and electric vehicles. This topology has high extensibility for high voltage gain output. The merits of the converters also lie in the fault tolerance operation and the voltage regulation with a minimum change in the duty ratio. Those features are built in when designing the modules and then integrating these into the DC-DC converter. Converter performance including voltage gain, voltage and current stress are focused and tested. The converter is modelled analytically, and its control algorithm is analyzed in detailed. Both simulation and experiment are carried out to verify the topology under normal operation and fault mode operation.

This work aims to develop an integrated fault location and restoration approach for microgrids (MGs). This work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (BCBV) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of fault, the voltage variation at each bus is calculated by using the Zbus modification algorithm to modify Zbus. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations is utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve the fault location and restoration problem in MGs.

This article reports a novel and efficient method to synthesize graphene by thermal decomposition process. In this method, silicon carbide (SiC) thin films grown on Si(100) wafers with an AlN buffer layer were used as substrates. A CO₂ laser beam heating without vacuum or controlled atmosphere was applied for SiC thermal decomposition. The physical, chemical, morphological, and electrical properties of the laser-produced graphene were investigated for different laser energy densities. The results demonstrate that graphene was produced in form of small islands with quality, density and properties depending on the applied laser energy density. Furthermore, the produced graphene exhibits a sheet resistance characteristic similar to graphene grown on mono-crystalline SiC wafer, which indicates its potential for electronic device applications.

China combines green energy and industrial policy in its power market reform with various policy initiatives, including price support scheme for electricity from renewable sources and subsidies in the push for broader use of greener energy. This study focuses on the impacts of power market reform on the stock price volatility of listed power companies: 1) we use the Iterative Cumulative Sums of Squares (ICSS) algorithm to identify structural break points in stock prices; 2) we analyze the characteristics of stock price volatility based on the GARCH model; 3) we report the impact of power regulation on stock price fluctuations based on the Autoregressive Distributed Lag (ARDL) model. The result suggests three structural breaks in China’s power stock price volatility were related to the promulgation of power market reform policies. We find that industrial policies promote the reduction of power stock price fluctuations and its impact on power stock price volatility is consistent in the long run. However, our study also indicates the recent policies related to renewable energy do not have a very significant impact on the power stock market.

Mobile robots can perform tasks on the move, including exploring terrain, discovering landmark features or moving a load from one place to another. This group of robots is characterized by a certain level of intelligence allowing making decisions and responding to stimuli received from the environment. As part of Industry 5.0, such mobile robots and humans are expected to co-exist and work together in a shared environment to make human work less tiring, quicker, and safer. This can only be realized when clean, dense, and economical energy sources are available. The aim of the study is to analyze the state of the art and to identify the most important directions for future developments in robotic power systems based mainly on batteries. The efficiency and performance of the battery depends on the design using different materials. Work environments and performance requirements are considered in this systematic review to classify solutions that help developers choose the best suited power system for specific application. Indirectly, the aim of the work is to generate discussion within the scientific and engineering community. A narrative review of publications from six major bibliographic databases according to preset inclusion criteria was combined with a critical analysis of current and future technologies. The main findings of the review allow answering question what is the role of modern power source technologies, artificial intelligence and ground-breaking research work in global policies related to energy saving, green policies, and sustainable development. The main opportunities and threats are discussed, and a brief feasibility analysis is carried out. Novelty of the article relates not only to the analysis of technologies, but also to approaches and their use under conditions of limited resource availability, when resource usage must be minimized. The article provides an overview of batteries, their specifications, classifications, and their advantages and disadvantages. In addition, we propose: (1) an algorithm for selecting main energy source for robot application, and (2) an algorithm for selecting electrical system power supply. Current mobile robot batteries are, in most cases, their biggest limitation. Progress in batteries development is too slow to catch up with the demand for robot autonomy and range requirements, limiting the development of mobile robots. Further intensive research and implementation work is needed to avoid years of delay in this area.

Directional protective relaying based on amplitude comparison of traveling wave on continuous co-phase auto-transformer(AT) power transmission system was proposed. Phase-model transformation is used for decoupling transient fault signals and get aerial mode component. The forward and backward traveling wave are obtained by calculating aerial mode component, then the intrinsic mode function(IMF) components can be obtained through Variational Mode Decomposition(VMD), the module maxima are obtained through calculating the IMF components. The fault direction is determined by the ratio of fault components. If two faults relays at the ends of electric traction networks detect a fault to be in the forward direction, the fault occurred in the internal area, the protection would operate properly. The simulation tests indicate that the protection scheme is feasible, and the proposed protection method can discriminate internal faults from external faults under various fault types, and its performances are immune to fault initial angle, ground resistance, etc.

Harmonic resonances are part of the Power Quality (PQ) problems of electrified railways and have serious consequences for the continuity of service and integrity of components in terms of overvoltage stress. The interaction between Traction Power Stations (TPSs) and trains that causes line resonances is briefly reviewed showing the dependence on infrastructure conditions. The objective is real-time monitoring of resonance conditions seen first of all from the onboard panto-graph interface, but it is equally applicable at TPS terminals. Voltage and current spectra, and de-rived impedance and power spectra, are analyzed proposing compact and efficient methods based on Short-Time Fourier Transform, suitable for real-time implementation with the hardware avail-able for energy metering and harmonic interference monitoring. The methods are tested by sweeping long recordings taken at some European railways, covering cases of longer and shorter supply sections, with a range of resonance frequencies of about one decade. They give insight into the spectral behavior of resonances, their dependency on position and change over time, and criteria to recognize genuine infrastructure resonances from rolling stock emissions.

On 2013 the Villonaco wind farm (16.5 MW), the first wind farm in continental Ecuador near the city of Loja, began operations. The power generated is delivered to the National Interconnected System (SNI), which services the city. This research confronts two sets of real data, the electricity use of the urban area of Loja, and the power generated by the Villonaco Wind Farm. Electricity use follows clearly defined daily and weekly cycles, and wind power has a seasonal behaviour. The study shows that wind power integration cannot be a long-term stable power source regardless power or generation surplus. Another essential finding is that time series can be used as a statistical source to determine the need for short- (seconds) and long- (days, weeks) term energy storage. Strategies to further the energy autonomy of the urban area through the expansion of the wind farm by a factor of 2 are discussed.

The basic equation for estimating the aerodynamic power captured by an Anderson Vertical Axis Wind Turbine (AVAWT) is a solution of the Navier-Stokes(N-S) equations for a baroclinic, inviscid flow. In a nutshell, the pressure difference across the AVAWT is derived from Bernoulli’s equation; an upshot of the integration of the N-S momentum equation for a baroclinic inviscid flow, Euler’s momentum equation. The resulting expression for the pressure difference across the AVAWT rotor is plotted as a function of freestream speed. Experimentally determined airstream speeds at the AVAWT inlet and outlet, coupled with corresponding freestream speeds are used in estimating the aerodynamic power captured. The aerodynamic power is subsequently used in calculating the aerodynamic power coefficient of the AVAWT. The actual power coefficient is calculated from the power generated by the AVAWT at various free stream speeds and plotted as a function of the latter. Experimental results show that, at all free stream speeds and tip speed ratios, the aerodynamic power coefficient is higher than the actual power coefficient of the AVAWT. Consequently, the power generated by the AVAWT prototype is lower than the aerodynamic power captured, given the same inflow wind condition.

Integrated photovoltaic-fuel cell (IPVFC) systems, amongst other integrated energy generation methodologies are renewable and clean energy technologies that have received diverse research and development attentions over the last few decades due to their potential applications in a hydrogen economy. This article systematically updates the state-of-the-art of IPVFC systems and provides critical insights into the research and development gaps needed to be filled/addressed to advance these systems towards full commercialisation. The design methodologies, renewable energy-based microgrid and off-grid applications, energy management strategies, optimisations and the prospects as self-sustaining power source were covered. IPVFC systems could play an important role in the upcoming hydrogen economy since they depend on solar hydrogen which has almost zero emissions during operation. Highlighted herein are the progresses as well as the technical challenges requiring research efforts to solve to realise numerous potential applications of IPVFC systems such as in unmanned aerial vehicles, hybrid electric vehicles, agricultural applications, telecommunications, desalination, synthesis of ammonia, boats, buildings, and distributed microgrid applications.

Various renewable energy sources such as wind power and photovoltaic (PV) have been increasingly integrated into the power system through power electronic converters in recent years. However, power electronic converter-driven stability issues under specific circumstances, for instance, modal resonances might deteriorate the dynamic performance of the power systems or even threaten the overall stability. In this paper, the integration impact of a hybrid renewable energy source (HRES) system on modal interaction and converter-driven stability is investigated in an IEEE 16-machine 68-bus power system. Firstly, an HRES system is introduced, which consists of full converter-based wind power generation (FCWG) and full converter-based photovoltaic generation (FCPV). The equivalent dynamic models of FCWG and FCPV are then established, followed by the linearized state-space modeling. On this basis, converter-driven stability analyses are performed to reveal the modal resonance mechanisms of the interconnected power systems and the modal interaction phenomenon. Additionally, time-domain simulations are conducted to verify effectiveness of dynamic models and support the converter-driven stability analysis results. To avoid detrimental modal resonances, an optimization strategy is further proposed by retuning the controller parameters of the HRES system. The overall results demonstrate the modal interaction effect between external AC power system and the HRES system and its various impacts on converter-driven stability.

The arrival of new developments in the field of power electronics circuit’s applications in power systems builds new control strategy to improve voltage quality for power grid by overcome interruptions. Wind energy resources are unconventional resources and get advanced problems to power grid when it is connected. Uncertainty of load sharing, peak energy management, climatic conditions, wind velocity and wind energy injected into power grid leads many of power quality problems on power grid based on the existing guidelines specified in IEC-61400 standard. This system plans efficient operation of DFIG to eliminate the voltage collapse and mismatch frequency to power grid. The DFIG connected diode rectifier and rotor side converter wind generator works as an Efficient Static Synchronous Compensator (E-SATCOM) for supplying the demand of reactive power for power grid to mitigate PQ problems. The benefit of using a combined controller was verified by simulink/Matlab and its simulated results used Doubly Fed Induction Generator (DFIG), wind Turbine. This simulation results gives good quality transient and stable state response to manage and support reactive power for both symmetrical and unsymmetrical faults in connection of grid codes to provide continuous quality of power supply, multiple wind generators are required for 140 bus power grid.

Neuroscientists are able to detect physical changes in information entropy in available neurodata. However, the information paradigm is inadequate to fully describe nervous dynamics and mental activities such as perception. This paper provides an effort to build explanations to neural dynamics alternative to thermodynamic and information accounts. We recall the Banach–Tarski paradox (BTP), which informally states that, when pieces of a ball are moved and rotated without changing their shape, a synergy between two balls of the same volume is achieved instead of the original one. We show how and why BTP might display this physical and biological synergy meaningfully, making it possible to tackle nervous activities. The anatomical and functional structure of the central nervous system’s nodes and edges allows to perform a sequence of moves inside the connectome that doubles the amount of available cortical oscillations. In particular, a BTP-based mechanism permits scale-invariant nervous oscillations to amplify and propagate towards far apart brain areas. Paraphrasing the BPT’s definition, we could state that: when a few components of a self-similar nervous oscillation are moved and rotated throughout the cortical connectome, two self-similar oscillations are achieved instead of the original one. Furthermore, based on topological structures, we illustrate how, counterintuitively, the amplification of scale-free oscillations does not require information transfer.

Power system decentralization has been an emerging topic for the past decade in an effort to improve power quality and environment protection via increased integration of renewable energy sources. Towards these objectives, decentralized microgrids have been proposed and thoroughly investigated in terms of technical capabilities and economic performance. In fact, the planning and actual operation of small-scale, decentralized microgrids has started in countries such as Canada, Japan, USA, UK and other countries. It is expected that the research in this area will progress and eventually take over the existing paradigm of large-scale power generation in the future. These small-size decentralized microgrids could be connected with nearby microgrids under normal operating conditions, but under special events, such as natural or man-made disasters, they would be disconnected and run in islanded mode. Under such high impact – low probability events, the microgrid must have resiliency to successfully re-connect with other microgrids and the main grid. In this paper, an Energy Management System (EMS) for a microgrid having a resiliency function, allowing to operate under islanded mode after an accident, is proposed. The proposed tool, called Resilient Energy Management System (ResEMS), aims at procuring reserve power into the microgrid’s Battery Energy Storage System (BESS) effectively, by importing it from the nearby connected power system. The accident is assumed to be a predictable natural disaster, which means that the accident occurrence time, duration and level of damage can be estimated. The proposed ResEMS has been applied to a microgrid comprising of a BESS, a diesel generator and several photovoltaic devices. The simulation results verify its beneficial operation.

This study analyses the short-run hydro generation scheduling for the wind power differences from the contracted schedule. The approach for construction of the joint short-run marginal cost curve for the hydro-wind coordinated generation is proposed and applied on the real example. This joint short-run marginal cost (SRMC) curve is important for its participation in the energy markets and for economic feasibility assessment of such coordination. The approach credibly describes the short-run marginal costs which this coordination bears in “real life”. The approach is based on the duality framework of a convex programming and as a novelty combines the shadow price of risk mitigation capability and the water shadow price. The proposed approach is formulated as a stochastic linear program and tested on the case of the Vinodol hydropower system and the wind farm Vrataruša in Croatia. The result of the case study is a family of 24 joint short-run marginal cost curves.

In this work, it is analyzed a Digital Signal Processor, DSP, based One Cycle Control, OCC, strategy for a Power Factor Corrector, PFC, rectifier, which presents Common-mode Voltage, CMV, immunity. The proposed strategy utilizes an emulated-resistance-controller in closed-loop configuration to set up dc-link voltage and achieve unity power factor, UPF. It is shown that if PFC can achieve UPF condition and if phase voltage is only affected by CMV, then phase current is free from CMV, as well as a lead-lag compensator, LLC, to average phase current. Another possible condition is also analyzed. The proposal is verified by simulation and experiments.

To reduce solar power production invariance, it is critical to study varying patterns of power production in the concerned region. Analyzing the patterns of past power production trends can help simulate power production scenarios for future. The current study area is around Amsterdam, located in Netherlands. PVoutput.org website is used to mine 6 months of solar power production data for 120 stations around Amsterdam city. FME Workbench software is used to actively fetch the data from the mentioned website and manage in a MySQL database. Solar attenuation maps created using ArcGIS, helped to graphically visualize the variations in solar power production at different times and locations. Further, spatial autocorrelation is checked between the stations using semi-variograms in geostatistical tool of ArcMap. This feature allows to check whether the stations located close to each other are more correlated to each other rather than stations which are far apart. The statistical data analysis of power production can aid solar power production companies to better interpolate and predict solar power in advance for the concerned study region.

In this study, a tuned mass damper is proposed as a seismic acceleration mitigating technique of an electrical cabinet inside the nuclear power plant. In order to know the mitigation performance, the electrical cabinet and the tuned mass damper were modeled using SAP2000. The sine sweep wave was used to confirm the vibration characteristics of the cabinet over a wide frequency range, and the several various earthquakes were applied to the cabinet to verify the control performance of the tuned mass damper. After analyzing the numerical results, it is summarized that the application of the proposed technique can reduce the acceleration response of the cabinet.

The paper presents the results of energy and environmental analysis of geothermal CHP plant operation in Polish conditions. As the most favorable, for the geothermal conditions prevailing in Poland, the variant of CHP plant based on Organic Rankine Cycle (ORC) has been taken into consideration. As the case study the existing geothermal well located in the town of Konin in the Wielkopolska voivodship has been chosen. The conceptual design of CHP plant has been proposed and evaluated from energy and environmental point of view. As energy performance criteria the non-renewable primary energy consumption has been chosen. In case of environmental performance carbon dioxide emission has been taken as evaluation criteria. The analysis has been performed for different operating conditions and three working fluids.

Generator automatic voltage control device (AVC) is an automatic voltage and reactive power optimization control terminal on the power plant side. Aiming at improving the performance of generator automatic voltage control device, this paper introduces a detection method of AVC substation performance based on virtual dispatching terminal environment. During the testing, the upper computer of redundant power plant is connected to the virtual dispatching terminal environment to simulate the sending instructions of AVC master station, the behavior of AVC sub stations and the excitation system of generators. The performance of AVC substation is evaluated according to the feedback adjustment results, which can effectively detect the abnormal behavior of AVC substation in power plant.

In response to the problem of increasing climate change and energy security, investment in renewable energy sources has increased significantly both in Europe and globally. Wind and solar power plants are expected to be the largest contributors to global decarbonization, ranking first and second in projected capacity by 2050. Since all power plants have some impact on the environment, this also applies to photovoltaic power plants. Because of the large capacities projected for PV installed capacity, their environmental impacts should be evaluated. The environmental impacts of PV power plants change over time. Improving the manufacturing technology of PV system components, increasing the efficiency of solar cells, and using materials that are less harmful to the environment will reduce these impacts. Manufacturing PV system components is a highly energy-intensive process that involves greenhouse gas emissions. As new renewable energy capacity is built, the amount of "green" electricity on the grid increases, reducing CO2 emissions per kWh consumed. The objective of this paper is to analyze the current status of the environmental impact of PV power plants under these changing conditions in terms of CO2 emissions, land use, pollutant and noise emissions, and water consumption. The capacity installed to date will reach the end of its lifetime by 2050, which means that the amount of waste associated with it will increase over time. This can have a significant impact on the environment, which is why part of the work is dedicated to this problem. In addition to the available information from the literature, in the part related to land use, the authors also made their own estimates based on data on newly installed PV power plants and PV modules available on the market. The results of the analysis show that there is enough land both in Europe and worldwide to install the planned capacities of rooftop and ground-mounted PV power plants. CO2 emissions are at the same level as for concentrated solar power, with a decreasing trend. Pollutant emissions, noise and water consumption are not a major problem compared to other types of power plants. Overall, it can be concluded that the expansion of PV capacity has a very positive impact on the environment.

Increasing distributed generation and intermittency, along with the increasing frequency of extreme weather events, impose a serious challenge for the electric power supply security. Understanding the costs of interruption is vital in terms of enhancing the power system infrastructure and planning the distribution grid. On the other hand, customer rights and demand response techniques are further reasons to study the worth of power reliability. In this paper, the authors make use of directional distance function and shadow pricing method for a case study from Finland. The aim is to calculate the cost of one minute of power interruption from the distribution network operator perspective. The sample consists of 78 distribution network operators from Finland with cost and network information between 2013 and 2015.

The recent advancements in the field of communication have led data sharing to become an integral part of today's smart cities with the evolution of concepts such as the internet of vehicles (IoV) paradigm. As a part of IoV, Electric Vehicles (EVs) have recently gained momentum as authorities have started expanding their Low Emission Zones (LEZ) in an effort to build green cities with low carbon footprints. Energy is one of the key requirements of EVs not only to support the smooth and sustainable operation of EV itself but to also ensure connectivity between the vehicles and infrastructure with controlling devices like sensors and actuators installed within an EV. In this context, renewable energy sources (such as wind energy) dramatically play their parts in the automobile sector towards designing the energy harvesting electric vehicles (EH-EV) to pare the energy reliance on the national grid. In this article, a novel approach is presented to achieve electric generation due to vehicle mobility to support the communication primitives in electric vehicles which enables plenty of IoV use cases in the presence of surplus energy at hand. A small-scale wind turbine is designed to harness wind power for converting it into mechanical power. This power is then fed to the onboard DC generator to produce electrical energy. Furthermore, the acquired power is processed through a regulation circuitry to consequently achieve the desired power supply for the end load, i.e. the batteries installed. The suitable orientation for efficient power generation is proposed on ANSYS-based aerodynamics analysis. The voltages induced by DC generator at No-Load condition are 35V while at Full-Load 25V are generated at rated current of 6.9A, along with the generation of power at around 100W (at constant voltage) at the rated speed of 90 mph for nominal battery charging. Moreover, the acquired data can be monitored via an android application interface by using a Bluetooth module.

The system design for Sustainable manufacturing is to consider both ecological and financial constraints. Manufacturing industry demands to advance in sustainable manufacturing by accounting in environment factors in it. All the factors that affect the environment need to be analyzed so that proper amendments or suggestions can be provided. To favour this, Computer aided life cycle inventory model has been presented for CNC milling and turning processes. Based on utilization of resources and stages, whole machining operation time can be divided into three phases named as process (milling or turning), idle and basic times. As parameters are different for evaluating the process times i.e. depth and width of cut in case of milling and initial and final diameters for turning, two different case studies has been presented one for each milling and turning process. Effect of material choice has been studied for different processes. Highly dense and hard materials takes more time in finishing the job due to low cutting speed and feed rates as compared to that of sot materials. In addition, face milling takes more time and consumes more power as compared to peripheral milling due to more retraction time caused by over travel distance and lower vertical transverse speeds than the horizontal transverse speed used in peripheral retraction process.

History is often thought to be dull and boring – where large numbers of facts are memorized for passing exams. But the past informs the present and future, especially in delineating the context surrounding specific events that, in turn, help provide a deeper understanding of their causes and implications. Scientific progress (whether incremental or breakthroughs) is built upon prior work. Chronological examination of computational chemistry’s evolution reveals the existence of major “epochs” (e.g., transition from semi-empirical methods to first principles calculations), and the centrality of key ideas (e.g., Schrodinger equation and Born Oppenheimer approximation) in potentiating progress in the field. The longstanding question of whether computing power (both capacity and speed) or theoretical insights play a more important role in advancing computational chemistry was examined by taking into account the field’s development holistically. Specifically, availability of large amount of computing power at declining cost, and advent of graphics processing unit (GPU) powered parallel computing are enabling tools for solving hitherto intractable problems. On the other hand, this essay argues (using Born Oppenheimer approximation as an example) that theoretical insights’ role in unlocking problems through simple (but insightful) assumptions is often overlooked. Collectively, the essay should be useful as a primer for appreciating major development periods in computational chemistry, from which counterfactual questions illuminate the relative importance of theoretical insights and advances in computer science in moving the field forward.

Coal combustion in thermal power plants releases ash. Ash is reported to cause different adverse health hazards in humans and other organisms. Owing to the presence of radionuclides, it is also considered as a potential radiation hazard. In this study, based on the surface radiation measurements and relevant ancillary data, expected radiation risk zones were identified with regard to the human population residing near the Thermal Power Plant. With population density as the risk determining criteria, about 20% of the study area was at ‘High’ risk and another 20% of the study area was at ‘Low’ risk zone. The remaining 60% was under medium risk zone. Based on the findings remedial measures which may be adopted have been suggested.

One of the most crucial and economically beneficial tasks for energy customer is peak load curtailment. On account of the fast response of renewable energy resources (RERs) such as photovoltaic (PV) units and battery energy storage system (BESS), this task is closer to be efficiently implemented. Depends on the customer peak load demand and energy characteristics, the feasibility of this strategy may warry. When adaptive neuro-fuzzy inference system (ANFIS) is exploited for forecasting, it can provide many benefits to address the above-mentioned issues and facilitate its easy implementation, with short calculating time and re-trainability. This paper introduces a data driven forecasting method based on fuzzy logic for optimized peak load reduction. First, the amount of energy generated by PV is forecasted using ANFIS which conducts output trend, and then, the BESS capacity is calculated according to the forecasted results. The trend of the load power is then decomposed in Cartesian plane into two parts, left and right from load peak, searching for BESS capacity equal. Network switching sequence over consumption is provided by a fuzzy logic controller (FLC) with respect to BESS capacity and PV energy output. Finally, to prove the effectiveness of the proposed ANFIS-based peak shaving method, offline digital time-domain simulations have been performed on a real-life practical test micro grid system in MATLAB/Simulink environment and the results have been experimentally verified by testing on a practical micro grid system with real-life data obtained from smart meter and also, compared with several previously-reported methods.

Considering the fault "N-1" checksum and the power flow, the single-phase power flow model is further transformed into a three-phase power flow model, and the asymmetry of the three-phase power flow is measured by the three-phase unbalance factor. The calculation model is linearized by the second-order cone relaxation and the Big-M method. At the same time, the load response and distribution network reconstruction are used to improve the reliability of the power supply network to cope with the power failure. The relationship between power supply capability and power flow constraints, main transformer capacity and distributed power parameters is analyzed by IEEE 33-node three-phase power distribution system. The feasibility of the proposed model and the accuracy of the second-order cone relaxation are verified by numerical examples, which provides a technical reference for distribution network planning.

The central limit theorem (CLT) and its generalization to stable distributions have been widely described in literature. However, many variations of the theorem have been defined and often their applicability in practical situations is not straightforward. In particular, the applicability of the CLT is essential for a derivation of heterogeneous ensemble of Brownian particles (HEBP). Here, we analyze the role of the CLT within the HEBP approach in more detail and derive the conditions under which the existing theorems are valid.

The differential transformation, an approach based on Taylor's theorem, is proposed as convenient for finding exact or approximate solution to the initial value problem with multiple Caputo fractional derivatives of generally non-commensurate orders. The multi-term differential equation is first transformed into a multi-order system and then into a system of recurrence relations for coefficients of formal fractional power series. The order of the fractional power series is discussed in relation to orders of derivatives appearing in the original equation. Application of the algorithm to an initial value problem results in a reliable and expected outcome.