Submitted:
16 December 2023
Posted:
18 December 2023
Read the latest preprint version here
Abstract
Keywords:
1. Introduction
2. Evaluating the Evolution of Efforts to Contest the Law of Energy Conservation
2.1. Scientific Perspective
2.2. Philosophical Perspective
2.3. Historical and Modern Shifts
2.4. The Need for a New Approach
3. Breaking the Law of Energy Conservation
3.1. The Energy Circuit-Unleashing the Power of Electrical Short Circuits
3.2. Design of the Proposed Energy Circuit (The Main Energy Circuit Operational Units)
3.2.1. Circuit Component 1 (Power Source): The energy circuit begins with a power supply (for safety check, a direct voltage and direct current power source is selected). This power source (variable power supply or using different rating power sources may be considered, as applied in this paper) represents the starting point of the energy conservation challenge. Details on the starting current, the connecting codes (conductors) practical resistance (and conductors material types) will be of importance in working out the input power for the subsequent circuit blocks, modeling the real world scenarios.
- is the diode current.
- is the reverse saturation current.
- is the voltage across the diode.
- is the ideality factor (typically around for ideal diodes).
- is the thermal voltage, approximately at room temperature.
3.2.2. Operation Principles of “Circuit Block 1” (Establishing Higher Resistive Circuit Element)

3.3. Harnessing the Short Circuit Power (“Circuit Block 2”)
3.3.1. Description of “Circuit Block 2” Components

3.4. Advancing Energy Transformation (“Circuit Block 3”)
3.4.1. Load Component_CB3
3.4.2. Boost Converter (“Load Component_CB3”) Design Mathematical Description
- is the inductor value.
- is the desired output voltage.
- is the input voltage.
- is the duty cycle of the converter.
- is the switching frequency.
- is the peak-to-peak inductor ripple current.
3.5. Energy Storage Component (“Circuit Block 4”)
3.5.1. The Choice for “Circuit Block 4” Unit
3.6. Automation and Safety Control (“Circuit Block 5”)
3.6.1. Design and Operation of the Sensing Element in “Circuit Block 5”
3.6.2. The Sensing Element Operation Mechanism
3.7. Overall Energy Circuit Representation
3.8. Interpretation and Simulation of the Proposed Energy Circuit Blocks
3.8.1. Simulated Results and Analysis
3.8.2. Description of Main Sections of the Simulation
3.8.3. Analysis of Simulation Results
3.8.4. Power Output from “Circuit Block 3”
3.9. How the Energy Circuit Breaks the Law of Energy Conservation
3.10. Possible Applications of the Energy Circuit-Addressing Some Critical Challenges
3.10.1. Energy Creation and Conservation
3.10.2. Applications in Electric Vehicles (EVs)
3.10.3. Microgrid Development
3.10.4. Renewable Energy Integration
3.10.5. Addressing the Energy Crisis
4. Discussion and Implications
4.1. Breaking Misconceptions and Limitations in Energy Conservation
4.2. Contributions to Addressing the Global Energy Crisis
4.3. Solutions to Noise Pollution and Innovations in Electric Vehicles
4.4. Greenhouse Gas Reduction and Addressing Current Clean Energy Systems
4.5. Innovations in Electronic Materials and Semiconductor Development
4.6. Challenging Philosophical Assumptions and Scientific Thinking
4.7. Merits over Current Systems-A Paradigm Shift in Energy Conservation
5. Conclusion
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A: Energy Circuit Simulation and Interpretation
Energy Circuit Simulation Code # This code was developed and executed on Google Colab
#Prepare/Import the necessary libraries
# You may need to begin by installing: #!pip install PySpice
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
# Circuit Component 1 (Power Source)
V_source = 10 # Source voltage in volts
R_conductors = 10 # Resistance of connecting conductors in ohms
# Power input to the diodes in “Circuit Block 1”
I_CB1 = V_source / R_conductors
# “Circuit Block 1”
n = 1.1 # Ideality factor
Vt = 0.0259 # Thermal voltage at room temperature
# Diode parameters
I_s = 1.5e-14 # Saturation current for diodes
# Diode voltages
V_D1 = 0.7 # Example forward voltage drop for diodes
V_D2 = 0.0
# Calculate total current through Block 1 (I_CB1)
I_CB1 = I_s * (np.exp(V_D1 / (n * Vt)) + np.exp(V_D2 / (n * Vt)) - 2) # Equation (4)
# Voltage across Block 1
V_CB1 = V_D1+ V_D2
# “Circuit Block 2”
R_0 = 1.5 # Reference resistance
R_short = 0.001 # Resistance change due to short circuit
V_CB2 = 0.8 * V_CB1 # Voltage drop after short circuit
a = V_source / R_0 # Current scaling factor
# Calculate short circuit effect current
I_short_circuit_effect = a * np.exp(R_short / R_0)
# Calculate power input to Block 2
P_out_CB2 = V_CB2 * I_short_circuit_effect
# Calculate effective resistance in Block 2
R_CB1_overall = R_conductors # Overall resistance in Block 1
R_short_effective = R_CB1_overall + R_short
# Design and set the Boost Converter Parameters
Vin = V_CB2 # Input voltage from the previous circuit (in volts)
Vout = V_source # Output voltage (in volts)
R = R_short_effective # Load resistance (in ohms)
L = 50e-6 # Inductor value (in henries)
C = 100e-6 # Output capacitor value (in farads)
fsw = 50e3 # Switching frequency (in hertz)
D = Vout / Vin # Duty cycle
# Use the short circuit current as the initial inductor current
IL_initial = I_short_circuit_effect
# Function to define the boost converter differential equations
def boost_converter(y, t):
IL, VC = y # Inductor current and capacitor voltage
# Function to define the boost converter differential equations
def boost_converter(y, t):
IL, VC = y # Inductor current and capacitor voltage
# Boost Converter Equations
dIL_dt = (Vin * D - Vout) / L
dVC_dt = IL / C
return [dIL_dt, dVC_dt]
# Initial conditions with short circuit current
initial_conditions = [IL_initial, Vout * D]
# Time points for simulation
t = np.linspace(0, 2e-3, 1000) # 2 milliseconds simulation time
# Solve the boost converter differential equations
solution = odeint(boost_converter, initial_conditions, t)
# Extract results
IL = solution[:, 0]
VC = solution[:, 1]
VR = IL * R # Voltage across the load resistor
# Print results
print("Circuit Component 1:")
print("Current Input to Diodes (“Circuit Block 1”):", I_CB1, "A")
print("\n”Circuit Block 1”:")
print("Total Current (I_CB1):", I_CB1, "A")
print("Voltage Across Block 1 (V_CB1):", V_CB1, "V")
print("\n”Circuit Block 2”:")
print("Voltage Drop After Short Circuit (V_CB2):", V_CB2, "V")
print("Short Circuit Effect Current (I_short_circuit_effect):", I_short_circuit_effect, "A")
print("Power Output from Block 2 (P_out_CB2):", P_out_CB2, "W")
print("Effective Resistance in Block 2 (R_short_effective):", R_short_effective, "ohms")
# Print individual power values
print("\nPower Input to Diodes (“Circuit Block 1”):", V_CB1 * I_CB1, "W")
print("Power Input to Block 3 (P_out_CB2):", P_out_CB2, "W")
print("Power Output Block 3 (W):", VR[-1] * IL[-1]) # Print the last value to represent the total power output
# Print individual power values
print("\nPower Input to Diodes (“Circuit Block 1”):", V_CB1 * I_CB1, "W")
print("Power Input to Block 3 (P_out_CB2):", P_out_CB2, "W")
print("Power Output Block 3 (W):", VR[-1] * IL[-1]) # Print the last value to represent the total power output
# Print time, inductor current, capacitor voltage, and load voltage
print("\nTime (s)\tInductor Current (A)\tCapacitor Voltage (V)\tLoad Voltage (V)")
for i in range(len(t)):
print(f"{t[i]:.6f}\t{IL[i]:.6f}\t\t\t{VC[i]:.6f}\t\t\t{VR[i]:.6f}")
# Plot results
plt.figure(figsize=(10, 6))
plt.subplot(2, 1, 1)
plt.plot(t, IL, label='Inductor Current')
plt.xlabel('Time (s)')
plt.ylabel('Current (A)')
plt.legend()
plt.subplot(2, 1, 2)
plt.plot(t, VC, label='Capacitor Voltage')
plt.plot(t, VR, label='Load Voltage')
plt.xlabel('Time (s)')
plt.ylabel('Voltage (V)')
plt.legend()
plt.tight_layout()
plt.show()
Appendix B: The Modified Ohm's Law and Its Application in Breaking the Law of Energy Conservation (Reflecting Real-World Scenarios)
- is the short circuit effect current.
- is the current scaling factor.
- is the resistance change due to the short circuit.
- is the reference resistance.
- : This parameter represents the base resistance in the circuit, providing a reference point for current scaling. It sets the initial conditions for the circuit and influences the short circuit effect.
- : This parameter models the impact of a short circuit on “Circuit Block 2” resistance. It quantifies the change in resistance during a short circuit event, influencing the short circuit effect current.
- : The current scaling factor adjusts the magnitude of the short circuit effect current. It is directly proportional to the source voltage () and inversely proportional to . It scales the exponential term in the equation, determining the overall impact of the short circuit.
- The parameters , , and play a crucial role in replicating real-world scenarios in the proposed energy circuit. Table (1) showcases the application of these parameters under different supply voltage settings.
- : Adjust based on the desired initial resistance conditions. Depending of other circuit parameters, adjusting “” has a direct impact on the overall magnitude of the current. Larger “” values result in smaller current values for a given resistance.
- : Vary to simulate different short circuit scenarios. Larger values represent a more pronounced change in resistance during a short circuit.
- : is directly linked to the source voltage ( as applied in the simulation, Appendix I). As increases, increases, influencing the magnitude of the short circuit effect current.
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| Supply Voltage (V) | Diode Forward Voltage (V) | R0 (Ohms) | Ideality Factor (n) | Saturation Current () (A) |
(W) |
(A) |
(W) |
(W) |
|---|---|---|---|---|---|---|---|---|
| 0.7 | ||||||||
| 0.7 | ||||||||
| 0.7 | ||||||||
| 0.7 | ||||||||
| 0.7 | ||||||||
| 0.7 | ||||||||
| 0.7 | ||||||||
| 0.7 | ||||||||
| 0.7 | ||||||||
| 0.7 |
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