Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm

Version 1 : Received: 22 February 2020 / Approved: 23 February 2020 / Online: 23 February 2020 (10:14:51 CET)

A peer-reviewed article of this Preprint also exists.

Grigoraș, G.; Neagu, B.-C.; Gavrilaș, M.; Triștiu, I.; Bulac, C. Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-based Algorithm. Mathematics 2020, 8, 549. Grigoraș, G.; Neagu, B.-C.; Gavrilaș, M.; Triștiu, I.; Bulac, C. Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-based Algorithm. Mathematics 2020, 8, 549.

Journal reference: Mathematics 2020, 8, 549
DOI: 10.3390/math8040549

Abstract

In the electric distribution systems, the “Smart Grid” concept is implemented to encourage energy savings and integration of the innovative technologies, helping the Distribution Network Operators (DNOs) in choosing the investment plans which to lead the optimal operation of the networks and increasing the energy efficiency. In this context, a new phase load balancing algorithm was proposed to be implemented in the low voltage distribution networks with hybrid structures of the consumption points (switchable and non-switchable consumers). It can work in both operation modes (on-line and off-line), uploading information from different databases of the DNO which contain: the consumers’ characteristics, the real loads of the consumers integrated into the Smart Metering System (SMS), and the typical load profiles for the consumers non-integrated in the SMS. The algorithm was tested in a real network, having a hybrid structure of the consumption points, on a time interval by 24 hours. The obtained results were analyzed and compared with other algorithms from the heuristic (Minimum Count of Loads Adjustment algorithm) and the metaheuristic (Particle Swarm Optimization and Genetic Algorithms) categories. The best performances were provided by the proposed algorithm, such that the unbalance coefficient resulted in the smallest value (1.0017). The phase load balancing led to the following technical effects: decreasing the average current in the neutral conductor with 94% and for the energy losses with 61.75 %, and increasing the minimum value of the phase voltage at the farthest pillar with the 7.14 %, compared to the unbalanced case.

Subject Areas

phase load balancing; smart meters; dynamic optimization; on-line implementation; low voltage electric distribution networks

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