Feeder Load Balancing using Fuzzy Logic and Combinatorial Optimization-based Implementation

TL;DR

This paper introduces a novel method combining fuzzy logic and combinatorial optimization to improve phase balancing in distribution systems, aiming for more efficient load reconfiguration.

Contribution

It proposes an integrated fuzzy logic and combinatorial optimization approach for feeder load balancing, enhancing reconfiguration accuracy and efficiency.

Findings

Effective load balancing achieved on South African distribution network.

Reduced energy losses through optimized phase reconfiguration.

Demonstrated improvement over traditional methods.

Abstract

The distribution system problems, such as planning, loss minimization, and energy restoration, usually involve the phase balancing or network reconfiguration procedures. The determination of an optimal phase balance is, in general, a combinatorial optimization problem. This paper proposes a novel reconfiguration of the phase balancing using the fuzzy logic and the combinatorial optimization-based implementation step back to back. Input to the fuzzy step is the total load per phase of the feeders. Output of the fuzzy step is the load change values, negative value for load releasing and positive value for load receiving. The output of the fuzzy step is the input to the load changing system. The load changing system uses combinatorial optimization techniques to translate the change values (kW) into number of load points and then selects the specific load points. It also performs the inter-changing of the load points between the releasing and the receiving phases in an optimal fashion. Application results using the distribution feeder network of South Africa are presented in this paper.