Multi-Objective Voltage and Reactive Power Coordinated Control Strategy for Distribution Networks Utilizing Gaining-Sharing Knowledge Based Algorithm

Existing heuristic optimization algorithms are prone to obtain a set of non-dominated solutions overconcentrated within an intermediate area in the objective space. It results in a poor diversity performance of the Pareto front when handling the problem on multi-objective voltage and reactive power coordinated control (MOVRPOC). For mitigating the aforementioned disadvantages, a newly developed heuristic algorithm, gaining-sharing knowledge based algorithm (GSK), is implemented to handle the problem of MOVRPOC. Then, the minimum system losses, the minimum average voltage deviation and the minimum curtailment rate are treated as optimization objectives, and then the revised IEEE 33-bus distribution system is utilized as the benchmark networks. Grey wolf optimization (GWO) and equilibrium optimizer (EO) are taken as a comparison to validate the improvement on diversity of GSK. The results reveal that GSK is capable to obtain more diverse non-dominated solutions to MOVRPOC for distributed networks, which can be better applied to the practical scenarios on MOVRPOC distribution networks.