Title :
MF-APSO-Based Multiobjective Optimization for PV System Reactive Power Regulation
Author :
Hong-Tzer Yang ; Jian-Tang Liao
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
This paper proposes a reactive power-regulation strategy for a distribution system connected with high-penetration photovoltaic (PV) generation. The PV reactive power regulation is formulated as a multiobjective optimization problem to relieve the overvoltage caused by high PV penetration and to minimize total line loss. With integrated power-flow analysis, a new mutation fuzzy adaptive particle swarm optimization (MF-APSO) algorithm is proposed to solve the multiobjective optimization problem. The proposed reactive power-regulation strategy and MF-APSO algorithm are, respectively, compared with conventional methods for overvoltage mitigation and total line-loss reduction, as well as with the referenced optimization algorithms for the problems of concern. Numerical results verify that the proposed multiobjective optimization method can more effectively mitigate the overvoltage issue and greatly reduce the total line loss as compared to other methods. Utilization of high-penetration PV systems can thus be further enhanced with reduced power curtailment owing to the added functions of voltage regulation and line-loss minimization.
Keywords :
distribution networks; load flow; minimisation; overvoltage; particle swarm optimisation; reactive power control; solar cells; voltage control; MF-APSO-based multiobjective optimization; PV system reactive power regulation; distribution system; high-penetration photovoltaic generation; mutation fuzzy adaptive particle swarm optimization algorithm; overvoltage mitigation; power curtailment reduction; power flow analysis; referenced optimization algorithm; total line-loss reduction; voltage regulation; Algorithm design and analysis; Distributed power generation; Particle swarm optimization; Photovoltaic systems; Reactive power; Voltage control; Distributed power generation; Pareto-optimal set; particle swarm optimization (PSO); photovoltaic (PV) systems; reactive power control;
Journal_Title :
Sustainable Energy, IEEE Transactions on
DOI :
10.1109/TSTE.2015.2433957