Coordinated Control of AGC and AVC based on Multi-objective Particle Swarm Optimization Algorithm

Abstract

Independent control mode of automatic generation control (AGC) and automatic voltage control (AVC) has exposed a lot of problems, including mutual influences between the control effect of each other and repeated adjustments of generators. In this paper, a coordinated automatic control system (CACS) of AGC and AVC is built, which can be described as a highly constrained multi-objective optimization problem (MOP). Indexes of economy, safety and quality are taken into account as the objective targets and the active power output and voltage magnitude of generators are selected as the control variables. Multi-objective particle swarm optimization (MOPSO) is used to solve this MOP and get the Pareto optimal set. Moreover, an approach of fuzzy decision making is presented to extract the best compromise solution from the Pareto optimal set. The proposed control strategy has been applied to New England 10-generator 39-bus system and several optimization simulations have been carried out on different control strategies. Results show the effectiveness of the proposed control system and strategy, which can obtain high quality solutions and is able to provide a satisfactory best compromise solution compared to the traditional techniques.