A multistage multiobjective substation siting and sizing model based on operator–repair genetic algorithm

Abstract

The establishment of a multistage multiobjective substation siting and sizing planning model, taking into account various constraints such as load flow constraint, maximum capacity constraint, and maximum power supply radius constraint makes possible substation planning between multiple years to be adjusted to achieve an optimal overall plan. Through multiple optimization objectives, it is possible to prevent the plan from becoming useless because of excessive changes in power supply affiliation during the multistage optimization process. To find the optimal solution for the model, a repair operator is proposed and used with an improved multiobjective genetic algorithm to repair the decision variables for each chromosome corresponding to one stage so as to satisfy the constraints while ensuring that population diversity evolves heuristically to the optimal solution. Moreover, a tournament selection operator based on crowding distance is adopted, which can prevent the algorithm from premature convergence and make populations trend to the Pareto frontier. Experimental results show that the proposed model and algorithm can efficiently solve the issue of rolling planning between multiple target years and achieve a joint optimal planning. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.