Residential Demand Response Scheduling Optimization and Simulation based on an Improved PSO Algorithm

doi:10.16182/j.issn1004731x.joss.20-FZ0473

Abstract

Abstract: Aiming at the problems of low utilization rate of household load energy and the potential damage to the power grid caused by the lack of systematic and efficient management of household power consumption, the power consumption characteristics of controllable equipment and the energy storage characteristics of electric vehicles are modeled respectively, and the scheduling optimization objective function of household equipment under time of use price is established, and the improved particle swarm optimization algorithm is used to solve the problem. Through the example simulation, the residential power dispatching under various scenarios is analyzed. The experimental results show that the proposed algorithm can satisfy the residents' power consumption comfort, and simultaneously reduce the power consumption cost and suppress the grid fluctuation.

Key words: demand response, time-of-use price, electric vehicle, power scheduling

CLC Number:

TP391

Li Huazhen, Liu Youquan, Zhu Jiawei, Liao Qiang. Residential Demand Response Scheduling Optimization and Simulation based on an Improved PSO Algorithm[J]. Journal of System Simulation, 2021, 33(8): 1969-1979.

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