Journal of Guangdong University of Technology ›› 2019, Vol. 36 ›› Issue (06): 66-73.doi: 10.12052/gdutxb.190034

• Comprehensive Studies • Previous Articles     Next Articles

A Household Electricity Load Optimal Control Strategy Based on Local Particle Swarm Optimization

Wu Dan-qi1, Lai Chun Sing1,2, Yang Jun-hua1, Li Xue-cong1, Lai Loi Lei1, Xiong Feng-jun1   

  1. 1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China;
    2. Faculty of Engineering, The University of Leeds, Leeds LS2 9JT, UK
  • Received:2019-03-11 Online:2019-11-28 Published:2019-11-01

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Abstract: In order to optimize the household electricity load, an optimal control strategy is proposed for household electricity consumption to minimize the total electricity charges under the time-of-use electricity pricing policy. Local Particle Swarm Optimization (LPSO) algorithm is used to minimize the electricity charges of four kinds of household electricity loads, and then compared with no-optimization treatment and traditional Particle Swarm Optimization (PSO) respectively. Using Python software, the mathematical model is built and simulated tests are carried out. The simulation results show that LPSO can significantly reduce the total electricity charges and has the advantages of strong global search ability and fast convergence speed, which can be applied to relevant researches in the field of household energy management.

Key words: household energy management, time-of-use pricing, simulation experiment, local particle swarm optimization

CLC Number: 

  • TM73
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