一种基于用户通勤行为的家庭能量管理优化策略

Optimization Strategy Based on Users′Commuting Behavior for Home Energy Management

随着电动汽车快速发展,V2G技术可大幅降低家庭能量管理系统中用户的用能成本,但V2G会影响用户出行。针对此问题提出了一种基于用户通勤行为的家庭能量管理系统优化策略,通过极大似然估计和蒙特卡罗模拟构建用户出行模型,其次将杂交粒子群与混沌算法、免疫算法相融合,利用多重混沌免疫杂交粒子群算法(MCIHPSO)对目标函数进行求解,最后,通过仿真及实验验证了本文所提控制策略显著降低V2G功能对用户出勤的影响。

With the rapid development of electric vehicles,V2G technology can greatly reduce the energy cost of users in the home energy management system,but V2G will affect user travel.This paper proposes an optimization strategy for home energy management system based on users′commuting behavior.The user travel model is constructed through maximum likelihood estimation and Monte Carlo simulation.Secondly,the hybrid particle swarm is integrated with chaotic algorithm and immune algorithm.Immune hybrid particle swarm optimization(MCIHPSO)is used to solve the objective function.Finally,simulation and experiments verify that the control strategy proposed in this paper can significantly reduce the impact of V2G function on user attendance.