基于局部粒子群算法的家庭用电负荷优化控制策略

提出一种分时电价政策下电能总花费最低的家庭用电负荷优化控制策略.采用局部粒子群算法对家庭中4类常见用电负荷的花费进行优化，与无优化处理和传统粒子群算法进行对比分析，并在Python平台上搭建数学模型和开展仿真实验.结果表明，局部粒子群算法可大幅度减少家庭用电花费，具有全局搜索能力强、收敛速度快等优点，可推广应用到家庭能源管理领域相关研究.

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

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.