【摘要】 本文提出了一种面向居民用户需求响应的家庭能源管理机制.考虑了用户的可控负荷、电动汽车和储能系统的联合调度,以及分布式光伏发电和不可控负荷的随机波动,建立了以用户期望用电成本最小为目标的随机优化模型,采用了一种二值粒子群与内点法相结合的混合优化算法对优化模型进行求解.该算法应用二值粒子群处理优化模型中的离散变量然后应用内点法来处理连续变量,克服了二值粒子群算法难以处理复杂等式及不等式约束的缺点.仿真结果表明提出的优化模型及采用的算法能够减少随机性对调度结果的影响,帮助用户减少用电成本.更多还原

【Abstract】 This paper proposes a home energy management mechanism for residential demand response and formulates a stochastic optimal scheduling model aimed to minimize expected electricity costs by coordinating controllable appliances,electric vehicles,energy storage systems,and uncertainties in solar generation and uncontrollable loads. A mixed optimization algorithm combining binary particle swarm optimization( BPSO) and the interior point( IP) method is adopted to solve the model; this employs BPSO to handle discrete variables and the IP method to tackle continuous variables,which thus overcomes the weakness of BPSO in handling complex equations and inequation constraints. Simulation results show that the proposed optimization model and algorithm can reduce the effect of randomness on scheduling results and assist in reudcing electricity costs for residential customers.更多还原