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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.
This paper presents a household energy management mechanism for residential users’ demand response.Considering the controllable load of users, the joint scheduling of electric vehicles and energy storage systems, and the random fluctuation of distributed photovoltaic power generation and uncontrollable load, The user-desired stochastic optimization model, which aims to minimize the cost of electricity, uses a hybrid optimization algorithm combining binary particle swarm optimization and interior point method to solve the optimization model. The algorithm applies binary particle swarm optimization to discrete variables And then apply the in-point method to deal with continuous variables, which overcomes the shortcomings that the binary particle swarm optimization algorithm is difficult to deal with complex equations and inequality constraints.The simulation results show that the proposed optimization model and the proposed algorithm can reduce the impact of randomness on the scheduling results and help Users reduce electricity costs.