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Optimal scheduling model for smart home energy management system based on the fusion algorithm of harmony search algorithm and particle swarm optimization algorithm

机译:基于和声搜索算法融合算法和粒子群优化算法的智能家居能源管理系统最优调度模型

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摘要

In the research of energy internet, demand response has become a hot issue which has been widely concerned. Smart home energy management system, as a necessary means to realize the demand response, has become the focus of research. A smart home energy management system with multilayer structure is designed in this paper, which includes the interface layer, the control layer and the load layer. The interface layer is the human machine interface (HMI), the control layer is the central controller, and the load layer contains loads of various electrical equipment. Optimal scheduling model for smart home energy management system is constructed, which takes into account factors such as environmental change, electricity price, user habits, load fluctuation and so on. The fusion algorithm of harmony search algorithm and particle swarm optimization algorithm is used to solve the model, which got the program to meet the needs of users. The simulation results showed that the load curve was effectively improved, and the electricity cost was obviously reduced.
机译:在能源互联网的研究中,需求响应已成为一个已被广泛关注的热门问题。智能家居能源管理系统,作为实现需求响应的必要手段,已成为研究的重点。本文设计了一种具有多层结构的智能家庭能源管理系统,包括界面层,控制层和负载层。接口层是人机界面(HMI),控制层是中央控制器,负载层包含各种电气设备的负载。构建了智能家居能源管理系统的最佳调度模型,考虑了环境变化,电价,用户习惯,负荷波动等因素。和声搜索算法和粒子群优化算法的融合算法用于解决模型,其中有程序满足用户的需求。仿真结果表明,负载曲线有效改善,电力成本明显减少。

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