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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
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.
Optimal scheduling model for smart home energy management system based on the fusion algorithm of harmony search algorithm and particle swarm optimization algorithm
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.
Optimal scheduling model for smart home energy management system based on the fusion algorithm of harmony search algorithm and particle swarm optimization algorithm
Zhang, Zhisheng (author) / Wang, Jidong (author) / Zhong, Haitao (author) / Ma, Hanjie (author)
Science and Technology for the Built Environment ; 26 ; 42-51
2020-01-02
10 pages
Article (Journal)
Electronic Resource
English
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