Research On Smart Home Energy Management System With Household Distributed Photovoltaic Generation

As an important component of smart grid, distributed photovoltaic(PV) generation has the advantages of high sustainability, efficiency as well as flexibility and load shifting, which enables it to promote energy saving and emission reduction, improve energy structure of the utility grid and realize the sustainability of economic development. To promote the development of distributed PV generation, the government encourages the public residents to install PV generation system in their houses by announcing subsidy policies. Therefore, distributed PV generation in resident side is under a quick development and it becomes the research focus how to increase the efficiency of household energy consumption and cut the electricity bill by using PV generation.In this thesis, a comprehensive research is carried out of home energy management with a grid-connected PV generation. Firstly, related background knowledge is introduced, including the key technologies and components of distributed PV generation, the structure of home energy management system, related subsidy policies and the economic analysis of the system. Secondly, a smart home system platform is built, including hardware and software design, to connect the PV generation and household appliances efficiently. A module to measure and collect electric information is developed based on CS5463 and a module to transmit data and information through ZigBee to the central controller is developed based on CC2530. A wireless network is built combining all the modules to monitor the operation situation of the PV generation and household appliances and control appliances in distance. Also, a central controller and a mobile APP are developed to realize long distance monitor and control. Thirdly, a mathematic model of household energy consumption is built according to the PV output, the operation feature of appliances and the varying electricity tariff. To obtain the optimal solution of the model efficiently, a modified genetic algorithm(GA) is introduced according to the features of the mathematic model. At last, simulations are carried out according to a given case which includes energy data of a house. Through the calculation the optimal schedule can be obtained and the performance of GA in this model can be testified, including stability, efficiency and precision.The smart home energy management system proposed in the thesis can manage the household PV generation and appliances efficiently and cut the electricity bill of the resident, providing a significant reference of promotion of PV generation in resident side.