Energy Optimization Management Of Smart Home System

At present,the world's energy consumption still depends on fossil energy,and the problems with energy security,environmental pollution,climate change become more and more prominent.To increase the proportion of renewable energy in the energy structure is the key to solve such problems.With the development of the smart grid and distributed power generation technology,smart home can achieve the greatest local consumption of distributed generation as an important component of smart grid,and also has drawn widely attention from scholars.Therefore,it is of great significance to establish models of supply side of smart homes and load,to analyze the influential factors such as transferable load,photovoltaic power generation,energy storage system on smart home optimization.Firstly,based on smart home energy supply side,this paper introduces the advantages of Distributed Generation(DG),classifies Photovoltaic System(PV)which are the most widely used in smart home,and constructs a PV unit model considering the factors influencing the PV,then a PV output curve is acquired based on the data from sunlight intensity and temperature under typical circumstances.Similarly,the energy storage unit is classified and modeled.Secondly,since the domestic daily load curve plays an important role in boosting smart home and developing smart grid,this paper makes a study on the characteristics of smart home loads and classifies them.On the basis of the above study,a model is constructed for the commonly-used appliances in the smart home,and since the application of DG has great impact on user's electricity consumption,a reasonable electricity pricing mechanism,as an important resort to meet people's demands,is the key to solve the problem of users' electricity consumption,so this paper introduces the electricity pricing mechanism and adopts spot price to optimize the energy of smart home system,and presents the spot price curve of an typical working days and weekends.Finally,by adopting the improved particle swarm optimization algorithm,the energy optimization management strategies are formulated on the basis of the smart home supply side model,load model and spot price.And the case simulation is carried out in which the minimized electricity cost of smart home is taken as the objective.By a comparative analysis of optimized results under various models,it is verified that energy optimization management of smart home system plays a role in controlling consumers' electricity utilization cost.