Uncertainty Analysis And Robust Optimization Research Of Smart Home Power Consumption

As a key component of the smart grid,the smart home power consumption system establish a home smart local area network through the support of information communication technology and intelligent hardware devices.The smart home power consumption system can obtain the running data of the electrical equipment.Then this system transmits the control signal and regulates the working state of the electrical equipment according to the consumer's consumption preference and the smart power control strategy.Besides,the system can participate in the demand-side response and achieve the goal of minimizing household electricity.Therefore the smart home power consumption system not only meets the challenges of diversification and flexibility of home electrical equipment and helps consumers achieve diversified and personalized power targets,but also has the two-way interact with the power system.It could help the power system to shave peaks and fill valley,save power and reduce emissions,and reduce the power burden on the public grid.This paper focuses on the operation optimization of household electrical equipment in the uncertain environments.Firstly,the operational characteristics and corresponding mathematical models of various household electrical equipment are studied.The smart home power consumption system with distributed photovoltaic and multiple electrical loads is built.Then,for the uncertainty parameter problem in the power system,this paper proposes the distributionally robust optimization method.Simulation results show that the distributionally robust optimization method has great robustness to uncertain problems and could fully meet the consumer's comfort requirements and the target of lowest power consumption.In view of the fact that the day-ahead optimized scheduling results cannot be fit for real-time control,this paper introduces the model predictive control method to track the changes of uncertain factors such as ambient temperature and user water consumption.On this basis,the model predictive control method is combined with distributed robust optimization method,interval number optimization method and opportunity planning constraint method,and it is applied to the operation optimization problem of household electrical equipment.Simulation results show that these three different real-time optimization methods have strong robustness and real-time performance.