Smart Grid Demand-Side User Behavior And Mutual Influence Of Mobile Social Network

As the representative of the power grid in the future development direction of smart grid from the date of birth, has always been the hot spot of the research and application.State grid companies have to develop a strong smart grid development strategy and overall planning, and demand management is an important part and one of the key links.As an important component of the power system of electric vehicle and its charge and discharge behavior could put forward severe challenge to the stability of the power system. Mobile social network is a social interaction network, for the purpose of relying on the mobile terminal and mobile Internet development. Electric cars in the future will be as an important part of vehicle network will inevitably involved in the interaction based on mobile social networks, the individual behavior(electric vehicles) to receive the main(mobile social network).Based on electric vehicle charging and discharging effect on power system load,summarizes the intelligent power demand side management contents and methods,analysis of the electric car charge and discharge the constraints of the situation, combined with the time-sharing electricity prices, set a goal in charge and discharge, basic charge and discharge forecasting model is established. At the same time, analysis the characteristics of the mobile social network, the influence of the mobile social network model is given, and the purpose to solve the interaction effects on individual behavior.Will influence the model applied to electric vehicle charging and discharging, set up the final prediction model of electric vehicle charging and discharging based on mobile social network. Through simulation,contrast without mobile social network and based on the electric vehicle charging and discharging behavior of mobile social network, which can better maintain the stability and reliability of power system, but also the benefit the user. Managers can also through regulating the prediction model, to ensure the safe operation of power system.