Research On Electricity Supply-demand Interaction Strategy Under Separated Distribution And Sales Environment

With the development of renewable energy,smart grid and power market,demandside resources have received more attention in balancing the power supply and demand and improving the operation of power systems.The existence of supply-demand interaction in the electricity market makes market trading more flexible and regulates the price formation mechanism,and also affects the resource allocation on the supply and demand sides.It is necessary for supply and demand sides to analyze the optimization strategy in order to maximize their benefits under separated distribution and sales environment.This article focuses on the strategy of electric energy supplydemand interaction under separated distribution and sales environment.The main work is as follows:A power supply-demand interaction service architecture based on multi-agent system was built.The electricity retail company was taken as the research object of supply side.The classification and trading approach of retailers were analyzed,and the decision making of electricity price was researched.Then,taking the household user as the research object of demand side,the control structure and function of household energy management system was given,and the home energy management optimization strategy was researched.On the supply side,based on the multi-agent service structure of "power trading center-electricity retail company-user",a day-ahead hourly pricing decision method considering risk of electricity retail company based on multi-agent system was proposed in the paper.Ensuring the user’s privacy,electricity price elasticity matrix for user’s side demand was built.Taking conditional value at risk as a risk decision evaluation method and considering profit of electricity selling and potential profit,a day-ahead hourly pricing decision model for electricity retail company was obtained,which solved with the chaos particle swarm optimization algorithm.Finally,case studies were provided to verify the effect of proposed method on the retail company coordination of profit and risk.On the demand side,a multi-time scale home energy management strategy based on electricity demand response was proposed.Demand response model considering user autonomy decision and a household load model with photovoltaic/battery was built.Then,multi-time scale home energy management mode based on model predictive control was established.The optimization model includes intraday household electricity optimization strategy and real-time electricity adjustment strategy.The former was aimed at minimizing the user net expenditure and load fluctuations,and the latter was in order to response to real-time operation of the unadjustable load and fluctuations in photovoltaic output by changing the battery charge and discharge power,and ensure that users met the demand response requirements.Finally,a typical family was taken as study case.The effectiveness of the strategy was verified,and the impact of the demand response mechanism on the user was analyzed.