Real-time Electricity Price Research Based On Virtual Energy Community And User Classification

In recent years,with the rapid development of economy,people’s demand for electricity has increased sharply,the stress of carbon emission reduction,the prominent contradiction between supply and demand,the impact of renewable energy grid connection on the power grid,and so on.These problems have seriously affected the healthy development and safe and stable operation of the power generation industry.It is difficult to solve the problem of power shortage and energy shortage by relying solely on power generation side resources.Demand side resources are considered to be equivalent to power generation side resources,and demand response has become an important means of power grid management of demand side resources.Under the price-based demand response mechanism,consumers can be guided to choose electricity consumption time and quantity reasonably according to the price signal or incentive mechanism,so as to achieve the purpose of peak load reduction and valley filling,and balance the load of the power grid,which is conducive to maintaining the stability and reliability of the power grid at the same time.In this paper,the domestic and foreign demand response and the present research on real-time electricity price are discussed,aiming at real-time price are still unable to implement large-scale and real-time price exists in the unfair defects such as the research object simplification,puts forward the necessity of real-time electricity price above is insufficient.First of all,based on the flexibility and heterogeneity of resident users,this paper proposes a method to classify virtual energy communities by considering five indicators: user flexibility,age of household head,family income,family size and environmental awareness.On the basis of this,the real-time electricity pricing mechanism based on community division is proposed.By using the power credit system to quantify the contribution of the community’s participation in the demand response,the optimization goal of maximizing the total utility of each community and the cost maximization of the general association area is constructed.Finally,the model was verified by the family resident user.The simulation results show that the real-time electricity pricing mechanism based on community division can effectively reduce the difference between users,and the benefits can be distributed fairly and the cost is reduced effectively.In addition,the machine can also allow consumers to adjust their electricity behavior in real time according to the price signal in the power market,which can help residents to develop good electrical usage.In order to realize the maximization of social welfare,three types of users,industrial users,commercial users and large-scale residents,are further considered on the basis of the above model of community welfare maximization.By considering the heterogeneity among the three types of users,this paper constructs a social welfare maximization model with weighting factors.The model aims at maximizing the utility sum of all users with weighting factors and the cost of power suppliers.Finally,some real data of industrial and commercial users in Jiangsu province are used for numerical simulation,and compared with the time-of-use price of peak and valley in Jiangsu province.The simulation results show that the electricity consumption of all kinds of users under the real-time electricity price is relatively more stable than that under the peak and valley time-of-use electricity price.Among them,the electricity consumption of residential users fluctuates greatly,so the real-time electricity price has the best effect.The welfare of the three types of users at peak times of electricity consumption is greater than that under time-of-use price of peak of valley,which indicates that the improved model has the advantages of peak-shaving,balancing supply and demand and improving the total welfare of consumers.