Research On The Real-time Electricity Strategy Based On The Social Utility And Its Application In Peak Regulation

In the power system,the thermal power which is high energy consumption and high pollution is still the main power generation mode,the installed capacity of the thermal power accounted for more than 60%of the total installed capacity,the thermal power consumed a lot of energy and had a serious impact on the environment.In addition,some other problems in the power system also constrain the development of power systems,in this context,many countries carried out on the research of smart grid,and achieved a series of results.Demand response,as a part of the content of smart grid,can effectively guide the user to arrange the electricity reasonably and achieve the rational use of resources to a certain extent.Real-time electricity as a form of the demand response,in recent years,also caused a wide range of interest in the domestic and foreign.Practice results of European and American power market also showed that the research of real-time electricity is of great significance.In this paper,the research content mainly includes the following several parts:In the first part,firstly,by discussing the formation mechanism of price,this paper pointed out that the pricing efficiency is the highest when the price is equilibrium price.On this basis,it is pointed out that the difference between competitive market and monopoly market lies in demand curve different and come to the conclusion that it has the meaning of studying the price when the market is the price setter by analyzing the pricing principle of competitive market and monopoly market.Then,it is pointed out that China's electricity market has the characteristics of price setter by analyzing the nature of China's electricity market,therefore,research on price in China's electricity market is meaningful.Finally,It is concluded that the study of real-time electricity price in China's electricity market environment has certain significance by analyzing four typical forms of electricity price,which provides a theoretical basis for later research.In the second part,firstly,through the concept of utility,the load can be divided into multiple subsets with no overlap,and the union set is complete set.On this basis,the demand side response model is established based on the demand price elasticity coefficient.Then,aiming at the problem of excessive calculation in the process of solving the problem,the optimal transfer mode of the load is studied based on the regulation efficiency.The model is solved by determining the optimal transfer mode.Based on the method,the output is stable and the calculation accuracy is high,calculation time is short.Finally,the paper analyzes the factors that influence the social utility in the process of pricing,and puts forward the pricing strategy of real-time electricity price based on the maximization of social utility.The strategy takes into account the short-term effects of electricity price on the load,the range of price fluctuation and the range of load variation.The simulation results show that the real-time pricing strategy based on the maximization of social utility is feasible.In the third part,considering the possible anti-peaking phenomenon after the wind power access,the peak-regulation method is studied based on the real-time pricing strategy.Firstly,the uncertain model of wind power is modeled based on the Weibull distribution model,and the possible anti-peaking phenomenon after the wind power access is analyzed.Then,the peak-regulation plants and its characteristics are discussed.Finally,based on the real-time price pricing strategy described in this paper,the peak-regulation method is studied with the source and load interaction and the maximization of social utility as the goal by considering the power flow constraint,peak load constraint and unit ramp constraint.The simulation results show that the proposed method can reduce the peak-valley difference of the equivalent load,thus reducing the number of unit start-up and the peaking cost.