Multi-time Scale Internal Optimal Dispatch And Benefit Balance Of Virtual Power Plant

With the continuous advancement of the lateral structural reform of energy supply,decentralized renewable energy power generation has developed rapidly,but a large number of decentralized energy access also poses new challenges for the safe,reliable.and economic operation of the power grid.As an effective means for the coordination and optimization and market transactions of aggregated various distributed energy sources,virtual power plants can reduce the market risk of independent operation of decentralized energy sources and obtain the benefits of economies of scale.This paper conducts research and discussion on the internal optimal dispatch and benefit distribution of virtual power plants in multi-time-scale power markets.First,this paper studies the multi-time-scale power market architecture of virtual power plants,including mid-to long-term,day-ahead,and real-time markets.The Latin Hypercube Monte Carlo is used to deal with the uncertainties of the schedulable members’ output,demand and electricity prices faced in the operation of the virtual power plant,and the various members of the virtual power plant are modeled and analyzed.On the basis of considering the connection between the medium and long-term market and the spot market,a medium-and long-term optimal scheduling model based on the principle of "value trend" is established;conditional value at risk is used to measure the operational risk of virtual power plants,and the goal is to maximize the overall benefits of virtual power plants.The joint market optimization scheduling model of the joint market,and the integration of the virtual power plant to participate in the multi-time scale market optimization scheduling model,lay the foundation for the subsequent profit distribution model.Subsequently,the influencing factors of the cooperative surplus distribution of virtual power plants are discussed.From the perspectives of utility theory,contribution degree,and willingness to cooperate,the virtual power plant members’ profit distribution improvement factors are modeled and analyzed.The concept of cooperative game and the application of its allocation method in the power system are sorted out.Based on the Shapley value method.the classical allocation method of cooperative game.A virtual power plant profit distribution model based on the improved Shapley value method of multiple factors is established.Finally,the CPLEX solver is used to solve the above model.After obtaining the mid-to-long-term time-sharing power plan of the virtual power plant,it was substituted into the virtual power plant joint market optimization scheduling model,and the result of the virtual power plant participating in the multi-time-scale power market internal optimization scheduling was formed.And set up two comparative examples to compare and analyze the two optimization results respectively.Since there are 31 different combinations of virtual power plants in this paper,each combination method is substituted into the virtual power plant’s multi-time-scale optimal scheduling model to solve,and finally the results of internal member profit distribution are obtained.The comparison and analysis between the model results and the Shapley value method distribution results verify the validity and rationality of the model.