Methods Of Risk-Constrained Economic Dispatch And Interactive Strategy For Virtual Power Plants Considering Demand Response

With the transformation of energy structure,renewable energy resources(RESs),represented by wind and solar energy,are gradually receiving more attention.Most of the RESs are connected to the distribution network in the form of distributed energy resources(DERs),which have the advantages of economy and flexibility.However,DERs have the characteristics of large quantity,small capacity and wide distribution.If a large number of DERs are integrated into the distribution network,the safe operation of the distribution network will be threatened.The advent of virtual power plants(VPPs)present a viable resolution to this issue.The VPP is an integrated system that combines distributed renewable energy resources,gas turbines,energy storage systems(ESSs),load and other power resources.It participates in the power spot market externally and optimizes internal scheduling through the cooperation of each unit to realize the consumption of RESs.However,the output power fluctuation of RESs causes the deviation between the day-ahead planned output power and the intraday actual output power of the VPP.This deviation results in VPPs being subject to penalties in the market.As a result,the income of the VPP declines.Therefore,this thesis studies the economic scheduling and interactive strategies of VPPs under the market environment.This thesis first introduces the concept of VPPs and establishes the characteristic models of VPPs’ internal units.The operating mechanism of VPPs in spot market is analyzed.This thesis also summarizes the risk management methods of VPPs under the market environment and analyzes their advantages and disadvantages.Then,aiming on the output power uncertainties of the distributed PV and the distributed wind power plant,Monte Carlo simulation(MCS)and k-means algorithm were used to construct the combined output scenario.A multi-level incentive price mechanism based on incentive-based demand response(IBDR)was proposed.On this basis,a two-stage scenario-based economic dispatch model of the VPP participating in electricity spot market is established according to stochastic programming theory with the goal of maximum profit.At the same time,the conditional value-at-risk(CVa R)is employed as the risk management methodology of the VPP.The results show that the method adopted in this thesis can effectively mitigate the output deviation caused by RESs and improve the profit of the VPP.The risk analysis provides effective reference information for VPP operators to balance the risk and profit.In addition,in order to further improve the profit of the VPP,the investment and construction cost of ESSs in the VPP is considered.Based on the operation mechanism of VPP participating in the electricity market and the portfolio theory,a multi-objective economic dispatch model of the VPP considering the capacity allocation of ESSs is established.The model was resolved through the utilization of GUROBI in conjunction with the particle swarm optimization(PSO)algorithm.The results indicate that the obtained optimal storage capacity allocation can effectively smooth the fluctuation of RESs’ output and reduce the investment and construction cost of ESSs,which improves the profit of the VPP.CVa R can effectively describe the impact of risk attitude on the decisions of the VPP operators after considering the investment cost of ESSs.