The Collaborative Optimization And Regulation Method Of Wind/Photovoltaic/Energy Storage Power Station Participating In Electricity Spot Market

With the proposal of the "dual carbon" target and the development of the electricity market,the wind/photovoltaic/energy storage power station(WPS),as an effective way to reduce emissions,has a huge potential for the electricity market.However,the current energy coupling between wind turbine generator(WT),photovoltaic(PV),and energy storage(ES)within WPS is not clear,which make the market decision behavior of WPS is difficult to portray.Furthermore,the decision-making method of WPS participating in two-stage spot market,including day-ahead(DA)market and real-time(RT)market,has not been formed.The development of carbon trading has brought essential changes to the electricity market,the WPS output and the traditional system energy allocation way.Therefore,how to reasonably bidding under the propose of achieving the maximum benefit of WPS has become a key issue restricting the development of WPS.In order to realize the cooperative regulation and market decision of WPS,this paper proposes an optimal regulation method for WPS to participate in the DA market.In the upper-layer,the WPS constructs the optimal bidding strategy with the propose of maximum revenue in the DA market,which realize the dynamic decision of the market.In the lower-layer,the independent system operator(ISO)receives the bidding parameters from WPS,conventional units and power users respectively,and constructs the clearing model of DA market with the goal of maximizing social welfare.Firstly,this method considers the energy coupling effect of ES,WT and PV,and constructs the cooperative regulation model of WPS.Then,based on the current electricity spot market mechanism,the optimal bidding model and clearing model of WPS are constructed.Finally,the simulation analysis proves that the proposed method can effectively solve the market decision-making problem of WPS,improve the revenue of the station and enrich the control means of ES.In order to analyze the impact of carbon trading on WPS’s participation in the market and realize market decision-making,this paper considers carbon trading and proposes an optimal regulation method for WPS participating in DA and RT based on the two-layer optimization framework introduced.Firstly,the Monte Carlo sampling and k-means clustering method are applied to generate typical WT and PV output scenarios to describe the uncertainty of WT and PV.Then,based on the carbon trading mechanism,the influence of carbon trading on the competitive environment of the electricity spot market is quantified.And a bi-level model is constructed:the upper-level optimizes WPS’s bidding strategy,and the lower-level is DA and RT market clearing process.Finally,the simulation analysis verifies the effectiveness of the framework and model,and proves that this method can optimize the bidding strategy of WPS and further enrich the means of energy storage regulation.With the introduction of carbon trading,WPS has been compensated by electricity price during the low load period and reduced the carbon emission of the system.