DISTRIBUTIONALLY ROBUST THERMOELECTRICITY TRADING OPTIMIZATION FOR MULTIPLE-INTEGRATED ENERGY SERVICE PROVIDERS BASED ON ASYMMETRIC NASH BARGAINING
In power systems with a high proportion of renewable energy,the uncertainty of the source side seriously affects the economic operation of multi-integrated energy systems.Additionally,the fairness of income distribution among multi-service providers influences their willingness to participate in cooperation,thereby affecting the stability of the overall alliance.Addressing these issues,a multi-energy integrated system model is established,incorporating electrothermal gas and multi-energy cooperation,including power-to-gas coupling,carbon capture and storage,and hydrogen fuel cells.Firstly,based on historical wind power and photovoltaic data,a two-stage distributionally robust optimization scheduling model for multi-integrated energy systems is proposed,utilizing a data-driven approach.The column and constraint generation algorithm is employed to solve this model.Next,a heat and power sharing trading model for multi-integrated energy service providers is established based on the Harsanyi game.The alternating direction method of multipliers is used to solve the problem of maximizing payment benefits through asymmetric bargaining.Numerical examples demonstrate that the proposed distributionally robust thermoelectric transaction model,which includes joint demand response,effectively promotes the consumption of new energy.The asymmetric bargaining method,considering multiple negotiation factors,ensures the fair distribution of benefits.
integrated energy systemdemand responsedistributionally robust optimizationthermal power tradingasymmetric bargaining
万方数据
维普
