Robust optimal scheduling of integrated energy system with the access of electric vehicles
A multi-stage robust optimization scheduling model for community integrated energy systems with the access of electric vehicles was proposed.Firstly,considering the uncertainties of generations and demands,and the scenario probability distribution of the system operation,the model was constructed as a three-stage four-level robust optimization model.The distributionally robust optimization method was adopted in the probability distribution optimization stage.Secondly,the optimal models were constructed as Stackelberg game problems,and the game models were transformed into a single-layer optimization problem by utilizing the Karush-Kuhn-Tucker conditions.At last,an iterative algorithm was adopted to iteratively solve the multi-stage RO optimization model.The numerical results prove that the proposed RO model improves the economy and robustness of system.
community integrated energy systemelectric vehiclemultiple uncertaintiesrobust optimizationStackelberg game
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