Demand response (DR) can provide a cost-effectiveness approach for reducing peak load while renewable energy sources (RES) can result in an environmental-friendly solution for solving the problem of power shortage. The increasing integration of DR and renewable energy bring challenging issues for energy policy makers, and electricity market regulators in the power grid. In this paper, a new two-stage stochastic game model is introduced to operate the electricity market, where Stochastic Stackelberg-Cournot-Nash (SSCN) equilibrium is applied to characterize the optimal energy bidding strategy of the forward market and the optimal energy trading strategy of the spot market. The sampling average approximation (SAA) technique is harnessed to address the stochastic game model in a distributed way. By this game model, the participation ratio of demand response can be significantly increased while the unreliability of power system caused by renewable energy resources can be considerably reduced. The effectiveness of the proposed model is illustrated by extensive simulations.
CITATION STYLE
Li, C., Liu, C., Yu, X., Deng, K., Huang, T., & Liu, L. (2018). Integrating demand response and renewable energy in wholesale market. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 2018-July, pp. 382–388). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2018/53
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