考虑多重不确定性的综合能源系统与充电站的鲁棒定价策略

Robust Pricing Strategies for Integrated Energy Systems and Charging Stations Considering Multiple Uncertainties

  • 摘要: 综合能源系统与电动汽车充电站联合运营,可通过多能互补、合理引导充电需求来促进可再生能源的利用,实现能源的可持续发展。为了有效规避二者面临的多重不确定性风险,基于Stackelberg博弈构建综合能源系统和充电站联合运营的双层鲁棒动态定价模型。该模型以综合能源系统为领导者,采用鲁棒优化方法处理冷、热、电负荷和风电、光伏出力的不确定性,以最大化自身效益为目标制定交易电价;充电站作为跟随者,以两阶段分布鲁棒优化方法描述电动汽车的不确定性,根据自身需求对电价做出响应。提出二分法结合列和约束生成(column and constraint generation,C&CG)算法的迭代求解方案,对该模型进行求解。最后,通过算例结果验证所提鲁棒博弈模型和算法的有效性。

     

    Abstract: The joint operation of integrated energy system and electric vehicle charging stations facilitates the utilization of renewable energy and achieve sustainable energy development through synergistic integration of multi-energy and reasonable guidance of charging demand. In order to effectively mitigate the risks associated with multiple uncertainties, a double-layer robust dynamic pricing model is constructed based on the Stackelberg game. Taking the integrated energy system as the leader while adopting robust optimization methods to address the uncertainty of cold, heat, electric loads and wind power and photovoltaic outputs, this model sets the trading price with the goal of maximizing its own benefits. The charging station, as a follower, described the uncertainty brought from electric vehicles with a robust two-stage distribution optimization method and responded to the price of electricity according to its own demand. An iterative solution scheme combining the bisection with column and constraint generation (C&CG) algorithm is proposed to solve the model. Finally, the effectiveness of the proposed robust game model and algorithm is verified through the case study.

     

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