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Energy Pricing and Dispatch for Smart Grid Retailers Under Demand Response and Market Price Uncertainty

机译:需求响应和市场价格不确定情况下智能电网零售商的能源定价和调度

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This paper proposes a two-stage two-level model for the energy pricing and dispatch problem faced by a smart grid retailer who plays the role of an intermediary agent between a wholesale energy market and end consumers. Demand response of consumers with respect to the retail price is characterized by a Stackelberg game in the first stage, thus the first stage has two levels. A risk-aversive energy dispatch accounting for market price uncertainty is modeled by a linear robust optimization with objective uncertainty in the second stage. The proposed model is transformed to a mixed integer linear program (MILP) by jointly using the Karush–Kuhn–Tucker (KKT) condition, the disjunctive constraints, and the duality theory. We propose a heuristic method to select the parameter in disjunctive constraints based on the interpretation of Lagrange multipliers. Moreover, we suggest solving an additional linear program (LP) to acquire a possible enhanced bidding strategy that guarantees a Pareto improvement on the retailer’s profit over the entire uncertainty set. Case studies demonstrate the proposed model and method is valid.
机译:本文针对智能电网零售商所面临的能源定价和调度问题,提出了一个两阶段的两级模型,该零售商扮演着批发能源市场和最终消费者之间的中介角色。消费者对零售价格的需求响应在第一阶段以Stackelberg游戏为特征,因此第一阶段有两个层次。在第二阶段,通过具有目标不确定性的线性稳健优化模型,对考虑了市场价格不确定性的风险平均能源调度进行建模。通过联合使用Karush–Kuhn–Tucker(KKT)条件,析取约束和对偶理论,将提出的模型转换为混合整数线性程序(MILP)。我们提出了一种基于拉格朗日乘子解释的启发式方法来选择析取约束中的参数。此外,我们建议解决一个额外的线性程序(LP),以获取可能的增强出价策略,以确保在整个不确定性范围内提高零售商利润的帕累托改进。案例研究表明所提出的模型和方法是有效的。

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