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Bi-Level Programming-Based Optimal Strategy to LSEs with Demand Response Bids

机译：具有需求响应的基于LSE的双层编程的最优策略

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摘要

As a profit-seeking market participant, load serving entities (LSEs) have been trying to apply demand response (DR) programs to induce the demand elasticity to further their profit. However, due to the different preference of DRs, it is difficult for LSEs to generate the optimal strategic bidding strategy in the ISO/RTO's market. Therefore, this paper proposed a bi-level optimization model considering DR bidding to maximize the total profit of LSEs: conceptually, the consumers participate DR through setting their bidding prices to LSEs with respect to their own preference and LSEs should determine the optimal reward value of DR as well as the amount of demanded electricity; technically, an original method has been implemented to solve the bi-level optimization model. The closed form of shadow price function with respect to the total load demand is derived to reduce the complexity. Hence, the proposed model is converted to a mixed integer second order cone programming and able to achieve the global optimality. It needs to be note that the closed form of shadow price introduced in this paper can also be applied to other bi-level programming models. Moreover, case studies have been performed to demonstrate the validity of the proposed method.
机译：作为寻求利润的市场参与者，负载服务实体（LSE）一直在尝试应用需求响应（DR）程序来诱导需求弹性以进一步提高其利润。但是，由于灾难恢复的偏好不同，伦敦证券交易所很难在ISO / RTO的市场中生成最佳的战略投标策略。因此，本文提出了一种考虑DR竞价的双层优化模型，以最大化LSE的总利润：从概念上讲，消费者通过根据自己的偏好为LSE设置竞标价格来参与DR，LSE应确定LSE的最优奖励价值。灾难恢复以及所需的电量；从技术上讲，已采用原始方法来解决双层优化模型。得出相对于总负荷需求的影子价格函数的封闭形式，以降低复杂性。因此，将所提出的模型转换为混合整数二阶锥规划并能够实现全局最优。需要注意的是，本文介绍的影子价格的封闭形式也可以应用于其他双层编程模型。此外，已经进行了案例研究以证明所提出方法的有效性。

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