Optimal Bidding Strategy of Load Aggregators for the Auxiliary Service Market of Peak Shaving and Valley Filling

Jinkun Liu, Xingying Chen, Hantao Liu, Kun Yu, Lei Gan, H. Hua
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引用次数: 2

Abstract

China’s existing methods of regulating and adjusting resources are difficult to achieve optimal allocation of resources. Load aggregators can participate in market operations by integrating dispersed adjustable resources to increase the flexibility of resource scheduling. In order to encourage load aggregators to participate in peak-shaving and valley-filling services in the power auxiliary service market, this paper develops an optimal bidding strategy model to optimize the bidding curve of load aggregators. Since there is a deviation between the actual daily electricity consumption in the market and the bid amount in the day-ahead market, the power deviation is additionally considered by this paper. Due to the bidding curves of other entities in the market are unknown, this paper proposes a random optimization method using Monte Carlo simulation. The results show that under different market environments, load aggregators can benefit by optimizing their bidding curves, and a loose market environment can stimulate their enthusiasm for participation.
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调峰填谷辅助服务市场负荷集成商最优竞价策略研究
中国现有的资源调控方式难以实现资源的最优配置。负荷聚合器通过整合分散的可调资源参与市场运作,增加资源调度的灵活性。为了鼓励负荷集成商参与电力辅助服务市场的调峰填谷服务,本文建立了最优竞价策略模型,对负荷集成商的竞价曲线进行了优化。由于市场的实际日用电量与日前市场的投标电量存在一定的偏差,故本文额外考虑了功率偏差。由于市场上其他主体的竞价曲线是未知的,本文提出了一种采用蒙特卡罗模拟的随机优化方法。结果表明,在不同的市场环境下,负荷聚合商可以通过优化其竞价曲线获得收益,宽松的市场环境可以激发其参与的积极性。
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