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Optimal Bidding Strategy of DER Aggregator Considering Bilateral Uncertainty via Information Gap Decision Theory

机译:基于信息缺口决策理论的双边不确定性的DER聚合商最优报价策略

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摘要

Distributed energy resources (DER), especially wind and photovoltaic power, and demand response (DR) are highly valued in recent years, for their advantages on environmental protection, sustainable development and so on. However, their volatility poses double risks to the DER aggregator when formulating a profitable bidding strategy and schedule scheme. To this end, firstly, this paper proposes an information gap decision theory (IGDT) based optimal bidding strategy to modeling the dual uncertainties confronted by the DER aggregator without knowing the specific distribution pattern of uncertainties. Secondly, the DER aggregator is assumed to be risk averse (RA) or opportunity seeking (OS) and the corresponding strategies could be obtained. The former comes up with a robust strategy under severe uncertain circumstance and the latter presents a profit-maximization scheme while endure more risks. The validity of the proposed method is examined using the dataset from the Thames valley vision (TVV) project, the obtained results demonstrate that proper adjustment on aggregator’s bidding strategy could be achieved based on its preference for high-profit or stability, which is also applicable for other market entities.
机译:分布式能源(DER),特别是风能和光伏发电,以及需求响应(DR),由于它们在环境保护,可持续发展等方面的优势,近年来受到高度重视。但是,在制定有利可图的投标策略和进度计划时,其波动性给DER聚合服务商带来了双重风险。为此,本文首先提出了一种基于信息缺口决策理论(IGDT)的最优竞标策略,以对DER聚合器面临的双重不确定性进行建模,而无需了解不确定性的具体分布方式。其次,假设DER聚合器是规避风险(RA)或寻求机会(OS)的,并且可以获得相应的策略。前者在严峻的不确定环境下提出了一个强有力的策略,而后者则提出了一个利润最大化的方案,同时承受了更多的风险。使用泰晤士河谷视野(TVV)项目的数据集检验了该方法的有效性,所得结果表明,基于聚集者对高利润或稳定性的偏好,可以对聚集者的出价策略进行适当的调整,这也是适用的对于其他市场实体。

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