Distributed energy resources especially wind and photovoltaic power, and demand response are highly valued in recent years for their advantages in 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, first, this article proposes an information gap decision theory-based optimal bidding strategy to model the dual uncertainties confronted by the DER aggregator without knowing the specific distribution pattern of uncertainties. Second, the DER aggregator is assumed to be risk-averse or opportunity-seeking, and the corresponding strategies could be obtained. The former comes up with a robust strategy under severe uncertain circumstances, and the latter presents a profit-maximization scheme while enduring more risks. The validity of the proposed method is examined using the dataset from the Thames valley vision 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.

中文翻译：

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基于信息差距决策理论的考虑双重不确定性的DER聚合器最优投标策略

分布式能源尤其是风能、光伏、需求响应等，近年来因其在环保、可持续发展等方面的优势而受到高度重视。然而，在制定有利可图的投标策略和进度计划时，它们的波动性给 DER 聚合器带来了双重风险。为此，首先，本文提出了一种基于信息差距决策理论的最优投标策略，在不知道不确定性的具体分布模式的情况下，对DER聚合器面临的双重不确定性进行建模。其次，假设DER聚合器是规避风险或寻求机会的，并且可以获得相应的策略。前者在严重不确定的情况下提出了稳健的策略，后者在承受更多风险的同时提出了利润最大化方案。使用来自泰晤士河谷视觉项目的数据集来检查所提出方法的有效性；得到的结果表明，可以根据聚合器对高利润或稳定性的偏好对聚合器的投标策略进行适当调整，这也适用于其他市场主体。