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

Abstract

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.