Application of decision-dependent uncertainty in power system planning and operation analyses: A state-of-the-art review

Abstract

Decision-dependent uncertainty appears when decisions can affect the random factors in the problem, which is endogenous. In recent years, it has gained considerable attention from scholars primarily due to its promising applications in the field of power systems. However, the emerging research is single and fragmented, which is not capable of showing the difference and complexity of this concept. This survey aims to provide a comprehensive and up-to-date overview of the various dimensions of decision-dependent uncertainty within power systems. First, it defines four types of modeling approaches in general forms. Subsequently, the survey identifies the primary sources of decision-dependent uncertainty from diverse perspectives within power systems. Furthermore, the paper lists the specific application fields where this uncertainty plays a crucial role. To tackle the challenges introduced by decision-dependent uncertainty, the survey delves into strategies that have been employed in previous studies. This is followed by a discussion of algorithms used in prior research. Lastly, the survey presents an outlook, highlighting its promising future. This research introduces key knowledge about the application of such uncertainty in power systems, attempts to make essential classifications, and contributes a summary perspective to both decision-dependent uncertainty and generalized uncertainty research.