Decision-Dependent Uncertainty Modeling in Power System Operational Reliability Evaluations

• Published in: IEEE transactions on power systems Vol. 36; no. 6; pp. 5708 - 5721
• Main Authors: Hu, Bo, Pan, Congcong, Shao, Changzheng, Xie, Kaigui, Niu, Tao, Li, Chunyan, Peng, Lvbin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Decision analysis; Decision-dependent uncertainty (DDU); force outage rate (FOR); Modelling; operational reliability evaluation; Optimization; Power system reliability; Reliability analysis; Stochastic processes; stochastic unit commitment (SUC); System reliability; Uncertainty; Unit commitment
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2021.3081765

The integration of the variable renewable energies makes the operation conditions of the power system ever-changeable. Consequently, the power system operational reliability evaluation is increasingly important. This paper introduces the concept of decision-dependent uncertainty (DDU) in the operational reliability evaluation. Unlike the exogenous uncertainties, DDU reveals that the decisions of the system operation could significantly affect the resolution of the uncertainties which influence the reliability metrics. In this paper, the proposed DDU modeling method links the device reliability indices, i.e., the forced outage rate, and the operational-decision variables. The impacts of DDU on operational reliability are analyzed based on a reliability-constrained stochastic unit commitment (UC) model. An adaptive reliability improvement UC (ARIUC) algorithm is proposed to efficiently solve the problem. Case studies underline the necessity of considering DDU in power system operational reliability evaluations.