Islanding and dynamic reconfiguration for resilience enhancement of active distribution systems

• Published in: Electric power systems research Vol. 189; p. 106749
• Main Authors: Xu, Jianchun, Zhang, Tingting, Du, Yaxin, Zhang, Wen, Yang, Tianyou, Qiu, Jifu
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.12.2020; Elsevier Science Ltd
• Subjects: Active distribution systems; Distributed generation; Dynamic programming; Electric power; Electric power distribution; Electric power systems; Electricity distribution; Electricity generation; Electronic equipment tests; Entropy; Entropy (Information theory); Fault diagnosis; Islanding; Power flow; Reconfiguration; Resilience; Resilience enhancement; Service restoration; Strategy; System effectiveness; Weather forecasting; Islanding; Dynamic programming; Active distribution systems; Reconfiguration; Resilience enhancement
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2020.106749

•The failure rate of distribution system is generated by vulnerability analysis.•The typical fault scenarios are screened based on the system information entropy.•Islanding and reconfiguration are both considered to maximize the power supply.•A multi-stage switch strategy is developed based on the dynamic programming. Increasingly frequent extreme weather events cause power outages in active distribution systems. Islanding and fault reconfiguration are effective approaches to service restoration and resilience enhancement. This paper proposes a multi-stage switch strategy based on dynamic programming (DP), considering both islanding and fault reconfiguration. First, numerous expected fault scenarios are constructed based on meteorological forecast and vulnerability analysis of system components, from which typical ones are selected by their information entropy. Second, for each typical scenario, a multi-stage switch strategy considering both islanding and fault reconfiguration is developed through DP. The objective is to make a tradeoff between minimizing total power shortage and minimizing the number of switching operations over the whole event's duration. The constraints comprise power flow limits, nodal voltage limits, and distributed generators’ capabilities. Finally, a risk-based resilience assessment is performed and the resilience improvement is presented. Tests on the IEEE 33-bus distribution system demonstrate the effectiveness of the proposed method.