A two-stage resilience improvement planning for power distribution systems against hurricanes. (November 2021)

• Record Type: Journal Article
• Authors: Ghasemi, Mostafa; Kazemi, Ahad; Bompard, Ettore; Aminifar, Farrokh
• Is Part Of: International journal of electrical power & energy systems. Volume 132(2021)
• Publication Date: 2021-11
• Subjects: Distribution system planning -- Resilience analysis -- Stochastic optimization -- Uncertainty; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2021.107214
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A two-stage stochastic model is developed to enhance the resilience of distribution system. The operation strategy of distribution network is devised for both emergency and normal conditions. A vulnerability threshold method is utilized to model the line damage scenarios based on the maximum wind speed. Resilience enhancement of the distribution system with various facilities is observed. Abstract: This paper presents a novel planning strategy for distribution system planners (DSPs) to enhance the resilience of distribution systems confronting emergencies. The problem is formulated as a two-stage stochastic programming model under emergency and normal scenarios. The decisions on line hardening, distributed generation (DG) placement, mobile emergency generators (MEG) allocation, and tie switch placement are made in the first stage to maximize the system resilience. In the second stage, the operation costs of the system pertaining to the DSP power purchase from the upstream network, DG power production, and forced load shedding in emergency conditions are minimized to achieve a techno-economic compromise of investment costs and enhanced operation/resilience benefits over both planning and operation scales. Since access to dependable distribution functions for probabilistic approaches is a notable challenge in resilience studies, an uncertainty modeling approach is presented based on the thresholds for the line damage in the worst-case event. The proposed approach can drastically decrease the number of line damage scenarios for resilience studies. The efficiency and effectiveness of the new approach are validated on two distribution system testbeds with 33 and 118 nodes.