Chance-constrained allocation of UFLS candidate feeders under high penetration of distributed generation. (May 2023)

• Record Type: Journal Article
• Authors: Badesa, Luis; O'Malley, Cormac; Parajeles, María; Strbac, Goran
• Is Part Of: International journal of electrical power & energy systems. Volume 147(2023)
• Publication Date: 2023-05
• Subjects: Under-frequency load shedding -- Distributed generation -- Chance constraints -- Convex optimisation; 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.2022.108782
• Languages: English
• ISSNs: 0142-0615

Abstract

Abstract: Under-Frequency Load Shedding (UFLS) schemes are the last resort to contain a frequency drop in the grid by disconnecting part of the demand. The allocation methods for selecting feeders that would contribute to the UFLS scheme have traditionally relied on the fact that electric demand followed fairly regular patterns, and could be forecast with high accuracy. However, recent integration of Distributed Generation (DG) increases the uncertainty in net consumption of feeders which, in turn, requires a reformulation of UFLS-allocation methods to account for this uncertainty. In this paper, a chance-constrained methodology for selecting feeders is proposed, with mathematical guarantees for the disconnection of the required amount of load with a certain pre-defined probability. The correlation in net-load forecasts among feeders is explicitly considered, given that uncertainty in DG power output is driven by meteorological conditions with high correlation across the network. Furthermore, this method is applicable either to systems with conventional UFLS schemes (where relays measure local frequency and trip if this magnitude falls below a certain threshold), or adaptive UFLS schemes (where relays are triggered by control signals sent in the few instants following a contingency). Relevant case studies demonstrate the applicability of the proposed method, and the need for explicit consideration of uncertainty in the UFLS-allocation process. Highlights: A chance-constrained methodology for selecting feeders contributing towards UFLS is proposed. Uncertainty and correlation driven by Distributed Generation are explicitly considered. A distributionally-robust option is given, requiring minimal information on uncertainty. The method applies to several communication requirements for the operation of the power system.