Optimal load shedding scheme using grasshopper optimization algorithm for islanded power system with distributed energy resources

• Main Authors: Ahmadipour, Masoud, Othman, Muhammad Murtadha, Salam, Zainal, Alrifaey, Moath, Mohammed Ridha, Hussein, Veerasamy, Veerapandiyan
• Format: Article
• Language: English
• Published: Ain Shams University 2023
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/104965/1/ZainalSalam2023_OptimalLoadSheddingSchemeusingGrasshopper.pdf; http://eprints.utm.my/104965/; http://dx.doi.org/10.1016/j.asej.2022.101835

In this paper, a new optimal load shedding method using a grasshopper optimization algorithm (GOA) is proposed for maintaining the stability of the islanded power system that comprises distributed energy resources (DER). The GOA is used in conjunction with the method of voltage stability margin (VSM) to handle the multi-objective shedding constraints, namely the generation restrictions, allowable load curtailment, and load priority. To assess the effectiveness of the offered method, a comprehensive evaluation study is applied to a system of IEEE 33-bus and four DG units in view of different scenarios. Furthermore, the effectiveness of performance of the GOA-based load shedding is compared in terms of fitness value, voltage stability margin, and percentage of load that should be curtailed with three well-known optimization approaches (i.e., the particle swarm optimization (PSO), grey wolf optimization (GW), and genetic algorithm (GA)) under different islanded scenarios. The obtained results show that the performance of the proposed method is better than other methods with the less value of load curtailed for totally islanded states (i.e., 45.67% for island A, 16.63% for island B, 38.05% for island C, and 27.98% for island D in this study). In addition, the results of the simulation display the efficacy of the proposed scheme to ensure voltage stability with the optimal load quantity to be shed for dissimilar islanding scenarios.