Optimization of shunt reactor design using evolutionary algorithms: PSO and DE - Ascencion-Mestiza, Hector; Maximov, Serguei; Olivares-Galvan, Juan C.; Ocon-Valdez, Rodrigo; Mezura-Montes, Efrén; Escarela-Perez, Rafael (Electrical engineering, 2025)
In this paper, two well-known metaheuristic algorithms are proposed to optimize the design of a 50-MVAr, 400/ 3 kV, 60- Hz core type shunt reactor. The overall objective of this study is to evaluate the performance and flexibility of particle swarm optimization (PSO) and differential evolution (DE) algorithms in the design of shunt reactors. The goal is to minimize material costs while considering the expected cost of losses, all to achieve maximum efficiency meeting relevant specifications and standards. The PSO and DE results demonstrate a reduction in total ownership cost of 3.34 and 5.55 %, respectively, compared to a prototype developed by a national manufacturer through trial and error and tested in the laboratory. Finally, the developed computational program is evaluated by performing various calculations based on the estimated cost of losses (USD/kW). The application of PSO and DE algorithms to the design of shunt reactors shows promising results, providing more efficient solutions in terms of cost and time. These solutions ensure compliance with current regulations and provide flexibility to optimize the design to specific grid efficiency requirements.