Óptimo ajuste de la potencia reactiva en sistemas de transmisión por la variación de taps en elementos estáticos usando el algoritmo de Mapeo Media-Varianza MVMO

Abstract

This work addresses the optimization of electrical power systems (EPS), focusing on the optimal reactive power adjustment (ORPA) to reduce active power losses, improve voltage profiles, and decrease the loading of generating units. These factors are crucial to ensuring efficiency and operational reliability in power systems. The proposed methodology is based on the comparison of two metaheuristic algorithms: the Mean-Variance Mapping Optimization (MVMO) and Particle Swarm Optimization (PSO). Both algorithms were implemented in MATLAB using the MATPOWER toolbox to perform power flow analysis and simulate the base system under different case studies. The analysis was conducted on the IEEE 39-bus test system, considering technical constraints, real operating conditions, and 21-position tap settings for transformers and static compensators. These components work together to achieve the precise adjustments required by the system. The results show that both methods effectively reduce active power losses, improve voltage levels, and decrease generator loading. MVMO demonstrated a strong exploration capability, whereas PSO exhibited rapid convergence. This comparative analysis provides valuable insights for selecting optimization techniques in power system design and operation.