Real Time Economic Dispatch Using Bat Algorithm Optimization Technique

This study presents a Real-Time Economic Dispatch (RTED) algorithm utilizing the Bat Algorithm (BA) optimization technique to enhance the integration of renewable energy resources in power systems. The approach aims to minimize operational costs by optimizing energy and calculating optimal participation factors, considering minute-to-minute variability in wind, solar, and load demand over a scheduling period. The results demonstrate that the BA method significantly reduces total costs by approximately 1.7% compared to conventional sequential methods and improves system stability, as indicated by better voltage stability indices (VSEI). This optimization technique shows superior performance in minimizing fuel costs across various load demands compared to other methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search (TS), and Artificial Bee Colony (ABC). The study’s findings indicate that BA optimization is a promising tool for real-time economic dispatch in power systems, particularly in scenarios with significant renewable energy integration.