Flow direction algorithm based optimal power flow for isolated microgrid integrated with renewable energy sources

Abstract

This study explores microgrids as small, independent electrical systems that reduce emissions, lower costs, and improve the efficiency and reliability of renewable energy sources (RES). It focuses on solving the optimal power flow (OPF) problem in isolated microgrids to minimize production costs, integrating variable RES like solar photovoltaic systems and wind turbines with a stable small hydropower plant. A novel physics-based Flow Direction Algorithm (FDA), inspired by the D8 hydrological model, is introduced, offering superior precision compared to bio-inspired metaheuristics. The FDA balances global and local search for accurate solutions. Monte Carlo simulation models uncertainties in wind speeds and solar irradiance. Validated on IEEE 33-bus, 69-bus, and 15-bus systems, the FDA outperforms algorithms like Whale Optimization, Ant Lion, Dung Beetle, and Walrus Optimization in efficiency and reliability, advancing microgrid performance.