Optimization of a Hybrid Microgrid Using the Multi-Objective Gray Wolf Optimizer

This paper presents the optimization of a hybrid microgrid designed to supply energy to a mining plant with a demand of 1.5 MW, connected to a weak power grid. The microgrid integrates several energy sources: solar, wind, microturbine, diesel generator, and battery storage. Energy management is optimized for a 24-hour horizon using the Multi-Objective Gray Wolf Optimizer (MO-GWO). This algorithm allows finding optimal solutions by balancing the minimization of three objectives: energy generation costs, CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> emissions, and flattening of the demand curve from the grid perspective. The development and analysis of the results were carried out in Python, using the Spyder integrated development environment.