Optimal Scheduling Scheme of an Autonomous Microgrid Considering the Operational and Maintenance Costs of the Micro-Sources

The solution of the combined Economic-Emission Load Dispatch (EELD) problem of conventional or micro-grid (MG) system entails determination of the optimal power output of dispatchable generating units, to meet the system load, at the lowest possible cost and reduced greenhouse gases emission, subject to some constraints. In most studies, the installation, maintenance and operational costs of renewable energy sources are neglected while formulating the EELD of MG system. This significantly affect the accuracy of the scheme. Thus, this study developed the EELD of an MG system powered through conventional Diesel Engine Generators (DEG), photovoltaic (PV) and wind turbine (WT) systems dispatched for 24-hours. The EELD is formulated to minimize the fuel cost and emission of toxic gases taking into account the operational and maintenance costs of the RES. Meercat Optimization Algorithm (MOA) was employed for its robustness, rapid convergence, and global search capabilities. The performance of the MOA-based approach was evaluated by comparing fuel and emission costs of a 3-unit and 10-unit MG systems with those obtained using Salp Swarm Optimization (SSA) and African Vulture Optimization Algorithm (AVOA). The simulations results revealed that the MOA-based EELD achieves significant reductions in fuel costs of 13.08% compared to AVOA and 18.02% compared to SSA for the 3-DEG MG system, and 13.06% compared to AVOA and 17.98% compared to SSA for the 10-DEG MG system, while also lowering the emission costs. The MOA-based EELD method not only outperforms SSA and AVOA in terms of cost efficiency but also demonstrates superior convergence speed.