Optimal Design of Microgrid at an Industrial Complex

Microgrid (MG) emerge as a potential solution for grid modernization. MGs can host distributed renewable generation and can increase fuel-based energy utilization efficiency and system reliability. This work designs an optimal industrial MG which provides economic and environmental benefits. Two Matlab/Simulink models are built, a reference system and an MG system. Both models calculate the annualized total cost and annual CO
₂
emissions. The reference system is the industrial facility connected to the utility grid. The MG components include solar photovoltaic modules, wind turbine generators, battery energy storage systems, and a selection of diesel generators of various sizes. MG component specs are iteratively varied; then, the model outputs are compared to determine by how much the updated MG system can reduce annualized total cost and CO
₂
emissions. Authentic data and realistic operational constraints are considered in this work. Particle swarm optimization is used to find the optimal solution. Different operating strategies are analyzed, under each of which there is an optimal combination of distributed renewable generators, battery energy storage system, and diesel generator lineup that maximizes the overall benefits. The results show that the best MG solution can achieve up to 74.8% cost savings and 31.9% CO
₂
emission reduction. The approach demonstrated can help with the transition toward a cleaner, more efficient, reliable, and decentralized power grid.