Optimal design of a cost-efficient campus microgrid: A case study for the University of Dhaka using hybrid metaheuristic optimization

Universities are facing pressure to increase the production of renewable energy and cut down carbon emissions. A campus-based microgrid is a viable option to address this need while reducing operational costs and enhancing resilience. This study presents a comprehensive design and optimization of a grid-connected microgrid for the University of Dhaka (DU), targeting the minimization of the levelized cost of energy. The proposed campus microgrid comprises solar photovoltaic systems, battery energy storage systems, and bidirectional inverters. It meets the energy demand of the campus while maximizing renewable energy capture, thus reducing fossil fuel use. An optimization framework is developed that incorporates dynamic load profiles, solar potential, storage constraints, and feed-in tariff policies. The Gray Wolf Optimizer is used for the optimization of the system, while the Real-Coded Genetic Algorithm and Particle Swarm Optimization are utilized for validation studies. First, the proposed solution is used to develop an optimal system configuration for the DU campus. Then, validation studies are run to show that this system reduces energy costs compared to traditional grid-connected operation, requires approximately 15 years to recover its installation cost, and reduces greenhouse gas emissions by almost 85% compared to before. This study and its findings can be used to develop and study similar low-carbon energy systems around the world.