Regional insights in microgrid planning: Combined optimal energy management and sizing across French cities

This study presents a comprehensive multi-objective optimization framework for microgrid design, focusing on reduction both the Levelized Cost of Energy (LCOE) and Life Cycle Emissions (LCE) via minimization of total cost and total emission in the context of several French cities. Employing a Mixed-Integer Linear Programming (MILP) approach, the research determines the optimal capacities for photovoltaic (PV) panels, wind turbines, and battery energy storage systems to achieve a sustainable and cost-effective energy mix. The proposed model not only balances the economic and environmental objectives but also evaluates the renewable energy penetration in a grid-connected university microgrid setting including electric vehicles. Simulation results across 11 French cities reveal significant trade-offs between economic feasibility and carbon reduction. Notably, a minimal increase in the Loss of Power Supply Probability (LPSP) can lead to notable reductions in LCE and LCOE. Optimal capacity configurations indicate a robust integration of PV and wind turbine resources when paired with strategically sized battery storage, ultimately enhancing renewable energy contributions by up to 40%. Conversely, the simulation results indicate that although the islanded microgrid configuration achieves complete renewable penetration by relying solely on local generation and storage, it leads to considerably higher LCOE and LCE values due to the need for high capacities to ensure reliability in the absence of grid support. This analysis highlights regional differences in resource availability, demonstrates the importance of customized microgrid strategies for diverse urban settings based on availability of the environmental resources. These findings show the effectiveness of the MILP-based framework in facilitating regional insights for informed microgrid planning and policy development with considering LPSP reliability aspect in the optimization problem.