Optimal sizing and energy management of a microgrid: A joint MILP approach for minimization of energy cost and carbon emission

The optimal design and operation of microgrids involves complex trade-offs between technical, economic, and environmental factors. This research addresses these challenges by proposing a comprehensive approach that combines the sizing and energy management problems of a microgrid into a single decision-making framework. The study introduces a joint multi-objective mixed-integer linear programming algorithm that minimizes the levelized cost of energy (LCOE) and life cycle emissions (LCE) of the microgrid formed by photovoltaic system, battery storage, and with/without grid connections. By considering 25-year project lifetime horizon and hourly energy management, the algorithm ensures an optimal solution that accounts for long-term planning and real-time operation. The research conducts an analysis of French electricity grid as a case study where a Pareto-front is created using the trade-off constraint approach. Furthermore, the impact of peak shaving is assessed on Pareto-front for various subscription power to utility grid. Lastly, the research examines energy sources in the French electricity grid, revealing insights into the energy mix’s implications for microgrid design. The results showed that LCOE and LCE can vary up to 28% and 17%, respectively, while the local renewable energy utilization can be increased to 54% by limiting the grid subscription power at 36 kVA. •Optimal microgrid sizing and energy management with multi-objective optimization problem solving.•Consideration of the technical, economical, and environmental aspects of the microgrid planning.•Analysis of the Pareto front in a weighted multi-objective optimization problem.•Assessment of peak shaving impact related to LCOE and LCE on the Pareto front analysis.•Examination of energy sources utilization in the French energy mix.