Energy exchange optimization among multiple geolocated microgrids: A coalition formation approach for cost reduction

This paper describes a hierarchical energy management system for multiple geolocated microgrids, with the aim of minimizing operational costs and maximizing individual benefits. To achieve this goal, a coalition formation algorithm is developed to optimize energy exchanges between geolocated microgrids, leading to a significant reduction in costs. At the local level (first layer), optimization is performed using mixed-integer linear programming, while at the central level, the optimization is carried out through the coalition formation algorithm. The formation of coalitions among geolocated microgrids has demonstrated substantial benefits. For instance, coalitions showed the highest percentage reductions in losses (52.63% to 71.53%) in the cooperative state compared to the non-cooperative state, indicating significant cost savings. In contrast, lower percentage reductions in losses (12.08% to 16.10%) were observed, yet they still benefited from reduced operational costs. Throughout the day, the cooperative method consistently proved to be more effective than the non-cooperative method. The effectiveness of coalitions in reducing losses and operational costs is demonstrated, emphasizing the importance of flexible approaches in addressing challenges such as geolocation and variable weather conditions. This study contributes to the advancement of distributed energy systems, supporting the transition to more sustainable and resilient systems. •Coalition algorithm reduces energy losses by up to 71.53% in geolocated microgrids.•Cooperative strategies enable GMGs to save up to 15% in energy costs.•Real-time coalition adjustment improves system reliability and balance.•Geolocation and weather data optimize coalition formation in GMG networks.•Scalable method efficiently handles large, distributed GMG energy networks.