Low-carbon economic optimization of microgrid clusters based on an energy interaction operation strategy

• Published in: Nonlinear engineering Vol. 14; no. 1; pp. 1557 - 72
• Main Authors: Li, Guoyu, Yin, Zekun
• Format: Journal Article
• Language: English
• Published: Berlin De Gruyter 14.08.2025; Walter de Gruyter GmbH
• Subjects: Carbon; Carbon content; Clusters; Distributed generation; Economic impact; Emissions; Energy; Energy costs; energy interaction; Energy utilization; Environmental protection; low carbon economy; microgrid cluster; Operating costs; operation strategy; Optimization; Optimization models
• ISSN: 2192-8029; 2192-8010; 2192-8029
• DOI: 10.1515/nleng-2025-0134

By optimizing energy utilization and integration, microgrids can improve the reliability of energy supply, reduce energy operating costs, and decrease energy emissions. However, there is insufficient coordination between energy interaction and low-carbon operation systems, resulting in increased carbon emissions and energy waste. Therefore, a low-carbon economic optimization method for microgrid clusters is built based on energy interaction operation strategies. This method adopts a multi-energy collaborative operation mode to construct a low-carbon optimization model for microgrid clusters. In the comparison of operating costs between microgrid clusters with and without energy interaction, for microgrids A, B, and C, when there was energy interaction, the operating costs of microgrids A and B both decreased by 25,400 RMB and 16,400 RMB, respectively, while the operating cost of microgrid C increased by 5,200 RMB. In terms of purchasing electricity costs, the purchasing electricity costs of microgrids A, B, and C all decreased in the energy interaction. In terms of purchasing gas costs, the purchasing cost of microgrid A slightly increased, while the purchasing cost of microgrids B and C decreased. Adopting energy interaction strategies has a positive effect on the economic cost of purchasing energy. After energy interaction, the purchasing demand of microgrid A was less than 4,000 kW, and most of the time, the purchasing energy demand was low. However, compared with before energy interaction, the purchasing demand of microgrids B and C significantly decreased. In the cost of carbon sales on microgrids, microgrids A, B, and C increased by $213.73, $230.02, and $415.92, respectively, in scenarios 1–3. The designed method has a promoting effect on the comprehensive operational economy and low-carbon emissions of microgrid clusters, providing technical references for the safety, stability, and environmental protection of microgrid clusters.