Microgrids (MGs) play a critical role to enhance the flexibility and efficiency of the distribution systems as well as reliability and environmental problems. In this paper, we propose a two-stage multi-objective optimization framework for optimal energy management of multi-microgrid systems (MMG). The proposed model considers the total cost, energy not supplied (ENS), and greenhouse gas emissions to determine the best plan for the MMG system. We propose a hybrid lexicography-compromise programming (CP) to handle non-homogeneous objective functions by the two-stage technique. At the first stage, the operation cost of the MMG system is minimized to determine the best plan from the economic perspective. At the second stage, the ENS and greenhouse gas emissions have been considered objective functions using CP method. The main advantage of the proposed model is that it remains the operation cost of the MMG system at its optimum. The proposed model is based on the cooperation of MGs to provide a stable and reliable solution, where the total cost of the MMG system has been allocated among MGs based on their contributions. The simulation results show the cost of the multi-microgrid system, ENS, and CO2 emissions are improved by 33.72%, 83.5%, and 8%, respectively.

微电网 (MG) 在提高配电系统的灵活性和效率以及可靠性和环境问题方面发挥着关键作用。在本文中，我们提出了一个两阶段多目标优化框架，用于多微电网系统 (MMG) 的优化能源管理。提议的模型考虑了总成本、未供应能源 (ENS) 和温室气体排放，以确定 MMG 系统的最佳计划。我们提出了一种混合词典编纂妥协编程（CP）来通过两阶段技术处理非齐次目标函数。在第一阶段，最小化MMG系统的运行成本，从经济角度确定最佳方案。在第二阶段，ENS 和温室气体排放已经被认为是使用 CP 方法的目标函数。所提出模型的主要优点是它使 MMG 系统的运行成本保持在最佳状态。所提出的模型基于 MG 的合作以提供稳定可靠的解决方案，其中 MMG 系统的总成本已根据其贡献在 MG 之间分配。仿真结果表明，多微电网系统成本、ENS 和 CO2 排放量分别提高了 33.72%、83.5% 和 8%。