Microgrids (MGs) are solutions to integrate high shares of variable renewable energy which can contribute to more economical and environmental benefits, as well as improving the energy supply efficiency. One significant potential of MGs is an expanded opportunity to use the waste heating energy from the conversion of the primary fuel (such as natural gas) to generate electricity. The use of waste heat in combined heat and power (CHP)-based MG is more efficient to meet local load and decrease the emission pollution. Hence, this paper elaborates on optimal multi-objective scheduling of CHP-based MG coupled with compressed air energy storage (CAES), renewable energy, thermal energy storage (TES), and demand response programs through shiftable loads, which considers a reconfiguration capability. The embedded CAES, in addition to the charging/discharging scheme, can operate in a simple cycling mode and serve as a generation resource to supply local load in an emergency condition. The daily reconfiguration of MG will introduce a new generation of MG named reconfigurable microgrid (RMG) that offers more flexibility and enhances system reliability. The RMG is coupled with TES to facilitate the integration of the CHP unit that enables the operator to participate in the thermal market, in addition to the power market. The main intents of the proposed multi-objective problem are to minimize the operation cost along with a reduction in carbon emission. The epsilon-constraint technique is used to solve the multi-objective problem while fuzzy decision making is implemented to select an optimal solution among all the Pareto solutions. The electricity prices and wind power generation variation are captured as random variables in the model and the scenario-based stochastic approach is used to handle them. Simulation results prove that the simultaneous integration of multiple technologies in CHP-based RMG decreases the operation cost and emission up to 3 % and 10.28 %, respectively.

微电网（MGs）是整合大量可变可再生能源的解决方案，这可以带来更多的经济和环境效益，并提高能源供应效率。MG的一个重要潜力是扩大了利用主要燃料（例如天然气）转化产生的废热能发电的机会。在基于热电联产（MGP）的MG中使用废热更为有效，可以满足当地的负荷并减少排放污染。因此，本文详细阐述了基于CHP的MG的最优多目标调度，并结合了可压缩负载的压缩空气能量存储（CAES），可再生能源，热能存储（TES）和需求响应程序，并考虑了重新配置功能。嵌入式CAES，除了充电/放电方案外，它还可以以简单的循环模式运行，并作为发电资源在紧急情况下提供本地负载。MG的每日重新配置将引入新一代的MG，称为可重配置微电网（RMG），它可提供更大的灵活性并增强系统可靠性。RMG与TES耦合在一起，以促进CHP单元的集成，从而使操作员不仅可以参与电力市场，还可以参与热力市场。提出的多目标问题的主要目的是在降低碳排放的同时将运营成本降至最低。ε约束技术用于解决多目标问题，而模糊决策则可在所有Pareto解中选择最佳解。电价和风力发电的变化被捕获为模型中的随机变量，并使用基于情景的随机方法来处理它们。仿真结果表明，将多种技术同时集成到基于CHP的RMG中，可将运行成本和排放分别降低3％和10.28％。