Abstract This paper proposes a cost-effective two-stage optimization model for microgrid (MG) planning and scheduling with compressed air energy storage (CAES) and preventive maintenance (PM). In the first stage, we develop a two-objective planning model, which consists of power loss and voltage deviation, to determine the optimal location and size of MG. Then, a stochastic scheduling model is presented in the second stage to balance outputs of distributed generations (DGs), charging and discharging power of CAES, power exchange costs of MG and PM costs of DGs. Whilst we derive a credibility assessment-based risk aversion model, named conditional value-at-credibility (CVaC), to hedge against uncertain wind power. The proposed model has been evaluated on the IEEE testing system and numerical results demonstrate the effectiveness of the model by providing the optimal trade-off solution in terms of the economy and security.

中文翻译：

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具有压缩空气储能和预防性维护的微电网规划和调度的经济高效的两阶段优化模型

摘要 本文提出了一种具有成本效益的两阶段优化模型，用于具有压缩空气储能 (CAES) 和预防性维护 (PM) 的微电网 (MG) 规划和调度。在第一阶段，我们开发了一个由功率损耗和电压偏差组成的双目标规划模型，以确定 MG 的最佳位置和大小。然后，在第二阶段提出了一个随机调度模型来平衡分布式电源（DGs）的输出、CAES的充放电功率、MG的换电成本和DGs的PM成本。同时我们推导出一个基于可信度评估的风险规避模型，称为条件可信价值 (CVaC)，以对冲不确定的风电。