The increasing number of distributed energy resources (DERs), advancing communication and computation technologies, and reliability concerns of the customers have caused an intense interest in the concept of microgrid. Although DERs are the biggest motivation of the microgrids due to their intermittent generation characteristics, they constitute a risk for system reliability. Battery storage systems (BSSs) stand as one of the most effective solutions for this reliability problem. However, the inappropriate use of BSS creates other operational problems in power systems. In order to deal with these concerns explicitly in microgrids, an optimized microgrid central controller (MGCC) is the key factor, which controls the realtime operation of a microgrid. This work proposes a model predictive control (MPC) based MGCC that will provide optimal control of the microgrid, considering economic and operational constraints. The proposed system will minimize the energy cost of the microgrid by utilizing mixed-integer linear programming (MILP) assuming the presence of DERs and BSS as well as the bi-directional grid connection. Moreover, the aging effect of BSS will be considered in the proposed optimization problem which will provide an up-to-date system model. The proposed method is evaluated using real load and photovoltaic (PV) generation data.

中文翻译：

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考虑电池老化的微电网模型预测控制

越来越多的分布式能源（DER），先进的通信和计算技术以及客户的可靠性问题引起了人们对微电网概念的强烈兴趣。尽管DER由于其间歇性生成特性而成为微电网的最大动力，但它们却构成了系统可靠性的风险。电池存储系统（BSS）是解决此可靠性问题的最有效解决方案之一。但是，BSS的不当使用会在电力系统中产生其他操作问题。为了在微电网中明确处理这些问题，优化的微电网中央控制器（MGCC）是关键因素，它控制着微电网的实时运行。这项工作提出了一种基于模型预测控制（MPC）的MGCC，它将在考虑经济和运营约束的情况下提供对微电网的最佳控制。假设存在DER和BSS以及双向网格连接，建议的系统将通过使用混合整数线性规划（MILP）来使微电网的能源成本最小化。此外，在提出的优化问题中将考虑BSS的老化效应，该问题将提供最新的系统模型。使用实际负载和光伏（PV）生成数据评估提出的方法。假设存在DER和BSS以及双向网格连接，建议的系统将通过使用混合整数线性规划（MILP）来使微电网的能源成本最小化。此外，在提出的优化问题中将考虑BSS的老化效应，该问题将提供最新的系统模型。使用实际负载和光伏（PV）生成数据对提出的方法进行评估。假设存在DER和BSS以及双向网格连接，建议的系统将通过使用混合整数线性规划（MILP）来使微电网的能源成本最小化。此外，在提出的优化问题中将考虑BSS的老化效应，该问题将提供最新的系统模型。使用实际负载和光伏（PV）生成数据评估提出的方法。