Abstract Standalone dc microgrid faces a significant reliability risk due to continuous variation in power from renewable energy generation and the load demand. Usually, the output power from the renewable generators fluctuates with the weather conditions. The load is also varying all the time. This leads to a continuous risk of power mismatch in the system. Thus, a complementary generation or a storage system is required for maintaining the power balance in the system. This paper introduces a supervisory power management strategy (PMS) for a standalone dc microgrid with multiple distributed generations, load, and a battery energy storage system. The PMS is designed based on the model predictive control (MPC) approach. The complete mathematical model of the system has been developed, and it has been utilized in the MPC controller to solve an optimization problem with operating constraints. A forecasting technique is also incorporated in the proposed MPC to predict the environmental and load demand parameters. Simulation results illustrate the effectiveness of the presented MPC-based power management approach. Accordingly, the proposed approach effectively manages the power among the generators, load, and the battery and stabilizes the dc voltage. The paper also evaluates the effects of various prediction methods on the controller performance.

中文翻译：

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基于 MPC 的具有储能的独立直流微电网的电源管理

摘要 由于可再生能源发电和负载需求的不断变化，独立直流微电网面临着重大的可靠性风险。通常，可再生发电机的输出功率会随着天气状况而波动。负载也一直在变化。这导致系统中功率不匹配的持续风险。因此，需要一个互补的发电或存储系统来维持系统中的功率平衡。本文介绍了一种用于具有多个分布式发电、负载和电池储能系统的独立直流微电网的监督电源管理策略 (PMS)。PMS 是基于模型预测控制 (MPC) 方法设计的。已经建立了系统的完整数学模型，它已被用于 MPC 控制器以解决具有操作约束的优化问题。建议的 MPC 中还包含一种预测技术，以预测环境和负载需求参数。仿真结果说明了所提出的基于 MPC 的电源管理方法的有效性。因此，所提出的方法有效地管理发电机、负载和电池之间的功率并稳定直流电压。本文还评估了各种预测方法对控制器性能的影响。所提出的方法有效地管理发电机、负载和电池之间的功率并稳定直流电压。本文还评估了各种预测方法对控制器性能的影响。所提出的方法有效地管理发电机、负载和电池之间的功率并稳定直流电压。本文还评估了各种预测方法对控制器性能的影响。