A microgrid control scheme for islanded operation and re-synchronization utilizing Model Predictive Control

IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Sustainable Energy Grids & Networks Pub Date : 2024-07-01 DOI:10.1016/j.segan.2024.101464
Fernando Fachini , Tetiana Bogodorova , Luigi Vanfretti , Sjoerd Boersma
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Abstract

Enhancing grid resilience is proposed through the integration of distributed energy resources (DERs) with microgrids. Due to the diverse nature of DERs, there is a need to explore the optimal combined operation of these energy sources within the framework of microgrids. As such, this paper presents the design, implementation and validation of a Model Predictive Control (MPC)-based secondary control scheme to tackle two challenges: optimal islanded operation, and optimal re-synchronization of a microgrid. The MPC optimization algorithm dynamically adjusts input signals, termed manipulated variables, for each DER within the microgrid, including a gas turbine, an aggregate photovoltaic (PV) unit, and an electrical battery energy storage (BESS) unit. To attain optimal islanded operation, the secondary-level controller based on Model Predictive Control (MPC) was configured to uphold microgrid functionality promptly following the islanding event. Subsequently, it assumed the task of power balancing within the microgrid and ensuring the reliability of the overall system. For optimal re-synchronization, the MPC-based controller was set to adjust the manipulated variables to synchronize voltage and angle with the point of common coupling of the system. All stages within the microgrid operation were optimally achieved through one MPC-driven control system, where the controller can effectively guide the system to different goals by updating the MPC’s target reference. More importantly, the results show that the MPC-based control scheme is capable of controlling different DERs simultaneously, mitigating potentially harmful transient rotor torques from the re-synchronization as well as maintaining the microgrid within system performance requirements.

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利用模型预测控制实现孤岛运行和再同步的微电网控制方案
有人建议通过将分布式能源资源(DER)与微电网相结合来增强电网的恢复能力。由于 DER 的多样性,有必要探索这些能源在微电网框架内的优化组合运行。因此,本文介绍了基于模型预测控制 (MPC) 的二次控制方案的设计、实施和验证,以应对两个挑战:最佳孤岛运行和微电网的最佳再同步。MPC 优化算法可动态调整微电网中每个 DER(包括燃气轮机、聚合光伏 (PV) 单元和蓄电池储能 (BESS) 单元)的输入信号(称为操纵变量)。为实现最佳孤岛运行,基于模型预测控制(MPC)的二级控制器被配置为在孤岛事件发生后立即维持微电网功能。随后,它承担起微电网内的功率平衡任务,并确保整个系统的可靠性。为了实现最佳的再同步,基于 MPC 的控制器被设定为调整操纵变量,使电压和角度与系统的公共耦合点同步。通过一个 MPC 驱动的控制系统,微电网运行的所有阶段都得到了优化,控制器可以通过更新 MPC 的目标参考值有效地引导系统实现不同的目标。更重要的是,研究结果表明,基于 MPC 的控制方案能够同时控制不同的 DER,减轻重新同步带来的潜在有害瞬态转子扭矩,并将微电网维持在系统性能要求范围内。
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来源期刊
Sustainable Energy Grids & Networks
Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology
CiteScore
7.90
自引率
13.00%
发文量
206
审稿时长
49 days
期刊介绍: Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.
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