A Resilience-Oriented Approach for Microgrid Energy Management with Hydrogen Integration during Extreme Events
A Resilience-Oriented Approach for Microgrid Energy Management with Hydrogen Integration during Extreme Events
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DOI：
10.3390/en16248099
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发表时间：
2023-12
期刊：
影响因子：
3.2
通讯作者：
Masoumeh Sharifpour;M. Ameli;H. Ameli;Goran Strbac
中科院分区：
文献类型：
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作者：
Masoumeh Sharifpour;M. Ameli;H. Ameli;Goran Strbac
本文提出了一种面向能量管理的方法（R-OEMA），旨在加强网络化微电网（NMG）在极端事件面前的弹性。R-OEMA方法战略性地结合了用于氢（H2）系统、可再生单元、可控分布式发电机（DG）和需求响应计划（DRP）的预防性调度技术。它力求在最大限度地提高业务收入和最大限度地降低成本之间实现最佳的微妙平衡，同时满足正常和关键业务模式的需要。R-OEMA框架的评估是通过对由三个微电网（MG）组成的测试系统进行数值模拟来进行的。模拟考虑了各种灾难场景，导致停电的不同持续时间。结果强调了R-OEMA方法在极端事件期间增强NMG弹性和提高运营效率的有效性。具体来说，该方法集成了氢气系统、需求响应和可控DG，通过预测性见解协调它们的协作操作。这确保了他们在中断情况下为紧急操作做好准备，使关键负载的供应在极端灾害情况下达到82%，在温和情况下达到100%。该模型采用混合整数线性规划（MILP）框架，无缝集成了预测见解和预调度策略。这种新的方法有助于推进NMG弹性，这些模拟的结果显示。
This paper presents a resilience-oriented energy management approach (R-OEMA) designed to bolster the resilience of networked microgrids (NMGs) in the face of extreme events. The R-OEMA method strategically incorporates preventive scheduling techniques for hydrogen (H2) systems, renewable units, controllable distributed generators (DGs), and demand response programs (DRPs). It seeks to optimize the delicate balance between maximizing operating revenues and minimizing costs, catering to both normal and critical operational modes. The evaluation of the R-OEMA framework is conducted through numerical simulations on a test system comprising three microgrids (MGs). The simulations consider various disaster scenarios entailing the diverse durations of power outages. The results underscore the efficacy of the R-OEMA approach in augmenting NMG resilience and refining operational efficiency during extreme events. Specifically, the approach integrates hydrogen systems, demand response, and controllable DGs, orchestrating their collaborative operation with predictive insights. This ensures their preparedness for emergency operations in the event of disruptions, enabling the supply of critical loads to reach 82% in extreme disaster scenarios and 100% in milder scenarios. The proposed model is formulated as a mixed-integer linear programming (MILP) framework, seamlessly integrating predictive insights and pre-scheduling strategies. This novel approach contributes to advancing NMG resilience, as revealed by the outcomes of these simulations.