由于可再生能源在配电系统中的密集集成以及发电中的相关不确定性,出现了许多挑战。因此,在分销层面制定本地管理策略,导致微电网等概念的出现。微电网包括各种加热,冷却,电力资源和负荷,运营商的目标是最大限度地降低运营和停机成本。由于严重的配电系统中断通常是由地震等事件引起的,洪水,和飓风,微电网运营商被迫提高弹性,以确保在这种情况下不间断的服务。本文设计了一种混合整数线性规划模型来优化微电网的能量管理和结构配置。此优化旨在提高弹性成本,最大限度地减少运营和资本成本以及电力损失和污染。为了实现这些目标,实现了几个工具,包括重新配置,storages,联合冷却,热力和动力装置,风力涡轮机,光伏板,以及电容器。定义了四个案例研究来证明开发的模型效率。第一个案例研究的重点是微电网中的能源管理,以实现运营成本的最小化。第二个案例研究强调了在能源管理的同时提高弹性,旨在最大限度地降低成本和增强弹性。在第三种情况下,微电网的重新配置能力也被添加到第二种情况。因此,此案例旨在优化微电网内的能源和结构管理,以同时增强弹性并最大程度地降低运营成本。最后,在第四种情况下,这个问题是用多目标方法研究的。通过比较结果,阐明了对微电网运行的弹性影响。通过考虑微电网运营中的弹性概念,并根据案例2的结果,发现运营成本平均增加了10.38%。然而,因为弹性成本平均降低了13.91%,与案例1相比,案例2的总成本平均降低了5.93%。此外,当比较情况2和3时,可以确定重构效果。可以看出,运营成本平均下降了4.5%。此外,弹性成本平均下降1.61%,与案例2相比,案例3的总目标函数平均减少了2.43%。
Many challenges have emerged due to the intense integration of renewables in the distribution system and the associated uncertainties in power generation. Consequently, local management strategies are developed at the distribution level, leading to the emergence of concepts such as
microgrids.
Microgrids include a variety of heating, cooling, and electrical resources and loads, and the operators\' aim is to minimize operation and outage costs. Since significant distribution system outages are typically caused by events such as earthquakes, floods, and hurricanes, microgrid operators are compelled to improve resilience to ensure uninterrupted service during such conditions. A mixed-integer linear programming model is designed in this paper to optimize the energy management and structural configuration of
microgrids. This optimization aims to enhance resilience cost, minimizing operation and capital costs as well as power loss and pollution. To achieve these goals, several tools are implemented including reconfiguration, storages, combined cooling, heat and power units, wind turbines, photovoltaic panels, as well as capacitors. Four case studies are defined to prove the developed model efficiency. The first case study focuses on energy management in the microgrid for operation cost minimization. The second case study emphasizes the improvement of resilience alongside energy management, aiming at minimizing costs and enhance resilience. In the third case, the microgrid\'s reconfiguration capability is also added to the second case. Therefore, this case aims to optimize both energy and structural management within the microgrid to simultaneously enhance resilience and minimize operational costs. Finally, in the fourth case, the problem is studied in a multi-objective approach. By comparing the results, the resilience impact on the operation of
microgrids is elucidated. By considering the resilience concept in microgrid operation and based on the results of case 2, it is found that the operating costs are increased by an average of 10.38 %. However, because of reducing resilience costs by an average of 13.91 %, the total cost is reduced by an average of 5.93 % in case 2 compared to case 1. Furthermore, when comparing cases 2 and 3, the reconfiguration effect can be determined. It can be observed that the operating costs are decreased by an average of 4.5 %. Moreover, the resilience cost is decreased by an average of 1.61 %, resulting in an overall reduction of the total objective function by an average of 2.43 % in case 3 compared to case 2.