Prevention and Survivability for Power Distribution Resilience: A Multi-Criteria Renewables Expansion Model
Prevention and Survivability for Power Distribution Resilience: A Multi-Criteria Renewables Expansion Model
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DOI：
10.1109/access.2020.2993020
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发表时间：
2020-05
期刊：
影响因子：
3.9
通讯作者：
Honggang Wang;T. Jin
中科院分区：
文献类型：
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作者：
Honggang Wang;T. Jin
分布式能源能够通过孤岛运行增强电网的应变能力。本文提出了一种多年、多准则的发电扩展模型，通过可再生能源的整合来实现配电网的抗冲击能力。在自然灾害后配电线路或燃料生命线被摧毁的情况下，风能和太阳能发电机形成岛状微电网，为关键负荷提供电力。目标是确定分布式能源的规模、选址和维护，以使系统成本和应急时的电力短缺降至最低。用矩方法和中心极限定理刻画了空间气候不确定性、发电间歇性和电压变化。研究贡献是双重的。首先，扩展模型通过满足年负荷增长、减少碳足迹和增强表现为预防和生存能力的电网弹性，实现了三重目标。其次，我们提出了一种改进的直接之字形算法来搜索Pareto解。数值算例表明，Z字形搜索算法的性能优于基于进化的算法，因为它可以通过探索更广泛的Pareto前沿来识别更高质量的非优势解。
Distributed energy resources are capable of enhancing grid resilience through island operations in contingency. This paper proposes a multi-year, multi-criteria generation expansion model to achieve distribution power resilience through renewable energy integration. In cases that distribution circuits or fuel lifeline are destroyed post natural disasters, wind- and solar-based generators form island microgrids to power the critical load. The goal is to determine the sizing, siting and maintenance of distributed energy resources such that system cost and power shortage in contingency are minimized. Moment methods and central limit theorem are used to characterize the spatial climate uncertainty, generation intermittency, and voltage variation. The research contributions are twofold. First, the expansion model achieves triple goals by meeting the annual load growth, reducing the carbon footprint, and enhancing the grid resilience manifested as prevention and survivability. Second, we present an improved direct zigzag algorithm to search for the Pareto solutions. Numerical examples show that the zigzag search outperforms evolutionary-based algorithms as it can identify higher-quality non-dominant solutions by exploring a wider Pareto frontier.