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A Scalable Method of Adaptive LVRT Settings Adjustment for Voltage Security Enhancement in Power Systems With High Renewable Penetration
IEEE Transactions on Sustainable Energy ( IF 8.8 ) Pub Date : 2021-09-28 , DOI: 10.1109/tste.2021.3116102
Chen Wang , Chetan Mishra , Virgilio Antonio Centeno

Recent expansion of inverter-based renewable generation (RG) has introduced unprecedented stability issues. One major challenge stems from tripping RGs offline during disturbances based on predefined operation thresholds (ride through curves) on voltage magnitudes and frequency at the point of common coupling (PCC). The current practice uses a single set of thresholds for the whole year across all RGs in the system. This could result in loss of these resources during critical times, particularly endangering system voltage security, i.e a significant reduction in the load margin (LM). On the other hand, relaxing these limits could result in them staying online even during islanding scenarios, which is a safety concern to the restoration crew. Thus, an approach to find minimal relaxations to these limits to enhance voltage security is proposed here. This process first constructs an optimization model aiming to minimize adjustments on RG voltage limits to reach anticipated LM increase and then solves it with a multi-stage screening method including base power-voltage (P-V) curve acquisition, critical RGs identification, successive screenings of candidate solutions based on sensitivities, and optimal solutions validation. This largely increases the scalability of the algorithm, which is demonstrated on the IEEE 14-bus, 118-bus systems, and a 500-bus system.

中文翻译:

可再生能源渗透率高的电力系统电压安全增强自适应低电压穿越设置的可扩展方法

最近基于逆变器的可再生能源发电 (RG) 的扩张引入了前所未有的稳定性问题。一项主要挑战源于在基于公共耦合点 (PCC) 处电压幅度和频率的预定义操作阈值(穿越曲线)的干扰期间使 RG 脱机。当前的做法是对系统中的所有 RG 使用一组全年的阈值。这可能会导致这些资源在关键时期丢失,特别是危及系统电压安全,即负载裕度 (LM) 的显着降低。另一方面,放宽这些限制可能会导致他们即使在孤岛情况下也能保持在线状态,这对修复人员来说是一个安全问题。因此,这里提出了一种找到这些限制的最小松弛以增强电压安全性的方法。该过程首先构建一个优化模型,旨在最大限度地减少对 RG 电压限制的调整以达到预期的 LM 增加,然后通过多阶段筛选方法解决该模型,包括基础电源电压 (PV) 曲线获取、关键 RG 识别、候选的连续筛选基于敏感性的解决方案和最佳解决方案验证。这在很大程度上增加了算法的可扩展性,这在 IEEE 14 总线、118 总线系统和 500 总线系统上得到了证明。和最佳解决方案验证。这在很大程度上增加了算法的可扩展性,这在 IEEE 14 总线、118 总线系统和 500 总线系统上得到了证明。和最佳解决方案验证。这在很大程度上增加了算法的可扩展性,这在 IEEE 14 总线、118 总线系统和 500 总线系统上得到了证明。
更新日期:2021-09-28
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