Statistical Modeling of Networked Solar Resources for Assessing and Mitigating Risk of Interdependent Inverter Tripping Events in Distribution Grids
Statistical Modeling of Networked Solar Resources for Assessing and Mitigating Risk of Interdependent Inverter Tripping Events in Distribution Grids
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DOI：
10.1109/tpwrs.2020.2973380
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发表时间：
2019-08
影响因子：
6.6
通讯作者：
K. Dehghanpour;Yuxuan Yuan;Fankun Bu;Zhaoyu Wang
中科院分区：
文献类型：
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作者：
K. Dehghanpour;Yuxuan Yuan;Fankun Bu;Zhaoyu Wang
据推测，基于逆变器的分布式光伏（PV）发电机的更高渗透率可能会增加由于电压波动而导致跳闸事件的风险。为了量化这种风险，公用事业公司需要实时求解联网PV的跳闸事件的交互式方程。然而，这些方程是不可微的，非线性的，指数复杂的，因此，不能被用来作为一个易于处理的基础，太阳能削减预测和缓解。此外，由于有限的电网可观测性，负载/PV功率值可能无法实时获得，这进一步使跳闸事件预测复杂化。为了应对这些挑战，我们采用切比雪夫不等式来获得另一种概率模型，用于量化联网PV的跳闸风险。该模型使运营商能够估计相互依赖的逆变器跳闸事件的概率，仅使用PV/负载统计，并在一个可扩展的方式。此外，通过将此概率模型集成到优化框架中，设计对策以减轻大规模相互依赖的跳闸事件。由于所提出的模型是参数化的节点有功/无功功率的统计特性，它是特别有益的，在实际系统中，具有有限的实时可观测性。采用真实的数据和馈线模型进行了数值实验，以验证所提出的技术的性能。
It is speculated that higher penetration of inverter-based distributed photo-voltaic (PV) power generators can increase the risk of tripping events due to voltage fluctuations. To quantify this risk utilities need to solve the interactive equations of tripping events for networked PVs in real-time. However, these equations are non-differentiable, nonlinear, and exponentially complex, and thus, cannot be used as a tractable basis for solar curtailment prediction and mitigation. Furthermore, load/PV power values might not be available in real-time due to limited grid observability, which further complicates tripping event prediction. To address these challenges, we have employed Chebyshev's inequality to obtain an alternative probabilistic model for quantifying the risk of tripping for networked PVs. The proposed model enables operators to estimate the probability of interdependent inverter tripping events using only PV/load statistics and in a scalable manner. Furthermore, by integrating this probabilistic model into an optimization framework, countermeasures are designed to mitigate massive interdependent tripping events. Since the proposed model is parameterized using only the statistical characteristics of nodal active/reactive powers, it is especially beneficial in practical systems, which have limited real-time observability. Numerical experiments have been performed employing real data and feeder models to verify the performance of the proposed technique.