Multi-level interval rolling warning method for distributed photovoltaic fluctuation events

Yumin Zhang, Yunrui Qi, Pingfeng Ye, Zhengmao Li, Jiajia Yang, Xingquan Ji
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Abstract

The power fluctuation of distributed photovoltaic (PV) systems significantly impacts the balance of the power system, leading to risks like PV curtailment and load shedding. This paper proposes a multi-level rolling warning method for distributed PV power fluctuation (DPPF) based on interval analysis, aiming to establish a framework for proactively mitigating the potential adverse effects of fluctuations in distributed PV systems. Firstly, the power control mechanism to deal with DPPF is clarified, and warning levels are defined to determine the range of fluctuations that can be controlled by different power control measures. Secondly, based on the probability density of DPPF, the probabilities of each warning level are obtained by integrating the probability densities within each warning range. Finally, the differences in the forecasting accuracy of PV power fluctuations at different time scales are analysed, and the rolling warning of DPPF is achieved by periodically updating PV power output to adjust the warning results. Simulation results demonstrate that the proposed method identifies the thresholds for each warning range and provides warnings for different system operating conditions and PV power fluctuation events, confirming its effectiveness and applicability.

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