The high penetration of distributed generation (DG) sources in distribution networks (DN) can induce overvoltage issues. In this paper, an artificial intelligence based fair and optimal method for voltage regulation in DN with high photovoltaic (PV) penetration is proposed. Based on the forecasting of solar radiance and load profiles, the method optimally dispatches the generation of PVs to prevent overvoltage with the objective of minimizing the energy curtailment of PVs for a given long period. In addition, the RPCM can adaptively adjust the curtailment of PVs based on fuzzy neural network algorithm so that the PV systems in the DN could reach and keep similar accumulated curtailments during the period. Steady state simulation studies under various scenarios have been carried out on a 69-bus distribution feeder and an actual distribution network to demonstrate the effectiveness of the proposed method.

中文翻译：

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基于模糊神经网络的高光伏渗透配电网电压安全优化和公平真实电力管理

分布式发电 (DG) 源在配电网络 (DN) 中的高渗透率会引发过压问题。在本文中，提出了一种基于人工智能的公平优化方法，用于具有高光伏 (PV) 渗透率的 DN 电压调节。该方法基于太阳辐射和负载曲线的预测，优化调度 PV 的发电以防止过电压，目标是在给定的长时间内最大限度地减少 PV 的能量削减。此外，RPCM 可以基于模糊神经网络算法自适应调整光伏的限电，使 DN 中的光伏系统在此期间达到并保持相似的累计限电。