Fuzzy Neural Network Based Optimal and Fair Real Power Management for Voltage Security in Distribution Networks with High PV Penetration

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.