Robust operation of distribution network based on photovoltaic/wind energy resources in condition of COVID-19 pandemic considering deterministic and probabilistic approaches.

In this paper, optimal allocation and planning of wind and photovoltaic energy resources are performed in a distribution network with the objective of reducing losses, improving reliability, and minimizing energy generation cost in terms of changes in load consumption pattern during the COVID-19 pandemic condition. The main goal is identifying the best operating point, ie the optimal location and size of clean energy resources in the worst load change conditions, which ensures the best network operation in all conditions during the COVID-19 condition via the turbulent flow of water-based optimization (TFWO). First, the deterministic approach is implemented in Hybrid and Distributed cases before and during COVID-19 conditions. The probabilistic approach is performed considering generation uncertainty during the COVID-19 conditions. The results showed better performance in the Distributed case with the lowest losses and higher reliability improvement. Moreover, the losses are significantly reduced and the reliability is improved during the COVID-19 pandemic conditions. The findings indicate that the allocation and planning during the COVID-19 conditions is a robust option in network operating point changes. Also, the probabilistic results showed that considering the uncertainty has increased active and reactive losses (4.67% and 5.82%) and weakened the reliability (10.26%) of the deterministic approach.