Hourly Congestion Management by Adopting Distributed Energy Storage System using Hybrid Optimization

In this paper, the optimal location and sizing of DESS are proposed for transmission congestion management. Transmission Congestion Cost (TCC) is used to find the optimal location of DESS, whereas hybrid optimization based on Flower Pollination Algorithm (FPA) and Differential Evolution (DE) is proposed for optimal sizing of DESS. The methodology considering Solar PV and Energy Storage System (ESS) as sources of energy is being used. 24 hours real temperature and solar irradiance data of Delhi are taken to mathematically model the generation from Solar PV to manage congestion throughout the 24 hours. ESS is used to store surplus energy. The proposed approach is tested on IEEE-30 and IEEE-57 bits systems, and 24 hours demand is assumed to follow the hourly load shape (summer season) of the IEEE reliability test system. The performance of the proposed approach is validated by comparing the results obtained through hybrid (FPA-DE) optimization with the results obtained through DE optimization. It is observed from the experiment that both the optimization techniques (DE, Hybrid) performed well in managing congestion. However, DE has a higher consumption of resources that lead to shortage of resources at the end of the day; hence fails to manage congestion the next day, when solar irradiance is not available. In contrast, hybrid optimization provides very encouraging results, and at the end of the day saves approx. 39% of ESS, thus can participate in congestion management for the next day in the absence of solar irradiance.