A novel optimization algorithm for UC, ELD and scheduling of hybrid energy storage system

In today's world, the use of renewable resources is increasing due to cost-effective and eco-friendly solutions. Predominantly, using renewable sources in power generation leads to a decrease in cost value. Renewable sources such as wind and solar have power variations in their output because of seasonal changes. Therefore accurate forecasting is required for solar and wind energy. In this paper, a hybrid storage unit is developed to store the generated energy from solar, wind, and diesel generator. Because of large power storage purposes, the paper combines battery and super magnetic storage systems. The power from the hybrid storage unit is decided using the cat swarm optimization algorithm. Moreover, the paper proposes black widow optimization algorithm to solve problems such as contingency-constrained economic load dispatch (CCELD) in the transmission line. The CCELD problem solves the minimum fuel cost and minimum severity index. A standard IEEE 57 bus system is used to study the efficacy of a BWO algorithm for the CCELD problem. The final fuel cost value of line outages L1-L2, L1-L3, L3-L4, and L2-L5 are 2069.84Rs/hr, 2484.27Rs/hr, 1750.95Rs/hr, and 1381.94Rs/hr, respectively. The proposed method reduces overall cost to 19.33% with branch and rescue navigator method and 23.39% with enhanced mixed particle swarm optimization.