Optimal Generation Programming using NSAIW PSO in a Cascade Hydroelectric System Placed on Narmada River

Abstract

In the process of cascade hydroelectric power plants, the water levels and their storage in each system within the cascade can be influenced by various factors. It is crucial to effectively manage the cascade system and optimize water resources to mitigate and anticipate both natural and operational challenges. This study introduces a novel approach known as Novel Self-Adapting Inertia Weighted Particle Swarm Optimization (NSAIW PSO) to enhance electric power Production in a hydroelectric system situated along the Narmada River. The research considers two distinct cases: Case 1: This scenario accounts for water loss due to evaporation, the necessity of meeting irrigation demands, and addressing irregularities in natural water flow. Case 2: In this case, the analysis includes losses occurring in the canal head powerhouse and other factors that might lead to excess water flow. The results indicate that in Case 2, an equivalent amount of water is utilized for power generation compared to Case 1, despite the need to meet the same load requirements. In two cases the total discharge of case 1 is more than case 2 and the Total average reservoir of case 1 is more than case 2. This finding underscores the significance of the Canal Head Power House in efficiently managing water resources and ensuring power generation meets demand. Omkareshwar plant has the highest capacity factor among all the power plants.