Multi-reservoir optimization for hydropower production using NLP technique

Abstract

Deriving the optimal operational rules for a multi-reservoir system serving various purposes like irrigation, multiple hydropower plants and flood control are complex. In the present study, such a multi-reservoir system with multiple hydropower plants are optimized for maximizing the hydropower production and satisfying the irrigation demands using a Non-linear Programming (NLP) technique. The developed NLP model has been applied to Koyna Hydro-Electric Project (KHEP) for maximizing the hydropower production and solved for three different dependable inflow scenarios under various operating policies. The complexity of the problem is such that the power releases and irrigation releases are in opposite direction and are non-commensurate. The total annual power production, monthly power production and the end of the month storage plots are compared for different inflows and operating policies. From the study, it is found that hydropower production can be increased to a minimum of 22% by slightly relaxing the tribunal constraint on releases towards the western side. The optimal releases from Policy 3 are further evaluated using a simulation model. The simulation result shows that the optimal releases have performed satisfactorily over long period of operation.