Derivation and performance evaluation of optimal operating policies for a reservoir using a novel PSO with elitism and variational parameters

ABSTRACT

In India, many major and medium reservoirs have been constructed to meet the fast-growing demands of irrigation, hydropower generation, drinking and industrial water supply. To achieve social and economic sustainability in water scarce areas, it is vital to efficiently manage available water resources. Indeed, water resources systems are complex and require systematic study to facilitate optimal planning and management decisions. The present study supports the strategies designed to check the deficit in water availability for Indira Sagar Reservoir system in Madhya Pradesh, India, using a novel approach of standard PSO combining two variants, elitism and variational parameters, namely a time-variant elitist mutation multi-objective particle swarm optimization (TV-EMMOPSO) . The performance of the proposed algorithm is compared with the optimal operation policies developed by multi-objective particle swarm optimization (MOPSO) and elitistmutation particle swarm optimization (EM-MOPSO). The results obtained can help the managers of Indira Sagar Reservoir  plan better strategies in future.

KEYWORDS:

• Multi-objective optimization
• particle swarm optimization
• elitist mutation
• time-variant
• reservoir operation

Acknowledgements

All data used during the study were provided by a third party. Direct requests for these materials may be made to the provider.

Disclosure statement

No potential conflict of interest was reported by the authors.