Multi-objective reservoir operation of the Ukai reservoir system using an improved Jaya algorithm

This paper introduces an effective and reliable approach based on a multi-population approach, namely the self-adaptive multi-population Jaya algorithm (SAMP-JA), to extract multi-purpose reservoir operation policies. The current research focused on two goals: minimizing irrigation deficits and maxi...

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Vydané v:Water science & technology. Water supply Ročník 22; číslo 2; s. 2287 - 2310
Hlavní autori: Kumar, Vijendra, Yadav, S. M.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London IWA Publishing 01.02.2022
Predmet:
Adaptive algorithms
Algorithms
Convergence
Genetic algorithms
Hydroelectric power
Hydroelectric power generation
hydropower generation
Invasive plants
Irrigation
Linear programming
Multiple objective analysis
Multipurpose reservoirs
optimization
Optimization algorithms
Optimization techniques
Particle swarm optimization
Reservoir operation
self-adaptive
water resources
India
ISSN:1606-9749, 1607-0798
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Shrnutí:This paper introduces an effective and reliable approach based on a multi-population approach, namely the self-adaptive multi-population Jaya algorithm (SAMP-JA), to extract multi-purpose reservoir operation policies. The current research focused on two goals: minimizing irrigation deficits and maximizing hydropower generation. Three different models were formulated. The results were compared with those for an ordinary Jaya algorithm (JA), particle swarm optimization (PSO), and an invasive weed optimization (IWO) algorithm. In Model-1, the minimum irrigation deficit obtained by SAMP-JA and JA was 305092.99 . SAMP-JA was better than JA, PSO and IWO in terms of convergence. In Model-2, the maximum hydropower generation achieved by SAMP-JA, JA and PSO was 1723.50 . When comparing the average hydropower generation, SAMP-JA and PSO performed better than JA and IWO. In terms of convergence, SAMP-JA was better than PSO. In Model-3, a self-adaptive multi-population multi-objective Jaya algorithm (SAMP-MOJA) was better than multi-objective particle swarm optimization (MOPSO) and multi-objective Jaya algorithm (MOJA) in terms of maximum hydropower generation, and MOPSO was better than SAMP-MOJA and MOJA in terms of minimum irrigation deficiency. While comparing convergence, SAMP-MOJA was found to be better than MOPSO and MOJA. Overall, SAMP-JA was found to outperform JA, POS and IWO.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:1606-9749
1607-0798
DOI:10.2166/ws.2021.374