e-ISSN 2231-8542
ISSN 1511-3701

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Optimisation of Multireservoir Operation Policy using Teaching-Learning Based Optimisation Algorithm

Jayantilal N. Patel and Pranita N. Balve

Pertanika Journal of Tropical Agricultural Science, Volume 26, Issue 3, July 2018

Keywords: Multireservoir operation, optimisation, TLBO algorithm

Published on: 31 Jul 2018

The multi reservoir water resource system has various purposes and therefore, operation planning is becoming complex and involves a number of decision variables. This paper presents an efficient and reliable teaching-learning based approach, namely teaching-learning based optimisation (TLBO) algorithm for optimisation of multireservoir operation policy. It is based on the teaching-learning process of the education system. TLBO algorithm does not require any algorithm-specific parameters for obtaining optimal results; instead it requires only the population size and number of iterations. The time required for obtaining the specific optimised algorithm parameter is reduced and results are also near the global-optimal solution. Furthermore, the number of function evaluations required is less. This TLBO algorithm is implemented at the five-reservoir model of the upper Godavari river project in the city of Nashik in Maharashtra, India. The efficiency of the results of the TLBO algorithm is compared with the genetic algorithm (GA). The results show that TLBO algorithm is considered to be a viable alternative to the operating policy of multireservoir system and it avoids the local optimal solution.

ISSN 1511-3701

e-ISSN 2231-8542

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