Optimization of of Energy Generation from Hydropower Dams using New Intelligent Methods

Document Type : Original Article

Authors

1 Assistant Professor, Department of Water Engineering, Faculty of Civil and Surveying Engineering, Graduate University of Advanced Technology, P.O. Box 76315116, Kerman, Iran.

2 Associate Professor, Department of Water Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.

3 Associate professor, Department of Water Engineering, University of Jiroft, Jiroft, Iran.

10.22125/iwe.2024.406481.1734

Abstract

Given the fact that hydropower energy is the third largest source of electricity generation and also the most important renewable energy producer in the world, the optimal use of the huge and expensive source of water is essential. In this research, the new optimization algorithms of dFDB-MRFO, ARO, EO, HMO, MRA,and WHO, compared to the well-known GA, have been used for optimization of the hydropower energy generation of the Jiroft Dam located in the Halilrood basin (south of Iran) for the long-term period of 19 years. For this purpose, a model was developed for the optimal hydropower energy operation of Jiroft Dam. The objective function in the mentioned model was defined as minimizing the ratio of produced energy to the installed power plant capacity. The results showed that the operation scenarios resulting from the dFDB-MRFO,ARO,EO,HMO,MRA,WHO and GA algorithms were capable to generate hydropower energy of 1482.43,1476.49,1468.30,1474.64,1430.44,1480.91 and 1403.65 GWh during the statistical period, respectively. Also, the best objective function values for the dFDB-MRFO, ARO, EO, HMO, MRA, WHO and GA algorithms were obtained as 8.10, 8.92, 10.04, 9.18, 15.66, 8.31 and 19.26, respectively. The obtained results indicate the high performance of the new dFDB-MRFO and WHO algorithms in comparison with the other studied algorithms in the optimal operation of hydropower dams. The operation scenarios resulting from the new dFDB-MRFO and WHO algorithms were able to produce energy at the rate of 96.41 and 96.31% of the total capacity of the Jiroft Dam power plant during the study period.

Keywords

Main Subjects