Optimal operation of hydropower reservoirs under climate change
The current research aims to optimize the water release to generate optimal hydropower generation for the future up to the year 2039. The study�s novelty is the adaptive and nonadaptive rule curves for power production using optimization algorithms under the climate change model. In addition, the st...
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Springer Science and Business Media B.V.
2023
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| author | Ehteram M. Ahmed A.N. Chow M.F. Latif S.D. Chau K.-W. Chong K.L. El-Shafie A. |
| author2 | 57113510800 |
| author_facet | 57113510800 Ehteram M. Ahmed A.N. Chow M.F. Latif S.D. Chau K.-W. Chong K.L. El-Shafie A. |
| author_sort | Ehteram M. |
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| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | The current research aims to optimize the water release to generate optimal hydropower generation for the future up to the year 2039. The study�s novelty is the adaptive and nonadaptive rule curves for power production using optimization algorithms under the climate change model. In addition, the study used the RCP 8.5 scenario based on seven climate change models. A weighting method was used to select the best climate change models. The method can allocate more weights to more accurate models. The results revealed that the temperature increased by about 26% in the future, while precipitation would decreased by around 3%. The bat algorithm was also used, given it is a powerful method in solving optimization problems in water resources management. The results indicated that less power could be generated during the future period in comparison with the base period as there will be less inflow to the reservoir and released water for hydropower generation. However, by applying adaptive rule curves, the hydropower generation may be improved even under the climate change conditions. For example, the volumetric reliability index obtained when using adaptive rule curves (92%) was higher than when nonadaptive rule curves (90%) were applied. Also, the adoption of adaptive rule curves decreased the vulnerability index for the future period. Therefore, the bat algorithm with adaptive rule curves has a high potential for optimizing reservoir operations under the climate change conditions. � 2022, The Author(s), under exclusive licence to Springer Nature B.V. |
| format | Article |
| id | my.uniten.dspace-27154 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Springer Science and Business Media B.V. |
| record_format | dspace |
| spelling | my.uniten.dspace-271542023-05-29T17:40:16Z Optimal operation of hydropower reservoirs under climate change Ehteram M. Ahmed A.N. Chow M.F. Latif S.D. Chau K.-W. Chong K.L. El-Shafie A. 57113510800 57214837520 57214146115 57216081524 7202674661 57208482172 16068189400 The current research aims to optimize the water release to generate optimal hydropower generation for the future up to the year 2039. The study�s novelty is the adaptive and nonadaptive rule curves for power production using optimization algorithms under the climate change model. In addition, the study used the RCP 8.5 scenario based on seven climate change models. A weighting method was used to select the best climate change models. The method can allocate more weights to more accurate models. The results revealed that the temperature increased by about 26% in the future, while precipitation would decreased by around 3%. The bat algorithm was also used, given it is a powerful method in solving optimization problems in water resources management. The results indicated that less power could be generated during the future period in comparison with the base period as there will be less inflow to the reservoir and released water for hydropower generation. However, by applying adaptive rule curves, the hydropower generation may be improved even under the climate change conditions. For example, the volumetric reliability index obtained when using adaptive rule curves (92%) was higher than when nonadaptive rule curves (90%) were applied. Also, the adoption of adaptive rule curves decreased the vulnerability index for the future period. Therefore, the bat algorithm with adaptive rule curves has a high potential for optimizing reservoir operations under the climate change conditions. � 2022, The Author(s), under exclusive licence to Springer Nature B.V. Article in Press 2023-05-29T09:40:16Z 2023-05-29T09:40:16Z 2022 Article 10.1007/s10668-022-02497-y 2-s2.0-85134348570 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134348570&doi=10.1007%2fs10668-022-02497-y&partnerID=40&md5=9a3005aa421cf8a25f7ef85e2b9f7bef https://irepository.uniten.edu.my/handle/123456789/27154 Springer Science and Business Media B.V. Scopus |
| spellingShingle | Ehteram M. Ahmed A.N. Chow M.F. Latif S.D. Chau K.-W. Chong K.L. El-Shafie A. Optimal operation of hydropower reservoirs under climate change |
| title | Optimal operation of hydropower reservoirs under climate change |
| title_full | Optimal operation of hydropower reservoirs under climate change |
| title_fullStr | Optimal operation of hydropower reservoirs under climate change |
| title_full_unstemmed | Optimal operation of hydropower reservoirs under climate change |
| title_short | Optimal operation of hydropower reservoirs under climate change |
| title_sort | optimal operation of hydropower reservoirs under climate change |
| url_provider | http://dspace.uniten.edu.my/ |