Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations
Climate change; Climate models; Digital storage; Neural networks; Reservoirs (water); Water resources; Coupled Model Intercomparison Project; Coupled model intercomparison project 5; Down-scaling; General circulation model; Klang gate dam; Metaheuristic; Optimisations; Reservoir operation; Simulatio...
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Elsevier B.V.
2023
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| _version_ | 1833350869519695872 |
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| author | Lai V. Huang Y.F. Koo C.H. Najah Ahmed A. El-Shafie A. |
| author2 | 57204919704 |
| author_facet | 57204919704 Lai V. Huang Y.F. Koo C.H. Najah Ahmed A. El-Shafie A. |
| author_sort | Lai V. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Climate change; Climate models; Digital storage; Neural networks; Reservoirs (water); Water resources; Coupled Model Intercomparison Project; Coupled model intercomparison project 5; Down-scaling; General circulation model; Klang gate dam; Metaheuristic; Optimisations; Reservoir operation; Simulation; Support vector regressions; Optimization; climate change; climate effect |
| format | Article |
| id | my.uniten.dspace-26694 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Elsevier B.V. |
| record_format | dspace |
| spelling | my.uniten.dspace-266942023-05-29T17:36:13Z Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations Lai V. Huang Y.F. Koo C.H. Najah Ahmed A. El-Shafie A. 57204919704 55807263900 57204843657 57214837520 16068189400 Climate change; Climate models; Digital storage; Neural networks; Reservoirs (water); Water resources; Coupled Model Intercomparison Project; Coupled model intercomparison project 5; Down-scaling; General circulation model; Klang gate dam; Metaheuristic; Optimisations; Reservoir operation; Simulation; Support vector regressions; Optimization; climate change; climate effect This study covers the application of sim-heuristics to simulate and optimise the KLang Gate Dam (KGD) operating rule curve using the Coupled Model Intercomparison Project 5 (CMIP5) climate scenarios. This research aims to examine future climate change impacts on the KGD reservoir water resources. First, based on model institution location and data availability, a few General Circulation Models (GCMs) under the CMIP5 were chosen. Most earlier studies had solely examined the impact of climate change on future reservoir operations using a single GCM. The ensemble of GCMs for precipitation, temperature (Maximum, Minimum, and Mean), and solar radiation for the base period (1991�2005) and future climatic scenarios under the Representative Concentration Pathways, RCP 2.6, RCP 4.5, and RCP 8.5 were downscaled, trained, and tested using data-driven techniques namely; the Artificial Neural Network (ANN) and the Support Vector Regression (SVR). During the base period, the SVR (Poly function) achieved R performance values of 0.6201, 0.5743, 0.6926, and 0.6073 for the respective predictant variables. Upon addressing for rainfall-runoff, the Turc-radiation evaporation strategy was utilised at this study location since it was suitable for the tropical, humid, or sub-humid region. Few scenarios were developed to forecast water demand. Scenario 1 was based on the base period (1991�2005) of water demand, whereas Scenarios 2 and 3 were based on maximum and mean temperatures, respectively (2020�2099). The results were then evaluated in terms of storage failure, reliability, resilience, and vulnerability. Overall, Scenario 3 showed the greatest reliability in satisfying exact demand with 93.54 %, as well as the least shortage index and length of water deficit under RCP 4.5. � 2022 Elsevier B.V. Final 2023-05-29T09:36:13Z 2023-05-29T09:36:13Z 2022 Article 10.1016/j.jhydrol.2022.128530 2-s2.0-85139876528 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139876528&doi=10.1016%2fj.jhydrol.2022.128530&partnerID=40&md5=887db40112f07b36bdc2190911bc7bb3 https://irepository.uniten.edu.my/handle/123456789/26694 614 128530 Elsevier B.V. Scopus |
| spellingShingle | Lai V. Huang Y.F. Koo C.H. Najah Ahmed A. El-Shafie A. Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations |
| title | Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations |
| title_full | Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations |
| title_fullStr | Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations |
| title_full_unstemmed | Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations |
| title_short | Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations |
| title_sort | conceptual sim-heuristic optimization algorithm to evaluate the climate impact on reservoir operations |
| url_provider | http://dspace.uniten.edu.my/ |