Forecast of the hydropower generation under influence of climate change based on RCPs and Developed Crow Search Optimization Algorithm
The world’s climate has changed dramatically in recent years due to the development of the industry. Climate change can significantly affect hydropower plants. One of the negative effects of climate change is the reduction of hydropower generation. Therefore, to better management of power supply and...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-11-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S235248472100007X |
| _version_ | 1819099892803436544 |
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| author | Qizi Huangpeng Wenwei Huang Fatemeh Gholinia |
| author_facet | Qizi Huangpeng Wenwei Huang Fatemeh Gholinia |
| author_sort | Qizi Huangpeng |
| collection | DOAJ |
| description | The world’s climate has changed dramatically in recent years due to the development of the industry. Climate change can significantly affect hydropower plants. One of the negative effects of climate change is the reduction of hydropower generation. Therefore, to better management of power supply and demand, the climate change effect on hydropower plants should be examined. The main purpose of this study is the prediction of future hydropower generation (2021–2050) in terms of climate change. One of the factors sensitive to climate change in hydropower plants is the amount of input flow to the reservoir. In this study, a method has been used that can increase the accuracy of flow estimation. This innovation is the use of the ANN model under the new version of the Developed Crow Search Algorithm (DCSA). This algorithm increases the accuracy of prediction by solving optimization disadvantages such as getting stuck in the optimal location, the imbalance between exploitation and exploration at different levels The results showed that the DCSA algorithm with minimum error (MSE = 1.06) and maximum correlation (R2 = 0.88) compared to other algorithms has the best performance. The results of the prediction of climate change under RCPs scenarios showed that the average annual power generation will decrease under RCP2.6 and RCP4.5 and RCP8.5 about 10.74% and% 16.38 and 22.25% respectively. Also, the average annual power generation under scenarios RCP2.6, RCP4.5, and RCP8.5 by 2050 are 740.33 MW, 603.12 MW, and 585.77 MW, respectively. |
| first_indexed | 2024-12-22T00:54:06Z |
| format | Article |
| id | doaj.art-34adee51b6944f85ad6ca9f45594db9d |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-12-22T00:54:06Z |
| publishDate | 2021-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-34adee51b6944f85ad6ca9f45594db9d2022-12-21T18:44:22ZengElsevierEnergy Reports2352-48472021-11-017385397Forecast of the hydropower generation under influence of climate change based on RCPs and Developed Crow Search Optimization AlgorithmQizi Huangpeng0Wenwei Huang1Fatemeh Gholinia2College of Art and Science, University of Defense Technology, Changsha Hunan, 410072, China; Corresponding author.College of Military Basic Education, University of Defense Technology, Changsha Hunan, 410072, ChinaFaculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, IranThe world’s climate has changed dramatically in recent years due to the development of the industry. Climate change can significantly affect hydropower plants. One of the negative effects of climate change is the reduction of hydropower generation. Therefore, to better management of power supply and demand, the climate change effect on hydropower plants should be examined. The main purpose of this study is the prediction of future hydropower generation (2021–2050) in terms of climate change. One of the factors sensitive to climate change in hydropower plants is the amount of input flow to the reservoir. In this study, a method has been used that can increase the accuracy of flow estimation. This innovation is the use of the ANN model under the new version of the Developed Crow Search Algorithm (DCSA). This algorithm increases the accuracy of prediction by solving optimization disadvantages such as getting stuck in the optimal location, the imbalance between exploitation and exploration at different levels The results showed that the DCSA algorithm with minimum error (MSE = 1.06) and maximum correlation (R2 = 0.88) compared to other algorithms has the best performance. The results of the prediction of climate change under RCPs scenarios showed that the average annual power generation will decrease under RCP2.6 and RCP4.5 and RCP8.5 about 10.74% and% 16.38 and 22.25% respectively. Also, the average annual power generation under scenarios RCP2.6, RCP4.5, and RCP8.5 by 2050 are 740.33 MW, 603.12 MW, and 585.77 MW, respectively.http://www.sciencedirect.com/science/article/pii/S235248472100007XClimate changeEnergyForecastingOptimization algorithmHydropower |
| spellingShingle | Qizi Huangpeng Wenwei Huang Fatemeh Gholinia Forecast of the hydropower generation under influence of climate change based on RCPs and Developed Crow Search Optimization Algorithm Energy Reports Climate change Energy Forecasting Optimization algorithm Hydropower |
| title | Forecast of the hydropower generation under influence of climate change based on RCPs and Developed Crow Search Optimization Algorithm |
| title_full | Forecast of the hydropower generation under influence of climate change based on RCPs and Developed Crow Search Optimization Algorithm |
| title_fullStr | Forecast of the hydropower generation under influence of climate change based on RCPs and Developed Crow Search Optimization Algorithm |
| title_full_unstemmed | Forecast of the hydropower generation under influence of climate change based on RCPs and Developed Crow Search Optimization Algorithm |
| title_short | Forecast of the hydropower generation under influence of climate change based on RCPs and Developed Crow Search Optimization Algorithm |
| title_sort | forecast of the hydropower generation under influence of climate change based on rcps and developed crow search optimization algorithm |
| topic | Climate change Energy Forecasting Optimization algorithm Hydropower |
| url | http://www.sciencedirect.com/science/article/pii/S235248472100007X |
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