期刊
ENERGIES
卷 14, 期 12, 页码 -出版社
MDPI
DOI: 10.3390/en14123643
关键词
artificial neural network; climate change; hydropower potential; small hydropower
资金
- National Research Foundation of Korea (NRF) - Korean government (MSIT) [2017R1A2B3005695]
- National Research Foundation of Korea [2017R1A2B3005695] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This study predicted the future potential of SHP using a climate change scenario and an artificial neural network model, showing a generally lower SHP potential compared to the past. This can serve as a basis for planning future energy supplies and reducing carbon emissions.
As the effects of climate change are becoming severe, countries need to substantially reduce carbon emissions. Small hydropower (SHP) can be a useful renewable energy source with a high energy density for the reduction of carbon emission. Therefore, it is necessary to revitalize the development of SHP to expand the use of renewable energy. To efficiently plan and utilize this energy source, there is a need to assess the future SHP potential based on an accurate runoff prediction. In this study, the future SHP potential was predicted using a climate change scenario and an artificial neural network model. The runoff was simulated accurately, and the applicability of an artificial neural network to the runoff prediction was confirmed. The results showed that the total amount of SHP potential in the future will generally a decrease compared to the past. This result is applicable as base data for planning future energy supplies and carbon emission reductions.
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