water quality analysis;
run-of-river hydropower plant;
change in temperature;
dissolved oxygen;
machine learning regression models;
D O I:
暂无
中图分类号:
T [工业技术];
学科分类号:
08 ;
摘要:
Hydroelectric power is a significant source of renewable energy generated by run-of-river hydropower plants. However, operation and maintenance of these plants pose a threat to the water quality of rivers. Diversion scheme adopted in these plants can substantially modify river ecosystems instream resulting to changes in the water quality parameters. These changes degrade the river ecosystem, thereby, compromising the health and growth of aquatic species. This study aimed to analyze water quality parameters used to evaluate the compliance to water quality standards. Based on DENR allowable values, change in temperature should not exceed 3 degrees C and dissolved oxygen should not be lower than 5 mg/l. Regression analysis was used to establish relationships in analyzing water quality parameters. With the use of various regression machine learning models, the water quality dataset was modelled to predict the change in temperature and dissolved oxygen downstream using water level downstream and water temperature downstream as predictors. Based on the Stochastic Gradient Boosting Model, while the water level downstream decreases and the water temperature downstream increases, the change in temperature increases. Based on the Linear Model or the Ridge Model, while the water level downstream decreases and the water temperature downstream increases, the dissolved oxygen downstream relatively decreases.
机构:
Cent Res Inst Elect Power Ind, Sustainable Syst Res Lab, Abiko 1646, Abiko, Chiba 2701194, Japan
Tohoku Univ, Grad Sch Engn, Aoba 6-6-06, Sendai 9808579, JapanCent Res Inst Elect Power Ind, Sustainable Syst Res Lab, Abiko 1646, Abiko, Chiba 2701194, Japan
Arai, Ryosuke
Toyoda, Yasushi
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机构:
Cent Res Inst Elect Power Ind, Sustainable Syst Res Lab, Abiko 1646, Abiko, Chiba 2701194, JapanCent Res Inst Elect Power Ind, Sustainable Syst Res Lab, Abiko 1646, Abiko, Chiba 2701194, Japan
Toyoda, Yasushi
Kazama, So
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h-index: 0
机构:
Tohoku Univ, Grad Sch Engn, Aoba 6-6-06, Sendai 9808579, JapanCent Res Inst Elect Power Ind, Sustainable Syst Res Lab, Abiko 1646, Abiko, Chiba 2701194, Japan