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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 張斐章(Fi-John Chang) | |
dc.contributor.author | Wei-De Lee | en |
dc.contributor.author | 李韋德 | zh_TW |
dc.date.accessioned | 2021-06-15T12:31:41Z | - |
dc.date.available | 2020-08-24 | |
dc.date.copyright | 2020-08-24 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-08-17 | |
dc.identifier.citation | 1. Guan, X., Mascaro, G., Sampson, D. Maciejewski, R. A metropolitan scale water management analysis of the food-energy-water nexus. Sci. Total Environ. 701, 134478 (2020). 2. Sarkodie, S. A. Owusu, P. A. Bibliometric analysis of water–energy–food nexus: Sustainability assessment of renewable energy. Curr. Opin. Environ. Sci. Heal. 13, 29–34 (2020). 3. Li, M., Fu, Q., Singh, V. P., Liu, D. Li, T. Stochastic multi-objective modeling for optimization of water-food-energy nexus of irrigated agriculture. Adv. Water Resour. 127, 209–224 (2019). 4. Li, P. C. Ma, H. wen. Evaluating the environmental impacts of the water-energy-food nexus with a life-cycle approach. Resour. Conserv. Recycl. 157, 104789 (2020). 5. Yu, L., Xiao, Y., Zeng, X. T., Li, Y. P. Fan, Y. R. Planning water-energy-food nexus system management under multi-level and uncertainty. J. Clean. Prod. 251, (2020). 6. Shi, H. et al. Coupling the water-energy-food-ecology nexus into a Bayesian network for water resources analysis and management in the Syr Darya River basin. J. Hydrol. 581, 124387 (2020). 7. Chang, F. J., Wang, Y. C. Tsai, W. P. Modelling Intelligent Water Resources Allocation for Multi-users. Water Resour. Manag. 30, 1395–1413 (2016). 8. Uen, T. S., Chang, F. J., Zhou, Y. Tsai, W. P. Exploring synergistic benefits of Water-Food-Energy Nexus through multi-objective reservoir optimization schemes. Sci. Total Environ. 633, 341–351 (2018). 9. Zhou, Y., Guo, S., Chang, F. J. Xu, C. Y. Boosting hydropower output of mega cascade reservoirs using an evolutionary algorithm with successive approximation. Appl. Energy 228, 1726–1739 (2018). 10. Zhou, Y., Guo, S., Hong, X. Chang, F. J. Systematic impact assessment on inter-basin water transfer projects of the Hanjiang River Basin in China. J. Hydrol. 553, 584–595 (2017). 11. Bai, T., Wei, J., Chang, F. J., Yang, W. Huang, Q. Optimize multi-objective transformation rules of water-sediment regulation for cascade reservoirs in the Upper Yellow River of China. J. Hydrol. 577, 123987 (2019). 12. Tsai, W. P., Chang, F. J., Chang, L. C. Herricks, E. E. AI techniques for optimizing multi-objective reservoir operation upon human and riverine ecosystem demands. J. Hydrol. 530, 634–644 (2015). 13. Tsai, W. P., Cheng, C. L., Uen, T. S., Zhou, Y. Chang, F. J. Drought mitigation under urbanization through an intelligent water allocation system. Agric. Water Manag. 213, 87–96 (2019). 14. Zhou, Y. et al. Prospect for small-hydropower installation settled upon optimal water allocation: An action to stimulate synergies of water-food-energy nexus. Appl. Energy 238, 668–682 (2019). 15. Campana, P. E. et al. Managing agricultural drought in Sweden using a novel spatially-explicit model from the perspective of water-food-energy nexus. J. Clean. Prod. 197, 1382–1393 (2018). 16. Luna, T., Ribau, J., Figueiredo, D. Alves, R. Improving energy efficiency in water supply systems with pump scheduling optimization. J. Clean. Prod. 213, 342–356 (2019). 17. Liu, L. et al. Power Generation Efficiency and Prospects of Floating Photovoltaic Systems. Energy Procedia 105, 1136–1142 (2017). 18. Mittal, D., Saxena, B. K. Rao, K. V. S. Floating solar photovoltaic systems: An overview and their feasibility at Kota in Rajasthan. Proc. IEEE Int. Conf. Circuit, Power Comput. Technol. ICCPCT 2017 (2017) doi:10.1109/ICCPCT.2017.8074182. 19. Ferrer-Gisbert, C. et al. A new photovoltaic floating cover system for water reservoirs. Renew. Energy 60, 63–70 (2013). 20. Pimentel Da Silva, G. D. Branco, D. A. C. Is floating photovoltaic better than conventional photovoltaic? Assessing environmental impacts. Impact Assess. Proj. Apprais. 36, 390–400 (2018). 21. Ranjbaran, P., Yousefi, H., Gharehpetian, G. B. Astaraei, F. R. A review on floating photovoltaic (FPV)power generation units. Renew. Sustain. Energy Rev. 110, 332–347 (2019). 22. Château, P. A. et al. Mathematical modeling suggests high potential for the deployment of floating photovoltaic on fish ponds. Sci. Total Environ. 687, 654–666 (2019). 23. Choi, Y. A Study on Power Generation Analysis of Floating PV System Considering Environmental Impact. 8, 75–84 (2014). 24. Spencer, R. S., Macknick, J., Aznar, A., Warren, A. Reese, M. O. Floating Photovoltaic Systems: Assessing the Technical Potential of Photovoltaic Systems on Man-Made Water Bodies in the Continental United States. Environ. Sci. Technol. 53, 1680–1689 (2019). 25. Silvério, N. M. et al. Use of floating PV plants for coordinated operation with hydropower plants: Case study of the hydroelectric plants of the São Francisco River basin. Energy Convers. Manag. 171, 339–349 (2018). 26. Holland, J. H. ADAPTATION IN NATURAL An Introductory Analysis with Applications to Biology ,. 183 pages (1975). 27. Deb, K., Pratap, A., Agarwal, S. Meyarivan, T. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6, 182–197 (2002). 28. 張建勛、甘俊二, 作物灌溉需水量之研究。 29. 陳清田、甘俊二, 台灣地域性作物需水量之推估研究。 30. 經濟部水利署,2014,石門水庫供水區水資源活化計畫。 31. 經濟部水利署,2012,再現千塘之鄉-桃園台地坡圳保存計畫。 32. 王昱中,2014,智慧型水資源調配策略以因應用水需求增長,國立台灣大學生物環境系統工程學研究所學位論文,1-92。 33. 楊舜年,2015,建立颱洪時期抽水站智慧型最佳化操作規則,國立台灣大學生物環境系統工程學研究所學位論文,1-126。 34. 鄭仲廉,2016,因應都市化影響之智慧型水資源管理系統,國立台灣大學生物環境系統工程學研究所學位論文,1-89。 35. 陳正炎、姚嘉耀、謝馥揚、廖苑雅,2006,運用遺傳演算法推求水庫操作規線之研究,中華水土保持學報, 第37期之2,173-184。 36. 溫庭玄,2017,運用多目標水庫最佳化操作提升水、糧食、能源之協同效益,國立台灣大學生物環境系統工程學研究所學位論文,1-150。 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/50176 | - |
dc.description.abstract | 全球正處於能源轉型的關鍵時代,綠色能源將是未來驅動經濟發展的新引擎,而可再生能源成為新興綠色能源產業,促進台灣能源自給自足的核心能源。近年來,水、糧食、能源鏈結(WFE Nexus)之議題備受重視,因此,本研究基於提升水、糧食、能源(水力+小水力+太陽能)之協同效益,擬建立一個多目標優化模型,尋找出WFE Nexus最佳解決方案。本研究選擇石門水庫及桃園地區埤塘進行聯合供水及發電操作,實現最佳化水庫及埤塘聯合供水以滿足不同部門的基本需求,並活用水庫水量提升水力發電量、研擬在渠道上建設小水力發電機及在灌溉埤塘水面上方架設之太陽能板進行發電,增加綠色能源產量。本研究在水庫M-5規則下使用NSGA-II方法進行最佳化,並模擬覆蓋太陽能板比率、溫室用地比率、豐水年、平水年、枯水年、水庫初始庫容等情境,研究成果除了與真實水庫操作比較之外,也根據上述情境展現不同的結果,並探討其合理性。主要結果顯示 : (1) 埤塘架設太陽能板,不僅降低池水溫度變化,每年減少約47.3萬噸的蒸發量,與農業需水量相比,多了約4%的可用水量,也提供魚類穩定生長的水質條件,並增加740GWh太陽能發電,充分展現光電埤塘的潛力;(2) 石門水庫與光電池塘的最佳聯合操作不僅可以促進水庫水力發電和渠道小水力發電,同時提高供水量、增加糧食和綠色能源的生產,促進水-食物-能源鍵結的協同效益值;(3) 初期可用水量的減少,會大大影響之後水庫的操作調度;(4) 溫室的建置,對於水、糧食、能源協同效益,最大提升幅度可達7%,具有高度的發展性;(5) 此研究能提供城市永續發展趨勢相關的長、短期政策,以有效管理WFE Nexus應對都市化的趨勢,從而維持綠色增長。 | zh_TW |
dc.description.abstract | The world is in a crucial era of energy transition, and green energy will serve as a new engine that drives sustainable development in the future. Renewable energy becomes the core energy to cultivate green energy industries and promote energy self-sufficiency in Taiwan. In recent years, water, food and energy nexus (WFE Nexus) has gained global attention. Therefore, a multi-objective optimization framework is proposed in this study to explore the optimal solution to the WFE Nexus for improving the synergistic benefits of water, food, and energy (hydropower, small hydropower and solar power). The joint multi-objective operation of the Shihmen Reservoir and irrigation ponds in the northern Taiwan constitutes the case study. This study aims at achieving the optimal water supply from reservoirs and ponds to fulfill basic demands from different sectors as well as increasing green energy output by using the reservoir water to lift up hydropower output, installing small hydropower in river channels, and setting up solar panels over irrigation ponds. This study applyed NSGA-II optimization method to search for the total amount of hydropower generation and the modified shortage index under the M-5 rule, and simulated the ratio of covered solar panels, the ratio of greenhouse land, wet year, general year, dry year, the initial storage capacity of the reservoir, etc. In addition, the results compared with real reservoir operations, it also presented different results according to different scenarios and discussed its rationality. The main results shows : (1) The high potential of photoelectric ponds because the installation of solar panels over irrigation ponds can 1) reduces water temperature and the evaporation of about 473,000 tons per year, it has about 4% more available water that compared with agricultural water distribution, and 2) provide water quality conditions suitable for growing fish while increasing 740GWh of solar power. (2) The optimal joint operation of the Shihmen Reservoir and photoelectric ponds not only can promote reservoir hydropower output and the small hydropower output in river channels while increasing green energy production, water supply and food production, but also can enhance the synergistic benefits of the WFE Nexus. (3) The reduction of the initial available water will greatly affect the operation and scheduling of the reservoir afterwards. (4) The construction of greenhouses are highly developmental for WFE Nexus benefits, with a maximum increase of up to 7%. (5) This study can provides long/short term policies for sustainable urban development to effectively manage the WFE Nexus response the trend of urbanization, thus maintaining green growth. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T12:31:41Z (GMT). No. of bitstreams: 1 U0001-1108202015032300.pdf: 4478608 bytes, checksum: fd27f7d7923084ba06b37471d0d054f9 (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 謝誌 i 中文摘要 v ABSTRACT vii 目錄 ix 圖目錄 xiii 表目錄 xv Chapter 1 緒論 1 1.1 研究背景 1 1.2 研究目的 2 1.3 研究架構 4 Chapter 2 文獻回顧 5 2.1 糧食、水、能源相關文獻 5 2.2 水庫操作與遺傳演算法相關研究 6 2.3 太陽能發電相關文獻 7 Chapter 3 理論概述 10 3.1 遺傳演算法(GA) 10 3.2 遺傳演算法演算流程 10 3.3 遺傳演算法基本元素介紹 12 3.3.1 編碼、解碼及產生初始群體 12 3.3.2 迭代次數 13 3.3.3 限制式及目標函數 13 3.3.4 複製、交配及突變 13 3.4 非支配排序遺傳演算法(NSGA-II) 14 3.5 非支配遺傳演算法演算流程 15 3.6 NSGA-II基本元素及運算子介紹 18 Chapter 4 研究案例 20 4.1 研究區域 20 4.2 研究資料蒐集 21 4.3 研究架構及流程 27 4.4 石門水庫供水操作(M-5運用規線) 29 4.4.1 石門水庫運用規線介紹 29 4.4.2 石門水庫運用規線操作步驟 31 4.5 NSGA-II優化操作分析 33 4.5.1 NSGA-II模式基本設定 34 4.5.2 埤塘與溫室設定 38 Chapter 5 結果與討論 44 5.1 模式操作情境 44 5.2 真實初始庫容比較結果 47 5.3 初始庫容情境模擬結果 51 5.3.1 水庫初始庫容100% 51 5.3.2 水庫初始庫容50% 52 5.4 溫室建置面積情境模擬結果 54 5.4.1 枯水年 54 5.4.2 豐水年 60 5.4.3 平水年 67 5.5 覆蓋太陽能板效益 75 5.6 WEF Nexus效益分析 77 5.6.1 枯水年 84 5.6.2 豐水年 87 5.6.3 平水年 90 Chapter 6 結論與建議 94 6.1 結論 94 6.2 建議 96 Reference 97 附錄一 總產量結果_能源(水力發電+太陽能發電) 102 附錄二 水庫操作結果(2014~2016年) 103 附錄三 水庫操作結果(2017年) 109 | |
dc.language.iso | zh-TW | |
dc.title | 審視水-糧食-能源鏈結關係下之水庫與光電埤塘智慧管理 | zh_TW |
dc.title | Intelligent management of reservoir and photoelectric ponds under water-food-energy nexus perspective | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-2 | |
dc.description.degree | 碩士 | |
dc.contributor.advisor-orcid | 張斐章(0000-0002-1655-8573) | |
dc.contributor.oralexamcommittee | 張麗秋(Li-Chiu Chang),黃文政(Wen-Cheng Huang),陳永祥(Yung-hsiang Chen) | |
dc.subject.keyword | 多目標水庫操作,非支配遺傳演算法,最佳化,綠色能源,水、糧食、能源鏈結,溫室, | zh_TW |
dc.subject.keyword | Multi-objective reservoir operation,Non-Dominated Sorting Genetic Algorithm (NSGA-II),Optimization,Green energy,Water, food and energy nexus (WFE Nexus),Greenhouse, | en |
dc.relation.page | 112 | |
dc.identifier.doi | 10.6342/NTU202002956 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2020-08-18 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
顯示於系所單位: | 生物環境系統工程學系 |
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