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  1. NTU Theses and Dissertations Repository
  2. 生物資源暨農學院
  3. 生物機電工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68720
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor江昭皚(Joe-Air Jaing)
dc.contributor.authorHsuan-Hsiang Hsuen
dc.contributor.author徐暄翔zh_TW
dc.date.accessioned2021-06-17T02:32:08Z-
dc.date.available2022-08-24
dc.date.copyright2017-08-24
dc.date.issued2017
dc.date.submitted2017-08-17
dc.identifier.citationAhmad, J. 2010. A fractional open circuit voltage based maximum power point tracker for photovoltaic arrays. 2nd International Conference on Software Technology and Engineering (ICSTE), Vol. 1.
Ali, A. N. A., M. H. Saied, M. Z. Mostafa, and T. M. Abdel-Moneim. 2012. A survey of maximum PPT techniques of PV systems. Proceedings of the IEEE Energytech: 1-17.
Azab, M. 2008. A new maximum power point tracking for photovoltaic systems. WASET. ORG 34: 571-574.
Chine, W., A. Mellit, V. Lughi, A. Malek, G. Sulligoi, and A. M. Pavan. 2016. A novel fault diagnosis technique for photovoltaic systems based on artificial neural networks. Renewable Energy 90, 501-512.
Chouder, A., and S. Silvestre. 2010. Automatic supervision and fault detection of PV systems based on power losses analysis. Energy Conversion and Management 51(10): 1929-1937.
Eke, R., and A. Senturk. 2012. Performance comparison of a double-axis sun tracking versus fixed PV system. Solar Energy 86(9): 2665-2672.
Gokmen, N., E. Karatepe, S. Silvestre, B. Celik, and P. Ortega. 2013. An efficient fault diagnosis method for PV systems based on operating voltage-window. Energy conversion and management 73: 350-360.
Gow, J. A., and C. D. Manning. 2000. Controller arrangement for boost converter systems sourced from solar photovoltaic arrays or other maximum power sources. IEE Proceedings-Electric Power Applications 147(1): 15-20.
Green, M. A., K. Emery, Y. Hishikawa, W. Warta, and E. D. Dunlop. 2015. Solar cell efficiency tables (Version 45). Progress in photovoltaics: research and applications 23(1): 1-9.
Heslop, S., and I. MacGill. 2014. Comparative analysis of the variability of fixed and tracking photovoltaic systems. Solar Energy 107: 351-364.
Hoffmann, W. 2006. PV solar electricity industry: Market growth and perspective. Solar energy materials and solar cells 90(18): 3285-3311.
Hussein, K. H., I. Muta, T. Hoshino, and M. Osakada. 1995. Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions. IEE Proceedings-Generation, Transmission and Distribution 142(1): 59-64.
Kim, D. J., D. H. Kim, S. Bhattarai, and J. H. Oh. 2011. Simulation and Model Validation of the Surface Cooling System for Improving the Power of a Photovoltaic Module. Journal of Solar Energy Engineering 133(4): 041-012.
Kottas, T. L., Y. S. Boutalis, and A. D. Karlis. 2006. New maximum power point tracker for PV arrays using fuzzy controller in close cooperation with fuzzy cognitive networks. IEEE Transactions on Energy Conversion 21(3), 793-803.
Moharram, K. A., M. S. Abd-Elhady, H. A. Kandil, and H. El-Sherif. 2013. Enhancing the performance of photovoltaic panels by water cooling. Ain Shams Engineering Journal 4(4): 869-877.
Reis, A.M., N.T. Coleman, M. W. Marshall, P. A. Lehman, and C. E. Chamberlin. 2002. Comparison of PV module performance before and after 11-years of field exposure. In: Proceedings of the 29th IEEE Photovoltaics Specialists Conference, New Orleans, Louisiana.
Sánchez‐Friera, P., M. Piliougine, J. Pelaez, J. Carretero, and M. Sidrach de Cardona. 2011. Analysis of degradation mechanisms of crystalline silicon PV modules after 12 years of operation in Southern Europe. Progress in photovoltaics: Research and Applications 19(6): 658-666.
Sullivan, C. R., and M. J. Powers. 1993. A high-efficiency maximum power point tracker for photovoltaic arrays in a solar-powered race vehicle. In 'Proc. 24th Annual Power Electronics Specialists Conference', 574-580.
Wang, F., H. Wang, H. Yang, J. Chang, P. Zhao, A. Wang, and D. Song. 2016. Effect of potential induced degradation on crystalline silicon solar modules in photovoltaic power plant. Photovoltaic Specialists Conference (PVSC), 2016 IEEE 43rd. Portland, OR, USA: IEEE.
Wang, J. C., Y. L. Su, J. C. Shieh, and J. A. Jiang. 2011. High-accuracy maximum power point estimation for photovoltaic arrays. Solar Energy Materials and Solar Cells. 95(3): 843-851.
Wang, J. C., J. C. Shieh, Y. L. Su, K. C. Kuo, Y. W. Chang, Y. T. Liang, J. J. Chou, K. C. Liao, and J. A. Jiang. 2011. A novel method for the determination of dynamic resistance for photovoltaic modules. Energy 36(10), 5968-5974.
Wang, J. C., Y. L. Su, K. C. Kuo, J. C. Shieh, and J. A. Jiang. 2015. Toward multiple maximum power point estimation of photovoltaic systems based on semiconductor theory. Progress in Photovoltaics: Research and Applications 23(7), 847-861.
Yi, Z., and A. H. Etemadi. 2016. A novel detection algorithm for Line-to-Line faults in Photovoltaic (PV) arrays based on support vector machine (SVM). In Power and Energy Society General Meeting (PESGM), 2016 (pp. 1-4). IEEE.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68720-
dc.description.abstract自21世紀開始,隨著環境保護及永續發展的意識逐漸提升,為減少碳排放量,世界各國都在積極研發對環境衝擊較低的替代能源,其中以再生能源中的太陽能最受重視。太陽能光電系統將太陽照射至地球的光能轉換成電能,擁有穩定且持續的能量來源,無二氧化碳排放且安裝限制因素較少,是個容易推廣至民間的再生能源系統。
太陽能光電系統研究發展至今已超過50年,提高產能方面的研究日趨成熟,除了研發出不同的半導體材料以提高轉換效率外,發電系統中追日機構的設計、逆變器的最大功率點追蹤演算法及太陽能模組的降溫系統都有相當數量的研究論文產出。但欲發展出一個完整且成熟的發電系統,除了產能的提升之外,擁有良好的監測系統並控制其運轉狀況和故障診斷系統也是不可或缺的一環。
在現有的太陽能電廠監測系統中,大多以實際佈線收集基本電力資訊和輻射照度等參數。本研究除了收集上述的基本資訊外,更增加了環境參數感測器,結合多種感測資料來完善對太陽能電廠的監控。本研究所提出的故障診斷機制,便是依靠分析多種感測參數及發電結果,以達成即時並準確地鎖定發生故障的變流器位置及其故障原因。電廠業者能依此機制迅速地通知工程師前來維修,大幅降低維修所需的作業時間及電廠的營業損失。
zh_TW
dc.description.abstractSince the 21st century, with the rising attention on environmental protection and sustainable development, most governments have actively participated in finding alternative energy, which generates fewer environmental impacts and carbon emissions. With the advantages of stable and sustainable energy sources, zero carbon dioxide emissions and low geographical limitation, Photovoltaic (PV) systems have become the most valuable asset in all renewable energy sources.
The studies on photovoltaic systems have been done over 50 years, so the techniques that improve solar energy generation have become mature. Except for studies on different semiconductor materials, sun lotus tracking devices, maximum power point tracking (MPPT) methods used by power inverters, and cooling devices for PV modules are particularly popular research issues. However, to develop a complete and mature solar power generation system, it is necessary not only to focus on power generation method improvement but also to develop a monitoring device which can collect important PV system data while performing fault diagnosis tasks.
Most of the recent PV monitoring systems only collect basic electrical and irradiation parameters. In this research, in addition to the parameters mentioned above, environmental sensors are used to collect environmental parameters. By analyzing electrical, irradiation and environmental parameters, this research proposes a reliable fault diagnosis method for PV systems. This method can accurately target the location of a faulty inverter and the reason causing the fault immediately. By using the proposed method, the industry can rapidly inform engineers to repair their devices so the time required on finding and excluding the fault can be reduced. The economic losses associated with the fault can also be decreased.
en
dc.description.provenanceMade available in DSpace on 2021-06-17T02:32:08Z (GMT). No. of bitstreams: 1
ntu-106-R04631046-1.pdf: 4020635 bytes, checksum: 4138bb547cd6a9a3e7abe075b15dfaf1 (MD5)
Previous issue date: 2017
en
dc.description.tableofcontents誌謝 i
中文摘要 iii
Abstract iv
Table of Contents vi
List of Illustrations ix
List of Tables xii
Chapter 1. Introduction 1
1.1 Background 1
1.2 Motivation and Purpose 4
1.3 Thesis Organization 5
Chapter 2. Literature Review 6
2.1 Photovoltaic System Description 6
2.1.1 Consists of PV system 6
2.1.2 Semiconductor material 8
2.1.3 Fixed/Tracking system 9
2.1.4 MPPT algorithms 9
2.2 Different Faults in PV System 11
2.2.1 Circuit fault 13
2.2.2 Fixed object shading 13
2.2.3 Partial shading 13
2.2.4 Soiling 13
2.2.5 Module degradation 14
2.2.6 Potential induced degradation (PID) 14
2.2.7 Hot spot effect 15
2.3 References of Fault Detection for PV system 16
Chapter 3. Experimental Materials and Method 18
3.1 Experimental Materials and Settings 18
3.1.1 The architecture of the proposed fault diagnosis 18
3.1.2 Weather module 19
3.1.3 Pyranometer 21
3.1.4 Resistance thermometer 22
3.1.5 Multi-crystalline silicon PV cells 22
3.1.6 PV inverter 24
3.1.7 Data collector 25
3.2 Experimental Method and Design 27
3.2.1 General operation generation 28
3.2.2 Partial shading 28
Chapter 4. Results and Discussion 30
4.1 General System Analysis 30
4.1.1 The influence of irradiance and temperature on PV module 30
4.1.2 Determine the PV system specifications 32
4.1.3 Related variable determination 33
4.2 Experimental Results and Data Analysis 34
4.2.1 Daily yield under the normal condition 34
4.2.2 Experimental results of all field tests 37
4.2.3 Partial shading effect 42
4.2.4 Employing the MPDE method with experimental data 46
4.3 Fault Diagnosis 47
4.3.1 Normal and abnormal operation state 47
4.3.2 Determine the different faulty cases 49
4.3.3 Fault diagnosis flow chart 51
4.4 Verified Field Test and Results 54
4.4.1 First verified test with same PV system 54
4.4.2 Second verified test with different PV system 56
4.4.3 Discussion of verified results 59
Chapter 5. Conclusions 60
References 61
dc.language.isoen
dc.subject太陽能光電系統zh_TW
dc.subject故障診斷zh_TW
dc.subject部分遮陰效應zh_TW
dc.subjectFault Diagnosisen
dc.subjectPhotovoltaic Systemen
dc.subjectPartial Shading Effecten
dc.title太陽能光電系統發電評估:故障偵測與診斷zh_TW
dc.titleAn Evaluation Approach for Photovoltaic System Operation: Fault Detection and Diagnosisen
dc.typeThesis
dc.date.schoolyear105-2
dc.description.degree碩士
dc.contributor.oralexamcommittee周呈霙(Cheng-Ying Chou),黃振康(Chen-Kang Huang),蕭瑛東(Ying-Tung Hsiao),郭昆璋(Kun-Chang Kuo)
dc.subject.keyword太陽能光電系統,部分遮陰效應,故障診斷,zh_TW
dc.subject.keywordPhotovoltaic System,Partial Shading Effect,Fault Diagnosis,en
dc.relation.page64
dc.identifier.doi10.6342/NTU201703752
dc.rights.note有償授權
dc.date.accepted2017-08-18
dc.contributor.author-college生物資源暨農學院zh_TW
dc.contributor.author-dept生物產業機電工程學研究所zh_TW
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