Wind Power Assessment for the Bay Islands, Honduras

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姓名

卡羅斯(Carlos Murillo) 查詢紙本館藏

畢業系所

國際永續發展碩士在職專班

論文名稱

(Wind Power Assessment for the Bay Islands, Honduras)

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摘要(中)

本研究針對洪都拉斯(Honduras)的海灣群島地區(Bay Islands Region)的羅丹島(island of Roatán)，發展風能的可行性進行初步調查。風場資料來自羅阿坦的胡安•曼努埃爾•加爾韋斯國際機場(Juan Manuel Galvez International Airport)的每日時間序列數據。首先以Windographer軟體進行風場分析，分析項目包含
 總體分析：包括整體數據的分析。
 年分析：包括2005至2014年的每年的數據進行單獨的分析。
 季，月分析：包括根據雨季，旱季，其每月的特性基礎上，區域行為的分析。
此外，從風每年功率輸出的估計，進行3個不同規模的情境進行評估：
 小規模：考慮能源生產來自10組小規模Seaforth AOC 50千瓦的發電機組。
 中等規模：考慮能源生產來自10組中等規模的Enercon E-33 330千瓦的發電機組。
 大型規模：考慮能源生產來自10組大型Gamesa G114 2百萬瓦的渦輪機。
根據風的分類系統，當地的風能屬於Class 3，10年的測量結果在5公尺的高度平均風速為4.89公尺/秒，在離地50公尺的功率密度為307 W/平方公尺。採用小規模的渦輪機，年發電量為146.8百萬瓦時（在30米的輪轂高度），利用中等規模的渦輪年發電量為742.2百萬瓦時（在37米的輪轂高度），採用大規模渦輪的年發電量為7,407.6百萬瓦時（在80米的輪轂高度）。然後我們根據這3個方案的經濟性進行評估，計算每單位能量的成本。財務可行性分析可利用RETScreen 4的軟體工具來進行。小規模發電機組每單位能源成本是0.33美元/千瓦時，中等規模發電機組的成本為0.15美元/千瓦時，大型規模的成本為0.08美元/千瓦時。財務分析表明，在0.14美元/千瓦時的市場價格條件下，小規模方案是在經濟上不可行，因為投資回收期超過20年的生命週期，且淨現值為負; 中等規模方案是可行的，具有正的NPV，然而，鑑於內部收益率都在12％以下，因此中等規模方案在經濟上不具有吸引力; 大型規模方案是可行的，經濟上有吸引力，因為它提出了較生命週期小的投資回收期，回報率具有吸引力，且淨現值為正。基於本研究的結果，很明顯，在胡安曼努埃爾加爾維斯國際機場的風力資源是適合風力發展，特別是在較大規模的應用的情況下。

摘要(英)

This study presents a preliminary investigation on the feasibility of generating clean energy extracted from the wind in the Bay Islands Region of Honduras, specifically the island of Roatán. The 2005-2014 measured daily-time series data from Roatán’s Juan Manuel Galvez International Airport was statistically analyzed using the Windographer software tool. The study assesses a wind analysis in different periods of time. The analysis done with Windographer was classified into several periods:
• Overall analysis: includes the analysis of the entire recollected data, from 2005 to 2014.
• Yearly analysis: includes a separate analysis of the data per year.
• Seasonal and monthly analysis: includes an analysis based on the regional behavior according to rainy season, dry season, and its monthly characteristics.
In addition, an estimation of yearly power outputs from the wind was examined under the basis of 3 different scenarios:
• Small scale: considers energy production with 10 small scale Seaforth AOC 50 kW turbines.
• Medium scale: considers energy production with 10 medium scale Enercon E-33 330 kW turbines.
• Large scale: considers energy production with 10 large scale Gamesa G114 2 MW turbines.
The region, according to the wind classification system, constitutes as Class 3. The 10 year measured results give it a mean wind speed of 4.89 m/s at a recording height of 5.00 m above the ground, with a wind power density of 307 W/m2 at a 50.00 m height above the ground. The annual energy output using small scale turbines resulted in 146.8 MWh for the first scenario (at a hub height of 30 m), using medium scale turbines 742.2 MWh for the second scenario (at a hub height of 37 m), and using large scale turbines 7,407.6 MWh for the third scenario (at a hub height of 80 m).
The economics under these 3 scenarios were also investigated, using the cost per unit of energy approach. Furthermore, a financial viability analysis was implemented with the help of the RETScreen 4 Software tool.
The cost per unit of energy was $0.33/kWh for the first scenario, $0.15/kWh for the second scenario, and $0.08/kWh for the third scenario. The financial analysis reveals that under a market price of $0.14/kWh, the first scenario is not economically viable because the payback period exceeds that of the projects life cycle of 20 years, and the NPV is negative; the second scenario is feasible, having a positive NPV, however, it isn’t economically attractive given that the internal rates of return are below 12%; the third scenario is feasible and economically attractive given that it presents a payback period within the projects life cycle, with an attractive IRR, and a positive NPV.
Based on the results and observations made during the course of the research, it is apparent that the wind resource at Juan Manuel Galvez International Airport is suitable for wind extraction, especially in the case of larger scale applications.

關鍵字(中)

★ wind power
★ windographer
★ wind assessment
★ RETScreen
★ economic analysis

關鍵字(英)

★ wind power
★ windographer
★ wind assessment
★ RETScreen
★ economic analysis

論文目次

Acknowledgements i
中文摘要 ii
Abstract iii
Contents v
List of Tables viii
List of Figures x
Acronyms xii
Chapter 1 : Introduction 1
1.1 Background of Honduras and the Bay Islands 1
1.2 Wind energy development in Honduras 3
1.3 Research Motivation 5
1.4 Research Objectives 6
1.5 Thesis Organization 7
Chapter 2 : Literature Review 8
2.1 Overview of Wind Energy 8
2.2 Origins of Wind Energy 10
2.3 Modern Wind Energy 15
2.3.1 Modern Wind Turbine Design 15
2.3.2 Power Output Prediction 19
2.4 Characteristics of Wind Resources 20
2.4.1 Use of Wind Data Sources 20
2.4.2 Variations with Height 21
2.4.3 Wind Power Density Function 21
2.4.4 Wind Direction 21
2.4.5 Turbulence 22
2.5 Wind Resource Assessment 22
2.5.1 Measurement Parameters 23
2.5.2 Recorded Parameters 23
2.6. Identifying and valuing costs 24
2.7 RETScreen4 Software Suite 24
2.7.1 Using RETScreen for Wind Energy Projects 25
2.8 Windographer Software 31
2.8.1 Windographer Analysis Windows 34
2.8.2 Wind Turbine Output Estimator Tool 34
Chapter 3 : Methodology 38
3.1 Selection of region 38
3.2 Framework 38
3.3 Data Recollection 41
3.3.1 Information for MHRO (78703) in Roatán 41
3.4 Data Validation 41
3.5 Data Processing 43
3.5.1 Turbulence intensity 44
3.5.2 Wind power density 44
3.6 Wind Turbine Selection 44
3.7 Economic Analysis 45
3.8 RETScreen Financial Analysis 47
Chapter 4 : Results 49
4.1 Results from Windographer Software Tool 50
4.1.1 Overall Analysis of Data 50
4.1.2 Yearly Analysis of Data 58
4.1.3 Seasonal and Monthly Analysis of Data 76
4.2 Wind Turbine Power Output 88
4.3 Economic Analysis 90
4.3.1 Scenario A 91
4.3.2 Scenario B 92
4.3.3 Scenario C 94
4.4 RETScreen4 Evaluation 96
4.4.1 Evaluation of Scenario A 96
4.4.2 Evaluation of Scenario B 99
4.4.3 Evaluation of Scenario C 102
Chapter 5 : Conclusions and Recommendations 106
5.1 Conclusions 106
5.1.1 Data Analysis 106
5.1.2 Economic Analysis 107
5.1.3 Financial Analysis using RETScreen 4 107
5.2 Limitations 108
5.3 Recommendations for Future Studies 108
References 109
Appendix 114
Thesis oral defense comments and responses 114

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指導教授

莊銘棟(Ming-Tung, Chuang Ph.D)

審核日期

2015-7-20

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