為民宿業者使用再生能源尋求最佳之設備組合及現場佈局

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盧凱(Luki Trihardani) 查詢紙本館藏

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論文名稱

為民宿業者使用再生能源尋求最佳之設備組合及現場佈局
(Making Optimal Location-Sizing Decisions for Deploying Hybrid Renewable Energy at B&Bs)

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摘要(中)

為民宿業者使用再生能源尋求最佳之設備組合及現場佈局

摘要

使用再生能源是民宿業者具前瞻性來緩解氣候變遷並同時維持競爭優勢的商業策略。然而，當前仍缺乏最佳化觀光旅宿再生能源設備組合的研究分析，因此本研究提出了一項具實用性的方法，使所有民宿業者能夠為其營運設施建立最佳的再生能源佈局決策。本研究透過混合整數規劃建立模型並對實際案例進行測試，該模型成功為兩種情境建構了最佳的能源系統組合，基本情境以每年21,499美元的成本產出116,942度電，而非傳統常規技術的情境則以每年24,670美元的成本提供了114,474 度的電力。與電網購置全部所需電力相比，兩種情境每年皆可減少排放超過26噸之二氧化碳當量。
在可負擔之預算內，本研究為民宿業者提供了成功能源轉型的重要參考，研究中考量了各種能源配置元素包含再生能源設備組合、電池、電網、能源自給率目標及各式再生能源技術。因此民宿業者可擬定理想的能源自給率，在配合電網的電力供應下滿足一定比例之再生能源需求，而該模型亦能評估再生能源技術的投資並權衡是否購置更大容量的電池。本研究之成果將有助於全球各地之民宿業者加速再生能源的使用。

摘要(英)

Making Optimal Location-Sizing Decisions for Deploying
Hybrid Renewable Energy at B&Bs

ABSTRACT

The adoption of renewable energy (RE) is a promising business strategy for bed and breakfasts (B&Bs) to mitigate climate change while maintaining a competitive edge. However, there is still a lack of analytical studies to determine an optimal RE mix for tourism accommodations. This study thus proposes a practical approach to enable all B&Bs to make optimal RE decisions for their business facility. A mixed-integer program-ming (MIP) model is developed and tested in a case study. The model successfully identi-fies an optimal hybrid energy system for two scenarios, the base case that generates 116,942 kWh of electricity annually at the cost of US $21,499, and the unconventional technology case that generates 114,474 kWh of electricity annually at the cost of US $24,670. Compared to purchasing all the required electricity from the power grid, both scenarios can save more than 26 tons of CO2e/year.
The analysis provides valuable information for B&Bs to initiate a smooth en-ergy transition with affordable costs. This study considers various energy components, in-cluding hybrid RE, batteries, the power grid, self-sufficiency targets, and various RE tech-nologies. Therefore, B&Bs can choose a preferred self-sufficiency target where RE satis-fies a specific portion of the energy demands and the power grid satisfies the rest. The model can also evaluate the tradeoff between investing in RE technologies and purchasing larger batteries. These findings will assist B&Bs in accelerating the adoption of RE glob-ally.

關鍵字(中)

★ 民宿
★ 溫室氣體排放
★ 再生能源
★ 數學最佳化

關鍵字(英)

★ bed and breakfast
★ greenhouse gas emissions
★ renewable energy
★ mathematical optimization

論文目次

Table of Contents

摘要 i
Abstract ii
Acknowledgments iv
List of Figures viii
List of Tables ix
List of Abbreviations x
Chapter 1 Introduction 1
1-1 Research Background 1
1-2 Research Motivation 3
1-3 Research Problem 6
1-4 Research Outline 8
Chapter 2 Literature Review 9
2-1 Optimization in Tourism Accommodation 9
2-2 Design Optimization Using Simulation-Based Tools 10
2-3 Design Optimization Using Heuristic Algorithms 12
2-4 Research Contributions 13
Chapter 3 Optimization Model 17
3-1 Assumptions 17
3-2 Notation 18
3-2 Objective Function 19
3-3 Constraints 20
Chapter 4 Methodology 23
4-1 Flowchart of the Methodology 23
4-2 The Base Case 24
4-3 The Unconventional Technology Case 25
4-4 Case Study of the B&B 26
4-4-1 Solar and Wind Energy Data 27
4-4-2 Layout at the Subject B&B 28
4-4-3 Demand at the Subject B&B 31
Chapter 5 Results And Discussion 34
5-1 Analysis of the Base Case 34
5-1-1 100% Self-Sufficiency in the Base Case 34
5-1-2 Different Self-Sufficiency Ratios in the Base Case 41
5-2 Analysis of the Unconventional Technology Case 48
5-3 Comparison of Base Case and Unconventional Technology Case 50
Chapter 6 Conclusions and Future Research 52
6-1 Conclusions 52
6-2 Future Research 53
References 55
Appendix 67
Appendix A Establish Solar and Wind Energy Data 67
Appendix B Determine Optimal Location-Sizing Decisions at the B&B 69
Appendix C Calculate the Costs of Purchasing Electricity from the Power Grid 69

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指導教授

王啟泰(Chi-Tai Wang)

審核日期

2022-7-26

推文