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研究生： 王廷鉅
Citra - Satria Ongkowijoyo
論文名稱： 群體決策風險分析於能源方案選擇之應用
Risk-based Group Decision Making Using Stochastic Graphical Matrix Model for Energy Scheme Selection
指導教授： 周瑞生
Jui-Sheng Chou
口試委員: 楊亦東
I-Tung Yang
楊立人
Li-Ren Yang
鄭明淵
Min-Yuan Cheng
學位類別： 碩士
Master
系所名稱： 工程學院 - 營建工程系
Department of Civil and Construction Engineering
論文出版年： 2012
畢業學年度： 100
語文別： 英文
論文頁數： 179
外文關鍵詞： Stochastic processes
相關次數： 點閱：194  下載：4 
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    • A sustainability enhancement is generally measurable by its environmental, economic, and socio-cultural effects. To apply this concept, this study developed and empirically tested a risk-based method for evaluating renewable energy policy. The proposed graphical matrix approach coupled with Monte Carlo simulation identifies and measures critical performance indicators at an acceptance level of reliability when comparing alternative renewable energy schemes. The mathematical model reliably prioritizes alternatives by majority voting to address uncertainty in the multi-criteria decision making process. Compared to conventional deterministic method, the stochastic approach provides more reliable estimation accuracy, decision quality, and efficiency in sustainable renewable energy decision making.

    TABLE OF CONTENTS ABSTRACT i TABLE OF CONTENTS vi LIST OF FIGURES x LIST OF TABLES xii NOMENCLATURE xvii ABBREVIATION xx Chapter 1 INTRODUCTION 1 1.1 Research Background 1 1.2 Research objectives 7 Chapter 2 LITERATURE REVIEW 9 2.1 Renewable Energy Development in Current Millennium 9 2.1.1 Ocean Power 11 2.1.2 Wind Power 12 2.1.3 Geothermal Energy 13 2.1.4 Solar Thermal Energy 14 2.1.5 Hydroelectricity 14 2.1.6 Bio-energy 15 2.2 Relationships among Sustainability and Renewable Energy Schemes 16 2.2.1 Environmental Impact Aspect 18 2.2.2 Economic Viability Aspect 19 2.2.3 Social Equity Aspect 20 2.3 Indicators of Sustainability 21 2.4 Construction Management Role in Renewable Energy Development 22 2.5 Decision Making Techniques 23 2.5.1 Multi-criteria Decision Making (MCDM) 23 2.5.2 Deterministic Approach 25 2.5.3 Probabilistic Approach 26 2.5.4 Group Decision Making 28 Chapter 3 RESEARCH METHODOLOGY 30 3.1 Graph Theory and Matrix Approach Basic Techniques 30 3.1.1 Attributes Digraph Conception 32 3.1.2 Matrix Representation of The Digraph 33 3.1.3 Application of Permanent Function 37 3.1.4 Relative Importance Value between Attributes 40 3.1.5 Attribute Index Measurement and Normalization 41 3.2 Monte Carlo Simulation 42 3.2.1 Creating Mathematical Model 45 3.2.2 Random Variable Generation Method 45 3.3 Sampling of Correlated Random Variables 48 3.3.1 Probability Distribution and Variable Determination 48 3.3.2 Correlation Coefficient between Two Variables 49 3.3.3 Building Block of Covariance Matrix 52 3.3.4 Establishment of Transformation Matrix 52 3.3.5 Checking Matrix 53 3.3.6 Probability Model: The Triangular Distribution 54 3.4 Goodness of Fit Test for Variable Distribution 55 3.4.1 Pearson’s Chi-Square Test 57 3.4.2 Kolmogorov-Smirnov Test 59 3.4.3 Anderson-Darling Test 62 3.5 Sustainability Assessment for RE Schemes 64 Chapter 4 DECISION MAKING MODEL SIMULATION 66 4.1 Designing Stochastic Graphical Matrix Method 67 4.1.1 Digraph Matrix Representation 68 4.1.2 Normalization of Sustainability Indicators as Attributes 70 4.2 Experts Judgment Considering Uncertainties Information 70 4.3 Stochastic Configuration within Graphical Matrix Operation 71 4.4 SGMM Algorithm and GOF Evaluation 72 Chapter 5 EMPIRICAL APPLICATION 74 5.1 Sustainability Indicator Determination 74 5.2 Indicators Normalization and Direct Graph Representation 76 5.3 Digraph Matrix and Permanent Equation Representation 79 5.4 Goodness of Fit Test and Variance of Ranking Result 80 5.5 Probabilistic Assessment for Selection Factor Matrix 81 5.6 Simulation Result and Discussion 83 Chapter 6 CONCLUSION AND FUTURE WORK 85 6.1 Research Limitation 86 6.2 Future Improvement 87 BIBLIOGRAPHY 89 APPENDIX A 97 APPENDIX B 102 APPENDIX C 104 APPENDIX D 113 APPENDIX E 159 APPENDIX F 164

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