Contents & References of Timing of transmission line repairs considering power system vulnerability
Table of Contents Eight
Abstract 1
Chapter One: Introduction
Chapter Two: History of Work Done
2-1. Introduction 8
2-2. An overview of the research conducted in the field of power system repairs. 9
2-3. An overview of the research conducted in the field of vulnerability of the power system. 25
2-4. Chapter summary and conclusion. 43
Chapter three: time model to investigate the vulnerability of the power system
3-1. Motivation 44
3-2. approach 45
3-3. Model innovations. 46
3-4. Modeling the vulnerability problem considering the time dimension. 46
3-4-1. Assumptions. 46
3-4-2. Modeling the investigation of power system vulnerability in a time horizon. 47
3-4-3. Converting the presented two-level model to a one-level model. 52
3-4-4. Transforming MPEC into a MILP problem. 53
3-5. The first numerical example. 54
3-5-2. Time horizon of the study. 54
3-5-3. Input data of the problem. 54
3-5-4. Defined scenarios 56
3-5-5. Presentation and analysis of results. 59
3-5-6. Computational load of the problem. 66
3-6. The second numerical example. 67
3-6-1. Time horizon of the study. 67
3-6-2. Input data of the problem. 68
3-6-3. Defining scenarios and presenting and analyzing the results. 69
3-7. Chapter summary and conclusion. 73
Chapter Four: A Model for Scheduling Transmission Line Repairs Considering Power System Vulnerability
4-1. Introduction and approach. 75
4-1-1. Model innovations. 77
4-2. Modeling the transmission line repair scheduling problem considering the vulnerability of the power grid. 78
4-2-1. Assumptions. 78
4-2-2. Modeling the timing of network transmission line repairs considering the vulnerability of the power system. 78
4-3. MWAW model to investigate power system vulnerability in a time horizon. 87
4-3-1. Formulation of MWaW model. 88
4-3-2. MPEC related to the MWaW model. 94
4-3-3. Converting the MPEC of the MWaW model into a MILP problem. 96
4-3-4. The final MWaW model as a one-level MILP problem. 98
4-4. The final model of VCTMS as a two-level MILP problem. 98
4-5. Using genetic algorithm to solve VCTMS model. 98
4-5-1. Selection of variables and objective function. 98
4-5-2. Coding. 99
4-5-3. primary population 100
4-5-4. choice 100
4-5-5. combination 101
4-5-6. jump 101
4-6. The first numerical example: the implementation of the MWaW model on the Garver six-bus network. 101
4-6-2. Study time horizon. 102
4-6-3. Input data of the problem. 102
4-6-4. Presentation and analysis of results. 104
4-7. The second numerical example: implementation of the VCTMS model for scheduling routine repairs in the Garver six-bus network. 106
4-7-1. Definition of scenarios 106
4-7-2. solution method 107
4-7-3. Presentation and analysis of the obtained results 109
4-7-3-a. Presentation and analysis of results related to scenario number 1. 109
4-7-3-b. Presentation and analysis of results related to scenario number 2. 113
4-7-3-C. Presentation and analysis of results related to scenario number 3. 118
4-7-3-d. Presentation and analysis of results related to scenario number 4. 121
4-8. Chapter summary and conclusion. 125
Chapter Five: Conclusion and Suggestions
5-1. Summary of results. 127
5-2. Suggestions and further research. 129
References. 131
Source:
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