臺灣博碩士論文加值系統

本論文之目的是應用猫群最佳化(Cat Swarm Optimization, CSO)演算法去研究台灣產業的負載管理(Load Management)及經濟調度(Economic Dispatch)最佳化問題，希望經由CSO演算法來建立最佳需量，進而為至台灣工業降低電費成本。
本研究結果顯示CSO比PSO是較快速收斂且有較佳的整體解，而且CSO演算法對於台灣產業界在負載管理最佳化是有助益的。
從需求面的觀點本研究應用SCADA監控系統和實用的負載管理項目幫助台灣工業節省電費成本，且本研究亦致力提供有用的負載管理策略供決策者參考。
最後，我們建議未來的研究可以應用CSO演算法去分析解決工程及電力系統之非線性最佳化的問題。

The aim of this research is to study the load management (LM) and economic dispatch decision for the Taiwanese industries through Cat Swarm Optimization (CSO) algorithm. CSO algorithm can be proposed to select optimal demand contract and drop the basic electricity cost.
Results indicated that the CSO is superior to Particle Swarm Optimization (PSO) in the fast convergence and better performance to find the global best solution, considering the same iteration time. Also the CSO algorithm is highly helpful to Taiwanese industries on the optimal LM decision.
From the view point of demand side management, this research is to apply SCADA system and a feasible LM options for the Taiwanese industries to reduce the power cost. Also this study refers to provide decision-makers with useful LM strategies as reference.
Finally, it is suggested that future research might explore in nonlinear optimization problem through CSO algorithm, as well as in engineering and power system.

CONTENTS
ABSTRACT iii
CONTENTS v
LIST OF TABLES vii
LIST OF FIGURES viii

CHAPTER
I INTRODUCTION 1
1.1 Motivation and Objective 1
1.2 Literature Review……………………………………………………………. 4
1.3 Outline………………………………………………………………………. 9
II THE PROBLEM AND OBJECTIVE FUNCTION 10
2.1 Introduction 10
2.2 The Objective Function of Optimal Demand (TOU Rate) 11
2.3 The Objective Function of Optimal Demand (Non-TOU Rate) 14
2.4 The Objective Function of Economic Dispatch 16
III RESEARCH METHOD 20
3.1 The CSO Algorithm 20
3.1.1 The Seeking Mode 20
3.1.2 The Tracing Mode 22
3.1.3 The Core Description of Cat Swarm Optimization 22
3.2 The PSO Algorithm 25
3.2.1 The Seeking Mode 26
3.2.2 The Core Description of Particle Swarm Optimization 28

IV PREVENIENT SIMULATION RESULTS 30
4.1 The Optimal Contract Capacity for TOU Rate Customer 30
4.1.1 Parameter Settings for CSO and PSO (TOU) 31
4.1.2 Experimental Results for CSO and PSO (TOU) 31
4.1.3 The Implementation of Optimal Demand Contract (TOU) 34
4.2 The Optimal Contract Capacity for Non-TOU Rate Customer 35
4.2.1 Parameter Settings for CSO and PSO (Non-TOU) 36
4.2.2 Experimental Results for CSO and PSO (Non-TOU) 36
4.2.3 The Implementation of Optimal Demand Contract (Non-TOU) 37
4.3 The Economic Dispatch (ED) 40
4.3.1 Parameter Settings for CSO and PSO (ED) 40
4.3.2 Experimental Results for CSO and PSO (ED) 42
4.3.3 The Implementation of Optimal Demand Contract (ED) 42
V AUTOMATIC LOAD MANAGEMENT: A CASE STUDY 46
5.1 A SCADA Management Framework 46
5.1.1 The SCADA Automatic Management System 47
5.1.2 The Function of MAC 49
5.1.3 The On-line Battery Monitoring System 50
5.1.4 The Dialup Modem Application in BS Transmission Network 51
5.1.5 The GPRS Application in BS Transmission Network 52
5.1.6 The Mix Type Transmission Network 53
5.1.7 The Analysis of Management and Maintenance Network 55
5.2 The Research Method 56
5.3 The Power Energy Management Strategies 58
5.3.1 The Implementation of the TOU Rate 58
5.3.2 The Implementation of the Optimal Demand Contract 59
5.3.3 The Participation of Interruptible Load 61
5.3.4 The Load Demand Automatic Control 62
5.3.5 The Load Demand Control and Monitor 65
5.3.6 Automatic Power Factor Compensation 66
5.4 Establishment of Battery Voltage Measurement Rules 67
5.4.1 Tracing Individual Voltage Response as Measurement 70
5.4.2 Tracing Total Voltage Response as Measurement 73
5.5 Devise Battery Load Management Strategy 76
5.5.1 Balance Charging Voltage and Current Implement (Strategy I) 76
5.5.2 Temperature Compensation during Battery Charging (Strategy II) 77
5.5.3 Replace Generators and Reduce Peak Power Consumption (Strategy III) 78
5.5.4 Prevent Battery Over-charge or Over-discharge (Strategy IV) 78
5.5.5 Battery Early Fault Precaution and Reliable Power Supply Improvement (Strategy V) 79
5.6 Discussion 80
VI CONCLUSION AND SUGGESTIONS 82
6.1 Conclusion 82
6.2 Suggestions 83
VII FUTURE WORKS 85
REFERENCES 87
PUBLICATION LIST 91

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