TABLE OF CONTENTS
Title page
Approval Page
Certification
Dedication
Acknowledgment
Abstract
Table of contents
List of Figures
List of tables
List of abbreviation
CHAPTER ONE: INTRODUCTION
1.1 Background
1.2 Statement of the Problem
1.3 Objective of the Study
1.4 The Scope of the Study
1.5 Significance of the Study
1.6 Organization of the Study
CHAPTER TWO: LITERATURE REVIEW
2.1 Load Shedding System
2.2 Power Management by Energy Harvesting System
2.3 Interface Circuit Impedance Matching
2.4 Process of Power Network Management
CHAPTER THREE: DESIGN METHODOLOGY
3.1 Design Strategy
3.2 Fuzzy Logic theory
3.3 Hardware and software approach
3.4 Fuzzy Logic Based Power Management
3.5 Methods of Data Analysis
3.6 Modeling the Power Management fuzzy logic Controller inference rules
3.7 Fuzzy Inference Rules
3.8 Objectives of the Network Reinforcement
3.9 Frequency and Load Control
3.10 The Line Bias Control
CHAPTER FOUR: IMPLEMENTING THE POWER MANAGEMENT
4.1 Implementing the Power Management
4.2 Sources of data
4.3 Fuzzy logic controller model
4.4 Simulating Power Supply Variation and Evaluating the Load Shedding Fuzzy Controller
CHAPTER FIVE: CONCLUSION AND RECOMMENDATION
5.1 Conclusion
5.2 Recommendation
References
Appendix
ABSTRACT
This project work is aimed at developing an efficient Algorithm for the management of Electric Power network using fuzzy logic. The fuzzy logic model functions as a system operator in making decision for load shedding and transfer switching. The new technique uses the system data frequency variation, load variation and voltage variation and the experience of the system operators to formulate fuzzy rules, which are then simulated using fuzzy logic toolbox in
MATLAB.
The fuzzy controller for the load shedding management of power system, was modeled and developed. Data collected from the New Haven Electric Power Distribution Substation was used to formulate the fuzzy logic interference rules. Simulation results indicates a remarkable improvement in the performance of the load shedding management at the power plants. Using the fuzzy controller the delay in load shedding transfer switching was reduced from 600 s to 0.02316 s, representing 99.99% reduction in load shedding transfer switching. The fuzzy logic controller achieved a power management efficiency of 90.57%.
CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
Future development and present operation of electric power system along
with other large system must pursue a number of different goals. Above all, the power system should be economically efficient, if it should provide reliable energy supply and should not have any detrimental impact on the environment. In addition to these global goals there is a number of supplementary goals, objectives and criteria. At the same time, operation and development of the system network is influenced by a variety of uncertain and random factors. As a result, the development strategy can be chosen from a large number of possible alternatives. Obviously, among a set of possible alternatives the developer attempts to find the best, or in accordance with accepted term, the optimal alternative. Thus, the complexity of the problem related to power systems planning is mainly caused by presence of multiple objectives, uncertain information and large number of variables.
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Item Type: Postgraduate Material | Attribute: 68 pages | Chapters: 1-5
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