The aim of the study is to model FACTS devices on weak transmission line in the Nigeria power network and consider their effect on the bus voltages, reactive and active power using genetic algorithm(GA) approach for loss minimization. The Nigeria 330KV existing network to be considered consist of nine (9) generating stations, thirty(30)Buses and forty one (41) transmission lines which will be modelled and simulated using Matlab Version 7.10.
The study is limited to Nigeria 330kV existing power network with the focus on the comparison of the Bus voltages and power flow on the transmission lines when FACTS devices are incorporated and when the FACTS devices are not incorporated.
Research Questions:
For the realization of the objectives mentioned above and the aim, the following research questions were set as a guide:
1. What is the significant effect of FACTS devices on weak transmission lines?
2. Can FACTS device be used with genetic algorithm for optimization of power loss and improvement of the bus voltages?
3. What is the limitation of using just genetic algorithm without FACTS device for the optimization of power loss and the improvement of the bus voltages?
This research work is divided into five chapters with each chapter buttressing more on minimization of power loss.
The scope of the work , the objective and aim of the research work to be achieved is addressed in chapter one (1). Chapter two(2) focus on the literature review of other researchers on FACTS device in the improvement of the power network, the concept of FACTS device and the choice of FACTS device to be used was also addressed in chapter two (2) of this research work.
Chapter three focus on the methodology used for this study. The simulation of the 330kV Nigeria power network was done on MATLAB /SIMULINK 7.5.
Also the chapter three focused on the use of power flow analysis toolbox which is a collection of a written codes of m files that has a compatible interface with MATLAB to generate the load flow of the power network instead of using ETAP. The genetic algorithm was also discussed as an optimization tool deployed to optimize the losses on the transmission line.
Chapter four focus on the research findings with possible explanation as to some of the result obtained. Finally chapter five talks about the conclusion of this research work and highlight some areas to explore in the future.
Table of Contents
CHAPTER ONE: INTRODUCTION
1.0 Background to the Study
1.1 Statement of the Problem
1.2 Aim and Objectives of the Study
1.2.1 Aim of the Study
1.2.2 Objectives of the Study
1.3 Research Questions
1.4 Scope of the Study
1.5 Significance of the Study
1.6 Project Layout
CHAPTER TWO: LITERATURE REVIEW
2.0 Introduction
2.1 Brief History of Nigerian 330kV, 30Bus Interconnected Electric Power System
2.2 Concept of Transmission Line
2.2.1. Line Load-ability
2.2.2. Transmission Systems Enhancement Strategies
2.3 Concept of FACTS Device
2.4 Types of FACTS Device Based on their Application
2.4.1 Series Devices
2.4.2 Shunt Devices
2.4.3 Combined Series-Series Devices
2.4.4 Combined Series-Shunt Devices
2.5 Choice of FACTS Devices/Controller
2.6 Power Flow FACTS Model
2.6.1 Static Compensator (STATCOM)
2.6.2 Unified Power Flow Controller
2.6.3 Thyristor-Controlled Series Compensator.
CHAPTER THREE: METHODOLOGY
3.1 Research Design
3.2 Modelled Network of the 330kV Nigeria Power Network on Matlab
3.3 Load Flow Analysis through Power Flow Analysis Tool Box
3.3.1 Mathematical Model of N-R Algorithm
3.4 Optimization through Genetic Algorithm
3.4.1 GA Flow Chart Iteration Process
3.4.2 Initiating the Initial Population/ Selection
3.4.3 Encoding and Initialization of the Device
3.4.4 Fitness Computation of Each Device
CHAPTER FOUR: RESEARCH FINDINGS AND DISCUSSION
4.0 Introduction on Research Findings and Discussion
4.2 The Load Flow Analysis with Optimization Techniques
4.2.1 Case One: Optimization with Facts Devices Approach
4.2.2 Case Two:Optimization of Power Loss using Genetic Algortihm Approach
4.2.3 Case Three: Optimization of Power Loss by using Facts Device and Genetic Algorithm
4.3 Discussion on the Case Three Optimization Approach With GA and FACTS Device
CHAPTER FIVE: CONCLUSION AND RECOMMENDATION
5.0 Conclusion
5.1 Recommendation for Future Research
Research Objectives and Key Topics
The primary aim of this research is to model and simulate the 330kV Nigerian power network using MATLAB to evaluate the effect of Flexible Alternating Current Transmission Systems (FACTS) devices on power loss minimization and voltage stability enhancement, utilizing genetic algorithms as the optimization strategy.
- Modeling of the 330kV Nigerian transmission network.
- Load flow analysis using the Newton-Raphson method.
- Integration and optimization of FACTS devices (STATCOM, UPFC, TCSC).
- Application of Genetic Algorithms (GA) for optimal device placement and loss reduction.
- Comparison of conventional control methods versus AI-based optimization techniques.
Excerpt from the Book
3.4 Optimization through Genetic Algorithm
Genetic algorithm is widely considered in numerical optimisation methods, which use the natural processes of evolution and genetic recombination. GAs are particularly useful when the goal is to find an approximate global minimum in a high-dimension, multi-modal function domain, in a near-optimal manner. Unlike the most optimisation methods, they can easily handle discontinuous and non-differentiable functions. The algorithms encode each parameters of the problem to be optimised into a proper sequence (where the alphabet used is generally binary) called a gene, and combine the different genes to constitute a chromosome. A proper set of chromosomes, called population, undergoes the Darwinian processes of natural selection, mating and mutation, creating new generations, until it reaches the final optimal solution under the selective pressure of the desired fitness function.
Hence, GA optimising technique can therefore, operate according to the following:
1) Encoding the solution parameters as genes;
2) Creation of chromosomes as strings of genes;
3) Initialisation of a starting population;
4) Evaluation and assignment of fitness values to the individuals of the Population.
5) Reproduction by means of fitness-weighted selection of individuals belonging to the population
6) Recombination to produce recombined members
7) Mutation on the recombined members to produce the members of the next generation.
8) Evaluation and assignment of fitness values to the individuals of the next generation.
Summary of Chapters
CHAPTER ONE: INTRODUCTION: Outlines the background of the Nigerian transmission network, identifying problems like insufficient generation, transmission line overloading, and poor voltage regulation.
CHAPTER TWO: LITERATURE REVIEW: Reviews existing FACTS technologies, transmission enhancement strategies, and historical developments of the Nigerian 330kV power system.
CHAPTER THREE: METHODOLOGY: Describes the design and development of the 330kV network model in MATLAB, including the implementation of the Newton-Raphson load flow analysis and the genetic algorithm optimization framework.
CHAPTER FOUR: RESEARCH FINDINGS AND DISCUSSION: Presents the simulation results of the three optimization cases, comparing network performance with and without FACTS devices and genetic algorithm intervention.
CHAPTER FIVE: CONCLUSION AND RECOMMENDATION: Concludes that appropriate placement of FACTS devices via genetic algorithms significantly minimizes line losses and stabilizes bus voltages compared to conventional methods.
Keywords
FACTS devices, Genetic Algorithm, 330kV Transmission Network, Power Loss Minimization, Voltage Stability, Load Flow Analysis, Newton-Raphson Method, STATCOM, UPFC, TCSC, Power System Optimization, Nigerian Power Grid, Transmission Constraints, Artificial Intelligence in Power Systems, Bus Voltage Regulation.
Frequently Asked Questions
What is the core focus of this research?
The research focuses on the optimization of the Nigerian 330kV power transmission network, specifically aiming to minimize power losses and improve voltage profiles using FACTS devices and genetic algorithms.
What are the central themes discussed in this work?
The central themes include power system load flow analysis, the application of Flexible AC Transmission Systems (FACTS), genetic algorithm-based optimization, and the practical challenges of the Nigerian national electricity grid.
What is the primary objective of this study?
The primary objective is to model the existing 330kV Nigerian grid to identify weak transmission lines and determine the most effective optimization technique to minimize line losses and maintain bus voltages within statutory limits.
Which scientific methodology is employed?
The study utilizes numerical simulation in the MATLAB/SIMULINK environment. It employs the Newton-Raphson method for load flow analysis and the Genetic Algorithm (GA) technique for the optimal placement and rating of FACTS devices.
What topics are covered in the main body?
The main body covers the literature review on transmission systems, detailed methodology including algorithm development for GA and N-R methods, and a thorough analysis of findings through three specific optimization case studies.
How would you characterize this work using keywords?
Key characteristics include Power System Optimization, FACTS integration, Genetic Algorithms, Voltage Stability, and Nigerian Grid Infrastructure.
What is the specific role of the Genetic Algorithm in this research?
The Genetic Algorithm is used to search the multi-modal space of possible FACTS device locations and ratings to find the global optimal solution that satisfies both equality and inequality power system constraints.
How do the three optimization cases differ in their approach?
Case one uses FACTS devices via conventional placement; case two utilizes only genetic algorithms to minimize loss; case three combines both by using genetic algorithms to find the optimal placement and sizing of FACTS devices, providing the most robust result.
- Arbeit zitieren
- Olalekan Olagunju (Autor:in), 2019, Modelling Flexible AC Transmission Systems (FACTS) Devices on Weak Transmission Lines in the Nigerian Power Network, München, GRIN Verlag, https://www.grin.com/document/510717
