ABSTRACT
Nigeria is faced with endemic electricity generation problem which has remained a big obstacle to her becoming one of the developed nations of the world despite her being endowed with vast natural resources. There exists many power generating stations in Nigeria that are not operating at full efficiency. Many methodologies of optimizing the cost of fuel in running generating stations are in existence but the this study focused on optimizing the cost of fuel in power generation using maximum output approach (Lagrange Multipliers method of solution) with the MATLAB/SIMULINK and MINITAB software packages as tool for the analysis. The study presents an effort to help in solving high cost of power generation in Nigeria. The aim of this thesis is to minimize the cost of power generation in Nigeria using Omoku Power Station as a case study. The overall outcome is to solve the cost function equations under the given constraints for improved performance. The cost function equations or cost models and constraints to obtain minimized cost values are formulated for the Omoku generating station turbines as non-linear equations. The two (2) different test cases of the six (6) turbines at the Omoku power generating station that were considered by keeping the generated power constant within 24 hours of operation daily for a month and varying the number of hours of operation of the station yielded only 3% fuel cost saving while varying the generated power between 18 MW and 25 MW under fixed operating hours a month yielded 32% fuel cost saving. The results so obtained from the varied exercises showed huge savings in fuel consumption better when the operating hours are kept constant. These results showed that the fuel cost of power generation can be minimized with maximum output. The system will assist operators in power generation stations or the Generating Companies of Nigeria (GENCOS) to minimize their costs of power generation so as to plan for generation in the most economic and efficient manner.
TABLE OF CONTENTS
Title page i
Declaration ii
Certification iii
Dedication iv
Acknowledgements v
Table of contents vi
List of Tables ix
List of Figures x
Abstract xi
CHAPTER 1 : INTRODUCTION
1.1 Background of Study 1
1.2 Problem Statement 3
1.3 Aim and Objectives 3
1.4 Significance of Study 4
1.5 Scope of the Study 4
1.6 Outline of Study 4
CHAPTER 2: LITERATURE REVIEW
2.1 Conceptual Framework 6
2.2 Concept of Power Generation and Generating Stations 6
2.3 Concept of Optimal cost or Optimization 11
2.4 Theoretical Framework 16
2.5 Empirical Studies 18
2.6 Research Gaps 26
CHAPTER 3: MATERIALS AND METHODS
3.1 Materials 27
3.2 Method of Data Collection 28
3.3 Model Formulation 29
3.4 Method of data analysis 35
CHAPTER 4: RESULTSAND DISCUSSIONS
4.1 Varied operating capacity and fixed operating hours in a month using MATLAB/SIMULINK software package for the analysis 36
4.2 Discussion of the graphs for varied operating capacity and fixed operating hours 37
4.3 Fuel cost optimization & comparison in naira for varied operating power capacity and fixed operating hours in a month using MATLAB/SIMULINK approach for the analysis 38
4.4 Fixed operating capacity versus varied operating hours in a month using MATLAB/ SIMULINK software package for analysis 39
4.5 Discussion of the graphs for fixed operating capacity and varied operating hours 41
4.6 Fuel cost optimization & comparison in naira for fixed operating power capacity and varied operating hours in a month using MATLAB/SIMULINK approach for the analysis 42
4.7 Optimal cost calculation for varied operating capacity and fixed operating hours in a month using MINITAB software package for the analysis 43
4.8 Discussion of the graphs for varied operating capacity and fixed operating hours 44
4.9 MINITAB approach in fuel cost optimization & comparison in naira for varied power operating capacity versus fixed operating house in a month 45
4.10 Discussion of the graphs for fixed operating capacity and varied operating hours 46
4.11 Fuel cost optimization & comparison in naira for fixed operating capacity versus varied operating hours in a month using MINITAB approach in the analysis. 47
CHAPTER 5: CONCLUSION, RECOMMENDATIONS AND
CONTRIBUTION TO KNOWLEDGE
5.1 Conclusion 53
5.2 Recommendations 54
5.3 Contribution to knowledge 55
References 56
Appendices 61
LIST OF TABLES
3.1 Installed/operating capacity of Omoku power generating station Rivers State, Nigeria 29
3.2 Omoku power generating station figures 30
3.3 Varied operating capacity and fixed operational hours in a month 32
3.4 Fixed operating capacity and varied operational hours in a month 34
4.1 Varied operating capacity and fixed operating hours in a month (MATLAB) 38
4.2 Fixed operating capacity and varied operating hours (MATLAB) 42
4.3 Minitab optimal cost result of varied operating capacity and Fixed operating hours in a month 44
4.4 MATLAB optimal cost result of varied operating capacity and fixed operating hours in a month 47
4.5 Fixed operating capacity and varied operating hours in a month using MINITAB software for the analysis. 49
4.6 MATLAB optimal cost result of fixed operating capacity and
varied operating hours in a month 52
LIST OF FIGURES
4.1 Line graph representation of optimized fuel cost for varied
operating capacity versus fixed operating hours in a month 36
4.2 Bar chart graph representation of optimized fuel cost for varied operating capacity versus fixed operating hours in a month 37
4.3 Line graph representation of optimized fuel cost for fixed operating capacity versus varied operating hours in a month 40
4.4 Bar chart graphical representation of optimized fuel cost for fixed operating capacity versus varied operating hours in a month 44
4.5 Line graph representation of optimized fuel cost for varied operating capacity versus fixed operating hours in a month 45
4.6 Bar chart graphical representation of optimized fuel cost for varied operating capacity versus fixed operating hours in a month 46
4.7 Line graph representation of optimized fuel cost for fixed
operating capacity versus varied operating hours in a month 47
4.8 Bar chart representation of optimized fuel cost for fixed operating capacity and varied operating hours in a month 48
CHAPTER 1
INTRODUCTION
1.1 BACKGROUND TO THE STUDY
High demand and use of power in various industries and organizations is one amongst many reasons that necessitated the issue of power generation optimization. Nigeria expends millions of naira on daily, monthly and annual basis to generate power to meet industrial and individual needs and energy demands. Notwithstanding the energy needs of these industries and individuals, they try to device means of reducing the running costs of their generating systems in order not to exist on finances (Uthman, 2017).
Power system engineering is concerned with the generation, transmission and distribution of electricity and design of related devices. These related devices include electric generators, electric motors, transformers and power electronics. This electric energy is gotten in volumes from nuclear power thermal and hydro-electric stations which are found far from the load centers. Systems are traditionally designed to bulk transfer (transmission) and supply individuals.
Electrical energy is generated by the conversion of available energy in different forms especially from natural sources such as kinetic energy from chemical energy of fuels, pressure head of water, blowing winds and nuclear energy of radio-active substances into electrical energy. These are usually from Conventional & non-conventional sources:
Conventional sources are namely:
a) Fuels/Thermal (Coal)
b) Nuclear/Atomic energy (Radio-active substances)
c) Gas
d) Water/ Ocean tides and waves
e) Terrestrial heat
Non conventional Sources include the following:
a) Wind
b) Solar
c) Biomass (Gupta, 2013)
Energy is seen to be one of the most important resources that pushes the economic development of a country. The main classes of the sources of the energy are from fossil and renewable sources. Yusuf (2017), states that there are presently two major types of power plants operational in Nigeria: hydro-electric and thermal power plants.
There exist presently 23 grid-connected generating plants operational in the Nigerian Electricity Supply Industry (NESI) with installed capacity of 10,396.0 MW and available capacity of 6,056 MW. Most generation is from thermal power plants, with an installed capacity of 8,457.6 MW (81% of the total) and an available capacity of 4,996 MW (83% of the total).
The current generation capacity includes:
1). Installed Capacity as at 2018: 12,522 MW
a. Thermal: 10,142 MW
b. Hydro: 2,380 MW (Source https://www.usaid.gov/powerafrica/nigeria).
2) National integrated power projects.
3) Existing federal government of Nigeria (FGN) power generation facilities.
4) Independent power projects.
1.2 PROBLEM STATEMENT
Big industries and organizations are nowadays characterized by large operations due to increase in industrialization. These industries and organizations need huge amounts of power on daily basis to run their operations. Consequent upon this, large power consumption and huge sums of money are spent to meet the emerging consumption levels through continuous fuel purchase to operate the generating stations. Therefore, there is a need to formulate and possibly device means of minimizing the amount of money expended on the fuel that operate the power stations. This thesis is poised to look at generation of electricity in Nigeria and the optimal cost of one of the generating stations in the Country with a view to improving the power output.
1.3 AIM AND OBJECTIVES
This project is aimed at minimizing the cost of power generation in Nigeria using Omoku Power Station as a case study and the objectives are as follows:
i. Formulate an economic dispatch optimal power flow model.
ii. Collect the data associated with the running of the turbines such as cost of fuel consumption and turbine capacities.
iii. Formulate the cost function equation along with the constraints.
iv. Solve the cost function equations and constraints using MATLAB/SIMULINK and MINITAP software packages to obtain minimized cost values.
v. To compare the minimized values with the real values and draw inferences.
1.4 SIGNIFICANCE OF THE STUDY
The significance of this study is to help reduce the cost at which generating stations produce power for use in industries, organizations and by individual consumers. This project uses Omoku power station in Rivers State as a case study.
The writer is confident that the result of the study would be of significant benefits to Government, power generating stations and future researchers. The Nigerian government has made attempts at increasing foreign participation in the electric power sector by commissioning independent power projects (IPPs) and National Integrated Power Project (NIPP) to generate electricity and thereby boost power generation. All these efforts geared towards matching demand with supply seem to be negatively impacting on the Country’s economy. The government needs to justify the huge sum of money spent on the power sector especially on generation plants and all the efforts made so far in Nigeria.
1.5 SCOPE OF THE STUDY
This study is limited to Omoku power station in Rivers State of Nigeria which is our case study, and only considers the power station with six turbines for power generation.
The study is to do the optimal cost of the Omoku power station in the Southern part of Nigeria.
1.6 OUTLINE OF THE STUDY
This study is broken into different chapters for ease of comprehension.
Chapter 1 deals with the introduction remarks.
Chapter 2 reviews different related literatures on the topic of study. It looked at the Concept of power generation and generating stations, Concept of Optimal cost or Optimization.
Chapter 3 deals materials and methods used in executing the thesis, methods of data collection, formation of the model and Methods of data analysis.
Chapter 4 focuses on the results of the analysis of the data collected from the analysis, optimizes the formed models using MATLAB/SIMULINK and MINITAB software packages, compares the optimized costs using MATLAB/SIMULINK and MINITAB software packages.
Chapter 5 dwells on the conclusion, recommendations and the contribution of the project to knowledge.
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