Despite Nigeria’s key position in Africa, electric power crisis and frequent outages in the Nation have degenerated to a major acute problem. These problems are associated with inadequate generation, insufficient and unreliable evacuation/transmission of same. As a result, dispatch centers and distribution companies find it difficult to optimally dispatch the limited energy particularly to economic viable consumers considering the fact that the bedrock of every industry is primarily to survive extinction through revenue collection. However, this research is focused on presenting an efficient and economic power dispatch technique in Umuahia Metropolis. The materials used in this research include load data from eight EEDC Injection Substations in Umuahia Metropolis, MATLAB Simulation Software and Microsoft Excel. Also, the methods adopted are statistical method of interpolation and Mann-Whitney’s test for data collection and evaluation. Load demand (daily, monthly and yearly) equations were used for data analysis and interpretation. Also, an economic load dispatch technique was developed using Microsoft Excel. This technique design has the ability to distribute available power (energy allocation) with respect to economically viable consumers. However, if these results are carefully implemented, it will afford EEDC the opportunity to serve their economically viable customers better and will also motivate other non-economic viable customers to improve. Thus, EEDC’s general revenue collection will increase, since the main aim of every business owner is primarily to increase productivity and maximize profit (Optimization).
TABLE OF CONTENTS
Title Page i
Table of Contents vi
List of Tables ix
List of Figures x
CHAPTER 1: INTRODUCTION 1
1.1 Background of the Study 1
1.2 Problem Statement 7
1.3 Aim and Objectives 7
1.4 Scope of Research work 7
1.5 Significance of the Study 8
1.6 Outline of the study 8
CHAPTER 2: LITERATURE REVIEW 9
2.1 Related Work 9
2.2 The Concept of Economic Load Dispatch 16
2.2.1 Load dispatch 16
2.2.2 Economic load dispatch 19
2.2.3 Load dispatch center (LDC) 22
2.2.4 Load dispatcher 25
2.3 Load Shedding 26
2.4 Load Demand Analysis 27
2.4.1 Load curve 27
2.4.2 Load duration curve 29
2.4.3 Load factor 30
2.4.4 Exploitation time 31
2.4.5 Load coincidence 31
2.5 Classification of Load 31
2.6 Method Employed for the Study 35
2.6.1 Method of data collection and evaluation 35
2.7 Method of Data Analysis 36
2.8 Data Interpretation 37
2.9 Constant Computation for Current to Power (kW) Conversion 37
CHAPTER 3: MATERIALS AND METHODS 39
3.1 Materials 39
3.2 Methods 39
3.3 Load Dispatch Model For Umuahia Metropolis 40
3.4 The Graphical Results 42
3.4.1 Afara1 injection substation 42
3.4.2 Afara2 injection substation 46
3.4.3 Ubakala injection substation 48
3.4.4 Nkata-Alike injection substation 50
3.4.5 Umudike injection substation 52
3.4.6 JDP injection substation 55
CHAPTER 4: RESULTS AND DISCUSSION 58
4.1 Total Average Load Demand of Umuahia Metrpolis in Graphical Format 58
4.2 Percentage Average Hourly Load Demand in Umuahia Metropolis in 59
Pie Chart Format
4.3 Percentage Composition for the Various Load Classifications Results 60
4.4 Economic Load Dispatch Simulation Results 62
CHAPTER 5: CONCLUSION AND RECOMMENDATIONS 66
5.1 Conclusion 66
5.2 Recommendations 67
LIST OF TABLES
1.1 EEDC cash collection analysis for 2014 5
2.1 Main function of supervisory control and data acquisition system (SCADA) 17
2.2 Task of control center at different classes or levels 24
4.1 Summary of the various load sums in respect to their load classifications 60
4.2 Economic load dispatch simulation results for zero (0) load allocation for Umuahia Metropolis 62
4.3 Economic load dispatch simulation results for 6MW load allocation for Umuahia Metropolis 63
4.5 Economic load dispatch simulation results for 30MW load allocation for Umuahia Metropolis 64
4.6 Economic load dispatch simulation results for 50MW load allocation for Umuahia Metropolis 65
LISTS OF FIGURES
1.1 EEDC power distribution network for Umuahia fed via Alaoji 132KV transmission line 6
2.1 Hierarchy of dispatch center 23
2.2 Typical chronological load curve showing the base and peak loads 28
2.3 Typical load duration curve 29
2.4 Typical chronological daily load curve for residential load 32
2.5 Typical chronological daily load curve for commercial load 33
2.6 Typical chronological daily load curve for industrial area 33
2.7 Typical chronological load curve for street lighting 34
2.8 Typical chronological load curve for street lighting 34
2.9 Method employed for the study 35
3.1 The flowchart of the model 41
3.2 The hourly load curve for Azikiwe feeder in Afara1 injection substation 42
3.3 The hourly load curve for World bank feeder in Afara1 injection substation 43
3.4 The hourly load curve for Aba road feeder in Afara1 injection substation 44
3.5 The hourly load curve for CBN feeder in Afara1 injection substation 45
3.6 The hourly load curve for township feeder in Afara2 injection substation 46
3.7 The hourly load curve of GRA feeder in Afara2 injection substation 47
3.8 The hourly load curve of Ubakala 11kV feeder in Ubakala injection substation 48
3.9 The hourly load curve of old Umuahia 11kV feeder in Ubakala injection substation 49
4.0 The hourly load curve of Nkwoegwu feeder in Nkata-Alike injection substation 50
4.1 The hourly load curve of Amaogwugwu feeder in Nkata Alike injection substation 51
4.2 The hourly load curve for research feeder in Umudike injection Substation 52
4.3 The hourly load curve for Umudike feeder in Umudike injection Substation 53
4.4 The hourly load curve for Olokoro feeder in Umudike injection substation 54
4.5 The hourly load curve for Ekenobiz feeder in JDP injection substation 55
4.6 The hourly load curve for Amachara feeder in JDP injection substation 56
4.7 The hourly load curve for Abiriba injection substation 57
1.1 BACKGROUND OF THE STUDY
In the Nigerian electric power system, electric energy generation has been a bit balanced unlike in the very near past where more emphases were in hydro plants (Iloh and Obi, 2016). Many thermal plants are under construction awaiting completion. The intention to generate electrical energy has not been matched with a proportional interest to transmit same since there is lack of serious attention in building new transmission lines and substations. In addition there has been additional pressure on the system due to monthly growth in demand of electricity. The effect of such monthly increase in demand has been pervasive and increasing problems associated with maintaining an acceptable voltage profile. Electric Power development in Nigeria started toward the end of 19th century (Awosope, 2014) when the first generating plant of 30kW was installed in the city of Lagos in 1898. From this date till present, many agencies, reforms and Organizations, both Governmental and Non-Governmental have been established. Subsequently, the usage of Electric power has been on the increase.
The Electricity Corporation of Nigeria Ordinance No.1 of 1950 was made to integrate power development and make it effective. The Electricity Corporation of Nigeria (ECN) then became the statutory body responsible for Generation, Transmission and Distribution of Electricity to all consumers in Nigeria. In 1962, the Niger Dams Authority was established by an Act of the Parliament. The Authority was responsible for the construction and maintenance of Dams and other works on the river Niger and elsewhere, generating electricity by means of water, improving navigation and promoting fisheries and irrigation (www.enugudisco.com/index.php/, 2012).
The Electricity Corporation of Nigeria (ECN) and the Niger Dams Authority (NDA) were merged to become National Electric Power Authority (NEPA) by decree No.24 of 1972. The Authority was to develop and maintain an efficient, co-ordinate an economic system of electricity supply for all parts of the Federation. (www.enugudisco.com/index.php/, 2012).The Authority generates electricity through two major sources: Hydro and Thermal. The Hydro Power stations are Kainji Hydro Power station with an installed capacity of (760MW), Jebba Hydro Power station with an installed capacity of (570MW), Shiroro Hydro Power Station with an installed capacity of (600MW) while the thermal Power stations includes Afam Thermal Power with of (977MW), Egbin thermal power station with an installed capacity of (1320MW), Delta IV thermal Power station with an installed capacity of (972MW) and Sapele Thermal Power station with an installed capacity of (1020MW).
However, the need to reform the Electricity industry necessitated the transformation of NEPA into Power Holding Company of Nigeria (PHCN) in 2004 (NEPA Mandate). (National Electric Power Authority). The Electricity Reform Act of 2005, unbundled PHCN into 11 Distribution companies, 1Transmission Company and 6 Generation companies (www.Power_Holding_Company_of_Nigeria). The unbundle led to the current division of PHCN distribution sector into separate companies referred to as Local Electric Distribution Companies. There exist the following: Abuja Distribution Company, Benin Distribution Company, Eko Distribution Company, Enugu Distribution Company, Ibadan Distribution Company, Ikeja Distribution Company, Jos Distribution Company, Kaduna Distribution Company, Kano Distribution Company, Port Harcourt Distribution Company and Yola Distribution Company. Also, the generation arm includes; Afam Power Station in Rivers State, Egbin Power Station in Lagos State, Sapele Power Station in Delta State, Ughelli Power Station in Delta State, Alaoji Power Station in Abia State, Geregu Power Station in Kogi State, Ibom Power Station in Akwa Ibom State, Ihovbor Power Station in Edo State, Opkai Power Station in Delta State, Olorunsogo Power Station in Oyo State, Omoku Power Station in Rivers State, Omotosho Power Station in Ondo State, Kainji Hydro-Electric Power in Niger State, Shiroro Hydro –Electric Power in Niger State and Jebba Hydro-Electric Power in Niger State.(www.power.ng, 2016).
Transmission Company of Nigeria (TCN) remains nationalized. The Nigerian Electricity Distribution Companies are separate and distinct entities from the Power Holding Company of Nigeria (PHCN). PHCN was actually unbundled into eighteen (18) distinct companies of which eleven (11) are electricity distribution companies which is the bone of contention in this research while six(6) are generation companies and one (1) is a transmission company (www.power.ng, 2016).
These privatization and reforms has necessitated the need for accurate models of electric power load forecasting for the operation and planning of the Nigerian power system. Also, Power system planning is done to ensure adequate and reliable power supply which now is the ultimate in Nigeria to meet the estimated load demand of 12000MW (www.power.ng, 2016) in near and distance future. More so, electricity usage is no more primarily for house lighting but for other serious services that are very instrumental to economic growth of Nations. Planning therefore is very necessary and must be done at minimum cost possible while maintaining satisfactory and reliable supply. The completion of some Nigeria Independent Power Project (NIPP) that is very eminent amongst the various generation, transmission and distribution will indubitably reposition the power sector in Nigeria in a better service to the Nigerian population. This will also help in meeting the target load demand of 12,800MW in Nigeria Power sector (Obi, 2016) by the year 2020. Effective load shedding amongst transmission substations at all levels across existing power networks during period so far normal peak load demand requires accurate short-term forecasts (Adegoke 2015).
The privatization of generation company (GENCOs) and distribution company (DISCOs) of Nigerian power sector has triggered total structural and organizational changes in the Nigerian power industry (Ugwuanyi, 2015) with the restructuring process taking place at the GENCO’s and DISCO’s level, the power industry is being positioned for better services to the Nigerian populace. This includes a plan to boost system generation capacity to meet the prevailing and forecast demand which will not be effective without economic dispatch model. Amongst these laid down plans, the DISCOs are still running on losses even after 4years of privatization. According to (Ugwuanyi, 2015), the 11 DISCOs across the country are reeling under huge debts, following poor revenue collection emanating from lines losses and the fact that most electricity consumers are willing to use power but never willing to pay (even when metered, they bypass it). These lead to the term that an average Nigerian does not pay his/her electricity bill(s). Although the opposite story is that majority of the consumers are not metered, hence leading to unfair billing methodology (estimation), but the fact still remains that a good number are very prompt in paying their electricity bills. Therefore, it will be a height of injustice for the DISCOs to keep the whole of Nigerians in blackout by rejecting load allocation from TCN just because some are not paying. This load rejection practice of the DISCOs often made the TCN to direct GENCOs to reduce the quantum of electricity generation owing to the fact that generation must balance with utilization to avoid collapse of the system; details are attached in Appendix B. However, this study focuses on efficient and economic power dispatch in Umuahia of Abia State under the catchment area of Enugu Electricity Distribution Company (EEDC).
Table 1.1: EEDC Cash Collection Analysis for 2014
From Table 1.1, it is evident that EEDC recorded significant poor revenue collection.
132KV INPUT VIA ALAOJI
Fig. 1.1: EEDC power distribution network for Umuahia fed via Alaoji 132KV transmission line.
Fig.1.1 shows EEDC power distribution network for Umuahia fed via Alaoji 132KV transmission line. The voltage is stepped down at Ohiya transmission station to 33KV and further distributed to the various EEDC load centers in Umuahia. Ohiya transmission line has two transformers which supplies power to the various substations which are Afara 1 and 2, Ubakala, Nkata-Alike, Umudike and JDP of a step down voltage of 11kv, but directly feds the CBN substation of 33kv, before they are then being distributed to the various feeders as shown in fig 1.1.
1.2 PROBLEM STATEMENT
Due to inadequate generation of electric power, insufficient and unreliable evacuation/transmission of same; dispatch centers and distribution companies find it difficult to optimally dispatch the limited energy particularly to economic viable consumers since the bedrock of every industry is primarily to survive extinction through revenue collection. Therefore, the need to develop an efficient and economic power dispatch tool that will effectively serve economic viable load consumers cannot be over emphasized.
1.3 AIM AND OBJECTIVES
The aim of this research is to determine a dynamic modeling of Umuahia metropolis load demand for efficient power dispatch.
The specific objectives are;
• Collection and evaluation of the daily hourly load data from the respective substations in Umuahia Metropolis.
• Analyzing the collated data.
• Implementation of data employing the measure of Central tendency solution.
• Evaluation and interpretation of the result.
• Development of statistical efficient and economic dispatch model.
1.4 SCOPE OF THE RESEARCH WORK
This thesis involves collection and collation of load data, determination of the load demand pattern using collated load data. Finally recommendation of the best economic dispatch model based on the analytical results determined while considering economically viable areas.
1.5 SIGNIFICANCE OF THE STUDY
The significance of this research shows that the utility company will use the information gotten from this project to economically dispatch the limited power available to Umuahia Metropolis. It will also provide timely information to the load dispatcher to plan and operate the system economically and reliably for the distribution and operation of power system in Umuahia metropolis, hence improving the economic social life of the entire inhabitants.
1.6 OUTLINE OF THE STUDY
Chapter one showcases the introduction and the general overview of the distribution company (EEDC) with the power distribution network of Umuahia Metropolis.
Chapter two x-rays the literature review, the related works, overview of economic load dispatch, load dispatch center, load shedding, load demand analysis and classification of loads.
Chapter three houses the methodology adopted, research design, statistical method employed, average hourly load demand, mode of data, data overall view, computer tools used, economic load dispatch model and the flowchart for the proposed economic dispatch model.
The results, discussions, graphical presentations of result, total average load demand for Umuahia metropolis presented in tabular and graphical format and economic load dispatch model results are found in chapter four.
Chapter five shows the conclusion and recommendation.
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