ABSTRACT
In Nigeria, there is a problem of inadequate electricity supply to the populace. A recognized reason for the energy poverty in the country is the poor handling of the electricity statistics provided by the National Electricity Regulatory Commission (Ajayi, 2006). Absence of good forecast is a dominant reason for the NERC‘s inability to manage the supply chain of electricity or carry out effective electricity demand and production planning. In this project, specific data has been obtained on electricity production (in kWh), electricity consumption (in kWh), electricity consumption per capita (in kWh), electricity transmission losses (in kWh) and percentage electricity transmission losses from the statistical bulletin of the National Bureau of Statistics between the year 1991 and 2011. This data reflects electricity demand and consumption pattern over the last two decades to help carry out a time-series analysis of the data and plot a time-series graph of the data to show the pattern of electricity demand and consumption using the Data Analysis Package, Time Series Modeller and Sequence Chart Analyser of the IBM SPSS 21 application. A Time series forecast of the data obtained was done using the Auto Regressive Integrated Moving Average model. The forecast predicted that if electricity consumption per capita remains static and unchanged at 145.146 kW per person per annum, the annual electricity consumption in 2016 will stand at 30.319 billion KWh thereby surpassing the total amount of electricity produced, 30.251 billion KWh if all other parameters that affect the production and consumption such as the amount of electricity lost in transmission continues in the same pattern as predicted by the model. Therefore the percentage of Nigerians that have access to electricity supply will also reduce from 48% in 2011 to about 41.83% in 2016. Error tests were carried out to ascertain the efficiency of the forecast and the model used. Forecasts are deemed to be accurate and authoritative enough if the MAPE value is below 10 and a forecast whose MAPE is between 1 and 5 is considered authoritative and accurate (Bozarth, 2011). The forecast was able to achieve a MAPE of 1.207 for the forecasts below the 10th Percentile of all forecasts and a MAPE of 1.714 for the forecasts between the 10th and 25th Percentile of all forecasts, which is the forecast between 2012 and 2017. This value increased to 25.037 as the model generated more forecasts. The results obtained by this forecast is further validated by the actual 2013 value of average annual electricity production which stands at 29.166 billion kWh according to (Nnodim, 2013), a 2.89% error difference from the forecasted 28.321 billion kWh. Hence, the forecasts between 2012 and 2017 are relatively accurate and authoritative.
TABLE OF CONTENTS
Title Page ii Declaration iii Certification iv Dedication v Acknowledgement vi Abstract vii Table of Content viii List of Tables xi List of Figures xii
1.0 INTRODUCTION 1
1.1 Background to the Study 1
1.2 Statement of Problem 2
1.3 The present Research 2
1.4 Aims of the Project 2
1.5 Objectives of the Project 3
1.6 Scope of the Project 3
1.7 Significance of the Study 3
1.8 Contribution to Knowledge 3
2.0 LITERATURE REVIEW 4
2.1 Electricity Demand in Nigeria 4
2.1.1 Sources and methods of compiling electricity supply and demand statistics
in Nigeria 5
2.1.2 Statistics involving electricity demand 6
2.2 Electrical Energy Review in Nigeria since 1960 7
2.2.1 Sources of energy 9
2.2.2 Relationship between energy consumption and standard of living 19
2.3 Statistical Forecasting Techniques 21
2.3.1 Forecast methods 21
2.3.2 Types of ARIMA Model 23
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2.3.3 Measurement of forecasting accuracy 24
2.3.4 Types of statistical data analysis tools 27 2.4 Data Forecasting: Importance and Its Application in the Energy Industry 32 3.0 MATERIALS AND METHODS 33 3.1 Research statement and research questions 33
3.2 Materials used 33
3.3 Data Collection and Gathering Techniques 33
3.4 Data Processing, Analysis and Forecasting Methods to be used 34 4.0 DATA PRESENTATION 35 4.1 Data presentation 35 4.1.1 Electricity production 37 4.1.2 Electricity consumption 38 4.1.3 Electricity consumption per capita 38 4.1.4 Electricity transmission losses 39
4.1.5 Percentage electricity transmission losses 40
4.2 Forecast 40
4.2.1 Model used for the forecast 43
4.2.2 Discussion and analysis based on the forecast 47 4.2.3 Accuracy of the forecast, error calculations and reliability of the forecast Model 48 5.0 CONCLUSION AND RECOMMENDATION 51 5.1 Conclusion 51 5.2 Recommendation 52
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References 53
CHAPTER ONE
INTRODUCTION
1.1 Background To The Study
The Nigerian power sector is known to not cater for the apparent demand of electrical energy by the country‘s teeming population of approximately 200 million according to the Nigerian Bureau of Statistics 2013 estimate. According to the United States Energy Information Administration (EIA), Nigeria has one of the lowest net electricity generation per capita rates in the world. Electricity generation falls short of demand, resulting in load shedding, blackouts, and a reliance on private generators. Demand has consistently outweighed the supply of electricity by the nation‘s eleven recognised power generation companies under the recent privatisation scheme. Electricity is an essential ingredient for socio-economic development and economic growth. The objective of the power sector is to provide energy services. Energy is central to sustainable development and poverty reduction efforts (Sambo, 2005). It affects all aspects of development-social, economic, and environmental-including livelihoods, access to water, agricultural productivity, health, population levels, education, and gender related issues.
As the very basis of development, energy use is closely related to the level of productivity in the industry, commerce, agriculture and even in office activities. Energy consumption per capita is one of the indicators or benchmarks for measuring the standard of living of a people or nation (Sambo, 2005). Hence, as long as energy supply cannot meet the energy demand of the people, there will be little hopes of achieving enviable national development and even improving the standard of living of the Nigerian people. The onus lies on the management personnel of the energy regulatory body, National Electricity Regulation Commission, NERC to be able to obtain specific information that denotes the energy demand of the people and be able to collate such information in an easily-understandable format for policy makers and generation companies and other relevant stakeholders. Having obtained the relevant information that shows the numeric energy demand of the nation over a past period of time. Management of the nation‘s energy regulatory body should be also responsible for collation of such information and analyse it to bring out and accentuate any recognisable patterns in the production and consumption of energy by the Nigerian economy. With this information and the recognised pattern, a forecast can be made using up to date statistical analysis and forecast tools and software that will depict the
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expected usage pattern and demand for electrical energy over a given period of time in the short or long term future. With this new information, the management of the nation‘s power sector can also proffer a means of solving and ensuring that the country plans towards meeting the nation‘s energy demands at any time in the future as depicted by the forecast.
1.2 Statement of Problem
The Nigerian energy sector has not been able to provide adequately for the demand of electrical energy by the Nigerian public. In actual fact, there is a problem of lack of ability to coordinate data collection to generate a forecast of the actual energy demand of the various sectors of the Nigerian economy (Okafor and Joe-Uzuegbu, 2010). This research project wishes to achieve a thorough analysis of average statistical data that shows the energy demand of the Nigerian economy and achieve the recognition of a known pattern of energy demand with time and hence generate a forecast for the energy demand and energy statistics for subsequent years.
1.3 The Present Research
This research project aims to therefore give a forecast based on previous data supplied by the NERC on electricity production, consumption and demand estimate of the Nigerian economy from 1990 till 2011. The forecast provides expected energy demand statistics by the country from 2012 to 2028 and creates a time-series of the energy demand statistics by the Nigerian economy from 2012 to 2028. 1.4 Aims of the Project Obtain a statistical time-series forecast of the pattern of energy demand, production and consumption of the Nigerian economy over a specific period of time and therefore predicts the nation‘s electricity statistics thereby creating a platform for effective demand planning.
1.5 Objectives of the Project
1. Carry out a statistical forecast of the energy data of Nigeria between the year 1991 and 2028 (38 years) using an efficient model.
2. Predict based on the forecast obtained, the projected electricity production, consumption and transmission losses and demand estimate of the nation in the short-term future.
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1.6 Scope of the Project
1. Carry out literature review.
2. Survey the demand, production and consumption of energy by the Nigerian economy over the last 21 years.
3. Tabulate the results of the survey.
4. Analyze the results for the survey
5. Using the SPSS ARIMA model, obtain a relationship between the available data and carry out a time-series forecast for the available data.
6. Interpret the information
7. Discuss the results based on the information
8. The results obtained from this forecast or any similar forecast is important information for intending investors in the newly privatized power sector and also for managers involved in policy formulation regarding the power sector especially the energy planning commission as such forecast data will help in demand planning and supply chain management.
1.7 Significance of the Study Management of the nation‘s energy regulatory body should be responsible for collation of electricity information and analyse it to bring out and accentuate any recognisable patterns in the usage and demand of energy by various sectors of the Nigerian economy. With this information and the recognised pattern, a forecast can be made using up to date statistical analysis and forecast tools and software that will depict the expected usage pattern and demand for electrical energy over a given period of time in the short or long term future. With this new information, the management of the nation‘s power sector can also proffer a means of solving and ensuring that the country plans towards meeting the nation‘s energy demands at any time in the future as depicted by this forecast and similar forecasts. 1.8 Contribution to Knowledge This work shows through accurate prediction and forecasting that the ARIMA Time-Series Modeller is a good model generator that is capable of carrying out a thorough analysis and forecast of Nigeria‘s electricity statistics. The work authoritatively predicts the nation‘s electricity statistics thereby creating a platform for effective demand planning.
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