Estimation and Forecasting of Nigeria’s Residential, Commercial, and Industrial Electricity Demands
Energy demand forecasting has emerged as a crucial area of research, driven by the need for accurate predictions of future electricity consumption. This is critically essential for the effective planning and operation of electric power systems. Several studies have only forecasted what could be best...
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2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/11053813/ |
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| author | Prosper O. Ugbehe Ogheneruona E. Diemuodeke Daniel O. Aikhuele Kenneth E. Okedu Gauri Kalnoor |
| author_facet | Prosper O. Ugbehe Ogheneruona E. Diemuodeke Daniel O. Aikhuele Kenneth E. Okedu Gauri Kalnoor |
| author_sort | Prosper O. Ugbehe |
| collection | DOAJ |
| description | Energy demand forecasting has emerged as a crucial area of research, driven by the need for accurate predictions of future electricity consumption. This is critically essential for the effective planning and operation of electric power systems. Several studies have only forecasted what could be best termed as ‘suppressed electricity demand’ in Nigeria, given the non-consideration of basic unmet demand factors. Suppressed electric energy demand arises from inadequate energy access accounting for unmet electricity needs such as electricity capacity utilization, access rate, outages, and transmission and distribution (T&D) losses. These unmet electricity needs are considered sensitive determinants in achieving optimal planning and utilization of electricity in a developing economy like Nigeria. This study, therefore investigated and estimated these unmet basic electricity needs in deriving a potential electricity consumption and typical demand forecast for Nigeria in consideration of sustainability and full capacity utilization. It aimed at forecasting Nigeria’s potential electricity demand by analyzing the various electricity usage patterns in the country. It presented a methodological approach for estimating and forecasting the expected electricity demand in the nation by developing and examining economic and environmentally sustainable models with the incorporation of unmet electricity needs. These needs were analyzed using the developed models and sourced data to obtain advanced estimates of electricity consumption. A high-precision, long-term forecasting procedure was then implemented using these estimates. The implementation and simulation of the procedure was conducted with a Machine Learning/AI procedure (using Python) compatible with the Google Collaboratory tool. The obtained results were post processed using MS Excel. The results indicated that Nigeria’s potential electricity demand will be 69783.099, 80383.785 and 90984.472 GWh by 2030, 2040 and 2050, respectively. The forecast results were further validated with those obtained using stochastic/probabilistic extrapolation method. While the Python simulation indicated a lower average Mean Square Error (MSE) of 0.008%, the stochastic/probabilistic extrapolation procedure gave an MSE of 0.021%. With the forecasting results, decision-makers and policy-makers in Nigeria’s energy sector are armed with the right tool for effective and informed decision-making in electricity planning and management. The approach of this study to solving the national energy challenge is timely and aims to help navigate the complex challenges of making informed decisions in the sector, and establish future research avenues that may facilitate the effective integration of renewable energy into the national energy landscape. |
| format | Article |
| id | doaj-art-207741bd646643d583d099ebdb8e84d1 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-207741bd646643d583d099ebdb8e84d12025-08-20T03:29:06ZengIEEEIEEE Access2169-35362025-01-011311208111210110.1109/ACCESS.2025.358262511053813Estimation and Forecasting of Nigeria’s Residential, Commercial, and Industrial Electricity DemandsProsper O. Ugbehe0https://orcid.org/0000-0003-3686-9552Ogheneruona E. Diemuodeke1https://orcid.org/0000-0002-0133-485XDaniel O. Aikhuele2Kenneth E. Okedu3https://orcid.org/0000-0002-9635-1029Gauri Kalnoor4https://orcid.org/0000-0001-9970-4697Department of Mechanical Engineering, Energy and Thermofluids Research Group, Faculty of Engineering, University of Port Harcourt, Port Harcourt, NigeriaDepartment of Mechanical Engineering, Energy and Thermofluids Research Group, Faculty of Engineering, University of Port Harcourt, Port Harcourt, NigeriaDepartment of Mechanical Engineering, Energy and Thermofluids Research Group, Faculty of Engineering, University of Port Harcourt, Port Harcourt, NigeriaSchool of Information and Engineering, Melbourne Institute of Technology, Melbourne, VIC, AustraliaDepartment of CSE, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, IndiaEnergy demand forecasting has emerged as a crucial area of research, driven by the need for accurate predictions of future electricity consumption. This is critically essential for the effective planning and operation of electric power systems. Several studies have only forecasted what could be best termed as ‘suppressed electricity demand’ in Nigeria, given the non-consideration of basic unmet demand factors. Suppressed electric energy demand arises from inadequate energy access accounting for unmet electricity needs such as electricity capacity utilization, access rate, outages, and transmission and distribution (T&D) losses. These unmet electricity needs are considered sensitive determinants in achieving optimal planning and utilization of electricity in a developing economy like Nigeria. This study, therefore investigated and estimated these unmet basic electricity needs in deriving a potential electricity consumption and typical demand forecast for Nigeria in consideration of sustainability and full capacity utilization. It aimed at forecasting Nigeria’s potential electricity demand by analyzing the various electricity usage patterns in the country. It presented a methodological approach for estimating and forecasting the expected electricity demand in the nation by developing and examining economic and environmentally sustainable models with the incorporation of unmet electricity needs. These needs were analyzed using the developed models and sourced data to obtain advanced estimates of electricity consumption. A high-precision, long-term forecasting procedure was then implemented using these estimates. The implementation and simulation of the procedure was conducted with a Machine Learning/AI procedure (using Python) compatible with the Google Collaboratory tool. The obtained results were post processed using MS Excel. The results indicated that Nigeria’s potential electricity demand will be 69783.099, 80383.785 and 90984.472 GWh by 2030, 2040 and 2050, respectively. The forecast results were further validated with those obtained using stochastic/probabilistic extrapolation method. While the Python simulation indicated a lower average Mean Square Error (MSE) of 0.008%, the stochastic/probabilistic extrapolation procedure gave an MSE of 0.021%. With the forecasting results, decision-makers and policy-makers in Nigeria’s energy sector are armed with the right tool for effective and informed decision-making in electricity planning and management. The approach of this study to solving the national energy challenge is timely and aims to help navigate the complex challenges of making informed decisions in the sector, and establish future research avenues that may facilitate the effective integration of renewable energy into the national energy landscape.https://ieeexplore.ieee.org/document/11053813/Electricity demandelectricity forecastpotential electricity demandsustainabilityunmet electricity needs |
| spellingShingle | Prosper O. Ugbehe Ogheneruona E. Diemuodeke Daniel O. Aikhuele Kenneth E. Okedu Gauri Kalnoor Estimation and Forecasting of Nigeria’s Residential, Commercial, and Industrial Electricity Demands IEEE Access Electricity demand electricity forecast potential electricity demand sustainability unmet electricity needs |
| title | Estimation and Forecasting of Nigeria’s Residential, Commercial, and Industrial Electricity Demands |
| title_full | Estimation and Forecasting of Nigeria’s Residential, Commercial, and Industrial Electricity Demands |
| title_fullStr | Estimation and Forecasting of Nigeria’s Residential, Commercial, and Industrial Electricity Demands |
| title_full_unstemmed | Estimation and Forecasting of Nigeria’s Residential, Commercial, and Industrial Electricity Demands |
| title_short | Estimation and Forecasting of Nigeria’s Residential, Commercial, and Industrial Electricity Demands |
| title_sort | estimation and forecasting of nigeria x2019 s residential commercial and industrial electricity demands |
| topic | Electricity demand electricity forecast potential electricity demand sustainability unmet electricity needs |
| url | https://ieeexplore.ieee.org/document/11053813/ |
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