Forecasting UAE Electricity Consumption by Sector Using the NDGM Model, Based on Data from 2012 to 2021

This work advances the efficiency of electricity demand forecasting in the United Arab Emirates (UAE) by utilizing the Non-Homogeneous Discrete Grey Model (NDGM) to predict electricity consumption from 2022 to 2040, with a focus on analyzing different sectors, filling up research gaps in this area. Based on historical data from 2012 to 2021, our model achieves a Mean Absolute Percentage Error (MAPE) of approximately 0.15%, indicating high accuracy. This makes our results more useful for energy planners and policymakers who want to make sure that supply matches demand and avoid overinvestment or load shedding. We also examine electricity use from a sector-specific perspective; a viewpoint that hasn’t been explored in previous research. Furthermore, our analysis uses data from sources that are specific to the UAE, like the Department of Energy in Abu Dhabi, DEWA, SEWA, and FEWA. The analysis includes sector-wise consumption for 2021, Relative Growth Rate (RGR), and Doubling Time (Dt) metrics. Results show future steady demand growth, with commercial and residential sectors dominating. These insights support sustainable energy planning and highlight the need for efficiency measures in high-consumption sectors. We offer some recommendations specific to the UAE that explain our empirical results and help policymakers of the country in making appropriate decisions about the future desired electricity supply.

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Publication Details

Journal
International Journal of Energy Economics and Policy
Published
2025-10-12
DOI
https://doi.org/10.32479/ijeep.21107
Primary Topic
Energy Load and Power Forecasting
Type
article
Field-Weighted Citation Impact
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article

Forecasting UAE Electricity Consumption by Sector Using the NDGM Model, Based on Data from 2012 to 2021

Salah Abosedra, Abdulkarim Ali Dahan, Munshi Naser Ibne Afzal
International Journal of Energy Economics and Policy
Energy Load and Power Forecasting
article

Forecasting UAE Electricity Consumption by Sector Using the NDGM Model, Based on Data from 2012 to 2021

Salah Abosedra, Abdulkarim Ali Dahan, Munshi Naser Ibne Afzal
article en

Abstract

This work advances the efficiency of electricity demand forecasting in the United Arab Emirates (UAE) by utilizing the Non-Homogeneous Discrete Grey Model (NDGM) to predict electricity consumption from 2022 to 2040, with a focus on analyzing different sectors, filling up research gaps in this area. Based on historical data from 2012 to 2021, our model achieves a Mean Absolute Percentage Error (MAPE) of approximately 0.15%, indicating high accuracy. This makes our results more useful for energy planners and policymakers who want to make sure that supply matches demand and avoid overinvestment or load shedding. We also examine electricity use from a sector-specific perspective; a viewpoint that hasn’t been explored in previous research. Furthermore, our analysis uses data from sources that are specific to the UAE, like the Department of Energy in Abu Dhabi, DEWA, SEWA, and FEWA. The analysis includes sector-wise consumption for 2021, Relative Growth Rate (RGR), and Doubling Time (Dt) metrics. Results show future steady demand growth, with commercial and residential sectors dominating. These insights support sustainable energy planning and highlight the need for efficiency measures in high-consumption sectors. We offer some recommendations specific to the UAE that explain our empirical results and help policymakers of the country in making appropriate decisions about the future desired electricity supply.

International Journal of Energy Economics and PolicyVol. 15(6)
Hamdan Bin Mohammed Smart University (AE), Libyan International Medical University (LY), American University in the Emirates (AE)
Openalex Percentile: Top 72%
Energy Load and Power Forecasting
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