Empowering Tomorrow: Innovative Forecasting for UAE's Electricity Consumption

10.6186/IJIMS.202403_35(1).0001

Amitabh Verma

Non-Homogeneous Discrete Grey Modelling ； Electricity ； Forecasting ； Mean absolute percentage error ； Relative growth rate

International Journal of Information and Management Sciences

35卷1期（2024 / 03 / 01）

1 - 19

英文

In the dynamic landscape of the United Arab Emirates (UAE) electrical sector, accurately predicting long-term trends is paramount for sustainable energy planning. Owing to the consistently elevated temperatures experienced in the Gulf region during the summer months, there is a notable surge in demand for electricity in the UAE, leading to an increased energy consumption per capita. This heightened demand during the summer renders the power system particularly susceptible, posing a substantial risk of power outages, production shortfalls, and a subsequent escalation. This study delves into the realm of forecasting using Non-Homogeneous Discrete Grey Modeling (NDGM), a cutting-edge approach tailored to the unique challenges of the UAE's electrical domain. By leveraging NDGM, this research aims to provide a robust framework for anticipating electrical trends over an extended period. Precise load demand forecasting would impact energy-generating capacity scheduling and power grid management. The results promise valuable insights for policymakers, industry stakeholders, and energy planners, facilitating informed decision-making to meet the ever-evolving demands of the UAE's power sector. The findings of this study were unique in that it avoids increasing generation capacity in mid- and long-term plans, which will assist in avoiding load shedding and meeting energy demands in various sectors.