Abstract
Electricity authorities in the UAE have not been successful in developing reliable and accurate models of system peak load. In this study, we develop a time-series-based decision-support system that integrates data management, model base management, simulation, graphic display, and statistical analysis to provide near-optimal forecasting models. The model base includes a variety of time-series techniques, such as exponential smoothing, Box-Jenkins (BJ), and dynamic regression. The system produces short-term forecasts (one year ahead) by analyzing the behavior of monthly peak loads. The performance of the DSS is validated through a comparison with results suggested by econometricians.
| Original language | English |
|---|---|
| Pages (from-to) | 579-589 |
| Number of pages | 11 |
| Journal | Energy |
| Volume | 22 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 1997 |
ASJC Scopus subject areas
- Civil and Structural Engineering
- Modelling and Simulation
- Renewable Energy, Sustainability and the Environment
- Building and Construction
- Fuel Technology
- Energy Engineering and Power Technology
- Pollution
- Mechanical Engineering
- General Energy
- Management, Monitoring, Policy and Law
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering