EDSSF: Decision Support System (DSS) for Electricity Peak-Load Forecasting

Authors

Masood A. Badri, United Arab Emirates UniversityFollow
Ahmed Al-Mutawa, United Arab Emirates University
Donald Davis, University of Southern MississippiFollow
Donna Davis, University of Southern MississippiFollow

Document Type

Article

Publication Date

6-1-1997

Department

Management and International Business

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. (C) 1997 Elsevier Science Ltd.

Publication Title

Energy

Volume

22

Issue

6

First Page

579

Last Page

589

Recommended Citation

Badri, M. A., Al-Mutawa, A., Davis, D., Davis, D. (1997). EDSSF: Decision Support System (DSS) for Electricity Peak-Load Forecasting. Energy, 22(6), 579-589.
Available at: https://aquila.usm.edu/fac_pubs/5277