Electrical Energy Consumption Forecasting Analysis Based on Conventional and Artificial Intelligence Methods: A Comparison

Authors

Aziza I. HusseinFollow

Abstract

Artificial intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review the classical techniques and the emerging new techniques based on AI of the building electrical energy consumption forecasting. The advantages of AI-based techniques over the classical are that AI methods can handle a large amount of data yet gives accurate results, the results can be found very quickly, in addition to AI having the ability to solve complex nonlinear patterns of raw data. This paper will discuss several studies using different models of forecasting based on AI and compare them. It will also discuss several studies using different models of forecasting based on AI and compare between them, coming up with the conclusion that the model that achieved the lowest MAPE is ANN with 0.928\%.

Recommended Citation

Hussein, Aziza I. (2022) "Electrical Energy Consumption Forecasting Analysis Based on Conventional and Artificial Intelligence Methods: A Comparison," Effat Undergraduate Research Journal: Vol. 3: Iss. 1, Article 5.
Available at: https://digitalcommons.aaru.edu.jo/eurj/vol3/iss1/5