Predicting electrical loads is critical since it requires the preparation of work schedules for main and minor transformer maintenance operations. This study aims to estimate the maximum evening electricity loads in Jordan in order to plan preventive maintenance. Because the data contains two sorts of patterns, trend and seasonal, methods that address both of these patterns must be applied. Long-term maximum peak forecasting for the next five years from 2022 to 2027 is performed by utilizing a weighted combination of two methods: Feed Forward Back Propagation Neural Network and Holt-Winters. The Seasonal Autoregressive Integrated Moving Average method is also used and found of less accuracy than the two other models. A near-optimal weighted combination of the Neural Network Model and Holt-Winter is then obtained by using a non-linear optimization local search heuristic model. The new model results are of high accuracy that the value of R2 was increased from 70.2 % for the Neural Network Model and 82.4 % for the Holt-Winters method to 84.3 % in the weighted combination between them. Moreover, the value of Mean Absolute Error was decreased to from 134 and 188 for the Holt-Winter and Neural Network models respectively to become 117.98. Upon the results, recommendations are provided to the decision-makers.
|Title of host publication||Proceedings of 3rd International Conference on Intelligent Engineering and Management, ICIEM 2022|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - 2022|
|Name||Proceedings of 3rd International Conference on Intelligent Engineering and Management, ICIEM 2022|
Bibliographical noteFunding Information:
This research was supported by the Jordanian Energy And Mineral Regulatory Commission and the Interdisciplinary Research Center of Smart Mobility & Logistics.
© 2022 IEEE.
- Maximum Peak Load Forecasting
- Weighted Forecasting Model
ASJC Scopus subject areas
- Management of Technology and Innovation
- Artificial Intelligence
- Computer Science Applications
- Information Systems and Management
- Engineering (miscellaneous)
- Health Informatics