doi: 10.7763/IJET.2010.V2.106
A Computing Model of Artificial Intelligent Approaches to Mid-term Load Forecasting: a state-of-the-art- survey for the researcher
Pituk Bunnoon
,
Kusumal Chalermyanont
,
Chusak Limsakul
- Department of Electrical Engineering, Prince of Songkla University, Thailand
Abstract
This article presents the review of the computing models applied for solving problems of mid-term load forecasting. The load forecasting results can be used in electricity generation such as energy reservation and maintenance scheduling. Principle, strategy and results of short term, midterm, and long term load forecasting using statistic methods and artificial intelligence technology (AI) are summaried, Which, comparison between each method and the articles have difference feature input and strategy. The last, will get the idea or literature review conclusion to solve the problem of mid term load forecasting (MTLF).
Keywords
- Artificial Intelligent
- Mid-term load
- Forecasting
- state-of-the-arts
How to Cite
Pituk Bunnoon, Kusumal Chalermyanont, and Chusak Limsakul, "A Computing Model of Artificial Intelligent Approaches to Mid-term Load Forecasting: a state-of-the-art- survey for the researcher," International Journal of Engineering and Technology, vol. 2, no. 1, pp. 94-100, 2010. https://doi.org/ 10.7763/IJET.2010.V2.106
Copyright & License
Copyright © 2010 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).