A New Approach in Short-Term Prediction of the Electrical Charge with Regression Models A Case Study

Farhad Soleimanian Gharehchopoghi, Freshte Dabaghchi Mokri and Maryam Molany
Additional contact information
Farhad Soleimanian Gharehchopoghi: Computer Engineering Department, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran
Freshte Dabaghchi Mokri: Computer Engineering Department, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran
Maryam Molany: Computer Engineering Department, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran

International Journal of Applied Metaheuristic Computing (IJAMC), 2013, vol. 4, issue 3, 34-46

Abstract: The accuracy of forecasting of electrical load for the electricity industry has a vital significance in the renewal of economic structure as well as various equations including: purchasing and producing energy, load fluctuation, and the development of infrastructures. Its short-term forecasting has a significant role in designing and utilizing power systems and in the distribution systems and having a variety of systems used to maintain security potentials for the system. In this paper, we attempted to carry out a short-term forecasting of electrical distribution company in west Azerbaijan state in Iran's electricity in a few days on the basis of regression multi linear model. This forecasting which was done during a three-day period is and categorized weekdays into three groups including working days, weekends, and holidays was carried out in an hourly manner. This model regardless of parameters like humidity, wind velocity, daylight time, etc. by minimizing the forecasting error managed to maximize the reliability of the results as well as the safety potential of the system. In this model the only influential parameter on the forecasting was the reliance of the forecasting day on previous days. The main purpose of the present study was to maximize the accuracy and reliability of forecasting for certain days (religious holidays, national holidays …). In this paper, the authors managed to decrease the error of forecasting for particular and regular off days to a great extent.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/ijamc.2013070103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jamc00:v:4:y:2013:i:3:p:34-46

Access Statistics for this article

International Journal of Applied Metaheuristic Computing (IJAMC) is currently edited by Peng-Yeng Yin

More articles in International Journal of Applied Metaheuristic Computing (IJAMC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().