Publisher of Iranian Journals and Conference Proceedings

Please waite ..
Publisher of Iranian Journals and Conference Proceedings
Login |Register |Help |عضویت کتابخانه ها
Paper
Title

Modeling and forecasting short-term electricity load:A comparison of methods with an application to West Azarbaijan data

Year: 1388
COI: PSC24_033
Language: EnglishView: 1,369
This Paper With 11 Page And PDF Format Ready To Download

Buy and Download

با استفاده از پرداخت اینترنتی بسیار سریع و ساده می توانید اصل این Paper را که دارای 11 صفحه است به صورت فایل PDF در اختیار داشته باشید.
آدرس ایمیل خود را در کادر زیر وارد نمایید:

Authors

Morteza Rahimbasiri - Department of Electrical Engineering, Islamic Azad University of science and Research Branch
Mohammad Bagher Menhaj - Department of Electrical Eng., Amirkabir University of Technology
Ashkan Rahimi Kian - Control and Intelligent Processing Center of Excellence, School of Electrical and ComputerEng., University of TehranTehran, Iran

Abstract:

To improve the short term load forecasting methods, at first the successfull ones must be compared and evaluated. The goal of this paper is to compare some methods, which are applied successfully to daily load forecasting (DLF), for the hourly electricity load in the area covered by an electric utility of West Azarbaijan State (WAS) located in the northwest of Iran. The proposed input variables selection algorithms are based on mutual information (MI), Gamma test and correlation analysis for neuro-fuzzy modeling, with locally linear model tree (LOLIMOT) learning algorithm. Then the results are compared with our previous paper on WAS power system (WASPS) to get the final conclusion. The performance of each method is evaluated over the low, medium and peak loads of WASPS during the summer week from August 25 to September 1, 2008. The simulation results show that model dependent input selection methods can be better than the model independent ones for several hours ahead forecasting. Also, for each load group the corresponding suitable forecasting method is suggested.

Keywords:

Paper COI Code

This Paper COI Code is PSC24_033. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/89206/

How to Cite to This Paper:

If you want to refer to this Paper in your research work, you can simply use the following phrase in the resources section:
Rahimbasiri, Morteza and Menhaj, Mohammad Bagher and Rahimi Kian, Ashkan,1388,Modeling and forecasting short-term electricity load:A comparison of methods with an application to West Azarbaijan data,24nd International Power System Conference,Tehran,https://civilica.com/doc/89206

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :

  • Raul Pino, Jose Parreno, Alberto Gomez, Paolo Priore, "Forecasting next-day ...
  • Thomas Trappenberg, Jie Ouyang, and Andrew Back, Input Variable Selection: ...
  • Khazaee Parviz, Mozayani Nasser, and M.R. Jahed Motlagh, Mutual Information ...
  • Vahabei, A.H., Rezaei Yousefi, M.M., Araabi, B.N., Barghinia, S., Ansarimehr, ...
  • Conference on control and Automation, Guangzhou, China, May 30-June 1 ...
  • Rezaei Yousefi, M.M., Mirmomeni, M., Lucas, C.: Input Variables Selection ...
  • Comparison of all the proposed methods As can be Seen ...
  • A. G. Bakirtzis, J. B. Theocharis, S. J. Kiatzis, and ...
  • identification, Springer Verlag, Berlin, 2001. ...
  • The Math Works, MATLAB. Available website: ...
  • Zhang Yun, Zhou Quan, Sun Caixin, Lei Shaolan, Liu Yuming, ...
  • International Multitopic Conference 2009 Pakistan, ...
  • (INMIC -2009) , Islamabad, December 2009. ...
  • Lacir J. Soares, Marcelo C. Medeiros, short-term ...
  • electricity load: A comparison of methods with _ application to ...
  • Modeling with the Application to Time Series Forecasting. In: Proceedings ...
  • Chemometris and Intelligent Laboratory Systems 80 (2006) 215 - 226. ...
  • Modelling & Software 23 (2008) 1289-1299 [8] N. Reyhani, J. ...
  • Modeling with the Application to Time Series Forecasting. In: Proceedings ...
  • networks, " Journal of Electric Power Systems Research 78 (2008) ...
  • Neuroc omputing 71 (2008) 2604- 2615. ...
  • A. Papoulis, and S. U. Pillai, Probability Random Variables and ...

Research Info Management

Certificate | Report | من نویسنده این مقاله هستم

اطلاعات استنادی این Paper را به نرم افزارهای مدیریت اطلاعات علمی و استنادی ارسال نمایید و در تحقیقات خود از آن استفاده نمایید.

New Papers

New Researchs

Share this page

More information about COI

COI stands for "CIVILICA Object Identifier". COI is the unique code assigned to articles of Iranian conferences and journals when indexing on the CIVILICA citation database.

The COI is the national code of documents indexed in CIVILICA and is a unique and permanent code. it can always be cited and tracked and assumed as registration confirmation ID.

Support