Application of nuSupport Vector Regression in Short-Term Load Forecasting
محل انتشار: بیستمین کنفرانس توزیع برق
سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 857
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شناسه ملی سند علمی:
EPDC20_193
تاریخ نمایه سازی: 1 مهر 1394
چکیده مقاله:
Short-term load forecasting (STLF) of electric power systems plays an essential role in the optimal operation of power systems. Economic performance and reliability of a power system is substantially dependent on the load prediction. STLF is a complex process in electric grid due to having many non-linear factors, such as daily and weekly cyclical changes. Support vector regression has a good ability to estimate non-linear equations. In this paper, a new support vector machine model called nu support vector regression (nu-SVR) is proposed for electrical load forecasting. Results of the proposed method are compared with forecasting results achieved using an artificial neural network (ANN). Results show that the nu-SVR is a proper method for STLF.
کلیدواژه ها:
نویسندگان
Adnan Omidi
Faculty of Electrical and Computer Sistan and Baluchestan University, Zahadan, Iran
S.Masoud Barakati
Faculty of Electrical and Computer Sistan and Baluchestan University, Zahadan, Iran
Saeed Tavakoli
Faculty of Electrical and Computer Sistan and Baluchestan University, Zahadan, Iran