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Kısa Dönem Yük Tahmini için Mevsimsel ve Çok Değişkenli Gri Tahmin Modellerinin Uygulanması

Application of Seasonal and Multivariable Grey Prediction Models for Short-Term Load Forecasting

Journal Name:

  • Alphanumeric Journal

Publication Year:

  • 2017
DOI: 
10.17093/alphanumeric.359942

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
Short-term electricity load forecasting is one of the most important operations in electricity markets. The success in the operations of electricity market participants partially depends on the accuracy of load forecasts. In this paper, three grey prediction models, which are seasonal grey model (SGM), multivariable grey model (GM (1,N)) and genetic algorithm based multivariable grey model (GAGM (1,N)), are proposed for short-term load forecasting problem in day-ahead market. The effectiveness of these models is illustrated with two real-world data sets. Numerical results show that the genetic algorithm based multivariable grey model (GAGM (1,N)) is the most efficient grey forecasting model through its better forecast accuracy.
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Abstract (Original Language): 
Kısa dönem elektrik yükü tahmini, elektrik piyasasında en önemli operasyonlardan biridir. Elektrik piyasasındaki işletmelerin operasyonlarındaki başarı, yük tahminlerinin doğruluğuna bağlıdır. Bu çalışmada, gün öncesi piyasasında kısa döneli yük tahmini problemi için mevsimsel gri model (SGM), çok değişkenli gri model (GM (1,N)) ve genetik algoritma esaslı gri model olmak üzere üç gri tahmin modeli önerilmiştir. Bu modellerin etkinliği, iki gerçek hayat veri kümesi ile gösterilmiştir. Sayısal sonuçlar, genetik algoritma esaslı gri modeli daha iyi tahmin doğruluğu sağlayarak en etkin gri tahmin modeli olduğunu göstermektedir.
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Özcan Application of Seasonal and Multivariable Grey Prediction Models for Short-Term Load Forecasting 338
Alphanumeric Journal
Volume 5, Issue 2, 2017
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