Title :
Short-term electricity price forecasting using a fuzzy stochastic predictor
Author :
Sheikh-El-Eslami, Mohammad Kazem ; Seifi, Hossein
Author_Institution :
Dept. of Electr. Eng., Tarbiat Modares Univ., Tehran
Abstract :
In the competition paradigm of the electric power markets, both power producers and consumers need some price prediction tools in order to plan their bidding strategies. This paper presents a fuzzy stochastic prediction method for short-term price forecasting in pool-based power markets. The method employs a fuzzy linguistic summary approach in its parameter calculation, which can eliminate outliers and limit the data to a normal condition for prediction. Finally, results from real-world case studies based on the NEPool and NordPool markets are presented
Keywords :
fuzzy set theory; load forecasting; power markets; pricing; stochastic processes; bidding strategies; electric power markets; fuzzy linguistic summary approach; fuzzy stochastic prediction method; outlier elimination; parameter calculation; pool-based power markets; price prediction tools; short-term electricity price forecasting; Accuracy; Artificial intelligence; Artificial neural networks; Contracts; Economic forecasting; Fuzzy logic; Helium; Power markets; Predictive models; Stochastic processes; electricity market; fuzzy theory; price forecasting; stochastic prediction;
Conference_Titel :
Power Engineering Society General Meeting, 2006. IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0493-2
DOI :
10.1109/PES.2006.1709049