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H ∞ Filter‐Based Short‐Term Electric Load Prediction Considering Characteristics of Load Curve
Author(s) -
Namerikawa Toru,
Hosoda Yasuhiko
Publication year - 2014
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.11558
Subject(s) - term (time) , filter (signal processing) , electrical load , control theory (sociology) , computer science , engineering , artificial intelligence , voltage , physics , control (management) , quantum mechanics , electrical engineering , computer vision
SUMMARY This paper deals with H ∞ filter‐based short‐term electric load prediction taking into consideration the characteristics of the load curve. We propose a predictive method to forecast the future electric load demand for 36 h from 12:00 PM, and evaluate the peak and bottom of the load curves on the next day. We propose a load model, estimate the unknown parameters of the model by means of an H ∞ filter using the data separated for nonworking days and weekdays, with the same pattern of the previous data chosen and assigned to the model parameters. The simulation results show the effectiveness of the proposed prediction methodology.