DocumentCode
44845
Title
Evaluating Combined Load Forecasting in Large Power Systems and Smart Grids
Author
Borges, Cruz E. ; Penya, Yoseba K. ; Fernandez, I.
Author_Institution
Deusto Inst. of Technol.-DeustoTech Energy, Univ. of Deusto, Bilbao, Spain
Volume
9
Issue
3
fYear
2013
fDate
Aug. 2013
Firstpage
1570
Lastpage
1577
Abstract
We present here a combined aggregative short-term load forecasting method for smart grids, a novel methodology that allows us to obtain a global prognosis by summing up the forecasts on the compounding individual loads. More accurately, we detail here three new approaches, namely bottom-up aggregation (with and without bias correction), top-down aggregation (with and without bias correction), and regressive aggregation. Further, we have devised an experiment to compare their results, evaluating them with two datasets of real data and showing the feasibility of aggregative forecast combinations for smart grids.
Keywords
load forecasting; smart power grids; aggregative short-term load forecasting method; bottom-up aggregation; global prognosis; power system; regressive aggregation; smart grid; top-down aggregation; Forecasting; Load forecasting; Load modeling; Polynomials; Predictive models; Smart grids; Support vector machines; Demand forecasting; prediction methods;
fLanguage
English
Journal_Title
Industrial Informatics, IEEE Transactions on
Publisher
ieee
ISSN
1551-3203
Type
jour
DOI
10.1109/TII.2012.2219063
Filename
6307853
Link To Document