Evaluating Combined Load Forecasting in Large Power Systems and Smart Grids

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 aggregati...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2013-08, Vol.9 (3), p.1570-1577
Main Authors: Borges, C. E., Penya, Yoseba K., Fernandez, Ivan
Format: Article
Language:English
Subjects:
Demand forecasting
Forecasting
Load forecasting
Load modeling
Polynomials
prediction methods
Predictive models
Smart grids
Support vector machines
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Summary: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.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2012.2219063