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A parametric approach to the prediction of the time-behavior of harmonic-quantities in electrical networks

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2 Author(s)
Cavallini, A. ; Fac. di Ingegneria, Ferrara Univ., Italy ; Montanari, G.C.

In this paper, the problem of harmonic modeling and prediction is dealt with the time-series approach. Techniques for order and parameter identification of seasonal auto-regressive integrated moving-average, SARIMA, models, are discussed. Forecasting tools, valid for power, harmonic distortion and harmonic-current amplitudes, are obtained, which provide accurate daily predictions. Moreover, the stochastic dependence between the investigated quantities are outlined

Published in:

Industry Applications Conference, 1995. Thirtieth IAS Annual Meeting, IAS '95., Conference Record of the 1995 IEEE  (Volume:3 )

Date of Conference:

8-12 Oct 1995