Data-Dependent Systems Approach to Short-Term Load Forecasting

K. P. Rajurkar, J. L. Nissen

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

A recently developed stochastic modeling and analysis methodology called data-dependent systems (DDS) is introduced. The forecasting application of a univariate DDS model is illustrated for the actual hourly load data for a small community (Curtis, Nebraska, USA). An accurate forecast for peak values of the load is provided by the conditional expectation of the statistically adequate model ARMA (4,3). The dynamics of this model and the possibility of applying multivariate DDS models to short-term load forecasting are also discussed.

Original languageEnglish (US)
Pages (from-to)532-536
Number of pages5
JournalIEEE Transactions on Systems, Man and Cybernetics
VolumeSMC-15
Issue number4
DOIs
StatePublished - Jan 1 1985

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Data-Dependent Systems Approach to Short-Term Load Forecasting. / Rajurkar, K. P.; Nissen, J. L.

In: IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-15, No. 4, 01.01.1985, p. 532-536.

Research output: Contribution to journalArticle

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