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Short term load forecasting in electric power systems: A comparison of ARMA models and extended wiener filtering

✍ Scribed by U. Di Caprio; R. Genesio; S. Pozzi; A. Vicino


Publisher
John Wiley and Sons
Year
1983
Tongue
English
Weight
910 KB
Volume
2
Category
Article
ISSN
0277-6693

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✦ Synopsis


On-line prediction of electric load in the buses of the EHV grid of a power generation and transmission system is basic information required by on-line procedures for centralized advanced dispatching of power generation.

This paper presents two alternative approaches to on-line short term forecasting of the residual component of the load obtained after the removal of the base load from a time series of total load. The first approach involves the use of stochastic ARMA models with time-varying coefficients. The second consists in the use of an extension of Wiener filtering due to Zadeh and Ragazzini.

Real data representing a load process measured in an area of Northern Italy and simulated data reproducing a non-stationary process with known characteristics constitute the basis of a numerical comparison allowing one to determine under which conditions each method is more appropriate.