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