The intrinsic uncertainties associated with demand forecasting become more acute when it is required to provide an invaluable dimension to the decision making process in a period characterised by fast and dynamic changes. In this paper, estimates of the peak demand, pertaining to a typical fast growing system with inherit dynamic load characteristics, have been derived from three classical time—series forecasting methods. These demand estimates are compared with corresponding actual values. Improved modelling of the system load characteristics, described in a companion paper, Part II, demonstrates better forecasts compared with forecasts obtained by direct application of classical time—series methods. © 1990 IEEE
