An Efficient On-Line Load-Modeling Algorithm for Short-Term Forecasting of Interconnected Power Systems

This note addresses itself to the problem of one-step-ahead forecasting of the load demand at all the loading nodes of an interconnected power system. A multivariable state-space combined parameter and state estimation technique is proposed. A normalized stochastic approximation method—which is computationally simple and exhibits good initial convergence—is used to generate estimates of the model parameters and the optimum filter gain matrix. The estimated parameters are then utilized to obtain a one-step-ahead forecast of the load demand. Some results of application of the proposed algorithm to real load pertaining to the Eastern Saudi Arabian power grids are presented.