Short term load forecasting by statistical time series methods

Abstract EN

The electricity demand forecasting is a pioneer study in the field of electrical engineering.

Demand forecasting is inevitable for impeccable operation of the power system on the other hand it is required for long term planning.

Recent year’s development of new methodologies for Short Term Load Forecasting (STLF) has gain the interest of researchers.

STLF is required for fixing the bidding strategies, strategic decisions and generator scheduling.

Early information of demand can be a beneficial tool for energy management centre.

In view of this light, this paper presents an application of statistical forecasting method for predicting the demand on hourly basis.

On the basis of average and peak demand the similar days are selected and forecast for next hours are carried out.

The paper also presents a meaningful comparison of different statistical load forecasting methods namely trend analysis, decomposition and moving average method.

It is observed that the moving method outperformed over other methods.