Application of MLP and stochastic simulations for electricity load forecasting in Russia

$EVWUDFW The work is devoted to an application of artificial neural network (multilayer perceptron) and conditional stochastic simulations to electricity load forecasting in Russia. One of the problems is missing data and some important weather parameters (wind, cloudiness, precipitation, historical information). This gives rise to rather large forecasting errors with complex statistical structure. Another problem deals with economic trends in the country during the last decade and its influence (sometimes contradictory) on electricity consumption. The methodological innovative aspect of the study is a use of geostatistical tools (variography) and simulations to characterise the expected variability of the results.