Power Load Forecasting using Back Propagation Algorithm

Abstract

The day today operation and scheduling activities of a power generation unit requires the forecast of power demand to meet the needs of the consumers. Load forecasting is categorized into short, medium and long term forecasts. The short term prediction refers to hourly load forecast for the period lasting from an hour to more than a few days. The medium term forecasts is prediction of power load ranging from one to several months ahead. Finally, the long term forecast indicates prediction of power load ranging from one to many years in near future. Excellence of short term hourly power load forecast has a considerable effect on cost effective functioning of power plants because numerous assessments are dependent on these forecasts. These assessments comprise cost effective scheduling of power plants, scheduling of coal acquisition, power plant security consideration, and planning for energy related business. The significance of precise load forecasts will reduce the wastage of power in the future because of remarkable changes taking place in the structure of power generation industries due to deregulation and heavy competition. This situation creates thrust on the power generation sectors to function at maximum possible efficiency, which leads to precise forecasting of the power load