Volume : 2, Issue : 5, May - 2013

Electric Load Forecasting using Neuro–Fuzzy Systems

S. Hemachandra, Dr. R. V. S. Satyanarayana

Abstract :

In energy sector, the load forecasting is the most noteworthy task, as it secures the trustworthiness and reduces the operational cost of a power plant. The companies make funds and decision on selling energy from the generating companies, and setting up for maintenance and development. It is therefore completely essential to have some awareness of prospect power load. Precise forecast of electric load is not easy, because it is determined largely by variables that hook up “uncertainty” and whose relation with the load is not given directly. The Electric load is characterized as a nonlinear and non stationary procedure that can experience quick changes due to weather, cyclic and financial variations. A huge number of the conventional forecast models are unsuitable for this modeling because of their obligation of linearity and seasonality. Researchers implemented various techniques to unravel the load forecasting assignment.