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Survey of Intelligent STLF Methods

Ahmad Shakeeb, Bhawesh Kr Bharti, Arvind kumar, Bimlesh Prasad, Prof. L.Ramesh

Improvement of STLF has been a cause of concern right since the origin of Load Forecasting for making numerous number of decision making process. The financial impact of an electrical blackout is very profound to both suppliers and consumers. A multiagent system for electric load forecasting, especially suited to simulating the different social dynamics involved in distribution systems, is presented. We also present here a combined aggregative short-term load forecasting method for smart grids, a novel methodology that allows us to obtain a global prognosis by summing up the forecasts on the compounding individual loads. In this paper a simple model is taken to estimate the relationship between demand and the driver’s variable. The results of various types STLF are taken and errors are calculated. After conclusion