Abstract:
Short term electric load forecasting is one of the important issues in the operation and system planning. Sliort term electric load forecasting is predicting a system load with a leading time of one hour to seven days, which is necessary for adequate scheduling and operation of power system .
Short term electric load forecasting parameters have been categorically classified into day types (work days, holidays, special days), weather information (temperature, relative humidity, wind velocity, rainfall, evaporation) and historical part electric load data .
Electric load forecasting problem has been solved using both conventional and
non conventional (ANN) methods and the The performance of the proposed algorithm
the IIT Roorkee daily peak load forecasting.
are encouraging and useful in the field.
result are compared. has been validated for The results so obtained
Accurate short-term electric load forecasts represent a great potential savings for electric utility corporations. The accuracy of the forecasted peak-load
influences decision-making in economic dispatch, unit commitment, hydro-
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thermal coordination, fuel allocation, and off-line network analysis, etc.
