N.-L. Tai, H.-Q. Zhai, J. Ye, and L.-B. Qi
Electric load, climatic factors, short-term load forecasting, revisedmodelNomenclatureΔL : the load correction valueΔT : the temperature difference at the same time pointbetween the forecasting day and the day beforeΔT : the temperature difference between the forecastingday and the day beforeF1: a daily load in the day when the temperature is similarwith the latest forecasting day (within 10 days)F0: the conventional forecasting resultα : a confidence coefficientTr0 : the temp
Considering the importance of the short-term load forecasting (STLF), researches in this area have resulted in the development of numerous forecasting methods. However, the weather factors will affect the precision of the traditional STLF methods greatly, especially temperature, humidity, wind and rain. Through the analysis of electric loads and weather data, their features and variation are discussed in this paper. Based on that, the amended model is presented. Simulation results verify that the new method can obtain high precision.
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