摘要：The paper presents the possibility of using statistical methods to automate the selection of explanatory variables to balance the daily load of the National Power System (NPS).With automation,the cost of input forecast purchase may be optimized by minimizing their number,and the results also allow for a reduction in the effort required to select input parameters (explanatory variables) for later forecasting of NPS daily loads.
关键词：NPS load;NPS power demand;hourly average forecasts;explanatory variables;input parameters;meteorological parameters;statistical methods;data mining
