Growing quantity of air-conditioners and extremely hot weather has made the temperature-lowing load increase as never before. To estimate temperature-lowering load more accurately

an estimation method based on meteorological data and entropy weight theory is proposed. The maximum value of annual maximum load curve load date less the benchmark curve without temperature-lowering load is annual maximum temperature-lowering load. A meteorological axis system is built based on temperature

relative humidity

precipitation and other meteorological data to determine base meteorological quadrant and filtrate benchmark weekday when calculating base load curve. According to the relevant coefficients between maximum daily load and temperature

relative humidity or precipitation on benchmark weekdays

the weights of benchmark weekday load curves are calculated using the entropy weight theory. Finally

the annual maximum temperature-lowering load is estimated according to Guangzhou 2009-2013 load and meteorological data. The result shows that the new method is more appropriate. This work is supported by National Natural Science Foundation of China(No. 50907023)and China Southern Power Grid Company Limited(No. K-GD2012-006).