| Title |
Analysis of Short-Term Load Forecasting Accuracy Based on Various Normalization Methods |
| Authors |
Bo-Sung Kwon ; Rae-Jun Park ; Kyung-Bin Song |
| DOI |
http://dx.doi.org/10.5207/JIEIE.2018.32.6.030 |
| Keywords |
Short-Term Load Forecasting ; Normalization ; Exponential Smoothing Method |
| Abstract |
The short-term load forecasting is necessary for stable and smooth power system operation. The accuracy of short-term load forecasting for weekdays according to various normalization methods is analyzed. The normalization methods to be analyzed are maximum and minimum normalization, maximum normalization, and Z-Score normalization. And the model used for 24-hours load pattern prediction is the exponential smoothing technique. In order to return the normalized 24-hour load value to the load value, the predicted maximum load, minimum load, average load and standard deviation of load are estimated using exponential smoothing. In the recent three-year case studies, the accuracy of the short-term load forecasting applying maximum normalization, maximum and minimum normalization and Z-Score to the exponential smoothing technique is analyzed based on the mean absolute percentage error(MAPE). The test results show that the maximum and minimum normalization method is better than the others. |