| Title |
Electrical Energy Consumption Forecasting Algorithm Using Multiple Regression Method |
| Authors |
Kyung-Bin Song ; Rae-Jun Park ; Kyeong-Hwan Kim ; Jong-Ryul Won |
| DOI |
http://dx.doi.org/10.5207/JIEIE.2017.31.11.069 |
| Keywords |
Electrical Energy Forecasting Algorithm ; Multiple Regression Model ; Power System |
| Abstract |
This paper proposes a electrical energy consumption forecasting algorithm using multiple regression analysis method that takes into GDP, population and monthly converted weekdays. In order to consider the uncertainty of the future temperature, forecasting monthly electrical energy consumption is applied the temperature sensitivity of the energy on the average temperature of the past 30 years based on multiple regression analysis algorithm. The proposed prediction model is generated based on the past five years' load data. Test results show that the accuracy of the proposed algorithm is 97.64% and the maximum error is 4.25% through 2010 to 2014. |