| Title |
Study of Temporal Data Mining for Transformer Load Pattern Analysis |
| Authors |
신진호(Shin, Jin-Ho) ; 이봉재(Yi, Bong-Jae) ; 김영일(Kim, Young-Il) ; 이헌규(Lee, Heon-Gyu) ; 류근호(Ryu, Keun-Ho) |
| Keywords |
Transformer Load Pattern ; Temporal Data Mining ; Calender Pattern ; Association Rule ; 3D Cube Mining |
| Abstract |
This paper presents the temporal classification method based on data mining techniques for discovering knowledge from measured load patterns of distribution transformers. Since the power load patterns have time-varying characteristics and very different patterns according to the hour, time, day and week and so on, it gives rise to the uninformative results if only traditional data mining is used. Therefore, we propose a temporal classification rule for analyzing and forecasting transformer load patterns. The main tasks include the load pattern mining framework and the calendar-based expression using temporal association rule and 3-dimensional cube mining to discover load patterns in multiple time granularities. |