A Study on Load Forecasting of Distribution Line Based on Ensemble Learning for Mid- to Long-Term Distribution Planning

Jintae Cho, Yeunggul Yoon, Yongju Son, Hongjoo Kim, Hosung Ryu and Gilsoo Jang
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Jintae Cho: School of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea
Yeunggul Yoon: School of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea
Yongju Son: School of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea
Hongjoo Kim: KEPCO Research Institute (KEPRI), 105 Munji-ro, Yuseong-gu, Daejeon 34056, Korea
Hosung Ryu: KEPCO Research Institute (KEPRI), 105 Munji-ro, Yuseong-gu, Daejeon 34056, Korea
Gilsoo Jang: School of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea

Energies, 2022, vol. 15, issue 9, 1-19

Abstract: The complexity and uncertainty of the distribution system are increasing as the connection of distributed power sources using solar or wind energy is rapidly increasing, and digital loads are expanding. As these complexity and uncertainty keep increasing the investment cost for distribution facilities, optimal distribution planning becomes a matter of greater focus. This paper analyzed the existing mid-to-long-term load forecasting method for KEPCO’s distribution planning and proposed a mid- to long-term load forecasting method based on ensemble learning. After selecting optimal input variables required for the load forecasting model through correlation analysis, individual forecasting models were selected, which enabled the derivation of the optimal combination of ensemble load forecast models. This paper additionally offered an improved load forecasting model that considers the characteristics of each distribution line for enhancing the mid- to long-term distribution line load forecasting process for distribution planning. The study verified the performance of the proposed method by comparing forecasting values with actual values.

Keywords: distribution system planning; distribution line; peak load; hybrid forecasting model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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