Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

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

Authors
Cho, JintaeYoon, YeunggulSon, YongjuKim, HongjooRyu, HosungJang, Gilsoo
Issue Date
5월-2022
Publisher
MDPI
Keywords
distribution system planning; distribution line; peak load; hybrid forecasting model
Citation
ENERGIES, v.15, no.9
Indexed
SCIE
SCOPUS
Journal Title
ENERGIES
Volume
15
Number
9
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/141841
DOI
10.3390/en15092987
ISSN
1996-1073
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.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > School of Electrical Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE