Analysis of distributed power generation forecasting model for power distribution planning

Jintae Cho, Hongjoo Kim, Hosung Ryu, Yongju Son, Sungyun Choi

Research output: Contribution to journalArticlepeer-review

Abstract

This paper researches a model that predicts a growth in distributed power, taking into account the recent increase in renewable energy interconnected in the distribution system. This paper describes the current state of distributed power and discusses the process of selecting input and output variables for the forecasting model. The, this paper defines various models that can be used for distributed power forecasting and analyze strengths and examples. Finally, this paper compares the utilization of input variables and forecasting models that can be used as mid to long-term distributed power forecasting.

Original languageEnglish
Pages (from-to)1248-1262
Number of pages15
JournalTransactions of the Korean Institute of Electrical Engineers
Volume70
Issue number9
DOIs
Publication statusPublished - 2021 Sep

Keywords

  • Deep learning model
  • Distribution planning
  • Mid to long-term forecasting
  • Renewable energy resources

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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