Renewable Energy Prediction Market Participation Type Photovoltaics Prediction Model Development

Jae-Hyeok Yu; Sang-jin Kim; Byung-Hoon Jang; Sung-Min Woo

doi:10.7836/kses.2022.42.6.001

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2022 Vol.42, Issue 6 Next Page

Research Article

Renewable Energy Prediction Market Participation Type Photovoltaics Prediction Model Development 신재생에너지 예측시장 참여형 태양광 발전량 예측 모델 개발

30 December 2022. pp. 1-13

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Abstract

For stable operation of the power system, predicting the amount of renewable energy generated can help establish a reasonable power generation plan. Solar photovoltaic power generation cannot be arbitrarily controlled and is directly affected by climatic conditions. Therefore, this study introduces a solar photovoltaic power generation forecasting technique that can reduce forecasting errors and maximize settlement income. This power generation forecasting technique uses easily accessible public meteorological data. Participation in the renewable energy generation prediction market is expected to be activated through this study, and various business models could possibly be developed by lowering the entry barrier for participation in the solar photovoltaic power generation prediction market.

Keywords

Photovoltaic

Korea Power Exchange Incentive

Deep Learning

Long Short-Term Memory

Public Data

Renewable Energy Prediction System

키워드

태양광 발전량 예측

한국전력거래소 인센티브

심층 학습

장단기 기억 메모리

공공 데이터

재생에너지 예측 제도

References

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Information

Publisher :Korean Solar Energy Society
Publisher(Ko) :한국태양에너지학회
Journal Title :Journal of the Korean Solar Energy Society
Journal Title(Ko) :한국태양에너지학회 논문집
Volume : 42
No :6
Pages :1-13
Received Date : 2022-09-19
Revised Date : 2022-10-24
Accepted Date : 2022-10-25
DOI :https://doi.org/10.7836/kses.2022.42.6.001

Journal of the Korean Solar Energy Society ISSN:1598-6411(Print) 2508-3562(Online) 한국태양에너지학회 논문집

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