Trend Review of Solar Energy Forecasting Technique

Jae ho Cheon; Jung-Tae Lee; Hyun-Goo Kim; Yong-Heack Kang; Chang-Yeol Yun; Chang Ki Kim; Bo-Young Kim; Jin-Young Kim; Yu Yeon Park; Tae Hyun Kim; Ha Na Jo

doi:10.7836/kses.2019.39.4.041

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2019 Vol.39, Issue 4 Preview Page Next Page

Research Article

Trend Review of Solar Energy Forecasting Technique 태양에너지 예보기술 동향분석

30 August 2019. pp. 41-54

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Abstract

The proportion of solar photovoltaic power generation has steadily increased in the power trade market. Solar energy forecast is highly important for the stable trade of volatile solar energy in the existing power trade market, and it is necessary to identify accurately any forecast error according to the forecast lead time. This paper analyzes the latest study trend in solar energy forecast overseas and presents a consistent comparative assessment by adopting a single statistical variable (nRMSE) for forecast errors according to lead time and forecast technology.

Keywords

Photovoltaic

Irradiance

ANN;Atificial neural network

Power forecasting

Forecasting horizon

키워드

태양광발전

일사

인공신경망

발전량예보

예보시간

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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 : 39
No :4
Pages :41-54
Received Date : 2019-06-11
Revised Date : 2019-08-01
Accepted Date : 2019-08-12
DOI :https://doi.org/10.7836/kses.2019.39.4.041

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

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