KSCE Journal of Civil and Environmental Engineering Research (대한토목학회논문집)

Korean Society of Civil Engeneers (대한토목학회)
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Study on Generation Volume of Floating Solar Power Using Historical Insolation Data

과거 일사량 자료를 활용한 수상태양광 발전량 예측 연구

  • 나혜지 (원광대학교 건설환경공학과) ;
  • 김경석 (원광대학교 건설환경공학과)
  • Received : 2022.11.16
  • Accepted : 2023.02.27
  • Published : 2023.04.01
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Abstract

Solar power has the largest proportion of power generation and facility capacity among renewable energy in South Korea. Floating solar power plant is a new way to resolve weakness of land solar power plant. This study analyzes the power generation of the 18.7 MW floating solar power project located in Saemangeum, Gunsan-si. Since the solar power generation has a characteristic that is greatly affected by the climate, various methods have been applied to predict solar power generation. In general, variables necessary for predicting power generation are solar insolation on inclined surfaces, solar generation efficiency, and panel installation area. This study analyzed solar power generation using the monthly solar insolation data from the KMA (Korea Meteorological Administration) over the past 10 years. Monte Carlo simulation (MCS) was applied to predict the solar power generation with the variables including solar panel efficiency and insolation. In the case of Saemangeum solar power project, the most solar power generation was in May, the least was in December, the average solar power generation simulated on MCS is 2.1 GWh per month, the minimum monthly power generation is 0.3 GWh, and the maximum is 5.0 GWh.

태양광발전은 현재 국내 신재생에너지 중 발전량과 설비용량 비중이 가장 크다. 수상태양광은 국내의 육상태양광 발전시설의 여러 가지 단점을 보완한 방식이다. 본 연구는 군산 새만금에 위치한 18.7 MW 시설용량의 수상태양광발전소를 대상으로 발전량을 분석하고자 한다. 기후의 영 향을 많이 받는 태양광발전사업의 특성으로 타당성을 확인하고자 관련 연구자들은 태양광 발전량 예측에 많은 기법들을 적용하였다. 일반적으로 발전량 예측에 필요한 변수들은 사업대상 지역의 경사면 일사량, 발전효율, 패널 설치 면적 등이다. 본 연구는 기상청 과거 10년간의 월 일사량 데이터를 활용하여 태양광 발전량을 분석하였다. 발전량을 예측하기 위해서 몬테카를로 시뮬레이션 기법을 적용하였으며, 태양광 패널의 발전효율과 일사량을 시뮬레이션의 변수들로 사용하였다. 새만금 태양광의 경우, 가장 태양광 발전량이 많은 달은 5월이며, 가장 적은 달은 12월로 예측되었으며, 발전량은 월평균 2.1 GWh이고, 최소 월 발전량은 0.3 GWh, 최대는 5.0 GWh로 분석되었다.

Keywords

Acknowledgement

본 연구는 한국연구재단의 지원을 받아 수행된 과제입니다 (NRF-2019R1C1C1010332).

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