All Issue

2024 Vol.44, Issue 2 Preview Page

Research Article

Correlation Analysis for LCOE and Cost Components with Terrain Complexity for Korean Onshore Wind Farms

지형복잡도에 따른 국내 육상풍력발전단지의 LCOE와 그 구성요소에 대한 상관도 분석

Keonwoo Lee1
,
Kyoungboo Yang2
,
Kyungnam Ko3*
이 건우1
,
양 경부2
,
고 경남3*
1Ph. D. Candidate, Multidisciplinary Graduate School Program for Wind Energy, Graduate School, Jeju National University
2Chief Researcher, Blue Economy Strategy Institute
3Professor, Department of Electrical and Energy Engineering, Jeju National University
1제주대학교 대학원 풍력특성화협동과정, 박사과정
2블루이코노미전략연구원, 연구위원
3제주대학교 전기에너지공학과, 교수
*Corresponding Author
30 April 2024. pp. 27-36
PDF XML Citation
Abstract

A study on the relationship between levelized cost of energy (LCOE), its components, and terrain complexity was conducted for Korean onshore wind farms. The 22 wind farms are selected for this study. The actual capital expenditures (CapExs) and operational expenditures (OpExs) of the wind farms are collected from the Data Analysis Retrieval Transfer (DART) system of the Korean Financial Supervisory Service. The capacity factors (CFs) of the wind farms are estimated using the dataset of system marginal price (SMP), renewable energy certificate (REC), and capacities of wind farms. To evaluate terrain complexity, the ruggedness index (RIX) is calculated using the installed wind turbine locations of analyzed onshore wind farms and the numerical terrain contour data. The average RIX is 25.53% that corresponds to mountainous terrain. The correlation analysis is performed to determine the relationship between CF, CapEx, and OpEx in accordance with RIX. The LCOE is calculated from the actual expenditures and estimated CFs. Consequently, the average LCOE is estimated to be 141.04 USD/MWh. The correlation analysis reveals no relationship between LCOE, its components, and RIX.

Keywords
Wind energy
LCOE
RIX
Onshore wind energy
Correlation analysis
키워드
풍력에너지
균등화 발전비용
복잡도 지수
육상풍력
상관분석
References
1

Korea Wind Energy Industry Association, 2022 Annual Report on Wind Energy Industry in Korea, KWEIA, 2023.

2

Korea Energy Agency, New & Renewable Energy Statistics 2022, 2023. https://www.knrec.or.kr/biz/pds/statistic/view.do?no=270. last accessed on the 14th January 2024.

3

IRENA, Renewable Power Generation Costs in 2022, International Renewable Energy Agency, Abu Dhabi, 2023.

4

GWEC, Global Wind Report 2023, Global Wind Energy Council, Brussels, Belgium, 2023.

5

Korea Energy Economics Institute, Study on Estimation of Levelized Cost of Energy by Power Sources, Korea Power Exchange [KPX], 2018.

6

Lee, K. and Ko, K., Analysis of LCOE for Korean Onshore Wind Farms using Monte Carlo Simulation, The 2018 Fall Conference of Korea Wind Energy Association, pp. 27-30, October 2018, Busan, Republic of Korea.

7

Lee, K. and Ko, K., Analysis of LCOE for Korean Onshore Wind Farm Considering Social Discount Rate, Journal of the Korean Solar Energy Society, Vol. 40, No. 1, pp. 1-13, 2020, https://doi.org/10.7836/kses.2020.40.1.001.

10.7836/kses.2020.40.1.001
8

Lee, K. and Ko, K., Analysis of LCOE for Korean and Foreign Onshore Wind Turbines in Operation in Korea, Journal of Wind Energy, Vol. 13, No. 3, pp. 54-60, 2023, https://doi.org/10.33519/kwea.2023.14.3.006.

9

Mun, K., Lee, K., and Ko, K., Long-term Trend of System Marginal Price with Amounts of Machine Learning Train Data, Journal of the Korean Solar Energy Society, Vol. 41, No. 5, pp. 13-24, 2021, https://doi.org/10.7836/kses.2021.41.5.013.

10.7836/kses.2021.41.5.013
10

Yun, S., Kim, Y., Moon, H., Im, H., and Kwon, P., A Study on Onshore Wind Investment Cost : Focusing on Major Countries, The 2019 Spring Conference of Korean Society for New and Rewable Energy, pp. 157, May 2019, Busan, Republic of Korea.

11

Financial Supervisory Service DART. http://dart.fss.or.kr/. last accessed on the 14th January 2024.

12

Ju, B., Shin, D., and Ko, K., Accuracy Assessment of Annual Energy Production Estimated for Seongsan Wind Farm, Journal of the Korean Solar Energy Society, Vol. 36, No. 2, pp. 9-17, 2016, https://doi.org/10.7836/kses.2016.36.2.009.

10.7836/kses.2016.36.2.009
13

Mortensen, N. G., Heathfield, D. N., Rathmann, O., and Nielsen, M., Wind Atlas Analysis and Application Program: WAsP 11 Help Facility, Department of Wind Energy, Technical University of Denmark, Roskilde, Denmark, p. 366, 2014.

14

Yu, J. and Lee, J., REC Distortion as a Quantitative Control Policy due to REC Depreciation, Journal of Environmental and Resource Economics Review, Vol. 31, No. 1, pp. 51-83, 2022.

15

Kim, S. and Kim, S., Domain Analysis of Research on Prediction and Analysis of Slope Failure by Co-Word Analysis, The Journal of Engineering Geology, Vol. 31, No. 3, pp. 307-319, 2021, https://doi.org/10.9720/kseg.2021.3.307.

16

Al-Taai, O. T. and Hadi, S. H., Analysis of the Monthly and Annual Change of Soil Moisture and Evaporation in Iraq, Al-Mustansiriyah Journal of Science, Vol. 29, No. 4, pp. 7-13, 2018, https://doi.org/10.23851/mjs.v29i4.151.

10.23851/mjs.v29i4.151
17

Onyutha, C., From R-squared to Coefficient of Model Accuracy for Assessing "Goodness-of-Fits", Geoscientific Model Development Discussions, pp. 1-25, 2020, https://doi.org/10.5194/gmd-2020-51.

10.5194/gmd-2020-51
18

Construction Technology DIgital Library, Standard Market Unit Price for Construction Work 2022. https://www.codil.or.kr/. last accessed on the 14th January 2024.

Information
  • Publisher :Korean Solar Energy Society
  • Publisher(Ko) :한국태양에너지학회
  • Journal Title :Journal of the Korean Solar Energy Society
  • Journal Title(Ko) :한국태양에너지학회 논문집
  • Volume : 44
  • No :2
  • Pages :27-36
  • Received Date : 2024-01-20
  • Revised Date : 2024-02-09
  • Accepted Date : 2024-02-22
  • DOI :https://doi.org/10.7836/kses.2024.44.2.027
Journal Informaiton Journal of the Korean Solar Energy Society Journal of the Korean Solar Energy Society
Online Submission
  • NRF
  • KOFST
  • crossref crossmark
  • crossref cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close