TY - JOUR
T1 - Potential capacity factor estimates of wind generating resources for transmission planning
AU - Hur, Jin
N1 - Funding Information:
This work was supported by the Ewha Womans University Research Grant of 2020 .
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/12
Y1 - 2021/12
N2 - Wind Generating Resources (WGRs) are variable, uncontrollable, and uncertain compared to traditional generating resources. As Wind Generating Resources (WGRs) have the intermittent nature of WGRs and uncertain characteristics according to the weather condition, the accurate prediction of WGRs' capacity factor is an essential factor associated with integrating a large amount of wind generating resources into the grid. As wind farm outputs depend on natural wind resources that vary over space and time, spatial correlation analysis is also needed to estimate power outputs of wind generation resources. In this paper, we propose the potential capacity factor estimates of new wind generating resources using the augmented spatial analysis and modelling of power outputs produced by wind farms that are geographically distributed in windy areas. To validate the proposed spatial prediction model, we use the empirical data from the Jeju Island's wind farms in South Korea.
AB - Wind Generating Resources (WGRs) are variable, uncontrollable, and uncertain compared to traditional generating resources. As Wind Generating Resources (WGRs) have the intermittent nature of WGRs and uncertain characteristics according to the weather condition, the accurate prediction of WGRs' capacity factor is an essential factor associated with integrating a large amount of wind generating resources into the grid. As wind farm outputs depend on natural wind resources that vary over space and time, spatial correlation analysis is also needed to estimate power outputs of wind generation resources. In this paper, we propose the potential capacity factor estimates of new wind generating resources using the augmented spatial analysis and modelling of power outputs produced by wind farms that are geographically distributed in windy areas. To validate the proposed spatial prediction model, we use the empirical data from the Jeju Island's wind farms in South Korea.
KW - Augmented spatial modelling
KW - Potential capacity factor
KW - Transmission planning
KW - Universal kriging
KW - Wind generating resources
UR - http://www.scopus.com/inward/record.url?scp=85111980225&partnerID=8YFLogxK
U2 - 10.1016/j.renene.2021.08.015
DO - 10.1016/j.renene.2021.08.015
M3 - Article
AN - SCOPUS:85111980225
SN - 0960-1481
VL - 179
SP - 1742
EP - 1750
JO - Renewable Energy
JF - Renewable Energy
ER -