TY - JOUR
T1 - Probabilistic Estimation of Wind Generating Resources Based on the Spatiooral Penetration Scenarios for Power Grid Expansions
AU - Kim, Gyeongmin
AU - Shin, Hunyoung
AU - Hur, Jin
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) funded by the Korean Government through the Ministry of Science and ICT (MSIT) under Grant 2019R1F1A1061557.
Publisher Copyright:
© 2013 IEEE.
PY - 2021
Y1 - 2021
N2 - The proportion of renewable energy generation is expanding worldwide with the goal of reducing greenhouse gas. According to the 8th Basic Plan for Long-term Electricity Supply and Demand in South Korea, South Korea reduces traditional energy generation such as nuclear and coal plants and achieves 20% (58.5GW) of renewable energy generation by 2030. Wind Generating Resources (WGRs) are affected by meteorological variables such as temperature, wind speed and wind direction. Specifically, WGRs have uncertainty and variability issues depending on temporal and spatial characteristics. In this paper, we propose the probabilistic estimation of wind generating resources based on the spatiotemporal penetration scenarios for power grid expansion. The data of WGRs are analyzed based on clustering method considering the spatiotemporal penetration scenarios, and the potential scenarios are estimated using Monte Carlo simulation by selecting a representative power distribution probability for each cluster. The proposed estimation model of WGRs will play a key role to develop the hedging strategies of investment decision on power grid expansion planning with high wind power penetrations.
AB - The proportion of renewable energy generation is expanding worldwide with the goal of reducing greenhouse gas. According to the 8th Basic Plan for Long-term Electricity Supply and Demand in South Korea, South Korea reduces traditional energy generation such as nuclear and coal plants and achieves 20% (58.5GW) of renewable energy generation by 2030. Wind Generating Resources (WGRs) are affected by meteorological variables such as temperature, wind speed and wind direction. Specifically, WGRs have uncertainty and variability issues depending on temporal and spatial characteristics. In this paper, we propose the probabilistic estimation of wind generating resources based on the spatiotemporal penetration scenarios for power grid expansion. The data of WGRs are analyzed based on clustering method considering the spatiotemporal penetration scenarios, and the potential scenarios are estimated using Monte Carlo simulation by selecting a representative power distribution probability for each cluster. The proposed estimation model of WGRs will play a key role to develop the hedging strategies of investment decision on power grid expansion planning with high wind power penetrations.
KW - Monte Carlo simulation
KW - Probabilistic model and estimation
KW - power grid expansion
KW - spatiotemporal penetration scenarios
KW - wind generating resources
UR - http://www.scopus.com/inward/record.url?scp=85099726020&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2021.3052513
DO - 10.1109/ACCESS.2021.3052513
M3 - Article
AN - SCOPUS:85099726020
SN - 2169-3536
VL - 9
SP - 15252
EP - 15258
JO - IEEE Access
JF - IEEE Access
M1 - 9328250
ER -