TY - GEN
T1 - Flexible Robust Unit Commitment Considering Subhourly Wind Power Ramp Behaviors
AU - Hu, Bo
AU - Gong, Yuzhong
AU - Chung, C. Y.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - The focus of existing studies on day ahead unit commitment (DAUC) considering wind power have mainly been on the hourly operation constraints. However, if the sub-hourly wind power variations are not carefully considered, the obtained unit commitment (UC) solutions may not be flexible enough to accommodate the sub-hourly wind variations and results in wind curtailments. To ensure the full utilization of wind power, in this paper a robust optimization-based UC model considering sub-hourly wind power variation is proposed. The objective is to provide a flexible and robust UC solution for the thermal units, which ensures sufficient ramp up and ramp down reserves for the variations of wind power in the intra-hour time frame. Firstly, a non-parametric approach based on the 2-dimensional kernel density estimation is proposed to quantify the sub-hourly wind power variability. Then, based on the quantification results, a set of ramp constraints are imposed on the robust UC model. A column and constraint generation method is applied to solve the improved UC model. The proposed model is tested and compared with conventional UC models on IEEE 39 bus test system to verify its effectiveness.
AB - The focus of existing studies on day ahead unit commitment (DAUC) considering wind power have mainly been on the hourly operation constraints. However, if the sub-hourly wind power variations are not carefully considered, the obtained unit commitment (UC) solutions may not be flexible enough to accommodate the sub-hourly wind variations and results in wind curtailments. To ensure the full utilization of wind power, in this paper a robust optimization-based UC model considering sub-hourly wind power variation is proposed. The objective is to provide a flexible and robust UC solution for the thermal units, which ensures sufficient ramp up and ramp down reserves for the variations of wind power in the intra-hour time frame. Firstly, a non-parametric approach based on the 2-dimensional kernel density estimation is proposed to quantify the sub-hourly wind power variability. Then, based on the quantification results, a set of ramp constraints are imposed on the robust UC model. A column and constraint generation method is applied to solve the improved UC model. The proposed model is tested and compared with conventional UC models on IEEE 39 bus test system to verify its effectiveness.
KW - column and constraint generation (CCG)
KW - kernel density estimation (KDE)
KW - robust optimization
KW - unit commitment (UC)
KW - wind power
UR - http://www.scopus.com/inward/record.url?scp=85074106426&partnerID=8YFLogxK
U2 - 10.1109/CCECE.2019.8861590
DO - 10.1109/CCECE.2019.8861590
M3 - Conference article published in proceeding or book
AN - SCOPUS:85074106426
T3 - 2019 IEEE Canadian Conference of Electrical and Computer Engineering, CCECE 2019
BT - 2019 IEEE Canadian Conference of Electrical and Computer Engineering, CCECE 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Canadian Conference of Electrical and Computer Engineering, CCECE 2019
Y2 - 5 May 2019 through 8 May 2019
ER -