TY - JOUR
T1 - A framework for estimating flexible resources according to future Korean renewables scenario
T2 - Robust optimization approach considering multiple uncertainties
AU - Jeong, Jinwoo
AU - Lee, Byongjun
N1 - Funding Information:
This research was supported by the Korea Electric Power Corporation (Grant No. R17XA05-4 ) and “Human Resource program in Energy Technology” of the Korea Institute of Energy Technology Evaluation and Planning , with financial resources granted from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20174030201820 ). Appendix A
Funding Information:
This research was supported by the Korea Electric Power Corporation (Grant No. R17XA05-4) and ?Human Resource program in Energy Technology? of the Korea Institute of Energy Technology Evaluation and Planning, with financial resources granted from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20174030201820).
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2020/6
Y1 - 2020/6
N2 - This study presents a robust optimization model to secure flexibility under a high penetration of renewable energy systems in a future grid. An increase in renewable energy into a power system causes difficulties and complexities with regard to power system planning and operation owing to an increase in uncertainty. This trend can create an issue in the flexibility of a power system under a high penetration of renewable energy. To acquire sufficient flexibility, numerous flexible resources such as conventional generators with a ramping capability, energy storage systems and demand response program should be procured. Herein, we propose estimating the flexible resource capacity required to prevent a flexibility deficit when considering multiple uncertainties such as the effective capacity and 1-min power fluctuation rate of the renewable energy systems. To solve this problem, including uncertainties, through an optimization technique, we adopt a robust optimization to deal with uncertainty by constructing an uncertainty set and provide a robust solution considering the worst case within such a set. The robust optimization model was tested using data from the Korean electric power system for the year 2030. In addition, the results from a robust optimization are compared with the results from a deterministic approach.
AB - This study presents a robust optimization model to secure flexibility under a high penetration of renewable energy systems in a future grid. An increase in renewable energy into a power system causes difficulties and complexities with regard to power system planning and operation owing to an increase in uncertainty. This trend can create an issue in the flexibility of a power system under a high penetration of renewable energy. To acquire sufficient flexibility, numerous flexible resources such as conventional generators with a ramping capability, energy storage systems and demand response program should be procured. Herein, we propose estimating the flexible resource capacity required to prevent a flexibility deficit when considering multiple uncertainties such as the effective capacity and 1-min power fluctuation rate of the renewable energy systems. To solve this problem, including uncertainties, through an optimization technique, we adopt a robust optimization to deal with uncertainty by constructing an uncertainty set and provide a robust solution considering the worst case within such a set. The robust optimization model was tested using data from the Korean electric power system for the year 2030. In addition, the results from a robust optimization are compared with the results from a deterministic approach.
KW - Energy storage system
KW - Power system flexibility
KW - Renewable energy
KW - Robust optimization
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85076318464&partnerID=8YFLogxK
U2 - 10.1016/j.ijepes.2019.105728
DO - 10.1016/j.ijepes.2019.105728
M3 - Article
AN - SCOPUS:85076318464
SN - 0142-0615
VL - 118
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
M1 - 105728
ER -