TY - GEN
T1 - Reliability evaluation of bulk power system considering compressed air energy storage
AU - Ansari, Osama Aslam
AU - Bhattarai, Safal
AU - Karki, Rajesh
AU - Chung, C. Y.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - The integration of large-scale energy storage systems (ESSs) have been identified as a viable option to mitigate the adverse effects of renewable energy sources (RES) on the power system operation and reliability. Currently, compressed air energy storage (CAES) is one of the two large-scale energy storage technologies with low capital and operational costs. This paper presents a method to integrate a new CAES reliability model in the bulk power system reliability evaluation and investigates quantitative benefits derived from the CAES. A state-duration sampling method is adopted for the reliability evaluation. A detailed reliability model of the CAES that considers its actual operating mechanism is first developed. Each system contingency state is then analyzed using a unit commitment (UC) method instead of hourly optimal power flow (OPF). This ensures that the inter-temporal constraints introduced by the CAES, such as its state-of-charge (SOC), are included in the analysis. Case studies are performed on a six-bus test system containing a wind farm and a CAES. The results indicate that the CAES can improve the overall reliability of the system. In particular, the reliability indices of the bus where the CAES is connected show the greatest improvement.
AB - The integration of large-scale energy storage systems (ESSs) have been identified as a viable option to mitigate the adverse effects of renewable energy sources (RES) on the power system operation and reliability. Currently, compressed air energy storage (CAES) is one of the two large-scale energy storage technologies with low capital and operational costs. This paper presents a method to integrate a new CAES reliability model in the bulk power system reliability evaluation and investigates quantitative benefits derived from the CAES. A state-duration sampling method is adopted for the reliability evaluation. A detailed reliability model of the CAES that considers its actual operating mechanism is first developed. Each system contingency state is then analyzed using a unit commitment (UC) method instead of hourly optimal power flow (OPF). This ensures that the inter-temporal constraints introduced by the CAES, such as its state-of-charge (SOC), are included in the analysis. Case studies are performed on a six-bus test system containing a wind farm and a CAES. The results indicate that the CAES can improve the overall reliability of the system. In particular, the reliability indices of the bus where the CAES is connected show the greatest improvement.
KW - bulk system
KW - Compressed air energy storage
KW - Latin Hypercube Sampling
KW - Monte-Carlo
KW - reliability
KW - reliability evaluation
UR - http://www.scopus.com/inward/record.url?scp=85050352256&partnerID=8YFLogxK
U2 - 10.1109/EPEC.2017.8286234
DO - 10.1109/EPEC.2017.8286234
M3 - Conference article published in proceeding or book
AN - SCOPUS:85050352256
T3 - 2017 IEEE Electrical Power and Energy Conference, EPEC 2017
SP - 1
EP - 6
BT - 2017 IEEE Electrical Power and Energy Conference, EPEC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Electrical Power and Energy Conference, EPEC 2017
Y2 - 22 October 2017 through 25 October 2017
ER -