TY - JOUR
T1 - Second-Order Cone Programming for Data-Driven Fluid and Gas Energy Flow with a Tight Reformulation
AU - Jia, Wenhao
AU - Ding, Tao
AU - Shahidehpour, Mohammad
N1 - Publisher Copyright:
© 1969-2012 IEEE.
PY - 2021/3
Y1 - 2021/3
N2 - The precise fluid and gas energy flow equations (FEFEs) are difficult to formulate due to the uncertain parameters. This paper proposes a data-driven approach to fit the FEFEs by polynomial functions through experimental data. Furthermore, a convex optimization model is set up to find the solution of the FEFEs, and a tight reformulation is proposed to exactly reformulate the proposed model as a second-order cone programming (SOCP) that can be tractably solved. Numerical results on several test systems show the effectiveness of the proposed method.
AB - The precise fluid and gas energy flow equations (FEFEs) are difficult to formulate due to the uncertain parameters. This paper proposes a data-driven approach to fit the FEFEs by polynomial functions through experimental data. Furthermore, a convex optimization model is set up to find the solution of the FEFEs, and a tight reformulation is proposed to exactly reformulate the proposed model as a second-order cone programming (SOCP) that can be tractably solved. Numerical results on several test systems show the effectiveness of the proposed method.
KW - Fluid and gas energy flow
KW - polynomial optimization
KW - second-order cone programming
KW - tight reformulation
UR - https://www.scopus.com/pages/publications/85098790580
U2 - 10.1109/TPWRS.2020.3038078
DO - 10.1109/TPWRS.2020.3038078
M3 - 文章
AN - SCOPUS:85098790580
SN - 0885-8950
VL - 36
SP - 1652
EP - 1655
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 2
M1 - 9259059
ER -