TY - GEN
T1 - Unit commitment with ACOPF constraints
T2 - 2019 IEEE Milan PowerTech, PowerTech 2019
AU - Tejada-Arango, Diego A.
AU - Wogrin, Sonja
AU - Sanchez-Martin, Pedro
AU - Ramos, Andres
PY - 2019/6
Y1 - 2019/6
N2 - This paper summarizes practical experiences of solving the UC problem with AC optimal power flow constraints using three main approaches: 1) solving a MINLP with commercial solvers, 2) an outer approximation approach with Successive Linear Programming (SLP), and 3) a Second Order Cone Programming (SOCP) approximation. We show a comprehensive review of each approach, including main characteristics and drawbacks. Although non-linear solvers have improved their performance in recent years, our results suggest that the binary nature of the variables in the UC problem still increases the solution time up to 75 times in comparison to a relaxed version of the UC. SLP approaches have shown a good behavior finding integer feasible solutions, however, the solution times are almost twofold the ones obtained for the MINLP. SOCP is a promising approach because it improves almost 6 times the approximation made by the classic DC approach. Nevertheless, its solving times are comparable to those found using the MINLP. Finally, parallel computing techniques could improve the performance of each approach in order to make them more computationally efficient for large-scale UC problems.
AB - This paper summarizes practical experiences of solving the UC problem with AC optimal power flow constraints using three main approaches: 1) solving a MINLP with commercial solvers, 2) an outer approximation approach with Successive Linear Programming (SLP), and 3) a Second Order Cone Programming (SOCP) approximation. We show a comprehensive review of each approach, including main characteristics and drawbacks. Although non-linear solvers have improved their performance in recent years, our results suggest that the binary nature of the variables in the UC problem still increases the solution time up to 75 times in comparison to a relaxed version of the UC. SLP approaches have shown a good behavior finding integer feasible solutions, however, the solution times are almost twofold the ones obtained for the MINLP. SOCP is a promising approach because it improves almost 6 times the approximation made by the classic DC approach. Nevertheless, its solving times are comparable to those found using the MINLP. Finally, parallel computing techniques could improve the performance of each approach in order to make them more computationally efficient for large-scale UC problems.
KW - AC optimal power flow
KW - Mixed integer non-linear programming
KW - Outer approximations
KW - Second order cone programming
KW - Unit commitment
UR - http://www.scopus.com/inward/record.url?scp=85072341887&partnerID=8YFLogxK
U2 - 10.1109/PTC.2019.8810928
DO - 10.1109/PTC.2019.8810928
M3 - Conference paper
AN - SCOPUS:85072341887
T3 - 2019 IEEE Milan PowerTech, PowerTech 2019
BT - 2019 IEEE Milan PowerTech, PowerTech 2019
PB - Institute of Electrical and Electronics Engineers
Y2 - 23 June 2019 through 27 June 2019
ER -