TY - GEN
T1 - A cutting-plane solution for chance-constrained unit commitment problems
AU - Chen, Y.
AU - Sato, T.
AU - Shiina, Takayuki
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this study, we addressed a unit commitment problem with uncertain demands during certain hours of the day. A chance-constrained stochastic mixed-integer program (SMIP) is used in the formulation to express the uncertain conditions that generally present difficulties during the computation. We introduce a cutting-plane method to carry out the calculations, and include valid inequalities to restrict the feasible region for the ease of finding suitable solutions. In addition, we utilize a linear approximation for the quadratic objective function that significantly improves the computational efficiency by reducing the complexity of the problem. The results indicate that the SMIP proposed in this study can be calculated within a short time where the chance constraints are satisfied in all the solutions.
AB - In this study, we addressed a unit commitment problem with uncertain demands during certain hours of the day. A chance-constrained stochastic mixed-integer program (SMIP) is used in the formulation to express the uncertain conditions that generally present difficulties during the computation. We introduce a cutting-plane method to carry out the calculations, and include valid inequalities to restrict the feasible region for the ease of finding suitable solutions. In addition, we utilize a linear approximation for the quadratic objective function that significantly improves the computational efficiency by reducing the complexity of the problem. The results indicate that the SMIP proposed in this study can be calculated within a short time where the chance constraints are satisfied in all the solutions.
KW - Chance-constrained optimization, cutting-plane method, unit commitment
UR - http://www.scopus.com/inward/record.url?scp=85139556673&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85139556673&partnerID=8YFLogxK
U2 - 10.1109/IIAIAAI55812.2022.00126
DO - 10.1109/IIAIAAI55812.2022.00126
M3 - Conference contribution
AN - SCOPUS:85139556673
T3 - Proceedings - 2022 12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022
SP - 641
EP - 646
BT - Proceedings - 2022 12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022
A2 - Matsuo, Tokuro
A2 - Takamatsu, Kunihiko
A2 - Ono, Yuichi
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022
Y2 - 2 July 2022 through 7 July 2022
ER -