Por favor, use este identificador para citar o enlazar este ítem:
http://hdl.handle.net/11531/36002
Título : | Unit Commitment with ACOPF Constraints: Practical Experience with Solution Techniques |
Autor : | Sánchez Martín, Pedro Tejada Arango, Diego Alejandro Wogrin, Sonja Ramos Galán, Andrés |
Resumen : | El artículo describe experiencias prácticas de resolución de problemas de asignación de grupos de generación eléctrica que incluyen restricciones que modelan la red de transporte en su formulación de corriente alterna. Se muestran los resultados de tres aproximaciones: 1) resolviendo el problema enterno no lineal con optimizadores comerciales 2) mediante una aproximación exterior que mediante programación lineal iterativamente resuelve el problema y 3) mediante programación cónica de segundo orden. 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. |
URI : | http://hdl.handle.net/11531/36002 |
Aparece en las colecciones: | Documentos de Trabajo |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
IEEE_PES_PowerTech_2019_UC_ACOPF_v1.pdf | 449,55 kB | Adobe PDF | Visualizar/Abrir Request a copy |
Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.