Mostrando 10 resultados de: 172
Filtros aplicados
Publisher
Computers and Chemical Engineering(33)
Journal of Process Control(11)
IFAC-PapersOnLine(9)
AIChE Journal(6)
Applied Energy(6)
Área temáticas
Física aplicada(52)
Ciencias de la computación(42)
Métodos informáticos especiales(30)
Dirección general(26)
Programación informática, programas, datos, seguridad(25)
Área de conocimiento
Optimización matemática(78)
Energía(29)
Política energética(18)
Aprendizaje automático(15)
Algoritmo(13)
Objetivos de Desarrollo Sostenible
ODS 7: Energía asequible y no contaminante(74)
ODS 12: Producción y consumo responsables(68)
ODS 17: Alianzas para lograr los objetivos(61)
ODS 8: Trabajo decente y crecimiento económico(53)
ODS 13: Acción por el clima(41)
Origen
scopus(172)
A Chance-Constrained Nonlinear Programming Approach for Equipment Design Under Uncertainty
Book PartAbstract: In this work there are shown different strategies to cope uncertainty in large-scale chance-constraiPalabras claves:design, flares, sigmoid conditional value at risk, UNCERTAINTYAutores:Cao Y., Ponce-Ortega J.M., Tovar-Facio J., Víctor M. ZavalaFuentes:scopusA Julia Framework for Graph-Structured Nonlinear Optimization
ArticleAbstract: Graph theory provides a convenient framework for modeling and solving structured optimization problePalabras claves:Autores:Cole D.L., Shin S., Víctor M. ZavalaFuentes:scopusA Parallel Decomposition Scheme for Solving Long-Horizon Optimal Control Problems
Conference ObjectAbstract: We present a temporal decomposition scheme for solving long-horizon optimal control problems. The tiPalabras claves:Autores:Faulwasser T., Shin S., Víctor M. Zavala, Zanon M.Fuentes:scopusA Stochastic Dual Dynamic Programming Framework for Multiscale MPC<sup>⁎</sup>
Conference ObjectAbstract: We derive and interpret stochastic dual dynamic programming (SDDP) from the perspective of MPC to arPalabras claves:duality, energy systems, MPC, multiscale, stochastic dynamic programmingAutores:Drees K.H., Elbsat M.N., Ellis M.J., Kumar R., Víctor M. Zavala, Wenzel M.J.Fuentes:scopusA Stochastic Model Predictive Control Framework for Stationary Battery Systems
ArticleAbstract: A stochastic model predictive control (MPC) framework is presented to determine real-time commitmentPalabras claves:battery storage, Demand charges, energy markets, Frequency regulation, Pbkp_redictive control, stochastic systemsAutores:Drees K.H., Elbsat M.N., Ellis M.J., Kumar R., Víctor M. Zavala, Wenzel M.J.Fuentes:scopusA computational framework for identifiability and ill-conditioning analysis of lithium-ion battery models
ArticleAbstract: The lack of informative experimental data and the complexity of first-principles battery models makePalabras claves:Autores:Flores-Tlacuahuac A., López D.C., Vasquez-Medrano R., Víctor M. Zavala, Wozny G.Fuentes:scopusA computational framework for quantifying and analyzing system flexibility
ArticleAbstract: We present a computational framework for analyzing and quantifying system flexibility. Our frameworkPalabras claves:Complex systems, Flexibility, UNCERTAINTYAutores:Pulsipher J.L., Rios D., Víctor M. ZavalaFuentes:scopusA computational framework for uncertainty quantification and stochastic optimization in unit commitment with wind power generation
ArticleAbstract: We present a computational framework for integrating a state-of-the-art numerical weather predictionPalabras claves:Closed-loop, economic dispatch, unit commitment, Weather forecasting, WindAutores:Anitescu M., Constantinescu E., Lee S., Rocklin M., Víctor M. ZavalaFuentes:scopusA decomposition algorithm for simultaneous scheduling and control of CSP systems
ArticleAbstract: We present a decomposition algorithm to perform simultaneous scheduling and control decisions in conPalabras claves:Dynamic optimization, electricity markets, mixed integer programming, solar energy, Thermal energy storageAutores:Dowling A.W., Víctor M. Zavala, Zheng T.Fuentes:scopusA dynamic penalty approach to state constraint handling in deep reinforcement learning
ArticleAbstract: Deep reinforcement learning (RL) has emerged as a promising approach to solving sequential optimizatPalabras claves:Constraint handling, Dynamic penalty, Penalty approach, reinforcement learningAutores:Lee J.H., Víctor M. Zavala, Yoo H.Fuentes:scopus