Improving scenario stochastic optimization for a dynamic hydrogen consuming plant
- Daniel Andres Navia Lopez
- Daniel Sarabia Ortiz
- Gloria Gutiérrez Rodríguez
- César de Prada Moraga
Verlag: Universidad de Jaén
ISBN: 978-84-693-0715-1
Datum der Publikation: 2010
Seiten: 99
Kongress: Jornadas de Automática (31. 2010. Jaen)
Art: Konferenz-Beitrag
Zusammenfassung
The aim of this work is to overcome the loss of generalization produced when a stochastic optimization is solved by means of discretizing a probability distribution function (scenarios), in a hydrogen supply problem. To do this, three strategies of application of the optimization results were tested in a Montecarlo simulation with the original continuous probability function: use the optimization results for the nearest scenario, apply the solution calculated for the nearest scenario that overestimates the system and interpolate between the discrete solutions. The results shows that by using the linear interpolation strategy in almost a 100% of the times the hydrogen distribution is feasible and the estimated costs is the lower obtained.