Solving a large energy system optimization model using an open-source solver
Open-source energy models are becoming more widely used for electric power systems planning. The solutions for these models are often computed using commercial optimization solvers, which require licensing fees that can be a potential barrier for certain organizations and researchers. This study exp...
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/9e6156d2163c41cda7d657128491a1eb |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | Open-source energy models are becoming more widely used for electric power systems planning. The solutions for these models are often computed using commercial optimization solvers, which require licensing fees that can be a potential barrier for certain organizations and researchers. This study explores the ability of the open-source COIN-OR linear programming (CLP) solver to compute solutions for the Regional Energy Deployment System (ReEDS) model—a large-scale, open-access electricity system planning model for the United States developed by the National Renewable Energy Laboratory (NREL). We find that open-source solvers, such as CLP, require some reduction of model size and detail. Although the solutions for reduced-form models may differ from full-featured models, we demonstrate that reduced-form solutions for ReEDS can still provide useful insight about drivers of power sector evolution. This research can help the modeling community better understand how open-source solvers can be applied to large-scale planning tools, and the potential steps that may be required to implement them. |
|---|