Name
Abstract | ||
|---|---|---|
Development of networked energy infrastructures (like gas pipe networks), generally requires a significant amount of capital investment under resources, market and institutional uncertainties. Several independent suppliers and consumers are to be connected into these networks. However, the actual commitment of these parties and the capacities they require from the network can remain uncertain for a long time. This is a challenging task for development co-owners because decisions, such as network architectures, have to be made while uncertainty exists. In order to effectively explore through the design space and identify architecturally flexible designs addressing a view of capacity uncertainty, a simulation framework based on a combination of Monte Carlo simulation and Graph Theory is proposed. It integrates a stochastic capacity demand model and network design heuristic algorithm. The framework will be able to evaluate architectural design options and show that architectural flexibility can significantly improve the value of the infrastructure project by reducing downside risks and benefiting from upside gains compared to the deterministic design approach. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.procs.2014.03.023 | Procedia Computer Science |
Keywords | Field | DocType |
networked energy infrastructures,uncertainty,architectural flexibility | Computer science,Pipe network analysis,Network architecture,Capital investment,Artificial intelligence,Design space,Graph theory,Monte Carlo method,Industrial engineering,Network planning and design,Heuristic (computer science),Simulation,Machine learning | Conference |
Volume | ISSN | Citations |
28 | 1877-0509 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Y. G. Melese | 1 | 0 | 0.68 |
| Petra W. Heijnen | 2 | 6 | 6.14 |
| Rob M. Stikkelman | 3 | 0 | 1.35 |