| dc.contributor.author | Roch Dupré, David | es-ES |
| dc.contributor.author | Gonsalves, Tad | es-ES |
| dc.date.accessioned | 2020-04-27T15:06:07Z | |
| dc.date.available | 2020-04-27T15:06:07Z | |
| dc.date.issued | 28/02/2020 | es_ES |
| dc.identifier.uri | 10.4018/978-1-7998-1659-1.ch012 | es_ES |
| dc.identifier.uri | http://hdl.handle.net/11531/45939 | |
| dc.description | Capítulos en libros | es_ES |
| dc.description.abstract | This chapter proposes the application of a discrete version of the Fireworks Algorithm (FWA) and a novel PSO-FWA hybrid algorithm to optimize the energy efficiency of a metro railway line. This optimization consists in determining the optimal configuration of the Energy Storage Systems (ESSs) to install in a railway line, including their number, location, and power (kW). The installation of the ESSs will improve the energy efficiency of the system by incrementing the use of the regenerated energy produced by the trains in the braking phases, as the ESSs will store the excess of regenerated energy and return it to the system when necessary. The results for this complex optimization problem produced by the two algorithms are excellent and authors prove that the novel PSO-FWA algorithm proposed in this chapter outperforms the standard FWA. | es-ES |
| dc.description.abstract | This chapter proposes the application of a discrete version of the Fireworks Algorithm (FWA) and a novel PSO-FWA hybrid algorithm to optimize the energy efficiency of a metro railway line. This optimization consists in determining the optimal configuration of the Energy Storage Systems (ESSs) to install in a railway line, including their number, location, and power (kW). The installation of the ESSs will improve the energy efficiency of the system by incrementing the use of the regenerated energy produced by the trains in the braking phases, as the ESSs will store the excess of regenerated energy and return it to the system when necessary. The results for this complex optimization problem produced by the two algorithms are excellent and authors prove that the novel PSO-FWA algorithm proposed in this chapter outperforms the standard FWA. | en-GB |
| dc.format.mimetype | application/pdf | es_ES |
| dc.language.iso | en-GB | es_ES |
| dc.publisher | Business Science Reference (Hershey, Estados Unidos de América) | es_ES |
| dc.rights | | es_ES |
| dc.rights.uri | | es_ES |
| dc.source | Libro: Handbook of research on fireworks algorithms and swarm intelligence, Página inicial: 263, Página final: 282 | es_ES |
| dc.title | Increasing energy efficiency by optimizing the electrical infrastructure of a railway line using fireworks algorithm | es_ES |
| dc.type | info:eu-repo/semantics/bookPart | es_ES |
| dc.description.version | info:eu-repo/semantics/publishedVersion | es_ES |
| dc.rights.holder | Es un capítulo de un libro de pago (no open-access) | es_ES |
| dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | es_ES |
| dc.keywords | Optimization of Energy Storage Systems.
Railway power systems.
Railway simulation.
Energy efficiency.
Nature-inspired optimization algorithms | es-ES |
| dc.keywords | Optimization of Energy Storage Systems.
Railway power systems.
Railway simulation.
Energy efficiency.
Nature-inspired optimization algorithms | en-GB |
