Research on economic planning and operation of electric vehicle charging stations
| dc.contributor.advisor | Rehtanz, Christian | |
| dc.contributor.author | Liu, Jiayan | |
| dc.contributor.referee | Zdrallek, Markus | |
| dc.date.accepted | 2022-04-25 | |
| dc.date.accessioned | 2022-05-06T12:21:55Z | |
| dc.date.available | 2022-05-06T12:21:55Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Appropriately planning and scheduling strategies can improve the enthusiasm of Electric vehicles (EVs), reduce charging losses, and support the power grid system. Thus, this dissertation studies the planning and operating of the EV charging station. First, an EV charging station planning strategy considering the overall social cost is proposed. Then, to reduce the charging cost and guarantee the charging demand, an optimal charging scheduling method is proposed. Additionally, by considering the uncertainty of charging demand, a data-driven intelligent EV charging scheduling algorithm is proposed. Finally, a collaborative optimal routing and scheduling method is proposed. | en |
| dc.identifier.uri | http://hdl.handle.net/2003/40895 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-22752 | |
| dc.language.iso | en | de |
| dc.subject | Electric vehicle | en |
| dc.subject | Charging station planning | en |
| dc.subject | Charging scheduling | en |
| dc.subject | Distribution network | en |
| dc.subject | Bi-level programming | en |
| dc.subject | Genetic algorithm | en |
| dc.subject.ddc | 620 | |
| dc.subject.rswk | Elektromobilität | de |
| dc.subject.rswk | Ladestation | de |
| dc.title | Research on economic planning and operation of electric vehicle charging stations | en |
| dc.type | Text | de |
| dc.type.publicationtype | doctoralThesis | de |
| dcterms.accessRights | open access | |
| eldorado.secondarypublication | false | de |