Impact of electric vehicles on the expansion planning of distribution systems considering renewable energy, storage and charging stations
Energy storage systems (ESS) have adopted a new role with the increasing penetration of electric vehicles (EV) and renewable energy sources (RES). EV introduce new charging demands that change the traditional demand profiles and RES are characterized by their high variability. This paper presents a...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universidad de Castilla-La Mancha |
| Repositorio: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/20433 |
| Acceso en línea: | http://hdl.handle.net/10578/20433 |
| Access Level: | acceso abierto |
| Palabra clave: | Clustering technique Distribuiton system expansion planing (DSEP) ESS EV charging demand Renewable energy |
| Sumario: | Energy storage systems (ESS) have adopted a new role with the increasing penetration of electric vehicles (EV) and renewable energy sources (RES). EV introduce new charging demands that change the traditional demand profiles and RES are characterized by their high variability. This paper presents a new multistage distribution expansion planning model where investments in distribution network assets, RES, ESS, and EV charging stations are jointly considered. The charging demand necessary for EV transportation is performed using a vehicle model based on travel patterns. The variability associated with RES along with the demand requires the incorporation of uncertainty, which is characterized through a set of scenarios. These scenarios are generated by the k-means++ clustering technique that allows keeping the correlation in the information of the uncertainty sources. The resulting stochastic program is driven by the minimization of the present value of the total expected cost including investment, maintenance, production, losses, and non-supplied energy. The associated scenario-based deterministic equivalent is formulated as a mixed-integer linear program, which can be solved by commercial software. Numerical results are presented for an illustrative 54-node test system. |
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