Distribution System Operation with Electric Vehicle Charging Schedules and Renewable Energy Resources

Gerardo J. Osório, Miadreza Shafie-khah, Pedro D. L. Coimbra, Mohamed Lotfi and João P. S. Catalão
Additional contact information
Gerardo J. Osório: C-MAST, University of Beira Interior, 6201-001 Covilhã, Portugal
Miadreza Shafie-khah: INESC TEC, 4200-465 Porto, Portugal
Pedro D. L. Coimbra: Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
Mohamed Lotfi: INESC TEC, 4200-465 Porto, Portugal
João P. S. Catalão: C-MAST, University of Beira Interior, 6201-001 Covilhã, Portugal

Energies, 2018, vol. 11, issue 11, 1-20

Abstract: Electric vehicles (EVs) promote many advantages for distribution systems such as increasing efficiency and reliability, decreasing dependence on non-endogenous resources, and reducing pollutant emissions. Due to increased proliferation of EVs and their integration in power systems, management and operation of distribution systems (ODS) is becoming more important. Recent studies have shown that EV can increase power grid flexibility since EV owners do not use them for 93–96% of the daytime. Therefore, it is important to exploit parking time, during which EVs can act either as a load or distributed storage device, to maximize the benefit for the power system. Following a survey of the current state-of-the-art, this work studies the impact of EV charging on the load profile. Since renewable energy resources (RES) play a critical role in future distribution systems the current case study considered the presence of RES and their stochastic nature has been modeled. The study proceeds with analyzing EV owners’ driving habits, enabling prediction of the network load profile. The impact of: EV charging modes (i.e., controlled and uncontrolled charging), magnitude of wind and photovoltaic (PV) generation, number of EVs (penetration), and driving patterns on the ODS is analyzed.

Keywords: distribution system; electric vehicle (EV); renewable energy resources (RES); stochastic programming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/11/3117/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/11/3117/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:11:p:3117-:d:182063

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().