Abstract
The EV portfolio management is to develop an EV charging management algorithm in order to determine EV charging
schedules with the goal of utilizing renewalbe energy production for EV charging as much as possible and ensuring that EV
energy requirements for driving needs are met. According to the day‐ahead spot price pattern in the Nordic power market, the spot prices are normally low when there is a lot of wind power production. Therefore, a fleet operator based EV charging
scenario considering day‐ahead spot prices is proposed to achieve this goal. The developed EV charging algorithm is to
determine the day‐ahead charging schedules of a fleet of EVs in order to minimize the EV charging cost with EV energy
constraints taken into account. In order to investigate the benefits of the spot price based EV charging scenario, two more
charging scenarios have been studied as well, i.e. plug and charging scenario (dumb charging) and timed charging scenario
schedules with the goal of utilizing renewalbe energy production for EV charging as much as possible and ensuring that EV
energy requirements for driving needs are met. According to the day‐ahead spot price pattern in the Nordic power market, the spot prices are normally low when there is a lot of wind power production. Therefore, a fleet operator based EV charging
scenario considering day‐ahead spot prices is proposed to achieve this goal. The developed EV charging algorithm is to
determine the day‐ahead charging schedules of a fleet of EVs in order to minimize the EV charging cost with EV energy
constraints taken into account. In order to investigate the benefits of the spot price based EV charging scenario, two more
charging scenarios have been studied as well, i.e. plug and charging scenario (dumb charging) and timed charging scenario
| Original language | English |
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| Number of pages | 134 |
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| Publication status | Published - 2009 |