
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Optimal Charging of Electric Vehicle Aggregations Participating in Energy and Ancillary Service Markets

Providing ancillary services through flexible electric vehicle (EV) charging has the potential to offer extra market benefit for EVs. EV aggregator controlling a fleet of EVs can play a significant role in managing the considerable EV charging demand and bid in the electricity markets. The increasing penetration of EVs has created the feasibility of participating in both the day-ahead energy market and frequency regulation market. This work presents a multi-market optimization model for minimizing the net operation cost of EV charging considering the benefit from performing frequency regulation. A two-level optimization algorithm for EVs controlled by the aggregator is proposed to determine optimal operation strategies of EV aggregations and the charging power of each individual EV. The optimization is able to merge revenue from frequency regulation with the cost reduction objectives of traditional EV charging management. The effectiveness of optimization algorithm is demonstrated by simulating EVs charged at the workplace and residential areas. The increased profitability of participation in the sequential electricity markets has been illustrated. Net operating cost of EV aggregations can be significantly reduced considering both capacity and energy remunerations in the regulation market and the charging demand in the energy market
- Tianjin University China (People's Republic of)
- Wrocław University of Science and Technology Poland
- Tianjin University China (People's Republic of)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).27 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
