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In power systems, demand and supply always have to be balanced. This is becoming more challenging due to the sustained penetration of renewable energy sources. Because of the increasing amount of electrical vehicles (EVs), and the high capacity and flexibility of their charging process, EVs are a good candidate for providing balancing services to electric systems. We propose a stochastic optimization method for an EV aggregator that models the uncertainty of the imbalance price, the reserve prices and the probability of acceptance and deployment of reserves. The model results in an optimal charging and discharging strategy considering day-ahead purchase, imbalance trading and reserve bids. Unlike previous studies, the reserve bids consists of both a quantity and an optimal price. Experimental evaluation shows that the proposed stochastic optimization method results in lower costs than deterministic and quantity-only bid solutions.
|Title of host publication||2018 15th International Conference on the European Energy Market (EEM)|
|Subtitle of host publication||Proceedings|
|Place of Publication||Danvers|
|Number of pages||5|
|Publication status||Published - 2018|
|Event||15th International Conference on the European Energy Market, EEM 2018 - Lodz, Poland|
Duration: 27 Jun 2018 → 29 Jun 2018
|Conference||15th International Conference on the European Energy Market, EEM 2018|
|Period||27/06/18 → 29/06/18|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
- Electrical vehicles
- stochastic opti-mization
- reserve markets
- day-ahead markets
- mixed integer programming
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