Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/F4C97A37-1DE1-4825-80E1-23270A6EB97A | ||
| Year | 2021 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
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| Bibliographic Citation | M. Dakanalis and F. D. Kanellos, “Efficient model for accurate assessment of frequency support by large populations of plug-in electric vehicles,” Inventions, vol. 6, no. 4, Nov. 2021, doi: 10.3390/inventions6040089. https://doi.org/10.3390/inventions6040089 | ||
| Appears in Collections |
In recent years, plug-in electric vehicles (PEVs) have gained immense popularity and are on a trajectory of constant growth. As a result, power systems are confronted with new issues and challenges, threatening their safety and reliability. PEVs are currently treated as simple loads due to their low penetration. However, as their numbers are growing, PEVs could potentially be exploited as distributed energy storage devices providing ancillary services to the network. Batteries used in PEVs are developed to deliver instantaneously active power, making them an excellent solution for system frequency support. This paper proposes a detailed dynamic model that is able to simulate frequency support capability from a large number of PEVs, using an innovative aggregate battery model that takes into account the most significant constraints at PEV and aggregate battery levels. The cost optimization algorithm, which is the most time-consuming process of the problem, is executed only at the aggregate battery level, thereby reducing the computational requirements of the model without compromising the obtained accuracy. The proposed method is applied to the power system of Crete exploiting detailed statistical data of EV mobility. It is proven that PEVs can effectively support power system frequency fluctuations without any significant deviation from their optimal operation.
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