The Influence of State-of-Charge Estimation Errors on Electric Vehicle Aggregator Benefits in Frequency Containment Reserves

Chaowanan Jamroen, Dulpichet Rerkpreedapong, Sanchai Dechanupaprittha, Poria Astero

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)
64 Downloads (Pure)

Abstract

In recent years, variable renewable energy sources (RES) have been integrated into electricity generation to reduce reliance on fossil fuels. RES integration into conventional power systems diminishes rotational inertia, causing frequency fluctuation vulnerability. Following the rapid increase in electric vehicle (EV) sales, an EV fleet can contribute to an automatic frequency reserve service in balancing markets through an EV aggregator. However, the benefits of an EV aggregator directly depend on the energy availability of each EV in an aggregator, represented by the state-of-charge (SoC). In the wider literature, SoC estimation is conventionally calculated using the ampere-hour (Coulomb counting) method. However, this approach is vulnerable to estimation errors, such as initial SoC and power measurement errors, that can positively or negatively affect aggregator benefits. Although previous studies have examined several ways to maximize aggregator benefits, none has explored the effect of SoC estimation errors on aggregator benefits. Therefore, this study aims to preliminarily explore the influence of SoC estimation errors on aggregator benefits in the frequency containment reserve (FCR) market. The regulatory framework and the FCR market are modeled in the European context. The simulation results demonstrate that SoC estimation errors affected the FCR provision period and forced charging activation, resulting in positive and negative changes in EV aggregator revenues.
Original languageEnglish
Title of host publicationEUROCON 2023 - 20th International Conference on Smart Technologies, Proceedings
PublisherIEEE
Pages478-483
Number of pages6
ISBN (Electronic)978-1-6654-6397-3
DOIs
Publication statusPublished - 6 Jul 2023
MoE publication typeA4 Conference publication
EventInternational Conference on Smart Technologies - Torino, Italy
Duration: 6 Jul 20238 Jul 2023
Conference number: 20

Conference

ConferenceInternational Conference on Smart Technologies
Abbreviated titleIEEE EUROCON
Country/TerritoryItaly
CityTorino
Period06/07/202308/07/2023

Keywords

  • Estimation error
  • Electric vehicles
  • Production
  • Europe
  • Simulation
  • Power measurement
  • Renewable energy sources

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