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Providing a cyber-secure E-mobility ecosystem

ELECTRON
Both the energy sector and the transport sector are going to confront significant challenges within the years to come. As a society, we are past the point of having the luxury to think of decarbonization or pollution reduction as something optional. It is vital that novel technologies and modern solutions are established and deployed so as to attain the demanding goals that were set out by the National and European policies such as for instance the European Green Deal. All the above argue in favor of the electric mobility forming an important building block for the energy systems of the future. Thereby, being a novel and flexible resource at the disposal of system operators (SOs) [1]. Specifically, Distribution System Operators (DSOs) are key entities when it comes to the management of the contribution/impact that the electric vehicles (EVs) have for the power systems. This is because the DSOs have gathered significant experience in the course of the years when it comes to the management of multiple EV Charging Stations (EVCSs) which are connected to their DSO networks throughout Europe. When it comes to planning and developing the distribution network, these processes necessitate analysis and system modelling, which also involve advanced estimation methodologies based on demand forecasts tools. These are utilizing metering data exhibiting a substantially high level of granularity and bottom-up aggregation of various load categories. DSOs make use of such factors and parameters in order to provide predictions on the future load impacts on the electricity grids [1]. Having all the above in mind, it is necessary to reiterate that this transformation to a more sustainable and viable electricity power system requires the establishment of new ways of network operation. In this context, the EVs and the EVCSs become flexible resource. Nevertheless, as has been studied, simultaneous charging of many EVs can potentially have harmful consequences for the power grid. The SOs have an interest in keeping the load on grid components at reasonable levels in order to protect grid components (such as transformers and electric lines) from damage and overheating, which might result in reduced component lifetime and earlier maintenance requirements [2]. In this context the Charging Station Operators (CSO) need to employ “smart charging” functionalities and strategies in order to keep the simultaneous charging of EVs limited (by limiting the amperage, or wattage for instance) and thus protecting the grid and its associated components from overloading. Specifically, studies have found that via Smart Charging strategies, it is possible to keep the stress on the grid within the grid limits. Via smart charging, it is possible to constantly monitor real-time charging relative to the available grid capacity [3].

Figure 1. The EVs as an interconnected energy resource within the smart cities [4]

A proactive analysis of the potential impact that a big number of EVCS will have on the transformers will assist the DSOs in the provision of input regarding the placement of EVCSs and the planning of investments. This, will therefore aid towards limiting the costs entailed in grid reinforcement, which are estimated to be of the order of several billion Euros in the case smart charging is not put into practice [3].
Cybersecurity in the energy infrastructure and the smart grid has become a main source of distress recently. There exist plenty examples such as for instance, the Colonial Pipeline attack, the Solarwinds Hack, Stuxnet, the Ukraine attack, etc. As has been recently studied, the power grid operation can be disrupted by compromising high wattage IoT (Internet of Things) devices. Emerging IOT ecosystems such as the EV ecosystem are vulnerable to cyberattacks due to weak encryption, insecure data transfer, guessable passwords, insufficient privacy protection, as well as a lack of secure update mechanisms [5]. Therefore, the EVs are a cyber-physical attack vector against the power grid, due to the fact that the EV ecosystem incorporates multiple IOT technologies and inherits their associated vulnerabilities. Charging of EVs, when note scheduled properly can lead to high peak loads and even to degradation of grid performance. By hacking into the EV system, and taking advantage of the vulnerabilities, an adversary can lead an attack against the power grid. Due to the EV’s load profile, it is ideal for an attack that aims to disrupt the grid operation [5].
To that respect, cybersecurity platforms such as ELECTRON can protect the EV and EVCS related infrastructure and thus become a great asset towards ensuring the protected and safe operation of the power grids, both in national and international level. By setting out security alarms, ELECTRON can notify the security operators in time so that they in turn inform the CSOs and the DSOs and thus result in pre-emptive measures and protection of the grid from the imminent cyberattack. More specifically, ML intrusion detection models are being utilized in order to detect imminent attacks on EVCSs and Charging Station Management Systems (CSMS) operation, warn the operators and then mitigate the attack and stop its adverse effects on the EV charging experience.

References:

  1. Gallego Amores and I. Losa, “E-mobility deployment and impact on european electricity networks. Innovation actions needed in the context of the european green deal,” CIRED Porto Workshop 2022: E-mobility and power distribution systems, Hybrid Conference, Porto, Portugal, 2022, pp. 651-655, doi: 10.1049/icp.2022.0789.
  2. Sevdari, L. Calearo, P. B. Andersen, and M. Marinelli, “Ancillary services and electric vehicles: An overview from charging clusters and chargers technology perspectives,” Renewable and Sustainable Energy Reviews, vol. 167. Elsevier BV, p. 112666, Oct. 2022. doi: 10.1016/j.rser.2022.112666. Available: http://dx.doi.org/10.1016/j.rser.2022.112666
  3. Zweistra, S. Janssen, and F. Geerts, “Large Scale Smart Charging of Electric Vehicles in Practice,” Energies, vol. 13, no. 2. MDPI AG, p. 298, Jan. 07, 2020. doi: 10.3390/en13020298. Available: http://dx.doi.org/10.3390/en13020298
  4. https://www.deiblue.gr/
  5. A. Sayed, R. Atallah, C. Assi, and M. Debbabi, “Electric vehicle attack impact on power grid operation,” International Journal of Electrical Power & Energy Systems, vol. 137. Elsevier BV, p. 107784, May 2022. doi: 10.1016/j.ijepes.2021.107784. Available: http://dx.doi.org/10.1016/j.ijepes.2021.107784