Imagine this scenario: the clock strikes five. Employees all over the city get out of work only to head home and simultaneously plug in their electric vehicles (EVs) for charging. While it may not seem like a worst-case scenario, this can equate to the load on the distribution grid accelerating from 40 to 100 miles per hour at lightning speed, and if that doesn’t leave the system in ruins, it would at the very least be extremely costly to recover from.
This brings us to our present-day challenge. As EVs approach the tipping point of economic affordability and take off in popularity, we must quickly integrate fast charging stations within the power grid to supply all these vehicles. Currently, there are no controls in place—at the grid edge level or at a large-scale system level—that can minimize congestion or offset peak demand. Distribution system operators (DSOs) have to keep up with the needs of the fleet operators that support the infrastructure needed to support EVs. These EV chargers, which are one category of distributed energy resources (DERs), can also be used to export power back to the grid. Currently, it’s estimated that approximately 96 percent of EV charging is performed at home or at the workplace [1], which underscores the issue at hand.
According to National Renewable Energy Lab's (NREL) Electrification Futures Study, a comprehensive analysis of the impacts of widespread electrification across all U.S. economic sectors, by 2050, EVs could contribute to a 33 percent increase in energy use during peak electrical demand, which is already the costliest period of the day to supply power.[2] It’s also expected that fleet operators will begin to accommodate medium- and heavy-duty vehicle charging loads (buses, delivery vehicles, etc.), which will exceed existing grid operation constraints.
Increasing DERs present two main distribution grid challenges. First, voltage drops and the thermal overloading of transformers and cables, which also have an impact on fault current levels and the network.[3] Second, discerning between fault current from overload current on the distribution system with DERs adding a whole new dimension of complexity.{4]
Generally, distribution feeders use radial design configurations and over-current based protection schemes are set for the unidirectional flow of fault currents. DERs on the other hand introduce bidirectional power flow that can contribute to fault currents in both directions. When DER power is injected in distribution systems, the protection schemes, which are designed for unidirectional flow, fail to provide the adequate protection coordination.[3]
To tackle this issue, protection and coordination studies resulting in specific protection schemes can be utilized in a number of classical and novel approaches. These approaches are typically utilized to implement an adaptive or static protection scheme involving primary and backup relay protection for a distribution grid. The adaptive technique involves settings that are dynamic (group settings on microprocessor relays) and will adjust, whereas the static settings are fixed (electromechanical) and won't adjust based on changing fault current limits due to the addition of DERs. Usually, the adaptive protection scheme involves the placement of a fault current limiter in series with the DERs to block the fault current during a fault condition.
From the fleet operator’s perspective, the National Renewable Energy Laboratory (NREL), in partnership with other industry leaders, is involved in the development of new power conversion hardware based on advanced materials like wide-bandgap semiconductors, and new controllers and algorithms that are ideal for online scheduling and real-time control.[3] In a grid capacity market, it’s valuable for fleet operators to utilize the online scheduling features and introduce improved charging schemes where the main objective is to avoid energy imbalance. Usually, more accurate data is provided to the fleet operators to accomplish this. There are also an increasing number of machine learning algorithms that have been developed to support optimal fleet charging scheduling allowing fleet operators to judge whether they need to reschedule the charging plan based on the utility and risk analysis.[3] A lot of that is made possible by the fleet operator determining an aggregated EV charging profile with the use of linear programming algorithm technology. As for real-time controls, one can assume that the EVs will charge according to the plan; however, if normal technical operation of the grid is compromised, fleet operator management can be overridden by the DSO operation, such as using a load shedding scheme [3] where coordination between the fleet operator and the DSO is of utmost importance.
To meet the future demands that EVs will place on distribution grids, a lot of preparation, planning, and compromises will be required. This will involve participation from all stakeholders that play a role in vehicle-grid integration including DSOs, DER operators, and the owners of vehicle-to-grid-capable EVs. The costs of failing to do so will mean instability within the distribution grid, leading to incorrectly operating protection schemes, islanding of DERs from the grid, and ultimately outages for both commercial and residential consumers. We can get ahead of this and avoid the EV danger zone. The answer is simple: implementing new protection and control schemes and refining existing ones at the grid level. We can help!
1 “Technical & Design Guidelines For EV Charging Infrastructure — #CleanTechnica Report”, CleanTechnica, published February 16, 2019, https://cleantechnica.com/2019/02/16/technical-design-guidelines-for-ev-charging-infrastructure-cleantechnica-report/
2 “Grid coordination opens road for electric vehicle flexibility”, National Renewable Energy Laboratory, published August 4, 2020
3 Hu, Junjie, You, Shi, Lind, Morten, and Østergaard, Jacob, “Coordinated Charging of Electric Vehicles for Congestion Prevention in the Distribution Grid”, IEEE Journals & Magazine, March 2014
4 Singh, Manohar, “Protection coordination in distribution systems with and without distributed energy resources-a review”, Protection and Control of Modern Power Systems, published July 21, 2017, https://pcmp.springeropen.com/articles/10.1186/s41601-017-0061-1
