Electric Vehicle: There might be more to it than just a marketing gimmick.

More and more talks about electric cars and motorcycles are floating around every year. As more people are now agreeing that electric automobiles are environmentally friendly and green due to their zero-carbon emissions, the issue lies within the source of energy that is used to charge the batteries. In countries such as France and Germany, where a sizable portion of the electricity grid is generated by nuclear energy or even renewable sources, it might not be a major problem. In reality, coal is still used to produce electricity in the majority of the world. In the end, this only modifies the location of the fuel's combustion, at best. At worst, things could get even worse than with a traditional combustion engine depending on the efficiency of the power plant, coal quality, power transmission losses, etc.

Another point is that personal automobiles, at least in the U.S., account for 15% of overall emissions. Ships, aircraft, and other modes of freight transportation account for an additional 15%. The remainder of approximately 70% is made up of grid power, residential and commercial heating, and other accumulated sectors, referring to the United States Environmental Protection Agency (EPA). At least, looking at the emissions alone, a freight ship running on heating oil may have a much bigger impact on the environment than a highly efficient, state-of-the-art combustion engine of modern cars. From that perspective, it almost makes sense to say that the effort to electrify the whole automobile is a made-up urgency by the industry. Is that really the case?

It is safe to say that this argument may not be 100% correct. Interestingly, there are some findings that looked at the problem from a different angle and may shed light on why the electrification of the transportation sector, particularly automobile, plays a significant role in the plot to achieve energy transition than just emission reduction.

Introduction: Demand-side Flexibility

Energy markets, and specifically electricity markets, have a pressing need for greater flexibility, largely due to the constantly rising share of renewable energy sources in the energy supply. In addition to the current model of guaranteeing demand-supply alignment primarily through investments in supply and transmission infrastructure, demand-centric approaches are just as equally important, an approach that is referred to as demand-side flexibility. Demand-side flexibility is defined as a portion of the demand, including that resulting from the electrification of other energy sectors (i.e., heat, transport via sector coupling) that could be increased, decreased, or shifted over the course of a certain period. These approaches mean to facilitate the integration of Variable Renewable Energy (VRE) by reshaping load profiles to match VRE generation, reducing peak load and seasonality, and lowering electricity generation costs by shifting load from periods of peak demand to other times of the day (source: IRENA 2019).

EVs to Grid as Demand-side Flexibility Solution

Although demand-side flexibility comes in many forms (e.g., power-to-heat, power-to-hydrogen, smart and efficient appliances, electric vehicles, and industrial demand response), due to their unique nature and secondary impact on the demand side-flexibility, it is found that electric vehicles (EVs) can also serve as an alternative. Inevitably, the market of EVs had grown exponentially in the past several years. The report from BCG (2019) shows that by 2030, EVs (mild and full hybrids, plug-in hybrids, and battery EVs) will account for 50% to 60% of new-car sales and 21% to 27% of all light-duty vehicles (such as passenger cars and SUVs) on the road. Plug-in hybrids and battery EVs – two of the largest, most impactful vehicle types, will account for 20% to 30% of new sales and 7% to 12% of all cars and trucks in use. Since a single full electric vehicle’s energy demand approximately amounts to that of a single typical residential household, the charging power leads to an increase in the electrical demand. However, the batteries can be used as temporary storage, offering additional flexibility to the grid.

Load Shifting and Peak Demand Shaving Potential

To support the aforementioned argument, studies about demand flexibility analysis were already done based on two different real-world datasets, notably the Netherlands, and Norway. Both studies presented the potential for EV charging to be used as a resource for DR. It can be utilized to balance the grid, reduce the need for new energy infrastructure, and ultimately lower the cost of energy for consumers.

iMove and ElaadNL infrastructures in The Netherlands

A study by Develder et al., 2016 took two different charging facilities, owned or monitored by two companies, iMove and ElaadNL, each representing home charging and public charging infrastructure, respectively. The data is then clustered based on charging session times. The data from iMove identified two clusters which are charge near home (59.1%) and park to charge (40.9%). Meanwhile, three clusters are identified at ElaadNL which are charge near home (29.1%), charge near work (9.4%), and park to charge (61.5%).

Using statistical modeling, the session within each of the behavioral clusters in terms of the durations of the sessions, and the fraction of time that is used to effectively charge the car is analyzed. To quantify the demand response (DR) potential from aggregated EV charging, two main contributing factors are determined, which are (1) the number of connected EVs, and (2) their flexibility in terms of how much their charging can be shifted in time. The DR potential is quantitatively defined as a function of time of charging, and delta, which is the duration of charging.

Comparably, the charge near home cluster mainly provides flexibility at night-time, although it spreads out over a larger portion of the day during weekends. The charge near work is complementary and provides flexibility during the daytime, but mostly on weekdays. The smaller park to charge cluster also exhibits daytime flexibility, which is uniformly spread over the day during the week, and more peaked around early afternoon on the weekends.

Risvollan Housing Cooperative in Norway

The analysis of the second dataset is based on field data from a large housing cooperative in Norway with 6,878 EV charging sessions registered by 97 user IDs (Sørensen et al., 2021). The study compares the two charging power assumptions of 3.6 kilowatts and 7.2 kilowatts. Similar to the first case, there’s a difference in residential charging habits between private charging points (CPs), compared to the shared CP, and the energy flexibility potential is translated from the non-charging idle time between the EV connection time and the charging time (note: idle capacity is energy which could’ve been charged during non-charging idle times).

The study discovers that when private parking spaces have a CP, there is a sizable possibility for residential EV charging flexibility. The findings also lend credence to the idea that the main source of flexible electricity use in apartment buildings is EV charging. For policymakers and decision-makers who can offer incentives for CPs at private parking places and for charging energy management systems, this is a crucial lesson to learn.

Energy Transition: Scaling-up Renewable Energy Adoption while Maintaining Affordable Retail Price

To justify the impact of demand-side flexibility, a study on bi-level optimization problem by Qiu et al., 2018 using Mathematical Program with Equilibrium Constraints (MPEC), and Mixed-Integer Linear Program (MILP) tries to demonstrate that the time-shifting flexibility of the consumers may influence retailers’ cost and revenue. The case study was developed using a pre-set of data from a wholesale electricity market consisting of 7 electricity producers. To optimize their utility, consumers can respond to the retailer's time-differentiated price offers by moving their demand from periods of higher prices to periods of lower prices when they demonstrate a certain degree of time-shifting flexibility. In a deregulated market, the retailer adjusts the prices it offers during off-peak periods and increases them during peak periods in expectation of this response from the consumer in order to keep its revenue at the maximum level while satisfying the average retail price restriction. The ability to shift demand (later referred to as demand-shifting flexibility - α) may flatten the price fluctuation from retailers as a result of a flat profile of demand fluctuation.

Although the correlation between demand flexibility potential and demand-shifting flexibility – α is not explicitly provided, a particular flexible demand technology as previously mentioned is capable of achieving such economic benefit for consumers. On the retailer side, however, there may be an impact on the total revenue because some demands are shifted from times of higher prices to times of lower prices. This is arguably true if the retailer's operating cost remains the same. As the adoption of renewable energy intensifies, a lower operating cost is expected. The relationship between the retailer's revenue decrease and cost reduction will determine the impact of demand flexibility on the retailer's net profit. Presumably, a higher level of competition tends to increase retailers’ profits with demand-side flexibility incorporated.

With smart charging, EVs can provide demand-side flexibility by charging when prices are low, therefore following Variable Renewable Energy - VRE availability and avoiding charging during scarcity events when prices are very high, causing, among other things, less stress in the distribution and transmission grid. The paper from IRENA highlights the two main types of smart charging strategies, unidirectional control - V1G, and bidirectional control or vehicle-to-everything - V2X. V2X can be subdivided into vehicle-to-home - V2H, and vehicle-to-grid - V2G.

As an example, the potential saving in grid operating costs from the state of California through deep adoption of EVs is between $90 to $550 million with a traditional, time-of-use - TOU charging system, and $120 to $690 million with smart charging. Similar to utility-scale energy storage, the amount of curtailment of electricity from renewable energy production is lesser as more EVs are deployed - which, consequently, will reduce investment costs for energy storage.

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Reference

1. C. Fernández, and E. Taibi, “Demand-side Flexibility for Power Sector Transformation Analytical Brief,” IRENA. 2019. www.irena.org
2. G. Morales-España, R. Martínez-Gordón, and J. Sijm, “Classifying and modelling demand response in power systems,” Energy, vol. 242, Mar. 2022, doi: 10.1016/J.ENERGY.2021.122544.
3. D. Qiu, D. Papadaskalopoulos, Y. Ye, and G. Strbac, “Investigating the impact of demand flexibility on electricity retailers,” in 20th Power Systems Computation Conference, PSCC 2018, Institute of Electrical and Electronics Engineers Inc., Aug. 2018. doi: 10.23919/PSCC.2018.8442911.
4. A. Sahoo, K. Mistry, and T. Baker, “The Costs of Revving Up the Grid for Electric Vehicles,” 2019.
5. C. Develder, N. Sadeghianpourhamami, M. Strobbe, and N. Refa, “Quantifying flexibility in EV charging as DR potential: Analysis of two real-world data sets,” in 2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016, Institute of Electrical and Electronics Engineers Inc., Dec. 2016, pp. 600–605. doi: 10.1109/SmartGridComm.2016.7778827.
6. L. Sørensen, K. B. Lindberg, I. Sartori, and I. Andresen, “Analysis of residential EV energy flexibility potential based on real-world charging reports and smart meter data,” Energy Build, vol. 241, Jun. 2021, doi: 10.1016/j.enbuild.2021.110923.
7. J. K. Szinai, C. J. R. Sheppard, N. Abhyankar, and A. R. Gopal, “Reduced grid operating costs and renewable energy curtailment with electric vehicle charge management,” Energy Policy, vol. 136, Jan. 2020, doi: 10.1016/j.enpol.2019.111051.