DEED research in Texas studies how to mitigate EVs’ deterioration of transformer life

by Peter Maloney
APPA News
April 14, 2021

The Bryan Texas Utilities (BTU) used a Demonstration of Energy & Efficiency Developments (DEED) student research grant from the American Public Power Association to support a student to analyze mitigation strategies for the potential deleterious effect electric vehicles could have on utility transformers.

With the adoption of electric vehicles expected to rise rapidly in the future, BTU wanted to look at the use of rooftop solar power and battery storage to offset potential degradation of transformers caused by the expected increase in electric vehicle adoption and charging.

Studies showing average electric vehicle adoption rates can be misleading, Mladen Kezunovic, a professor of electrical engineering at Texas A&M University and the education advisor overseeing the DEED project, said. It is more likely that electric vehicle adoption will not occur evenly and will be concentrated in certain neighborhoods. In those neighborhoods, utilities could see much higher loads on their distribution transformers, possibly even a doubling of loads, Kezunovic said. And higher loads lead to higher heat in a transformer, which can shorten the expected useful life of the equipment.

Using the DEED grant, which took the form of a $5,000 scholarship, Milad Soleimani, a doctoral student at Texas A&M, developed a series of calculations to study the effect of overloading on transformers and mitigation strategies to offset those effects. The DEED study ran from December 2019 to December 2020.

The case study considered a residential area with a transformer with a nominal power of 63 kilovolt amps (kVa) and a total solar generation capacity of all the buildings of 10 kilowatts (kW). The rated power of the battery storage inverters was 5 kW, and it was assumed that the electric vehicles only operate in grid-to-vehicle mode.

For the study, Soleimani used load data available from the National Renewable Energy Laboratory (NREL) on OpenEI. Solar generation was calculated using NREL’s PVWatts Calculator. Weather data was extracted from the Iowa State University’s Environmental Mesonet archive. And electricity price data came from the Electric Reliability Council of Texas records.

The case study looked at seven different scenarios, ranging from a baseline with no electric vehicles, solar generation or battery storage to a scenario with a high penetration of electric vehicles with no solar or battery storage to a scenario in which there is solar generation, a high penetration of electric vehicles and battery storage is optimized by considering both electricity prices and transformer loss of life estimates.

Among the results, Soleimani found that the loss of energy in the charging and discharging of battery systems increases total energy consumption and presents challenges to the sole use of battery storage to mitigate transformer loss of life.

The study found that using battery storage, both with and without solar generation, optimized based on electricity prices, but did not mitigate transformer loss of life and had a negative impact on utility profits. The most successful approaches in the study were those that modeled the optimization of solar and storage based on prices and transformer loss of life calculations.

“Utilities as the owners of the distribution transformers benefit from the transformer loss of life mitigation strategy,” Soleimani wrote in the DEED report. “In the long term, the lower expenses for the utility will lead to cheaper electricity delivery to the end consumer. Thus, utility and consumers are both benefitting.” There should be incentives from utilities for consumers to make the investment viable, he said.

Broadly speaking, Kezunovic said the DEED study looked at three broad strategies: staggering electric vehicle charging times to minimize load, using solar photovoltaic panels and battery energy storage to minimize increased loads on transformers, and a combination of the first two options that uses algorithms to reduce the loads on transformers. The third option proved to be the most realistic, but it requires an algorithm for optimization that is not available today, Kezunovic said.

Today, “there is a disconnect between utilities and customer owned resources,” Kezunovic said. Utilities need to gain a better understanding of what customer resources, such as solar panels and electric vehicles, can do to their systems, he said, “and customers need to get on board with what utilities want them to do” and maybe utilities could incentivize them to do that.