A recent report from Canada-based energy consultancy Enverus Intelligence Research (EIR) said analyzing the optimal sizing and operation of battery energy storage systems (BESS) for large-load energy management can not only reduce energy costs but provide a source of revenue.
The study finds that hybrid battery configurations, combining behind-the-meter (BTM) and front-of-the-meter (FTM) strategies, can reduce total energy costs by up to 44%, with payback periods as short as 2.2 years, especially for industries with highly variable loads such as EV fleet charging and public infrastructure.
Juan Arteaga, principal analyst at EIR, told pv magazine USA that the motivation for the analysis and report was that they were seeing that loads were becoming more of a dynamic factor in the power markets. As a result, battery systems are no longer just a backup solution, they’re a strategic asset.
“Historically, loads would just draw power and that’s it,” he said. “Batteries with management systems behind the meter got smarter on when to discharge to reduce costs. But now they’re actually getting way smarter, and it’s possible to actually follow the generation profile on both sides of the meter.”
Arteaga explained that in certain solar-heavy grids like California it is already common practice to move consumption to the most productive parts of the day, when energy is cheapest. The battery is a great component for this because it enables commercial and industrial (C&I) customers to manage loads without affecting core business operations.
“We asked ourselves, ‘what if these customers want to be super smart and really optimize how big of a battery they need and how to operate that battery to minimize overall costs?’” Arteaga said. “And when we were at it, we wondered what if this battery can also be a source of an income; generating some profits to offset those costs. So, we went ahead and developed this algorithm to analyze how that would work.”
According to Arteaga, the algorithm performs a two-step optimization for battery capacity based on conflicting goals. One the one hand, you want to find the minimum cost of a battery. And then on the other, you want to find a battery that gives you the most revenue from the market. EIS analysts separate these two problems and iterate through them until they find what is the optimal battery size that satisfies both operational capacity and minimizes overall cost.
One result of these kinds of optimization analyses is they show that certain industries can get more creative about managing power usage than others. In general, Arteaga said, industries that have widely variable power requirements throughout the day or periods of high loads and low can use batteries to control costs.
For example, a business operating a fleet of EVs may have them out and about during the day and then have a heavy load recharging them at night. At the same time, a data center has a relatively flat load profile. What spikes occur do so at such close intervals that there is no real idle time for the batteries, which are primarily serving as a backup.
“The biggest opportunities are when the battery is sitting there most of the day doing nothing,” Arteaga said. “Then we can trade that idleness for participation in the ancillary services market. The battery is making money instead of doing nothing. When the load comes, where the spikes are present, the battery is able to discharge there and reduce those spikes.”
The Enverus BESS optimization algorithm shows that a hybrid BESS strategy combining BTM and FTM activities can improve energy costs for C&I customers, particularly in certain industries. Arteaga said the model can also be adapted for customers with on-site generation, whether it’s solar, wind, gas or hydrogen for that matter.
“There could be a really good investment opportunity there,” he said.
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