In the rapidly evolving world of battery energy storage, accuracy matters. Whether it’s powering a grid during peak demand or maximizing returns in electricity markets, knowing exactly how much energy your system has left isn’t just helpful—it’s critical.
That’s why we’re excited to share the next leap in battery intelligence: Powin’s New State of Charge (SOC) Algorithm. This upgrade transforms how we estimate available energy in our battery systems—delivering improved accuracy, reliability, and operational value to our customers.
What Is SOC, and Why Is It So Important?
State of Charge (SOC) is like a fuel gauge for your battery system. It tells you how much energy is currently stored and available for use. But measuring SOC—especially in large-scale systems using lithium iron phosphate (LFP) batteries—isn’t as simple as checking a meter. Voltage-based methods, which have been widely used, can mislead operators due to the flat voltage profile of LFP cells, especially between 20% and 80% charge.
Misestimating SOC can lead to either leaving usable energy on the table or overdrawing and risking performance. That’s where Powin’s New State of Charge (SOC) Algorithm changes the game.
How Powin’s New SOC Algorithm Works
The new SOC Algorithm introduces a smarter, data-driven approach to energy estimation. It utilizes a Kalman filter to blend estimates based on two methods:
- Coulomb Counting – Tracks how much charge goes in and out of each cell (like a running tally).
- Machine Learning Estimate – Instantly assesses estimated energy based on voltage, temperature, and current, leveraging a model trained on years of real-world battery performance data.
By combining these two insights, the algorithm produces a much more accurate picture of the true energy available.
But we didn’t stop there—Powin’s new algorithm also shifts from estimating SOC at the string level to doing it at the individual cell level. This is crucial because even slight differences between cells can add up to significant errors in large systems. By starting at the cell and building up, we account for “stranded energy” caused by imbalance and improve system-level insight.
From Cell to Site: Recent field research confirms that this bottom-up approach leads to a dramatic reduction in error rates, outperforming earlier string-level estimation methods in over 80% of real-world cases.
And the financial implications of improved accuracy are just as compelling. Joint research by Powin and Tierra Climate—analyzing a 101.5 MW / 203 MWh LFP battery system in ERCOT—revealed how SOC precision directly affects system performance and revenue:
- For systems performing energy arbitrage, every 1% increase in SOC error results in a 0.82% revenue loss
- For ancillary service-heavy operations, the impact is lower but still meaningful—about 0.20% revenue loss per 1% SOC error
- Each 1% SOC error also leads to a 1.2% reduction in effective usable energy capacity
- Most importantly: overestimating SOC causes nearly double the damage in lost revenue and capacity compared to underestimating
These findings show why accurate, cell-level SOC estimation is more than a technical upgrade—it’s a business imperative.
What’s New—and Better
Powin’s New State of Charge Algorithm offers a significant improvement over its predecessor:
- Average error dropped from 10% to 3% at the string level
- More accurate estimates of both charge and discharge energy
- Built-in awareness of battery health (State of Health, or SOH) to ensure degradation is accurately factored in
This means less guesswork, more trust in your system’s performance, and ultimately better decision-making.
What This Means for Customers
As we roll out Powin’s New State of Charge Algorithm, here’s what our customers can expect:
- More precise charge and discharge metrics in kWh especially helpful in energy market participation
- Lower reported max SOC in cases of cell imbalance—not a problem, but a more realistic view of usable energy
- Consistent data across the system—from cell to inverter to site
For operators, the result is higher confidence in available energy and improved system utilization, especially in real-time and market-driven environments.
Built for the Real World
Powin’s New State of Charge Algorithm has already been quietly running in the background at most Powin sites for over 6 months—and the results speak for themselves. It’s a smarter, more adaptive algorithm designed for today’s energy needs, and tomorrow’s grid challenges.
Stay tuned as we continue rolling it out across our platform, along with updated documentation and UI enhancements to support your operations.
Because when it comes to powering a cleaner future, precision is power.
Larissa Conrad, Product Manager at Powin
Blake Rector, Markets & Optimization, Principal at Powin
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