Insuring an electrified future: Predictive battery analytics for system operators and their insurers 

As the world races to decarbonise, battery energy storage systems (BESS) are growing in importance for greening electricity grids and ensuring a stable supply of clean energy. BESS facilities, largely powered by lithium-ion batteries, can store renewable energy from solar and wind to be deployed at future dates. In 2022, over USD 5 billion was invested in BESS, with expectations that the market could grow to USD 150 billion by 2030.

Battery analytics providers play a key role in supplying data- and algorithm-powered solutions that offer a more efficient, in-depth way of assessing the performance and safety of the burgeoning BESS sector – also benefitting those who insure the owners and operators.

For insurers, such insights are essential to build “a detailed and accurate understanding of the health, safety and performance of battery systems, and to assess risk, set premiums and develop products that reflect the true risk profile of BESS installations,” says Manuel Scheibel, Vice President of Energy, EMEA and Asia at TWAICE, a battery analytics software firm.

Battery energy storage systems are still a nascent sector. That said, predictive battery analytics, assisted by artificial intelligence and machine learning, are already analysing data from BESS installations to help operators maximise their battery systems’ performance and lifecycles, while maintaining the highest safety standards.

As Schiebel explains, these tech-first solutions provide precise metrics on the key battery parameters, such as state of health, state of charge, and voltage or temperature spreads. TWAICE’s software analyses troves of battery systems data in near real time to assess the state of health, safety and degradation of the batteries. It does so by “identifying trends and anomalies and predicting performance with high precision,” he says. 

This “predictive maintenance and alerting” enables operators to reduce the risk of incidents − ranging from battery failure and thermal runaway to system downtime and operation in critical conditions. “It also helps optimise maintenance schedules and extend battery lifespan, ultimately enhancing the overall safety and reliability of the systems,” Scheibel adds.    

“Should an issue arise − such as a rise in temperature that grows into a safety threat − BESS operators are immediately alerted and can resolve the issue before it spirals out of control.”

Compared to conventional battery management systems, predictive battery analytics provide more detailed and granular insights. For example, issues such as cell imbalances or thermal management challenges can lead to underperformance in battery components. With advanced analytics, operators can monitor and analyse performance and safety concerns more effectively, allowing them to “dig deeper into individual components to diagnose the exact problem and its severity,” Scheibel says.

These advances have the ability to mitigate risks for BESS operations and to enhance relationships between insurers and BESS owners. For BESS operators, the ability to predict and prevent failures can “reduce the frequency and severity of claims − leading to more sustainable and profitable insurance practices and optimised policies for both sides,” Scheibel says. For those providing the insurance coverage, battery analytics offers a better and deeper understanding of battery risks − meaning better decision-making and the easing of claims management through structured and actionable insight to battery asset data. 

The energy storage industry is maturing into a well-established field, with advances in both battery technology and the analytics software that tracks such systems.

Sodium-ion batteries are now stepping up to challenge low-cost and lightweight lithium-ion batteries. Analytics providers like TWAICE are adapting their software to reflect industry trends. TWAICE recently released a simulation model for sodium-ion batteries that enables operators to compare the performance and degradation of these next-generation batteries to current battery technology, like the lithium iron phosphate (LFP) or nickel manganese cobalt (NMC) batteries used in energy storage systems.

But even as the world sees more large-scale energy projects being developed and deployed, Scheibel notes that the major barrier to adoption of battery analytics for insurers is a lack of awareness.