“In the dynamic world of energy storage, realistic projections and O&M assumptions lay the foundation for success. By embracing advanced analytics and machine-learning methods, we unlock the power of planning, optimize returns, and light the path towards a sustainable future.”
-Erik Egan, Vice President, Stem Consulting Services
Energy storage battery degradation and its impact on O&M costs are critical concerns for site developers and asset owners. While current industry practice relies on conservative estimates provided by OEMs, Stem offers an alternative approach that leverages years of operating data from their award-winning AI-driven platform, Athena®. By utilizing a company’s specific data and battery usage profile, Stem’s modeling allows for a more accurate total cost of ownership projections and O&M assumptions, leading to better planning and increased returns.
Understanding the Impact of Battery Degradation on O&M Costs
Battery degradation refers to the gradual loss of capacity and performance in energy storage systems over time. Several factors influence the degradation rate, including temperature, depth of discharge, charge rates, and cycling frequency. Deviations from expected degradation rates can significantly impact O&M planning, as it affects the system’s efficiency, maintenance requirements, and lifespan.
The Limitations of OEM Estimates
Most companies rely on OEM estimates for battery lifespans, which tend to be conservative. While this approach ensures a safety margin, it often results in leaving potential value on the table. By planning for a worst-case scenario, site developers and asset owners may overestimate O&M costs and miss out on revenue-generating opportunities.
Stem’s Battery Degradation Modeling Approach
Stem’s alternative modeling approach is founded on the vast operating data collected from Athena. Stem’s experts develop custom models that provide accurate projections of degradation rates, costs, and overall system performance by analyzing a company’s historical battery performance data and understanding their specific usage patterns and load profiles.The benefits to Stem’s approach include improved planning, maximized value, and reduced risk.
Improved O&M Planning
Accurate modeling of expected returns enables site developers and asset owners to optimize O&M planning. They can allocate resources more effectively, budget for maintenance and augmentation cycles, and make informed decisions about operational strategies.
Maximized Value Extraction
By avoiding overestimation of O&M costs, site developers and asset owners can capitalize on additional revenue opportunities. Stem’s modeling approach identifies the optimal use of the battery, ensuring maximum return on investment and better overall system performance.
Stem’s battery degradation modeling helps site developers and asset owners identify potential performance deviations early on. This enables proactive maintenance and augmentation strategies, minimizing downtime and revenue losses associated with unexpected failures.
Implementing Stem’s Battery Degradation Modeling
Stem has an established methodology based on extensive expertise and successful projects. This includes gathering your site’s data, consulting with Stem’s experts, and then putting the analysis to work.
Gathering Operating Data
To leverage Stem’s modeling approach, site developers and asset owners need to gather historical battery performance data. This data should include relevant information about usage patterns, load profiles, and environmental conditions.
Collaborating with Stem’s Experts
By engaging Stem’s team of experts, site developers and asset owners can take advantage of their deep knowledge and experience in battery degradation modeling. Stem’s experts will analyze the collected data and work closely with you to develop a comprehensive total cost of ownership projection.
Incorporating Modeling Results
Once the modeling analysis is complete, site developers and asset owners can integrate the insights into their O&M planning. They can optimize operational strategies, identify cost-saving opportunities, and make data-driven decisions to maximize returns on their energy storage investments.
Accurate battery degradation modeling is crucial for effective O&M planning and maximizing returns on energy storage investments. Stem’s alternative approach – leveraging operating data from Athena – provides site developers and asset owners with a comprehensive understanding of their batteries’ behavior and degradation rates. By embracing data-driven modeling, stakeholders can optimize O&M costs, unlock additional value, and mitigate risks associated with energy storage battery degradation.