VIDEO: Predicting battery lifecycles with AI and machine learning

By Solar Media Staff
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Energy-Storage.news proudly presents our latest webinar with HMS Networks, on the role of cloud-based analytics in optimising battery lifecycles and asset performance.

Batteries for stationary storage applications usually have design lifetimes of between 10 and 15 years. But even batteries produced by the same machine and on the same day show substantial differences in their aging behavior.

With BESS playing an integral role in the transition to renewables and the long-term sustainability of our energy grid, strategic battery asset management and monitoring deployed assets are key to reducing operational risks and maximising profitability.

This webinar is for project leaders of BESS systems, asset managers, owners and operators who want to accurately track and predict battery lifecycles, safety, performance, and aging.

It explores explore how to build a data-driven foundation for BESS asset management using cloud-based battery analytics, how to leverage existing data from battery management systems (BMS) and differentiate the role of the BMS from analytics.

Speakers in this webinar:

Matt Shustack, business development manager, Americas at HMS Networks

Yuan Lee, business development manager, EMEA, at HMS Networks

Jan Figgener, battery expert, ACCURE Battery Intelligence

Moderator:

Andy Colthorpe, editor, Energy-Storage.news

You can also access the recording on-demand on the site (registration required), at the link here.

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