Operation and Maintenance is a critical factor in energy storage systems as availability is key to a successful business model and often required by contractual circumstances with customers or grid operators. Not only is non-availability lowering the revenue of a plant, it can as well causing liquidated damages or even harm business relationships on a ling term.
An battery energy storage system is complex and consists of many parts which in total requires a interdisciplinary team to cover all upcoming problems during O&M. From my time at Vattenfall in the maintenance of conventional power plants I experienced that the maintenance is limited nowadays to reactive maintenance. When a part has a failure, the asset manager reacts and mostly replace the part. In case of battery systems this methodology will not succeed on a long term as availability is a crucial factor. Here we will experience the advantages of predictive maintenance with machine learning and big data analysis to lear more about battery operational behavior and failure prediction.
Read an interesting article from energy-storage.news here
With a proof of concept, Engie and Connected Power have integrated their second-life EV storage system into the distribution system of TenneT in Rotterdam, the Netherlands.
More information on PV magazine: https://www.pv-magazine.com/2018/10/26/engie-launches-second-life-ev-battery-grid-services/