The introduction of the Advanced Metering Infrastructure (AMI) in electricity networks implies the existence of large volumes of data, which, with appropriate processing, interpretation and use can enable functionality related with resource planning, adaptiveness and fault-tolerance in electricity networks. For example, it is envisioned that with the right information in-hand it can be possible to (i) raise early warnings and react in emergency situations, (ii) to aggregate power where/when needed, (iii) to help customers/components make scheduling decisions for improved use of electricity power, and more. With the increasing volumes of data implied, the possibilities and challenges go hand-in- hand; namely, processing the data to produce information that can enable the above possibilities is a main challenge, which requires competence and new research in processing, including parallel and distributed/collaborative computing methods.
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