Mike will focus on the need for utilities to become data-driven organizations in the era of the smart city, and on the challenges this transition will entail. The smart grid involves much more than just traditional top-down distribution, and managing energy under these conditions has become more of an exercise in information management than a static engineering issue.
Utilities can take advantage of the wide array of data sources in a smart city, applying analytics algorithms to them to gain new insight into customer behavior, exception usage, grid health and capacity demands. Socio-economic, geographic, weather, and even cultural data can be combined in new ways to help energy utilities more accurately predict demand and serve energy users.
Mike will also discuss how the combined analysis of historic and real-time data will allow utilities to anticipate future hot spots, which will allow them to proactively address exceptional demand conditions or disruptions to energy generation. This will be particularly valuable in managing the effects of unexpected weather on renewable generation.
Finally, Mike will shed light on how and why utilities should establish an open flow of information between their network assets, customers and field workforce. When it comes to network maintenance, for example, this approach will provide utilities with an up-to-date view of where and when works are needed, and allow them to schedule field maintenance dynamically and in real-time. Linking up the flow of data in this way will also give customers more visibility into service issues, and make it possible for utilities to instantly factor customer feedback and status updates into their field operations.