How outage analytics drives change management

As many electric utilities work through rising temperatures and storm season, annual conversations on outage management occur. These discussions often inevitably are linked to weather-related events, as seen in Michigan and Indiana. Of course, there is the occasional unusual outlier, like a monkey bringing down generation for the entire country of Kenya. Don’t worry, the monkey survived and is doing quite well.

For the last number of years, utility executives have dialed up the volume about how to improve outage planning, infrastructure, and in-event response time. These discussions have included a renewed focus on outage analytics. Analytics are hardly a new thing for utilities. Historic performance analysis, also known as business intelligence, has been around for quite some time. As well, storm playback, visualization, and simulation analysis have enabled utilities to tap data to better pinpoint root causes, eliminate response lags, and speed in-event reporting.

The difference now is that many utilities are integrating more sources of new and complex data into outage analytics—smart meters, sensors, distributed energy, mobile workforce, and social media, just to name a few. The expectation from utility executives seems to be that the enterprise analytics enabled by integrating all these high-volume and real-time data sources will significantly improve grid reliability, outage management, and customer communication.

As an example, consider the incorporation of distributed energy resources (DER) into outage management. As regulators continue push utilities around the globe to support a more decentralized distribution grid, DER will inevitably begin to have a much more direct impact on outage management. Provided that utilities have visibility to these assets, analysis of data from DER and related sources can provide new ways to avoid or significantly reduce outages.

DER typically produce extremely high volumes of data, and do so both situationally and in real time. A solution that taps DER for outages might have to include any combination of technology or equipment deployment, new work and business processes creation, or elimination of manual workflow. That is where the ripple effects of outage analytics can get tricky. The change management caused by new ways of integrating and analyzing data can be unforeseen and quite significant. For DER integration into outage management, data analytics can raise business strategy-level questions, such as:

• How significantly will DER impact restoration processes, systems, and budgets?


• What will customer agreements need to look like for the utility wishing to use DER when and how it needs to during an outage?


• What are the command and control requirements for DER and what systems will support them?


• What is the impact of DER growth on capital spending and related planning processes?


• If permitted, does the utility get in the business of DER maintenance, and what is the impact of that decision on workforce budgeting and training?


• Are there any 3^rd party vendors that the utility should partner with to support DER-related services, such as dynamic customer communications?


 

These are big questions involving many different work groups, systems, and processes. Correctly answering them requires people; the right ones with the right perspective at the right time. As utilities, and other asset-intensive businesses for that matter, embrace enterprise approaches to outage analytics, their leadership teams must take great care to ensure the correct stakeholders are involved.