The challenges ahead for the collection of data are significant. Netinium reports that the Netherland’s largest distribution system operator, Alliander takes 3.5m meter reads per day across 2.6m meters.
“We are living in interesting times, I would say, with a lot of changes happening at the same time in society that all somehow impact our energy systems,” Ferry Cserép began in our Engerati webinar, “How can distribution utilities innovate? It’s all about data”.
Between local generation, the electrification of heating and transportation and local fixed and flexible energy storage devices, Cserép believes that the leveraging of smart meter infrastructure beyond billing is key.
Based on key learnings from its 20-year partnership with Alliander, Cserép presents key takeaways and use cases for data innovation in utilities.
The need for data is changing
With a current roll-out of 2.6m smart meters at a rate of 750,000 per year, Alliander was keen to leverage its data collection and analysis beyond billing.
Cserép explains: “When you start rolling out smart meters, the original intent is collecting billing data once every month. We initially forecast the amount of data that had to be collected, as well as the amount of times a DSO needed to go out and collect that data.”
The forecast showed a steady increase in data correlated to the volume of meters being deployed. However, in reality, what happened was a steep, sudden increase in data requests as time went on.
Cserép continues: “Somewhere along that line, we hit a critical mass of the amount of meters rolled out, which triggered all sorts of external parties to invest in systems that reap the benefits of smart meters, and request more and more data from smart meters to provide services for smart meters.”
Consumers and DSOs alike now wanted to see and understand more of the data that was being collected. He explains, “after that, not only did the consumers become interested in the data from smart meters, but also the DSOs realised that there’s a lot of data that could be useful for them to innovate on and improve their operational processes.”
Use cases for data innovation
This new interest in data deviated from Netinium’s forecast, and the shift in demand drastically changed how Alliander needed to treat and think about data.
Cserép outlines these changes in the following use cases:
 Advanced grid planning
Using data to derive models based on forecasts and estimates of how the advanced grid would look based on predictive analytics, it can help DSOs plan where to invest in new grid assets.
“By collecting data from smart meters,” says Cserép, “we are able to create a heatmap of potential power quality and voltage problems, and then create a probability chart based upon those models.”
Over time, as more smart meter data is collected, the probabilities can be tweaked and amended to continually improve accuracy.
 Insight in topology and outages in LV grids
Using smart meter data, DSOs can monitor and track better where their distribution networks are being used and connected to. This also allows them to identify, isolate and manage outages in a much more efficient, economic way.
“DSOs usually have the topology of their distribution network available in their geographical information systems, but it turns out that the reality is probably different from what is typically in the systems,” explains Cserép.
 Aging assets and predictive maintenance
By looking at the performance and conduction of service across the grid, smart meter data can also provide insight into how various assets are performing and degrading.
Cserép exemplifies this, saying: “If we are able to look at, for instance, voltages across lines from the distribution stations towards the homes, we can use that data to pinpoint failures on the lines, but also potential failures and their locations.”
 Technical and administrative grid losses
Better usage and monitoring of data can also prevent and detect fraud, a use which Cserép recognises all too well in the Netherlands, where power fraud and theft has been an issue.
“One way to do it is to have a meter at the transformer station, then have the data reads from all the meters in peoples homes. From that we can derive when there is a loss that is unexpected, but also pinpoint the exact location,” Cserép explains.
GDPR and shifting data behaviours.
However, Cserép clarifies, not all data is equal. He says, “we cannot use all of this data freely. Some of it is considered to be privacy sensitive, and the use of it would be subject to consumer consent.”
To combat this, DSOs have to balance between things that they are allowed to do and things that they want to do.
Netinium has invested considerable time into positioning itself well in preparation for GDPR, to ensure its solutions are airtight.
Cserép says, “we’ve been in discussion with regulators about how we can either change the way we use data to be GDPR compliant, or provide other innovations to help us provide data in a way so that it doesn’t have to break privacy regulations.”
Despite these new regulations, however, Cserép does not see data innovation as a lost cause. He suggests, “the key takeaway is that we can use smart meters in these different ways, but in order to do any data management we have to look at the ways we collect data across different systems.”
To do this effectively, he suggests utilities remember that different consumers and end-points have different data needs. To do this, DSOs have to reconsider the IT systems that they use.
To learn more about how best to manage and facilitate the delivery, analysis and management of heightened data levels, watch our Engerati webinar “How can distribution utilities innovate? It’s all about data”, featuring Ferry Cserép and insights from Alliander.