Leveraging smart meter data analytics for proactive grid management


With grid management proving a perplexing conundrum, smart meter data management continuous to prove the way forward for ensuring optimised control and efficacy for utilities.

In a recent webinar on smart meter data and leveraging data analytics to inform grid management, Tobie DeVilliers, Head of Network Intelligence for the Australian power utilities, United Energy, CitiPower and Powercor, touched on various use cases for smart meter data analytics.

During the broadcast, titled Using Analytics to Proactively Manage the Grid & Work Smarter, DeVilliers spoke to Gary Kessler, Senior Product Manager for Itron, on the experiences of United Energy, CitiPower and Powercor on how to best use such data to bolster operations efficiency.

DeVilliers spotlighted the most immediate and obvious use case to be expediting procedures.

“The most obvious is … the moment the power goes off, the meters say [that power has been lost] and sends out a message… This helps identify where the problem is on the network. We’ve also built an outage verification system, which watches the data, and only the true outages [are registered].”

The practice of using smart meters to proactively register these outages has enabled early detection, and the location of outages, resolving up to 26% of cases without the need for customer calls. In Australia, “knowing where to go and send the truck,” is critical information regarding voltage management. Australia has seen a rapid increase in residential rooftop solar installations, which makes voltage management increasingly difficult to coordinate.

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Automated applications

United Energy developed a tool to clearly identify a specific transformer, existing penetration and the need for additional load. This fully automated application process uses smart meter data to perform load flow calculations and check for voltage breaches and any phase or transformer overloads.

This tool calculates the maximum customer export. If the customer requests more than what the network can handle, the installation is approved based on a reduced export capability into the network.

In this way, it is hoped that utilities will streamline the onboarding process for customers by enabling them to see what will happen if they integrate their solar generation systems into the grid.

“To keep voltages under control and maximise solar throughput, we built a DVMS (dynamic voltage management system) to look at what every customer is experiencing. It organises each group of customers into a voltage control zone,” which enables heightened insight into voltage management and customer experiences.

DeVilliers emphasized how this enables a heightened level of insight into near real-time energy consumption, accurately indicating the on-the-ground experience of the consumer. This information, which is fed back into an analytics platform, allows the utility to work out what the most appropriate voltage control setting would be for those particular customers.

It is also fed back to SCADA (supervisory control and data acquisition), then back to the voltage regulators and any necessary adjustments can be made.

DeVilliers notes how this entire process, from analysing what the smart meters see to adjusting the control back to the smart meters through the network, takes up to seven minutes.

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Types of voltage settings

According to DeVilliers, there are four types of voltage settings that are currently being implemented, which consist of:

  1. Normal mode
    This mode is used when maximising solar connections, new connections and exports for the customer. It provides extensive edge room on the high-voltage side and keeps customers from dropping off on the low-voltage side.
  2. Demand increase
    This is when the market operator reports network stress, due to minimum demand conditions.
  3. Occasional test to flush out all the non-compliance solar inverters, their manufacturers and installers
    DeVilliers stated how this was introduced as a result of new inverter settings: “With our network analytics control system, we can increase the volts, push the inverters over their limits, see how they respond, and (use this to help) identify manufacturers who provide non-compliant inverters into the market as well as installers who can configure non-compliant converters.”
  4. Voltage conservation mode
    This is the case where there is an incredibly high load, load shedding is a necessity and voltage requires conservations to reduce loads.
Voltage control points are configurable per voltage control zone. Courtesy Itron.

The boon of analytical metering

In the midst of such extensive monitoring and voltage management, DeVilliers stated how smart meter data and its accompanying analytics have been a significant boon.

“We sit with a few regulators that are not monitored. There’s no communication (for half of them). There are no alarms if they aren’t operating the way they should… A good tool was using an analytics platform and seeing what our customers are seeing for each of the voltage regulation zones. We (then) work out what the set point should be.”

With all of this information at hand, DeVilliers stated how the utility is then able to place alarms on these regulators, monitoring such behaviour and notifying the control room with speed.

This in turn can allow for easy notification of any problem, enable a crew to be dispatched and attend to a grid issue prior to consumers being troubled.

Damage control

DeVilliers stressed the importance of this level of analytical insight for improving the responsive processes for field crews sent to coordinate damage control and mitigate potential faults.

“Meter data is sent with a serial number and two minutes later they get all the information necessary – on the meter, on the network topology, on the last days’ voltage current power factor profile for that customer as well as the substation or transformer.”

This forms a powerful tool for field crews to gain an awareness of what’s happening on the ground. “We also send them a dispatch with a notification on all the supporting information from the analytical platform to disseminate what we’ve seen so they don’t have to request information.”

While this is happening, affected consumers are sent a notification to keep them updated. “If there are special alarms we request the data and evaluate the status to see how bad it is, disconnecting the customer (if absolutely necessary).”

According to DeVilliers, for this, a turnaround time has been between three to 20 minutes, which he considers a big step forward.

This type of information use has also allowed United Energy, CitiPower and Powercor to see big improvements in shock resolution. In particular, 76% for United Energy and 64% for the latter two.

For a more in-depth look into how smart metering can improve the efficiency of utility operations, make sure to register for the on-demand webinar, Using Analytics to Proactively Manage the Grid & Work Smarter, hosted by Itron.