Clock Icon - Technology Webflow Template
min read

GRIDSIGHT'S INSIGHTS Q3 2021 | Interval Consumption Data, Network Unbalance & Volt-VAr Learnings

Interval consumption data is freely available to all DNSPs and has significant value propositions.

At Gridsight, our mission is to accelerate the grid's transition to renewable energy and as we increase the number of DNSPs we're working with across Australia and New Zealand, we're increasingly discovering new insights that many in the industry are often not yet aware of.

So, we've decided to publish a highlights reel quarterly, in the hope that by doing so, we will help DNSPs navigate the transition to a distributed grid more efficiently and effectively than they would have otherwise.

Below you’ll find the most actionable data, network and customer insights that we discovered during Q3 of 2021. We hope that you find them useful! If you would like to learn more about any of the insights contained in this report, please reach out to us - we would love the opportunity to discuss them further with you.


Interval Consumption Data is Underutilised

Interval consumption data, specifically net load data from smart meters, is freely available to all DNSPs and has significant value beyond just billing. It can be used for a wide range of applications, such as DER detection and even power quality analysis.

By combining interval consumption data with machine learning techniques such as regression and classification, it is possible to identify and size behind the meter customer DER based on the shape of the load profile. This identification can be used to ensure GIS records are up to date and to assist in determining the level of remaining capacity available throughout the network.

The chart below shows a typical customer with residential solar and another customer with both solar and a battery. Notice the difference in the slope of the blue curve between 8:30 and 12:00 due to the battery charging from the solar system. With the right algorithms, interval consumption data can be used to both identify and estimate the installed capacity of solar and batteries.

Residential customer load comparison in Gridsight

We recommend that you investigate how you can better leverage your interval consumption data to improve DER registers and streamline network operations - whether that be by building an internal team, leveraging a third party application, or both!


Residential Solar is Increasing Unbalance

Voltage unbalance can occur when one phase has significantly more load or generation connected to it compared to the other two phases. We have discovered that unbalance within low voltage (LV) networks is widespread, with 12% of LV feeders experiencing significant voltage unbalance.

On closer inspection, we discovered that the feeders with highest unbalance had high penetrations of residential solar and that it was common for over 40% of installed solar capacity to be installed on a single phase. In the worst cases, 80% of installed solar was installed on a single phase, resulting in a difference in line-neutral voltage across phases of +10V!

While historically the distribution network has been built with enough headroom to withstand such levels of unbalance, the increasing prevalence of residential solar, as well as increasing demands from regulators to increase network utilisation, means phase selection for new connections needs to improve and re-balancing existing connections should be considered.

An example of extreme unbalance is shown below.

solar-induced voltage unbalance in Gridsight

It’s time for the industry to bin the term Short-Arm Linesman Syndrome and put the onus back on Network Planning to specify & verify exact phases for single phase loads and generators. Determining the optimal phase for new connections using network data will not only reduce unbalance but will also increase network hosting capacity and facilitate the implementation of non-network solutions such as dynamic operating envelopes.


Volt-VAr Mode is Often Disabled

In our previous edition of Gridsight’s Insights, we highlighted that there are many instances where residential solar systems are disconnecting from the grid due to overvoltage, resulting in a significant amount of value and renewable energy being wasted.

We explored this issue further and found that the majority of inverters that are disconnecting do not have ‘volt-VAr’ mode enabled. When volt-VAr mode is enabled, inverters will absorb reactive power when the voltage begins to rise too high, providing an additional layer of voltage regulation beyond what is possible with just active power curtailment or volt-watt mode (for more details see AS 4777.2:2020). An example of inverter induced reactive power absorption due to volt-VAr response mode is shown below.

inverter increasing reactive power absorption as voltage approaches 253V

Although newly installed inverters have mandated volt-VAr settings per AS 4777.2:2020, millions of systems were already installed before the standard was introduced in 2020, and most of these do not have volt-VAr enabled.

Being able to programmatically determine where these systems are located enables our clients to work with inverter owners as a proactive response to managing overvoltage issues. Specifically, if customers have volt-VAr compatible inverters, they are suggesting they contact their electrician to get volt-VAr mode enabled. If the inverter isn’t volt-VAr compatible, some DNSPs are offering to replace the inverter (reducing the energy lost as a result of inverter disconnections, while improving network performance).


Gridsight helps electrical utilities transition to a decentralised grid by generating actionable, AI-powered network insights. These insights enable utilities to dramatically reduce the network augmentation required to safely and efficiently support more residential solar, batteries and electric vehicles. Based on CEO Brendan Banfield's PhD research, Gridsight was founded in 2020 to accelerate the transition to renewables.

Brendan Banfield

Co-Founder, CEO

Passion for research and innovation related to integrating renewable energy technologies into distribution networks using data.