by Ruchika Deora, Program Director, The Centre for New Energy Technologies (C4NET)

Australia’s transition to a new energy future will not be a smooth one without a massive shift in operational and market management.

The rapid uptake of hyper- localised, consumer driven technologies is upon us. Current solar, heating and cooling, electric vehicle (EV) and storage trends, collectively known as Distributed Energy Resources (DER), require systematic management to ensure we maintain a cost-efficient, secure and reliable electricity supply that also supports our environmental objectives.

But the path to successfully integrating and accommodating these DER is littered with political hurdles, conjecture and technical and regulatory complexity. Traditional power system planning and assessment tools must evolve to better serve customer and market requirements.

This means industry requires new ways to ensure network and market stability. Thankfully, the recent democratisation of multiple data streams means that the opportunities to use detailed analysis to inform our system planning do exist.

However, access to reliable electricity consumption data will be key to ensuring that evidence-based decision making will guide the entire sector into our new energy paradigm.

Data access services

The Centre for New Energy Technologies (C4NET) has access to this energy consumption data as well as the experts to be able to model this data to provide useful insights to any interested party. Its Data Access Services now allow any interested group to request its aggregated data.

As a first step, we need to utilise all available evidence and data at hand to forge our pathway forward. These two terms are often used interchangeably but there is a difference and it is important to understand the nuance between the two.

The former is the narrative for defining and understanding where we have been and where the sector needs to go; from one-way delivery
of electricity to multi-directional power flows.

Data on the other hand is the instrument that enables and gives credibility to this narrative. Both are required to advance change in any industry, but for reasons still unknown, we often fall to one or the other, rarely leveraging them together to create a complete pathway for multiple stakeholders to accomplish our objectives.

Big data was originally associated with three key concepts: volume, variety, and velocity, better defined as how much, how many types and how fast. But recently, two arguably more important “Vs” have emerged – value and veracity.

Data itself can have intrinsic value, but can be worthless until that value is uncovered and applied. Equally, without veracity – how truthful is your data and how reliable it is – your data has no value.

In the past, detailed visibility of low voltage systems wasn’t necessary to efficiently manage the secure and cost-effective supply of electricity to consumers. But, as more consumers become generators and exporters of electricity, local power quality maintenance is essential in meeting policy and compliance objectives.

Confidence in network performance i.e. voltage management and line impedance, is fundamental for system and market planners to manage bi-directional power flows to meet customer needs.

It would not be a stretch to say that the current system of modelling growth and capacity is not keeping pace with the commercialisation of consumer technologies that influence power system operations. But it does not have to be so.

For instance, AMI meter data can inform what is happening on the network at specific times and locations, from how much electricity load is being exported onto or drawn from feeders and transformers.

Other new forms of modelling AMI data can assist in phase grouping of customers, topology estimates, impedance levels of distribution lines and service cables and identification of unmetered loads.

This level of visibility enables more uptake of new DER and renewable energy based on the capacity and capability of existing assets. It also helps guide infrastructure investment decisions based on real world information.

It really underscores that access to detailed data, from the source can and should be used to model, forecast and anticipate system requirements.

Putting the data to work

The question of who has access to accurate data can also define how an industry will evolve. Is data freely available such that different parties can create diverse narratives to inform transition? Or are there still barriers, whether perceived or real, to accessing information from various data holders?

In Victoria, we are not only fortunate to have a high penetration of smart meters, but also that the data from these smart meters is available to a variety of stakeholders. As a result, the data has been used to provide rich, rigorous insights on the future of the market and operational and technical requirements to support change in how our grid operates.

Interested parties such as community energy groups clamouring for data can now request their actual consumption by local government area or post code so that they can better understand commercial and retail options available to them.

Achieving greener energy independence is also possible through the assessment of NMI level consumption data. Others like the state government are using AMI data to inform policy development so that system-wide integration is achieved holistically and with customer, market, network, technology, operational and regulatory objectives in mind.

Meanwhile industry and researchers are collaborating on new ways of using data to forecast and model EV penetration, vehicle-to-grid
storage solutions, early fault detection, and digital network topology. The list goes on.

All of these examples illustrate the substantial return on investment in big data when you analyse and act on your data. So move forward on your path towards our new energy future by getting clarity with a visual analysis of varied data sets.

Explore the data further to make new discoveries. Share your findings with others. Build data models with machine learning and artificial intelligence. Put the data to work.

As an industry we still need to do more to fully maximise the value of data and how we create the evidence narrative to support change. Working in silos is no longer compatible with an integrated smart grid.

The collision of consumers acting as generators, aggregators supporting network and market operations, and rapidly changing policy and regulatory guidelines requires us to work together. Sector needs to invest in understanding how to manage millions of DER using 5 minute settlement techniques to operate a stable network.

It’s a collaborative discovery process that requires insightful analysts, business users, network planners, market operators, government,
regulatory bodies, compliance organisations and executives to ask the right questions, recognize patterns, make informed assumptions and forecast behaviour.

Only then will we have a roadmap that not only charts our pathway to our new energy future but creates the cross function and industry buy-in required to execute this future successfully. Data isn’t the solution to the energy transition, but it is the path to the solution.

To find out more about C4NET’s Data Access Services go to

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