Keeping Blackouts at Bay

Better demand-side flexibility is required to prevent blackouts from occurring.

In Japan, the government has urged people in Tokyo and its surrounding area to use less electricity, as it warned that supplies will be strained as the country faces a heatwave.

In Milan, a series of blackouts left part of Italy’s capital in the dark for hours at a time, as power usage soared amid soaring temperatures.

And, in Australia, on June 15 this year the Australian Energy Market Operator (AEMO) suspended trading across the country’s east coast electricity power network as it faced an increasingly volatile situation.

AEMO was set up in 2009 and this is the first time the operator took such drastic action across the entire network that it manages.

There has been much debate and discussion on the causes ranging from the onset of winter to the war in Ukraine and maintenance shutdowns at power stations.

While policy makers, regulators and power generators grapple with the situation, consumers are being asked to better manage their consumption. The conversation is evolving from generating more energy to better managing the energy we produce.

With domestic consumption, energy transmission terminates at the premises of the end consumer. In the current situation, a lot is being asked of this often-neglected group. They are being requested to reduce consumption by shutting down appliances in certain times or use them outside peak periods. Customers have also been warned about potential blackouts.

Current policies around demand management are focused on industrial plants and other large energy consumers, and these are governed by clear policies and processes. Consumers meanwhile are bracing themselves for energy price hikes and power cuts.

Fortunately, technology has advanced and, when implemented, can give consumers more visibility and control over their energy usage. A good example is Sense  which has developed AI that runs on smart meters. Over two million Sense-enabled meters have been announced in the US and this technology is now coming to Australia. Their machine-learning algorithms can assess domestic electricity right down to the appliance level in real time.

Sense AI technology incorporates high-resolution processing that can be built directly into smart meters. Sense technology can give consumers real-time insights into energy usage down to the individual device level.

According to a directions paper released by the Australian Energy Market Commission (AEMC), only 25 per cent of premises in New South Wales, Queensland, South Australia and the ACT have a smart meter installed. The paper recommended accelerating the rollout of smart meters for households and small businesses, because digital smart meters will be a vital tool in the grid of the future.

If AEMO or the utilities put out a call to reduce power usage, Sense-enabled consumers know exactly what to turn down to have the greatest possible impact on their demand at any moment.

“The highest consuming discretionary devices can be identified, and consumers are able to turn off the appliances that have the greatest immediate impact on load, without disrupting their lives,” explains Michael Jary, Managing Director – International at Sense. “Consumers are not left to work it out themselves and don’t end up sitting in the dark.”

“Crucial to enabling these consumer benefits will be smart meter manufacturers ensuring that meters being made now are compatible with Sense AI technology,” said Jary.

It all comes down to device disaggregation which is referred to as the Holy Grail of energy management. It uses AI and data analysis to separate the whole-home electricity usage into device-specific individual consumptions.

Studies have shown that real time device disaggregation increases demand side flexibility. Sense-enabled homes were able to shift 4.5 times more load than homes that didn’t have it. Sense can even measure and verify that the reduction action took place as expected.

A recent study commissioned by the AEMC found that 73% of the respondents are interested in working out ways to save money on their electricity bill by changing how and when they use electricity. Their main way of lowering bills is to turn off lights, avoid leaving appliances on standby and looking for more efficient appliances.

As Sense can analyse high-resolution energy data, its benefits extend outside the home. For example, tiny voltage sags in the grid can be identified and are indicative of vegetation brushing overhead power lines.

Similarly, corrosion in transformers or other grid assets are apparent when applying Sense AI to high resolution energy data. Across a fleet of meters, it is even possible to geo-locate the source of the error by comparing those meters that experience the same anomaly against a network map.

To properly benefit from real time device detection and the potential of AI, Australia will need to ensure that the next generation smart meters become intelligent hubs for the home and form the basis for a flexible, cleaner grid.

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