Energy conservation is perhaps the most pressing environmental and geopolitical issue of our time. Modern living standards depend on finding more sustainable uses of power.
The 2015 Paris Agreement commits signatories to actively reduce their emissions. But these promises are empty without all levels of society actively pulling together to reduce their energy usage. But relying on individuals to massively change their behaviours is not a feasible strategy. Effective change will be ushered in by technology.
This is where Smart Energy comes into play.
Smart energy is a collective term for so-called intelligent technologies that cover the entire value chain of the energy industry: from energy generation to storage, transmission and consumption control.
Anyone with a smart meter in their home is already playing a part in the shift towards smart energy. Encouraging, right? On its own, this won’t be enough to reach net zero by 2050. But these devices are just one part of a larger transition across the whole industry.
Let’s explore how technology can answer the biggest question marks surrounding smart energy. We’ll work through the big opportunities, the factors holding progress back and the potential solutions for clearing these obstacles.
With gas peaking stations becoming less economically viable, the stage is set for the rise of distributed generation. This is where generation and storage are decentralised across a network of smaller, grid-connected devices known as distributed energy resources (DER).
DERs harness renewable sources like wind or solar, with their outputs aggregated by Virtual Power Plants (VPP). VPPs are, in essence, computer networks that imitate the functions of traditional plants without taking up physical space. The VPPs turn these energy sources into the power we all use.
Unfortunately, a tangle of differing national regulations saps distributed generation projects’ financial attractiveness.
Fortunately, smart technology can clear these obstacles. Data filtering can ensure consistency between assets and operators. Predictive modelling can be deployed to allay market anxieties. Granular AI solutions can forecast individual DER’s outputs. These tools also work on a larger scale to forecast the mix of power sources set to flow into people’s homes.
The smart energy chain functions as a network of interconnected sensor and control devices. This runs from the supply side through DERs to VPPs, all the way down to customer-facing utilities like meters. The Internet of Things (IoT) is the glue that holds it all together.
This huge proliferation of web-enabled devices is a major cybersecurity headache. Hackers targeting critical points in the chain could bring an economy to its knees overnight. Proper network maintenance and optimisation are obviously essential, which makes poor national governance an even scarier prospect. States need to take their responsibilities to analyse and monitor network efficiency very seriously.
This mass of devices also creates vast oceans of data to store and process. Prudent data controllers will be the heroes of the smart energy age.
While some countries have already made great strides, smart energy provision remains patchy. Governments and utilities providers will need to accelerate the rollout of efficient consumer tools like smart meters and heat pumps.
European energy markets frequently find themselves in situations of over- and undersupply. To balance supply and demand, nations must trade across borders (and even between internal regions).
Automated dashboards allow governments and suppliers to track performance against service-level agreements on dashboards. This data then feeds into AI-generated forecasts that help all parties look ahead with confidence.
Another trend will be harder to solve technologically. Government subsidies for domestically produced green energy can make renewable production cost-effective. However, they can also cause international tensions. In late 2022, the EU and the US clashed over green subsidies in the US’s Inflation Reduction Act that the EU perceives as discriminatory. There is no tech shortcut here; these are political problems that will require deft political solutions.
For the first time in decades, European countries have called on their populations to restrain their energy use. Governments and suppliers are now in the business of flattening peaks and managing scarcity.
In the UK, the National Grid ESO’s new ‘Demand Flexibility Service’ pays businesses and individuals to reduce electricity consumption during peaks.
This initiative would be impossible without intelligent tech. Smart meters automatically validate customers’ actual energy use data in real time so that discounts can be paid out digitally.
All this information helps anticipate future demand and consumption capacities – yet another use case for data-driven AI models.
Solar, wind and small hydro all play their parts in the distributed generation model. So what’s the new tech model for storing this energy and getting it to end users? One word: microgrids.
As you’d expect from the name, microgrids take the principle of the electric grid and scale it down to serve a smaller geography, such as a hospital. They can connect to the main grid and to other microgrids. But they can also run independently when needed.
Microgrids also efficiently orchestrate these energy sources. Humans, fallible as we are, may not always know when to switch between these inputs for optimal output. No bother; there’s an algorithm for that now.
Data and predictive analytics tools will tell controllers when to store energy in batteries, while energy consumption will be closely monitorable in real time, all the time.
There are more than five reasons why we’re strongly optimistic about the transition to sustainable energy. The prevailing technological winds are blowing us closer and closer to achieving net zero. But there are still many miles to go.
Endava’s software helps smart energy pioneers generate, store and distribute green power. Get in touch to find out more.
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