Our electricity grids may be getting smarter — there’s now a whole sector devoted to smart grid solutions — but they’re still limited when it comes to dealing with the various ways people generate their own power.
The traditional electricity end-user can now produce at least some of the energy they need to power their home using solar panels and other renewable energy technologies that use feed in tariffs (FITs). But it’s inefficient. Complicated. A European Union-funded research project called Scanergy hopes to provide a scalable and modular system that will improve the process.
In the UK, solar power capacity doubled in 2014
The great thing about renewable energy sources is that they can typically be exploited on a micro scale by consumers looking to cut their electricity bills and help the environment at the same time. In sun-drenched Australia, where renewable energy accounts for around 14 percent of the nation’s power supply, more than 1.4 million homes and businesses had installed solar panels by the end of 2014.
In Belgium, Scanergy team member Mihail Mihaylov tells iQ that 10 percent of households produce a portion of their own energy. And even in the UK, where sunny days are considered cause for mass celebration, solar is making a real difference — total solar power capacity doubled from 2.8GW to 5GW in 2014 thanks to investments in rooftop panels and larger-scale solar farms.
So everything’s good, right? Actually no.
The trouble is that you get new complexities and inefficiencies when homes and businesses are producing power as well as consuming it. Some of this renewable power being put back into the grid goes to waste because the tools to measure and trade them (which typically take the form of tariffs) are insufficient.
Today’s smart grids aren’t actually that smart.
Scanergy pays customers a Bitcoin-like digital currency
The Scanergy project proposes a way around this with a real-time automated market trading system called NRG-X-Change, which is loosely based on the stock exchange. This exchange system checks the supply of renewables and the overall demand for electricity in a given neighbourhood via its smart meters every 15 minutes, then automatically brokers trades with other neighbourhoods for any excess or shortfall.
It pays a Bitcoin-like digital currency the researchers call NRGcoin to those who feed energy back into the grid according to actual electricity usage rather than predicted usage.
Under the proposed system, Mihaylov explains, “the price follows the law of supply and demand.” So-called energy “prosumers” would then want to shift their consumption patterns as much as possible to fit the inverse of the broader consumption curve — to maximise profit, they’d try to consume more power when supply is high (and thus price is low) and less power when supply is low.
“On a global level, this behaviour will spread demand to flatten the demand curve and reduce the need to fire up emergency coal peak power generators, which are both costly and pollutant,” Mihaylov says. He notes also that reducing the peak demand lowers stress on grid infrastructure, which would lower operational costs and thereby shrink your energy bill.
Smart grid technology could ultimately shrink your energy bills
Scanergy won the best demo award at the International Conference on Autonomous Agents and Multiagent Systems in Istanbul in May. The demo used featured a model replica of a 62-home “typical” Belgian neighbourhood complete with an electrical substation and tiny solar panels that drew power from a spotlight overhead. Conference participants could “install” new panels and affect the weather in the neighbourhood and then observe in real time how these actions affected energy supply and demand (and by extension prices).
The team are now preparing to deploy their system in a larger test environment with greater complexity in its smart grid. Mihaylov is confident this will go smoothly, as Scanergy was designed from the outset to be completely scalable and modular.
The project is due to complete next year, after which point we’ll hopefully see the algorithms that manage our real-world energy supply and demand get smarter. — Richard Moss (@MossRC)
Photo credit: Main image, sandro/Shutterstock