An EU-funded project has developed technologies for use in smart grids which help consumers manage and minimise their energy consumption, as well as enabling electricity suppliers to match supply with demand.
The 'Energy-saving information platform for generation and consumption networks' (ENERSIP) project focused on developing tools to collect and analyse real-time information on energy consumption and generation.
By providing energy suppliers and consumers with real-time and forecast information about energy consumption, electricity supply and demand could be made to match each other more closely – reducing waste and improving reliability.
ENERSIP partners collaborated on the development of an open platform that provides a suite of energy monitoring and control services designed to improve the flexibility and responsiveness of the electricity grid.
“Our platform and services were designed to pave the way for near real-time generation and consumption matching in residential and commercial buildings and across whole neighbourhoods,” said Dr Leire Bastida, ENERSIP’s project coordinator.
ENERSIP harnessed technologies such as sensors and wireless communication devices for monitoring the electricity consumption of home appliances. Algorithms were applied to predict energy demand, and control systems employed that can switch off appliances and switch on generation systems.
The project’s strategy was three-fold: the realisation of high energy-efficiency through improved co-ordination, convenient management of resources on the grid and altering users’ behaviour by giving them accurate feedback and advice.
The project also therefore involved changing consumer behaviour and educating people through the Internet and social networking to change people’s energy habits.
Central to ENERSIP’s achievements is the communication between every device inside a consumer’s house. To this end, the team developed a set of smart plugs, used to connect appliances to power sockets, in order to monitor electricity consumption.
The consumption data is sent wirelessly in real-time to a ‘concentrator’, which collates the data and sends the information via the Internet to the local energy provider or distributor.
“Consumption data is absolutely key,” explained Bastida. “You can begin to analyse it, spot patterns and, most importantly, begin to make predictions."
From there you can take an appropriate action.
ENERSIP built a Web platform so households could visualise their consumption and optimise their electricity usage against supply and unit costs. This platform provides users with advice on how to reduce or optimise their consumption. It does so based on its neighbourhood knowledge and predictive capabilities.
For example, by letting users programme the washing machine via a microchip in the plug to run at 03:00 rather than during peak demand at 20:00.
The system was tested in two pilot trials, and the project demonstrated through simulations a theoretical energy saving potential of up to 30 per cent.