Upside Energy, an award-winning start-up based in Salford, has been awarded grant funding to develop artificial intelligence (AI) for its innovative Virtual Energy Store.
The partnership project with Heriot-Watt University in Edinburgh will use machine learning and AI methods to manage a portfolio of energy storage assets to provide real-time energy reserves to the grid.
The project has been awarded a Knowledge Transfer Partnership (KTP) grant by Innovate UK to maximise the opportunities presented by the emerging energy demand response market.
Virtual Energy Store
Upside Energy’s aim is to create a cloud service that aggregates the energy stored in thousands of small energy devices in businesses and homes, such as batteries attached to solar PV systems, electric vehicles and uninterruptible power supplies (UPS), to create a ‘Virtual Energy Store’.
This store can then be used by the grid as a back-up power source, reducing the UK’s reliance on traditional power stations.
In return, the National Grid provides a cash incentive for providing extra capacity and Upside then redistributes this revenue back to the device owners.
By flexing their electricity demand to meet the needs of the grid through energy demand response, it is estimated that businesses could provide the equivalent supply of six new power stations by 2020, while reducing their own energy costs in the process.
Upside Energy has developed a substantial ensemble of algorithms that can manage demand response of difference devices in parallel.
The new grant funding will be used to optimise its existing algorithms using Heriot-Watt University’s specialist skills in machine learning and AI.
Dr Graham Oakes, founder and chief executive of Upside Energy, said: “This is a really exciting project.
“Our strategy is to work with academic partners to develop the intellectual property that will be at the heart of an intelligent energy system, one where resources are used carefully and thoughtfully and hence at low cost and with minimal impact on the environment. This partnership with Heriot-Watt is a great example of that strategy coming to fruition.”
Dr Valentin Robu from Heriot-Watt University added: “Demand response is emerging as a key technology to assure the stability of next-generation power grids, and there is an increasing need for smart control strategies that enable distributed energy storage assets to perform demand response.
“Techniques developed in the machine learning and distributed AI communities will have an increasing role to play in enabling these efforts.”