Improved utilisation of renewable energy by asset owners increases the total value realised over the life of the asset; this improves investment cases for future installations and contributes towards achieving net-zero. Accurate forecasting is critical to improving utilisation and gives visibility to the future output of the assets. An exciting project in the UK is demonstrating how the Tangent Information Modeller’s (TIM) scalable model building capabilities enables end users to get value from their individual assets.
Renewable asset owners generate green power at no unit cost. However, the initial investment case for the assets relies on the utilisation of this energy, which is intermittent. Realising value is particularly an issue for smaller scale assets where investment in expensive forecasting solutions is not practicable.
The Tangent Works TIM InstantML forecasting solution is being used at the Keele University Smart Energy Network Demonstrator (SEND) to explore how behaviour is affected by providing users with high quality forecast changes of the renewable power output. Not only does this reduce the net imported power of each asset owner, but it also has the effect of reducing the swings that Network Operators must manage due to the intermittent nature of renewable power. This improves the investment cases and the capacity for renewable assets to be connected to the grid.
The Demonstrator was established to deliver better energy management, reduce reliance on fossil-fuel derived energy and significantly reduce energy waste. Data from the campus infrastructure will be used with TIM’s award-winning forecasting solution to understand how the behaviour of users can be influenced through visibility of their electricity generation.
Dr Mark Turner, SEND Project Officer said “The ability to automatically create a unique model for each individual asset makes for a truly scalable solution to improve renewable energy adoption. The project will utilise the data and knowledge from the Smart Energy Network Demonstrator at Keele University, particularly in regard to weather forecasting”
“The SEND project (ref. 32R16P00706) is part-funded through the European Regional Development Fund (ERDF) as part of the England 2014 to 2020 European Structural and Investment Funds (ESIF) Growth Programme, and is available to ERDF eligible companies. The project is also receiving funds from the Department for Business, Energy and Industrial Strategy (BEIS).”