"The adoption of renewable energy systems in commercial properties has been low in comparison to the residential market in the UK, due to reductions in subsidies and feed-in-tariffs which make investing in the technology financially unattractive to building owners. There is however a need for this situation to change as renewable generation sources are anticipated to play a significant role in enabling the UK to meet the ambitious emission reduction target of at least 80% of the 1990 level. Other technologies proposed to help lower emissions are electric vehicles and heat pumps, though both of these will further increase the load on the power system. There is an urgent need for innovative solutions to utilise existing assets while integrating energy storage asset in the power system to ensure security of supply while providing the owners of these assets with long-term savings and new revenue streams.

This project, a collaboration between QBOTS Technology Ltd and The University of Manchester (UoM), will design and validate a decision-support energy management framework for commercial buildings that will optimise multiple performance criteria, including self-consumption from local renewable generation sources, usage of energy storage systems, provision of grid support services, load shaping, economic costs and comfort, together with the standard objectives of controlling the indoor air quality and thermal environment. The decision-support framework will be validated using existing assets available at The University of Manchester to form a test platform (a blend of real-time simulation modelling using a high-fidelity Real Time Digital Simulator (RTDS) system to emulate appropriate fidelity renewable system models and the building power architecture, together with hardware-in-the-loop by interfacing a commercial 240 kW 180 kWh Siemens SieStorage battery energy storage system to the RTDS to enable the decision-support framework to be evaluated over a diverse range of commercial building operating schedules."