Enhancing the energy performance of existing buildings in the UK is a vital step in the Government's pathway to net-zero carbon. If environmental targets are to be reached, R&D is required to understand the capabilities of low carbon technologies and how digital services can be used to better manage their energy use. In this context, novel building control approaches that can be derived from data-driven, cloud-based solutions is of high interest for building owners and operators who soon will need to upgrade outdated building management systems (BMS). Yet today there is limited implementation of such solutions due to 'hidden' installation costs, lack of standards and modularity and 'risk averse' attitudes in the building sector. Bridging the gap between the academic literature and real-world applications is hence paramount to support live implementation and explore the potential of greater connectivity.

Under this context, the DEMSIS project employs a supermarket as a case study and uses it as a test bed to implement in real-time a model predictive control (MPC) scheme to enhance HVAC and refrigeration systems; the two most energy intensive services in a supermarket which are responsible for 45-60% of a store's overall electricity usage. MPC schemes work by predicting how a system will respond to a control change over the next 12-24 hours, considering other relevant forecasts such as energy prices and weather data. By understanding these future states, it allows the system to pre-emptively prepare for, for example, high electricity prices or cold weather, hence reducing its overall energy and carbon usage. As well as developing this control logic, the required hardware and software infrastructure will be designed and deployed in the pilot store to allow for real-world testing of the proposed MPC schemes. The proposed modelling and software framework will be replicable across a wide range of commercial buildings, lowering the barrier to entry for many businesses across the UK. Furthermore, due to the flexible nature of MPC formulation the proposed approach could incorporate additional constraints related to demand-side management for the grid, e.g. ensuring power thresholds aren't breached during peak periods.

The challenge for researchers in this field is how best to integrate the abundant data being captured to coordinate the management of systems to reduce energy use in buildings. A combination of hardware components and software tools are required to update existing legacy control systems. If such upgrades take place, the academic literature suggests there is significant potential in enhancement of operational management by applying internet-of-things concepts to support real-time optimisation. In this project the researchers collaborate with a major food retailer (Sainsbury's Supermarkets) to implement cutting edge solutions that give insights into how future buildings should be operated.

The DEMSIS project has as key objectives to:
1. Provide recommendations on the best hardware and software solutions that are compatible with existing controllers (e.g., HVAC).
2. Quantify the business case for implementing such novel solutions in a commercial building by conducting multiple tests in the supermarket.
3. Outline the technical and commercial barriers building operators are facing to implement smart control schemes.
4. Propose new key performance indicators that provide information on how heating and refrigeration systems are performing.
5. Give insights on how control cloud-based solutions can support the UK power system with regards to demand side management and smart-grid applications.

Findings from the project will support enabling a cost-effective transition towards smarter digital services for the built environment. Transferring knowledge to key stakeholders in academia, industry, and policy makers responsible for the decarbonisation of the property sector.