Everyone knows that warm air rises and cold air sinks. Yet the implications of this apparently simple phenomenon are neither widely appreciated nor properly understood. The phenomenon produces vertical variations in temperature, known as thermal stratifications, that play a profound role in civil and environmental engineering. Thermal stratifications determine how much thermal and mechanical energy is needed to produce comfortable temperatures in the lowest parts of a room. By restricting the direction of air flow, thermal stratifications also determine the eventual fate of airborne pathogens and are therefore crucial in influencing the spread of viruses such as SARS-CoV-2 inside buildings. In reservoir management, thermal stratification is often biologically undesirable; hence energy is used for mixing to destratify the water. In water tanks, on the other hand, thermal stratifications are used as an effective means of storing solar-thermal energy. In all cases, the evaluation of appropriate design and control strategies requires understanding of how hot fluid and cold fluid interact to produce or destroy a stratification, which is an extremely challenging and open question at the forefront of current research in turbulence. This project will address the outstanding problem of predicting the thermal stratifications that are produced by non-uniform heating and cooling of a confined space and culminate in a design tool called [D*]stratify, which will enable the prediction and control of stratifications by identifying and using a limited number of key measurements. Our approach will transcend existing models by discovering and accounting for the energy behind turbulent plumes and thermal stratifications, coupling theory with real-time measurements. Utilising existing infrastructure, we will initiate a unique working laboratory for producing thermal stratifications, alongside direct numerical simulations of confined turbulent plumes. Our discoveries and modelling will facilitate the prediction, design and manipulation of thermal stratifications for both research and operation, whilst providing fundamental information about the underlying energy conversions.

To meet national greenhouse gas emissions targets and ensure our energy security, our energy system needs to undergo a radical transformation. We need to enhance the energy efficiency of the buildings stock, invent new methods to secure low carbon power, and develop ways of providing low carbon heat. Further, incorporating demand flexibility, where homes and workplaces modify their consumption at opportune moments, can reduce overall energy demand, increase the efficiency of grid operations, minimise the use of high carbon generators and increase the uptake of renewable energy sources. The optimal use of demand response can contribute 40 billion pounds in efficiency savings to the electricity grid. This potential has yet to be achieved, however, as it requires a re-envisioning of the energy system and new developments in building system intelligence. This innovation fellowship aims to jump start this transformation by developing new techniques to enable buildings to operate efficiently and provide services to the broader energy system. The FlexTECC control strategy will use a decentralised model predictive control framework to imbue buildings with the capability to minimise their own energy consumption but also offer their flexibility to an aggregator that can maximise the collective revenue. The decentralised approach is needed to minimise the problem complexity, provide autonomy to individual buildings and to enable a liberalised flexibility market. To realise the FlexTECC control strategy, three challenges must be overcome. The first is the challenge of perspective. Small energy consumers, such as homes and work places, are not perceived as capable of providing balancing services to the grid, due to their small size. Therefore control algorithms to supervise the collective actions of building energy systems under this paradigm do not exist, and need to be developed. The second challenge is that of implementation. The easiest pathway to ensure widespread use of the FlexTECC strategy is to develop its intelligence with existing hardware and communication protocols. Through collaboration with a nationally recognised building controls company, the FlexTECC controller architecture will be developed and experimentally validated using a large commercially operated building and two of the Loughborough University test homes. The third challenge is that of market potential. Different communities will result in different aggregations of building demands and therefore different flexibility offerings. Further, those offerings will garner different revenue potential depending on which market or markets are leveraged. To overcome this challenge a series of simulation studies will be undertaken to understand the revenue potential from different types of communities participating in various energy markets. The three-year fellowship will result in a tested and experimentally validated control algorithm that can minimise the energy consumption of an individual building but also provide energy services to the grid. Further, the market potential will also be assessed, providing knowledge to future aggregators on how to select buildings and energy markets that will maximise the overall revenue. The new field of decentralised control of urban energy systems, required to achieve these aims, will be brought to the forefront through an academic summit. Regulatory hurdles preventing the full implementation of flexible systems will be highlighted through an industry focused workshop on Flexible Cities. This robust research and engagement plan will lead to high impact research outcomes and begin the dynamic transformation of our energy system.

Non-domestic buildings account for approximately 18% of UK carbon emissions and 13% of final energy consumption. In contrast to domestic buildings, which can be well characterised by a few representative archetypes, the non-domestic sector is highly diverse incorporating a range of built forms to satisfy the needs of commercial, retail, public service, and other end-use sectors. These assets are also very long-lasting and it is estimated that 70% of the UK's current non-domestic buildings will still be in service in 2050. Consequently a major challenge is to design technologies and operating strategies that support a transformation of existing non-domestic buildings into efficient buildings compatible with the UK's energy and climate policy goals. Facilities managers must balance people (the occupants), place (the building's context), and processes (the installed equipment) in order to deliver agreed levels of building services to occupants, of which energy services are particularly important. However, experience has shown that the variability of occupant behaviour and long-term changes in the demand for energy services creates significant challenges for maintaining highly efficient building energy systems. Furthermore it cannot be taken for granted that future innovations will overcome these barriers. New technologies and business models - such as smart meters, heat pumps, phase change materials, real-time pricing, pervasive sensing, and more - will bring with them implicit assumptions about buildings and their occupants and facilities managers will again need to determine how they can be installed and operated effectively, in an integrated fashion. Therefore, although the future holds significant technical potential for improving the energy efficiency of non-domestic buildings, experience suggests that none of these innovations will remove the need for fundamental improvements in the energy management of non-domestic buildings, and indeed provide more opportunities for optimisation. The proposed three-year research project will therefore develop and demonstrate novel adaptive methods both to improve the energy performance of existing buildings and to ensure that these gains are preserved in the face of technological and societal change. This will be achieved by working with partners representing the education, commercial, and retail sectors, thus delivering immediate impact to the energy management of their buildings and also enabling the developed techniques to be sufficiently flexible for widespread use in other non-domestic buildings. The research will therefore help the UK transform its building stock to meet a range of energy and climate policy goals, while enabling the facilities management industry to demonstrate new products and services for domestic and international markets.

Non-domestic buildings currently generate 18% of the UK's carbon emissions, >40% of which is due to space heating/cooling. Innovations in control are predicted to save > 25% of this figure making a sizeable contribution to the UK's carbon reduction target. Such innovations, however, must also address building refurbishment as well as new build since the rate of building replacement is rather low. This proposal aims to effect a step change in the building energy management of non-domestic buildings by making model-predictive control (MPC) an economically-viable control technology for buildings. MPC is well-suited to controlling buildings, which typically have a large time delay between the application of an input and observable response. Importantly, MPC is based explicitly on optimisation as distinct from current building management systems, which use empirically-crafted rules. Currently, the generation and updating of the predictive dynamical model, which lies at the heart of MPC, has to be done manually by highly-skilled control engineers. Although MPC has been demonstrated to achieve energy savings >25% in non-domestic buildings in a research setting with hand-crafted predictive models, the cost of hand tuning these models is currently prohibitive for commercial deployment. We will use advanced machine learning techniques to automatically produce the predictive dynamical model from data acquired from the building-in-operation; hence we will capture key characteristics of the actual building, such as the profound influence of occupants on the building's energy performance. More than this, our approach will be able to periodically update the predictive model to accommodate the inevitable changes in building fabric, use and local environment, all of which will affect the building's thermal dynamics and hence its energy efficiency. To cost-effectively demonstrate the potential of the research idea, we will make extensive use of building simulation by computer to explore a diverse range of different building forms, weather conditions, and modifications. We will also develop a stochastic model suitable for use in the simulation of non-domestic buildings allowing us to to better account for the impact of building occupants on energy performance. We will supplement these extensive simulation studies with a practical demonstration on different real buildings, one of which will be a passive design school; controlling peak temperatures in passive design buildings is a known challenge particularly in the summer months. The overall outcome of this project will be to facilitate a step change in building control, producing an acceptable internal environment with the minimum use of primary, non-renewable energy. This derives from the fact that MPC is explicitly based on optimisation. As well as contributing to carbon reduction targets and greater workplace well-being, this will also produce significant cost savings for building operators. We will disseminate knowledge about MPC and its potential contributions to carbon reduction to the UK building services community using a variety of channels, including an end-of-project workshop.