There has been a huge investment in micro generation from both customers and small scale providers, particularly in residential PV. Individual participation of these assets (offers to buy/sell/store energy) by micro/domestic scale agents in local, distributed electricity markets is currently a significant business and technological challenge in the UK's large-scale energy systems. A solution to enable energy trading between small scale generators and consumers that provides a compelling business case for storage and further penetration of embedded renewables is essential. New aggregators, that is, new market players who are highly adaptable in terms of dynamically organising Distributed Energy Resources (DERs), are emerging to provide a retail service to distributed groups of customers who could not manage to act in the energy market on their own. These aggregators would deal with requirements of the wider energy system by utilising diverse and multiple low carbon and renewable technologies for generation and storage to provide local/micro-grid solutions. However, there are significant barriers to the emergence of such entities which can be overcome by adoption of contemporary digital technologies. Our AGILE proposal sets out an integrated digital solution which can deliver suitable mechanisms to allow aggregators to offer the wider energy market bundled DER services of particular duration and value. To allow this, the preferences and descriptions of DERs, which form smart, micro contracts, will be articulated using an agent based model. Bids and offers will be enabled through integration with Distributed Ledger Technologies (DLTs) which will provide a trustworthy implementation of the scheme through a distributed database trusted by all agents. AGILE will examine the synergies between several permissioned, public, and hybrid DLTs as there are key questions about which type of ledger and related services is best for this elastic aggregator approach. An optimisation model will recommend particular configurations of DERs satisfying several portfolio optimisation strategies (financial, environmental and social welfare). The validation of preferred configurations of DERs is an essential step to ensure the feasibility of DER incorporation and a digitised, stylised IEEE network will be integrated into the digital solution to achieve this. Validation using a range of realistic network topologies will be performed to evaluate the effect on aggregator business models.

FlexNet has been set the goal of researching the future form of the electricity network. This is a great challenge because electricity networks are formed from long lifetime equipment that will often be in place for more than 50 years and which costs a great deal to replace. Much of the UK network was constructed in the 1960s and 1970s and falls due for replacement soon. This is both an opportunity and a threat. The plans for replacement must stand the test of time or future generations will face a large bill for making changes. We are at a point where the future of electricity generation is uncertain. We know that low-carbon energy is the objective but the network required to support offshore wind is very different from the network to support domestic-scale fuel cells. The key will be to plan, design and build networks that are sufficiently flexible to meet several quite different scenarios. There are limits to the flexibility though. First, flexibility generally requires more investment for which electricity consumers ultimately pay. Second, electrical networks are major projects that impact local communities and those communities' have important views on what technology is acceptable. Third, flexibility calls for a far greater level of real-time control of the network which poses challenges in analysis and implementation. FlexNet will research the technologies to provide flexibility, the market mechanisms through which investment is encouraged efficiently and the way in which public attitudes might shape what can be done. FlexNet is a consortium of universities, electrical network operators, equipment manufacturers and NGOs. The seven universities combine expertise in electrical engineering, economics and social science. The consortium builds on the work of its predecessor, FutureNet.

Investing in new European interconnection capacity is one strategy to integrate renewables and nuclear power stations in the electricity systems of GB and Ireland, by maximising their value through exports and meeting demand peaks through imports. This project aims to assess the value of UK interconnectors to the EU-27 and Norway, examining both the GB and the Irish Single Electricity markets, by investigating five hypotheses: 1. Expanding GB-linked interconnectors would reduce the cost of electricity for both the UK and the EU-27. 2. The operational value of interconnectors will be affected by post-Brexit market relationships (e.g. the GB relationship with the European Energy Union and the Irish Single Electricity market). 3. Balancing markets could be an important future source of revenue for interconnectors. 4. Previous interconnection modelling studies have misinterpreted spurious correlations caused by continent-wide increases in renewables and other system evolutions. 5. The optimal level of investment in GB and I-SEM interconnectors, and between Northern Ireland and the Republic of Ireland, in terms of both security and cost, will be affected by the outcome of Brexit negotiations. The ETM-UCL European energy system model and the ANTARES European electricity dispatch model are being used to assess the potential benefits of existing and new interconnection between the UK and the EU-27 and Norway, for a range of post-Brexit policy environments. The impact of interconnectors and renewables on electricity system stability is being assessed. The GCDCN model, adapted from neuroscience, is being developed to identify causal relationships between interconnection investments and price variations across UK and EU-27 markets. This provides a foundation for improving regulatory models and investment business case analyses.

Heating indoor spaces by burning natural gas accounts for ~30% of the UK's total CO2 emissions. Around 23 million properties are connected to the gas network. Each 1kg of gas burned delivers ~12kWh of heat and releases ~4kg of CO2. That cannot continue in a future net-zero UK and capturing CO2 at individual buildings is completely implausible using any known technology. Many consider that hydrogen should replace natural gas in the gas network. Technically, this is feasible. Hydrogen can be produced from electrolysis or from natural gas. In case of the latter, 'carbon-capture' methods can collect most of the resulting CO2 and pump that underground. However, distributing hydrogen through the gas network might not necessarily be the most sensible course of action in all cases. This project will answer the question about how best to use different parts of existing gas network in a future net-zero UK. Even with carbon-capture, producing hydrogen from natural gas does cause some CO2 emissions. Typically >5% escapes. Using renewable electricity to make 'green' hydrogen via electrolysis and then burning that in boilers delivers less than 7kWh of heat into homes for every 10kWh of electricity used. By contrast, using electrically driven heat pumps can deliver 40kWh of heat for every 10kWh of electricity consumed. Although there are other advantages to producing hydrogen for heating, it remains questionable whether this is optimal in many parts of the UK. It is very likely that a large fraction of the existing infrastructure will be used for distributing hydrogen across the country. However, some specific parts of the network could be better exploited in a different way. This project will explore the different possible uses for those parts of the gas network. All of these potential uses are motivated mainly by solving problems that would arise if heat pumping were deployed very extensively in the UK as the primary heating mechanism. One possible future use for parts of the gas network is to feed non-potable water into properties. This water could serve as the source of low-temperature heat to support heat pumps. A new variety of heat pump turns incoming water into an ice slurry and discards the slurry to melt again later. This 'Latent Heat Pump' (LHP) can extract a lot of heat out of cold water (12L of water provides ~1kWh of heat). That heat emerges from the water at about 0C and as a consequence, the LHP can have a coefficient-of-performance (COP) >4 even when the outside air is very cold. For most air-source heat pumps, the COP falls sharply in very cold weather and, for obvious reasons, the COP matters most in very cold weather. A second possible future use for the gas network is to serve as a return (collection) network rather than as a delivery (distribution) network. Here, the fluid returning through the gas network would be an aqueous solution of a chemical that was hydrated (mixed with water) at the property to release heat. This measure would be taken only in very cold weather. Calcium Chloride and Magnesium Sulphate are two very cheap salts that release heat when dissolved in water. There are other inexpensive substances that release large quantities of heat upon reacting with water. Finally, if water was being conveyed in the low-pressure tiers of the gas network, the high-pressure tiers of the gas network would be free for another use. A very attractive possibility here would be to use those parts as the pressure vessel for a compressed air energy storage system. That system would simultaneously be able to assist the electricity transmission system by doing a parallel transmission from North to South at times of high North-South power traffic. How acceptable each of these propositions is to key social stakeholders (including policy makers, prospective business, and public end-users) will be integral to their real-world viability, and so will be examined here also.

Overview: We propose a Centre for Doctoral Training in Data Science. Data science is an emerging discipline that combines machine learning, databases, and other research areas in order to generate new knowledge from complex data. Interest in data science is exploding in industry and the public sector, both in the UK and internationally. Students from the Centre will be well prepared to work on tough problems involving large-scale unstructured and semistructured data, which are increasingly arising across a wide variety of application areas. Skills need: There is a significant industrial need for students who are well trained in data science. Skilled data scientists are in high demand. A report by McKinsey Global Institute cites a shortage of up to 190,000 qualified data scientists in the US; the situation in the UK is likely to be similar. A 2012 report in the Harvard Business Review concludes: "Indeed the shortage of data scientists is becoming a serious constraint in some sectors." A report on the Nature web site cited an astonishing 15,000% increase in job postings for data scientists in a single year, from 2011 to 2012. Many of our industrial partners (see letters of support) have expressed a pressing need to hire in data science. Training approach: We will train students using a rigorous and innovative four-year programme that is designed not only to train students in performing cutting-edge research but also to foster interdisciplinary interactions between students and to build students' practical expertise by interacting with a wide consortium of partners. The first year of the programme combines taught coursework and a sequence of small research projects. Taught coursework will include courses in machine learning, databases, and other research areas. Years 2-4 of the programme will consist primarily of an intensive PhD-level research project. The programme will provide students with breadth throughout the interdisciplinary scope of data science, depth in a specialist area, training in leadership and communication skills, and appreciation for practical issues in applied data science. All students will receive individual supervision from at least two members of Centre staff. The training programme will be especially characterized by opportunities for combining theory and practice, and for student-led and peer-to-peer learning.