With increasing opposition to building new transmission lines, transfer of bulk energy is going to be a major challenge in the UK and in many parts of Europe. Examples include the transmission link from the north of the UK to the load centres in the south and the corridor importing hydro power from north of Norway to the load centres near Oslo. It is therefore, absolutely critical that the existing power transmission assets are fully utilised by loading them much closer to their capacity. To ensure secure operation under such heavy loading, the dynamic performance of the system needs to be improved through appropriate control of voltage and power flow using the flexible ac transmission systems (FACTS) devices. It is often difficult to obtain accurate information about all the components (e.g. loads) of a power system which poses fundamental limitation on conventional model based control design. In the above context, this project aims at designing and validating a self-tuning control scheme for FACTS devices that rely solely on the measured signals and thereby, obviate the need for accurate system information. Such controllers are designed independent of the system operating condition and therefore, need no retuning with changes in system configuration. Use of more than one feedback signals from strategic locations, available though wide-area measurement systems (WAMS), can potentially improve the effectiveness of the FACTS controller. Hence, the control design needs to be formulated in a multi-variable framework. The performance of the controller would be validated in real-time through hardware-in-loop (HIL) simulation employing a test bench, emulating the behaviour of large power systems, and a commercial control simulator. The proposed project essentially integrates FACTS with WAMS and could potentially provide the developers and user of both these technologies a new edge.

This project focuses on a radical change to chemical manufacturing with a view to effective step changes in environmental sustainability and in circularity of materials. We shall focus on the emerging electrochemical sector which is expected to grow strongly and within which there are many opportunities for the deployment of digital technologies to underpin system design and operation. In response to this call, we have united a cross-disciplinary team of leading researchers from three UK universities (Imperial College, Loughborough, and Heriot-Watt) to create a digital circular electrochemical economy. The chemical sector is a "hard to decarbonise" sector. Its high embedded carbon comes from two aspects: (1) the intensive energy use; and (2) the use of fossil feedstock. Therefore, the decarbonisation requires the substitution of both two with renewable energy (electrifying the chemical processes) and feedstock (e.g., H2O, CO2). We foresee a closer integration of the electrical energy system with the industrial chemistry system, with the former providing reducing energy formerly available in fossil fuels and which enables the processing of highly oxidised but abundant feedstocks. The intermittency of renewable electricity supply and the economic benefits of flexible processing and closer integration between these two sectors will give rise to opportunities for new digital technologies. These will enable improved design and operation of emerging electrochemical processing technologies and provide new pathways to chemical building blocks (e.g. olefins) and fuels. The integration of the sectors also provides opportunities for cost savings in the electrical system through improved flexibility and demand management. We propose three work packages (WP) to look at the challenges at different levels, and finally integrate as a whole solution: - WP1 Digital twins of key electrochemical operation units and processes. - WP2 Digitalisation of the value chain encompassing the integration between the chemical and electrical systems - WP3 Policy, Society and Finance, including business models to capture value generation opportunities from industrial integration

The international offshore energy industry currently faces the triple challenges of an oil price expected to remain less than $50 a barrel, significant expensive decommissioning commitments of old infrastructure (especially North Sea) and small margins on the traded commodity price per KWh of offshore renewable energy. Further, the offshore workforce is ageing as new generations of suitable graduates prefer not to work in hazardous places offshore. Operators therefore seek more cost effective, safe methods and business models for inspection, repair and maintenance of their topside and marine offshore infrastructure. Robotics and artificial intelligence are seen as key enablers in this regard as fewer staff offshore reduces cost, increases safety and workplace appeal. The long-term industry vision is thus for a completely autonomous offshore energy field, operated, inspected and maintained from the shore. The time is now right to further develop, integrate and de-risk these into certifiable evaluation prototypes because there is a pressing need to keep UK offshore oil and renewable energy fields economic, and to develop more productive and agile products and services that UK startups, SMEs and the supply chain can export internationally. This will maintain a key economic sector currently worth £40 billion and 440,000 jobs to the UK economy, and a supply chain adding a further £6 billion in exports of goods and services. The ORCA Hub is an ambitious initiative that brings together internationally leading experts from 5 UK universities with over 30 industry partners (>£17.5M investment). Led by the Edinburgh Centre of Robotics (HWU/UoE), in collaboration with Imperial College, Oxford and Liverpool Universities, this multi-disciplinary consortium brings its unique expertise in: Subsea (HWU), Ground (UoE, Oxf) and Aerial robotics (ICL); as well as human-machine interaction (HWU, UoE), innovative sensors for Non Destructive Evaluation and low-cost sensor networks (ICL, UoE); and asset management and certification (HWU, UoE, LIV). The Hub will provide game-changing, remote solutions using robotics and AI that are readily integratable with existing and future assets and sensors, and that can operate and interact safely in autonomous or semi-autonomous modes in complex and cluttered environments. We will develop robotics solutions enabling accurate mapping of, navigation around and interaction with offshore assets that support the deployment of sensors networks for asset monitoring. Human-machine systems will be able to co-operate with remotely located human operators through an intelligent interface that manages the cognitive load of users in these complex, high-risk situations. Robots and sensors will be integrated into a broad asset integrity information and planning platform that supports self-certification of the assets and robots.

The importance of international collaborations in research is recognised both by individual researchers and by institutions and government, with studies showing that the average impact of publications resulting from these collaborations is significantly higher than that of papers with national co-authorship. This collaborative project between leading academic groups in the UK and India addresses the purification operations used to manufacture biopharmaceuticals e.g. antibodies and hormones such as insulin. They are supported in this activity by four industrial partners selected to provide support to the analytical and manufacturing aspects (being leading companies in their respective areas) as well as to provide a route to transfer the findings of the research to practice. Many of the latest drugs are based upon proteins rather than traditional small molecules (e.g. antibiotics). These protein drugs are produced for the treatment of diseases such as cancer. Antibodies such as Herceptin dominate this market. The research collaboration described here is focused on the study of the performance of the core purification method used for the manufacture of biopharmaceuticals - chromatography. Specifically we seek understand the mechanisms which determine the manufacturing lifetime of this operation and can lead to changes in performance. This issue presents a major hurdle to manufacturers. They must establish a robust purification process with acceptable costs for production before seeking approval for such medicines from the regulatory agencies. Clearly problems leading to delays can lengthen the times before medicines can made available to patients. This can affect both manufacturers of new products and those seeking to compete at reduced costs and widen the availability of this class of medicines (products often termed biosimilars). In comparison to other areas of manufacturing, bioprocessing is unusual in several respects. Typical product quantities are small (~250 kg/year), but are manufactured to extremely high purity and quality specifications (impurities < 0.001%). The variability typically seen in these processes has led to extremely regulated manufacturing, whose dictum is that "the process is the product". No significant change can be made to a licensed manufacturing process without detailed and time-consuming review by the international regulatory authorities. Developing and validating a bioprocess for manufacture takes ~10 years at a cost of £800M. Development is often empirical, with little use of modelling compared to other manufacturing sectors. These unusual features emphasise the need for a more fundamental understanding of the bioprocess. This research programme is structured towards building mechanistic understanding of the events that lead to changes in chromatographic performance in the manufacturing setting. There is evidence for several mechanisms the first stage is to structure these into a series of proposed mechanisms. Following consultation and study of historical data from our industrial partners we will embark upon experimental studies. Here detailed analytical measurements are required to identify specific critical species that are associated with the root cause of the mechanism. The project is to be led by UCL in London and IIT in Delhi in collaboration with IIT Bombay and the University of Kent. These academic groups are supported by industrial partners; ABB, Dr Reddy's Labs, GE Healthcare, Genzyme, PerkinElmer and Regeneron.

Sensors are everywhere, facilitating real-time decision making and actuation, and informing policy choices. But extracting information from sensor data is far from straightforward: sensors are noisy, prone to decalibrate, and may be misplaced, moved, compromised, and generally degraded over time. We understand very little about the issues of programming in the face of pervasive uncertainty, yet sensor-driven systems essentially present the designer with uncertainty that cannot be engineered away. Moreover uncertainty is a multi-level phenomenon in which errors in deployment can propagate through to incorrectly-positioned readings and then to poor decisions; system layering breaks down when exposed to uncertainty. How can we be assured a sensor system does what we intend, in a range of dynamic environments, and how can we make a system ``smarter'' ? Currently we cannot answer these questions because we are missing a science of sensor system software. We will develop the missing science that will allow us to engineer for the uncertainty inherent in real-world systems. We will deliver new principles and techniques for the development and deployment of verifiable, reliable, autonomous sensor systems that operate in uncertain, multiple and multi-scale environments. The science will be driven and validated by end-user and experimental applications.