|
Dr Solomon F. BrownI am a Professor of Process and Energy Systems in the Department of Chemical and Biological Engineering at The University of Sheffield. I'm the Director of the EPSRC's CDT in Energy Storage and its Applications and lead the Brown Group at Sheffield with ongoing projects funded by the EPSRC, BEIS, DASA, RAEng, the EC and Industry.
My research focusses on mathematical modelling, process analysis and optimisation with a particular focus on clean energy processes, energy storage and energy systems. Key areas include:
|
|
Group members |
|
Post-doctoral Researchers
Dr Peter Bugryniec
Research Associate Energy Storage | Battery Safety |
Dr Mathew Dennis Wilkes
Research Fellow in Clean Energy CCUS | BECCS | Process Modelling |
|
Diarmid Roberts: The goal of my project is to perform a techno-economic analysis of Redox Flow Batteries in grid-connected applications. The work has two major components:
|
|
Robert Milton is a mathematician, with a diverse background in finance, polyglot software development and applied mathematics. His interest is in creating novel mathematical and computational methods, which he has contributed to a variety of fields including McCabe-Thiele iteration and hydrological flow duration curves. A novel combination of techno-economic, process and supply-chain modelling was a major software project. The centrepiece of his research is building the rom-comma python package, combining original and existing machine learning techniques in a novel way. This tool uses Gaussian Processes to perform Global Sensitivity Analysis and locate an Active Subspace, dramatically reducing the problem dimension. It is already being applied to carbon capture, thermal runaway in batteries, wet granulation, and syntheses from Metal-Organic Frameworks to personalised medicines to mRNA vaccines. His short term goal is to integrate these techniques into a new class of device called an Agile Soft Sensor.
|
|
Tim Hutty's project seeks to assess the efficacy and cost of reversible solid oxide fuel cells (ReSOFC) as a tool for implementing a small scale, low-carbon distributed energy generation/storage system when interacting with a larger grid. To this end a microgrid simulation will be constructed using AnyLogic software.
|
|
Thomas Cowley is a PhD student researching district heat network modelling, design and operation, focusing on utilising low-grade renewable heat sources. His current research employs agent-based modelling techniques to inform policymakers on how the UK can decarbonise the heating sector. He started within the group during his MEng degree, which looked at generating value from wind turbine and electrolyser systems using multi-integer linear programming to schedule the dispatch of hydrogen to storage and electricity via a grid connection. He then received the Hossein Farmy scholarship that now funds his PhD.
|
|
Min Tao is a Research Associate in Soft Sensors and Digital Twins for RNA Vaccine Manufacture funded via the Welcome Leap R3 Program. His project focuses on developing advanced digital tools for enhancing the development and operation of RNA vaccine and therapeutics production processes. Previously, He got his PhD degree at The University of Manchester.
|
|
Oludayo Asuni is a Ph.D. Student working on the techno-economic analysis of supercritical water gasification of biomass integrated with physical absorption-based CCS using modelling and simulation for the production of Hydrogen. Her past research projects include CCS integration with bio-power plants and bio-ethanol production with CHP integration using lignocellulosic biomass.
LinkedIn |
|
Joseph Hammond is a PhD student researching hydrogen network modelling, design and integration with small industrial clusters. His research uses a whole system approach encompassing local hydrogen generation, the design of infrastructure, and its end-use, primarily in foundational industries. His involvement with the group started during his MEng degree, where he helped develop an agent-based tool for district heat networks.
|
|
Veysel Yildiz's research involves the application of numerical modelling, control theory, and optimization methods to contribute to scientific and technical advances in hydropower plant design. He developed a MATLAB toolbox (called HYPER) of run-of-river (RoR) power plants, which produce hydroelectricity using river flow instead of water stored in a reservoir. He has developed the HYPER-MORDM approach (HYPER - Many-objective robust decision making ) to help optimize the design and operation of power plants. The results of his research significantly enhance our ability to determine which design is most robust and reliable for given site conditions under deep uncertainty.
|
|
Daniel Williams is a PhD student investigating ultrasonic monitoring of lithium-ion batteries. His research focusses on determining and quantifying the effects of temperature, charge level and capacity fade has on the ultrasonic signal. He previously used ultrasound in his MEng degree, in which it was deployed - alongside acoustic emission and small-scale acceleration - to detect thin oil film breakdowns in journal bearings.
OrcidID ResearchGate |
|
Jack Gower is a PhD student researching energy markets and deployment of long-duration energy storage. His research uses agent-based modelling techniques to investigate the dynamic behaviour of energy markets under different future scenarios to inform policymakers on increasing storage in the UK. His previous work includes techno-economic analysis and life cycle assessment of a novel approach to carbon capture, completed during his MEng degree.
OrcidID |
Alumni Members
|
Jude Ejeh joined us as part of the Energy Open Piazza – Power Forward Challenge project, he works on developing optimisation models for electrical energy systems. This involves and extends to models for optimal scheduling of electrical energy storage devices for efficient integration of renewable energy sources – solar and wind, energy arbitrage, balancing mechanism services and other energy services for behind-the-meter and front-of-meter applications. It further covers the use of static electrical energy storage devices as well as the optimal scheduling of electric vehicle charging/discharging for vehicle-to-home (V2H) and vehicle-to-grid (V2G) applications. He also has experience in developing techno-economic optimisation models for process systems, with emphasis on multi-floor process plant layout configurations; in research relating to obtaining fuels from plastic wastes, as an intern in a Petroleum refining company and a Nuclear research laboratory. His current research interests lie in operations research (OR) applications to energy systems and supply chains.
Google Scholar |
|
Rachel Lee’s research is aimed at combining technical analysis of vehicle-to-grid (V2G) systems with a human behaviour model in order to move from current ‘technically feasible’ to more realistic “practically achievable” volumes of V2G response. The work employs an agent-based simulation using the ‘consumat’ behaviour model to first establish the growth in electric vehicle deployment and then the uptake of V2G contracts. Data from the National Travel Survey is used to model journeys and locations of vehicles so that the availability of V2G connection points at different locations can be considered within the analysis.
|
|
Emma Chandler's PhD focussed on applying the McCabe Thiele method to liquid-liquid biological separations. Her current interests are on purification techniques suitable for biological separations.
|
|
Aaron Yeardley's research interests include applying data analytics and machine learning to help engineering issues. During his PhD, Aaron used Robert Milton's novel ROMCOMMA Python Package to apply Gaussian Processes as a surrogate model to help other researchers with sensitivity analysis and forecasting capabilities to build accurate computational models. Currently, Aaron uses his solid mathematical skills as a Senior Carbon Reduction Engineer, working with many businesses to calculate their baseline emissions. Then, data analytics is used to present the carbon hotspots and promote reduction opportunities to the client. In the future, Aaron would love to combine his work in applying machine learning models to help the environment. In particular, the future could apply digital twin optimisation to create a circular economy and energy synergies between partnering manufacturing facilities.
|
|
Flora Biggins' research looks at how energy storage can be utilised to generate value in different integration scenarios. Case studies have explored locational effects of co-locating battery storage with solar, optimising bidding strategies in competitive energy markets and community storage partially accessed by a value-maximising aggregator. Ongoing work includes developing a model for a wind-based hydrogen electrolysis and applying a real-options approach to energy storage projects.
|
