Staff profile
Affiliation | Telephone |
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Associate Professor in the Department of Engineering | +44 (0) 191 33 42538 |
Biography
Peter Matthews is an Associate Professor in Design Informatics at the Department of Engineering. His research in Design Informatics utilises data mining and machine learning tools to critically appraise technical data sets, such as operational sensor data from wind turbines (typically from SCADA systems). Gaining insights to the underlying processes governing these systems gives us a deeper understanding, which ultimately leads to improved design for the next generation of system.
The primary goal for machine learning with technical data is to be able to predict with sufficient warning when a machine is likely to fail. This prognostic ability has the potential of providing significant cost savings to industry: maintenance can be performed at the optimal time, allowing better planning, and the risk of incurring secondary damage is mitigated. Dr Matthews has led several successful projects which have accurately predicted failures for specific sub-systems (see results with Chen (2015), Godwin (2013), and Smith (2015)).
Another important component of Dr Matthews’ research is the production of tractable and humanly-understandable rules. Tractable rules require a much simpler validation process and are therefore more useable by system operators and designers when seeking to improve a system’s performance.
Wind Energy
Dr Matthews' wind energy research is primarily in data mining SCADA and other wind turbine operational data. This research is primarily aimed at developing diagnostic and prognostic measures for individual wind turbine health. The approach taken is based around statistical modelling of healthy wind turbines, and then comparing live wind turbines against this healthy model. Other methods (eg physics based) are under development as well, again using ‘big data’ approaches to validate.
In addition to SCADA analysis, Dr Matthews has directed research in wake optimisation and maintenance strategy simulation. The wake optimisation research has delivered a workable dynamic wind farm controller that can minimise the effect of in-farm wakes on total production. The maintenance strategy simulation provided a Monte Carlo based approach for developing and testing alternative off-shore wind farm maintenance strategies.
Much of the Wind Energy research is undertaken with industrial partners Ørsted Energy and Maia Eolis (now Engie Green).
Energy Distribution
The energy distribution sector has a broad range of customers, from domestic through to large industrial customers. All these customers use electricity in different ways, and their consumption is recorded using SCADA systems. Dr Matthews’ research in the Energy Distribution sector centres around data mining these SCADA databases of thousands of customers, as well as hundreds of electrical substations, to gain better understanding of the overall picture of electricity use. Dr Matthews has also directed research to forecast the demand increases at substation level using substation demographic customer profiles.
Much of this research is undertaken with Northern Powergrid.
Design Analysis
The Design Analysis research is based on data mining, but with considerably smaller datasets. Here, the aim is to extract the tacit rules the human designers have applied, and gain better understanding of the design domain through making these rules explicit. Design data often contains greater textual information, and so text mining approaches have also been applied with interesting results. Other techniques that have been used include Bayesian Belief Network and p-boxes. These techniques have been used to mitigate against the greater uncertainty levels that can be associated with early designs.
This research has been undertaken with Rolls-Royce (Aerospace) and BAE Systems.
Research interests
- Monte Carlo methods
- Engineering Uncertainty modelling and management
- Knowledge Management
- Engineering Design
- Artificial Intelligence and Machine Learning
- Design process
- Game theory
- Data mining
- Wind Energy
Publications
Authored book
Chapter in book
- Godwin, J., & Matthews, P. (2014). Robust Statistical Methods for Rapid Data Labelling. In V. Bhatnagar (Ed.), Data mining and analysis in the engineering field (107-141). IGI Global. https://doi.org/10.4018/978-1-4666-6086-1.ch007
- Lomas, C., Maropoulos, P., & Matthews, P. (2007). Implementing Digital Enterprise Technologies for Agile Design in the Virtual Enterprise. In P. Cunha, & P. Maropoulos (Eds.), Digital enterprise technology : perspectives and future challenges (177-184). Springer Verlag. https://doi.org/10.1007/978-0-387-49864-5_20
Conference Paper
- Correa-Delval, M., Sun, H., Matthews, P. C., & Chiu, W. (2022). Appliance Scheduling Optimisation Method Using Historical Data in Households with RES Generation and Battery Storage Systems. . https://doi.org/10.1109/repe55559.2022.9949497
- Correa-Delval, M., Sun, H., Matthews, P., & Jiang, J. (2021). Appliance Classification using BiLSTM Neural Networks and Feature Extraction. . https://doi.org/10.1109/isgteurope52324.2021.9640061
- Hua, W., Li, D., Sun, H., Matthews, P., & Meng, F. (2018). Stochastic environmental and economic dispatch of power systems with virtual power plant in energy and reserve markets. In 2nd International Conference on Power and Renewable Energy (ICPRE 2017) : Chengdu, China, September 20-23, 2017 ; proceedings (654-658)
- Al Moubayed, N., Breckon, T., Matthews, P., & McGough, A. (2016). SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder. In A. E. P. Villa, P. Masulli, & A. J. Pons Rivero (Eds.), Artificial neural networks and machine learning – ICANN 2016 : 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016 ; proceedings. Part II (423-430). https://doi.org/10.1007/978-3-319-44781-0_50
- Ahmad, T., Girard, N., Kazemtabrizi, B., & Matthews, P. (2015). Analysis of Two Onshore Wind Farms with a Dynamic Farm Controller.
- Smith, C., Wadge, G., Crabtree, C., & Matthews, P. (2015). Characterisation of Electrical Loading Experienced by a Nacelle Power Converter.
- Sidwell, N., Ahmad, T., & Matthews, P. (2015). Onshore Wind Farm Fast Wake Estimation Method: Critical Analysis of the Jensen Model.
- Smith, C., Crabtree, C., & Matthews, P. (2015). Evaluation of Synthetic Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms.
- Ahmad, T., Matthews, P., Kazemtabrizi, B., & Smith, C. (2015). Dynamic Wind Farm Controller.
- Smith, C., Crabtree, C., & Matthews, P. (2015). Experimental Set-up for Applying Wind Turbine Operating Profiles to the Nacelle Power Converter.
- Akperi, B., & Matthews, P. (2014). Analysis of clustering techniques on load profiles for electrical distribution. In POWERCON 2014 Chengdu : 2014 International Conference on Power System Technology : Towards green, efficient and smart power system. Proceedings of a meeting held 20-22 October 2014, Chengdu, China (1142-1149). https://doi.org/10.1109/powercon.2014.6993986
- Smith, C., Crabtree, C., Matthews, P., & Kazemtabrizi, B. (2014). Modelling and Evaluation of Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms.
- Ahmad, T., Smith, C., Matthews, P., Crabtree, C., & Kazemtabrizi, B. (2014). Determining the Wind Speed Distribution within a Wind Farm considering Site Wind Characteristics and Wake Effects.
- Akperi, B., & Matthews, P. (2014). Analysis of customer profiles on an electrical distribution network. In M. Conlon, D. D. Micu, M. Al-Tai, & C. Ferreira (Eds.), Proceedings of 2014 49th International Universities Power Engineering Conference (UPEC) : 2-5 September 2014, Cluj-Napoca, Romania (1-6). https://doi.org/10.1109/upec.2014.6934624
- Chen, B., Matthews, P., & Tavner, P. (2013). Automated Wind Turbine Pitch Fault Prognosis using ANFIS.
- Ullah, B., Trevelyan, J., & Matthews, P. (2012). Structural optimisation using boundary element based level set method.
- Matthews, P., & Philip, A. (2011). Bayesian Project Monitoring. In S. Culley, B. Hicks, T. McAloone, T. Howard, & P. Clarkson (Eds.),
- Matthews, P. (2010). Comparing Stochastic Design Decision Belief Models: Pointwise versus Interval Probabilities. In J. Gero (Ed.),
- Matthews, P., & Coates, G. (2007). Pre-emptive Concurrent Design Planning and Scheduling.
- Matthews, P., & Coates, G. (2007). Stochastic based Pre-emptive Planning and Scheduling.
- Lomas, C. D. W., & Matthews, P. C. (2007). Meta-Design for Agile Concurrent Product Design in the Virtual Enterprise. In P. C. Matthews (Ed.),
- Matthews, P. (2007). Bayesian Networks for Engineering Design Decision Support. In S. I. Ao, L. Gelman, D. W. L. Hukins, A. Hunter, & A. M. Korsunsky (Eds.), 2007 International Conference of Data Mining and Knowledge Engineering, ICDMKE07, 2-4 July 2007, London, UK ; proceedings (284-289)
- Lomas, C., Wilkinson, J., Matthews, P., & Maropoulos, P. (2006). Implementing Digital Enterprise Technologies for Agile Design in the virtual enterprise. In P. Cunha, & P. Maropoulos (Eds.),
- Matthews, P., Lomas, C., & Maropoulos, P. (2006). A Methodology for Negotiating Change Propagation in Agile Design. In H. Andersin, & A. Verma (Eds.),
- process. In H. Andersin, & A. Verma (Eds.),
- Matthews, P. (2006). Bayesian Networks for Design. In J. Gero (Ed.),
- Matthews, P., Coates, G., & Lomas, C. (2006). Agile resource allocation through pre-emptive planning. In H. Andersin, & A. Verma (Eds.),
- Matthews, P., Keegan, J., & Robson, J. (2005). Development of a simple information pump. In A. Samuel, & W. Lewis (Eds.), Proceedings of the International Conference on Engineering Design
- Matthews, P. (2005). Machine learning stochastic design models. In A. Samuel, & W. Lewis (Eds.), 15th International Conference on Engineering Design, ICED05, 15-18 August 2005, Melbourne, Australia ; proceedings
- Armoutis, N., Matthews, P., Lomas, C., & Maropoulos, P. (2005). Partner Profiling to Support Agile Design. In M. Zäh (Ed.), First International Conference on Changeable, Agile, Reconfigurable and Virtual Production (267-272)
- Lomas, C., Matthews, P., Armoutis, N., & Maropoulos, P. (2005). Verification of Event Impact Levels for an Agile Design Framework.
- Baguley, P., Qaqish, T., Matthews, P., & Maropoulos, P. (2005). An Agile Digital Enterprise Technology Cost Engineering Tool. In H. Andersin (Ed.), International Conference on Agile Manufacturing 2005
- Matthews, P., Lomas, C., Armoutis, N., & Maropoulos, P. (2005). Foundations of an Agile Design Methodology. In H. Andersin (Ed.), International Conference on Agile Manufacturing 2005
- Matthews, P., & Lowe, D. (2003). Inducing Change Propagation Models using Previous Designs. In A. Folkeson, K. Gralén, M. Norell, & U. Sellgren (Eds.),
- Matthews, P., & Wallace, K. (2003). Using Self Organizing Maps as a Design Exploration Tool. In A. Folkeson, K. Gralen, M. Norell, & U. Sellgren (Eds.),
- Matthews, P., Langdon, P., & Wallace, K. (2001). New techniques for design knowledge exploration: A comparison of three data grouping approaches. In S. Culley, A. Duffy, C. McMahon, & K. Wallace (Eds.),
- Matthews, P., Ahmed, S., & Aurisicchio, M. (2001). Extracting Experience through Protocol Analysis. In F. Kurfess, & M. Hilario (Eds.), Integrating Data Mining and Knowledge Management
- Matthews, P., Wallace, K., & Blessing, L. (2000). Design Heuristics Extraction: Acquiring engineering knowledge from previous designs. In J. Gero (Ed.), Artificial Intelligence in Design 2000 (435-453)
- Matthews, P., Blessing, L., & Wallace, K. (1999). Conceptual Evaluation using Neural Networks. In U. Lindemann, H. Birkhofer, H. Meerkamm, & S. Vanja (Eds.), Proceedings of the 12th International Conference on Engineering Design (1777-1780)
- Matthews, P. (1998). Using a Guideline Database to Support Design Emergence: A Proposed System based on a Designer's Workbench. In S. Chase, & L. Schmidt (Eds.), Workshop Proceedings of the AID'98: Emergence in Design (13-18)
- Ball, N., Matthews, P., & Wallace, K. (1998). Managing Conceptual Design Objects: An Alternative to Geometry. In J. Gero, & F. Sudweeks (Eds.), Artificial Intelligence in Design '98 (67-86)
- Charlton, C., Ball, N., & Matthews, P. (1998). Towards Mechanical Design Object Reuse: The Description, Retrieval and Classification of Cases. In J. Gero, & F. Sudweeks (Eds.), Artificial Intelligence in Design '98 (311-325)
- Ball, N., & Matthews, P. (1998). Active Design Support with a Hierarchical Blackboard Structure. In Poster Proceedings of the Third International Conference on Adaptive Computing in Design and Manufacture (58-61)
- Murdoch, T., Ball, N., & Matthews, P. (1997). Constraint Based Templates for Design Re-use. In A. Riitahuhta (Ed.), Proceedings of the 11th International Conference on Engineering Design (267-270)
Doctoral Thesis
Journal Article
- Hua, W., Xiao, H., Pei, W., Chiu, W., Jiang, J., Sun, H., & Matthews, P. (2023). Transactive Energy and Flexibility Provision in Multi-microgrids using Stackelberg Game. CSEE journal of power and energy systems, 9(2), 505-515. https://doi.org/10.17775/cseejpes.2021.04370
- Ahmad, T., Basit, A., Ahsan, M., Coupiac, O., Girard, N., Kazemtabrizi, B., & Matthews, P. (2019). Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms. Energies, 12(7), Article 1266. https://doi.org/10.3390/en12071266
- Ahmad, T., Basit, A., Anwar, J., Coupiac, O., Kazemtabrizi, B., & Matthews, P. (2019). Fast Processing Intelligent Wind Farm Controller for Production Maximisation. Energies, 12(3), Article 544. https://doi.org/10.3390/en12030544
- Hua, W., Li, D., Sun, H., Matthews, P., & Meng, F. (2018). Stochastic environmental and economic dispatch of power systems with virtual power plant in energy and reserve markets. International journal of smart grid and clean energy, 7(4), 231-239. https://doi.org/10.12720/sgce.7.4.231-239
- Ahmad, T., Coupliac, O., Petit, A., Guignard, S., Girard, N., Kazemtabrizi, B., & Matthews, P. (2018). Field Implementation and Trial of Coordinated Control of Wind Farms. IEEE Transactions on Sustainable Energy, 9(3), 1169-1176. https://doi.org/10.1109/tste.2017.2774508
- Trenkel-Lopez, M., & Matthews, P. (2018). Method for Designing a High Capacity Factor Wide Area Virtual Wind Farm. IET Renewable Power Generation, 12(3), 351-358. https://doi.org/10.1049/iet-rpg.2017.0396
- Smith, C., Crabtree, C., & Matthews, P. (2017). Impact of wind conditions on thermal loading of PMSG wind turbine power converters. IET Power Electronics, 10(11), 1268-1278. https://doi.org/10.1049/iet-pel.2016.0802
- Chen, B., Matthews, P., & Tavner, P. (2015). Automated on-line fault prognosis for wind turbine pitch systems using supervisory control and data acquisition. IET Renewable Power Generation, 9(5), 503-513. https://doi.org/10.1049/iet-rpg.2014.0181
- Ullah, B., Trevelyan, J., & Matthews, P. (2014). Structural optimisation based on the boundary element and level set methods. Computers and Structures, 137, 14-30. https://doi.org/10.1016/j.compstruc.2014.01.004
- Chen, B., Matthews, P., & Tavner, P. (2013). Wind turbine pitch faults prognosis using a-priori knowledge-based ANFIS. Expert Systems with Applications, 40(17), 6863-6876. https://doi.org/10.1016/j.eswa.2013.06.018
- Chandler, S., & Matthews, P. (2013). Through-Life Systems Engineering Design & Support with SysML. Procedia CIRP, 11, 425-430. https://doi.org/10.1016/j.procir.2013.07.002
- Godwin, J., Matthews, P., & Watson, C. (2013). Classification and Detection of Electrical Control System Faults Through SCADA Data Analysis. Chemical engineering transactions, 1, 985-990. https://doi.org/10.3303/cet1333165
- Godwin, J., & Matthews, P. (2013). Classification and Detection of Wind Turbine Pitch Faults Through SCADA Data Analysis. International journal of prognostics and health management, 4, Article 016
- Matthews, P., & Philip, A. (2012). Bayesian project diagnosis for the construction design process. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 26(4), 375-391. https://doi.org/10.1017/s089006041200025x
- Matthews, P. (2011). Challenges to Bayesian decision support using morphological matrices for design: empirical evidence. Research in Engineering Design, 22(1), 29-42. https://doi.org/10.1007/s00163-010-0094-1
- Matthews, P. C., & Lomas, C. D. (2010). A methodology for quantitative estimates for the work and disturbance transformation matrices. Journal of Engineering Design, 21(4), 413-425. https://doi.org/10.1080/09544820802310909
- Cheung, W., Maropoulos, P., & Matthews, P. (2010). Linking design and manufacturing domains via web-based and enterprise integration technologies. International Journal of Computer Applications in Technology, 37(3/4), 182-197. https://doi.org/10.1504/ijcat.2010.031934
- Cheung, W., Matthews, P., Gao, J., & Maropoulos, P. (2008). Advanced product development integration architecture: An out-of-box solution to support distributed production networks. International Journal of Production Research, 46(12), 3185-3206. https://doi.org/10.1080/00207540601039767
- Matthews, P. (2008). A Bayesian support tool for morphological design. Advanced Engineering Informatics, 22(2), 236-253. https://doi.org/10.1016/j.aei.2007.05.001
- Armoutis, N., Maropoulos, P., Matthews, P., & Lomas, C. (2008). Establishing agile supply networks through competence profiling. International Journal of Computer Integrated Manufacturing, 21(2), 166-173. https://doi.org/10.1080/09511920701607683
- Lomas, C., & Matthews, P. (2007). Meta-Design for Agile Concurrent Product Design in the Virtual Enterprise. International journal of agile manufacturing, 10(2), 77-87
- Matthews, P., & Chesters, P. (2006). Implementing the Information Pump using Accessible Technology. Journal of Engineering Design, 17(6), 563-585. https://doi.org/10.1080/09544820600646629
- Matthews, P., Standingford, D., Holden, C., & Wallace, K. (2006). Learning inexpensive parametric design models using an augmented genetic programming technique. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 20(1), 1-18. https://doi.org/10.1017/s089006040606001x
- Matthews, P., Lomas, C., Armoutis, N., & Maropoulos, P. (2006). Foundations of an Agile Design Methodology. International journal of agile manufacturing, 9(1), 29-38
- Lomas, C., Wilkinson, J., Maropoulos, P., & Matthews, P. (2006). Measuring Design Process Agility for the Single Company Product Development Process. International journal of agile manufacturing, 9(2), 105-112
- Matthews, P., Blessing, L., & Wallace, K. (2002). The introduction of a design heuristics extraction method. Advanced Engineering Informatics, 16(1), 3-19. https://doi.org/10.1016/s1474-0346%2802%2900002-2
Patent
- Matthews, P., Standingford, D., & Holden, C. (2003). Method of Design using Genetic Programming
- Matthews, P., Standingford, D., & Holden, C. (2002). Method of design using genetic programming
Report
- Capova, K., Wardle, R., Bell, S., Lyon, S., Bulkeley, H., Matthews, P., & Powells, G. (2015). High Level Summary of Learning: Electrical Vehicle Users. Northern Powergrid (Northeast) Limited, Northern Powergrid (Yorkshire) Plc, British Gas Trading Limited, University of Durham and EA Technology Ltd
- Bulkeley, H., Matthews, P., Whitaker, G., Bell, S., Wardle, R., Lyon, S., & Powells, G. (2015). High Level Summary of Learning: Domestic Smart Meter Customers on Time of Use Tariffs. Northern Powergrid (Northeast) Limited, Northern Powergrid (Yorkshire) Plc, British Gas Trading Limited, University of Durham and EA Technology Ltd
- Bell, S., Capova, K., Barteczko-Hibbert, C., Matthews, P., Wardle, R., Bulkeley, H., …Powells, G. (2015). High Level Summary of Learning: Heat Pump Customers. Northern Powergrid (Northeast) Limited, Northern Powergrid (Yorkshire) Plc, British Gas Trading Limited, University of Durham and EA Technology Ltd
- Bulkeley, H., Whitaker, G., Matthews, P., Bell, S., Lyon, S., & Powells, G. (2015). High Level Summary of Learning: Domestic Solar PV Customers. Northern Powergrid (Northeast) Limited, Northern Powergrid (Yorkshire) Plc, British Gas Trading Limited, EA Technology Limited and the University of Durham
- Bulkeley, H., Whitaker, G., Matthews, P., Bell, S., Lyon, S., & Powells, G. (2015). High Level Summary of Learning: Domestic Smart Meter Customers. Northern Powergrid (Northeast) Limited, Northern Powergrid (Yorkshire) Plc, British Gas Trading Limited, EA Technology Limited and the University of Durham
- Jones, O., Wardle, R., & Matthews, P. (2014). Micro-CHP Trial Report. Northern Powergrid (Northeast) Limited, Northern Powergrid (Yorkshire) Plc, British Gas Trading Limited, University of Durham and EA Technology Ltd
- Whitaker, G., Wardle, R., Barteczko-Hibbert, C., Matthews, P., Bulkeley, H., & Powells, G. (2013). Insight Report: Domestic Time of Use Tariff: A comparison of the time of use tariff trial to the baseline domestic profiles. Northern Powergrid (Northeast) Limited, Northern Powergrid (Yorkshire) Plc, British Gas Trading Limited EA Technology Ltd and the University of Durham
- Matthews, P. (2003). Identifying Design Micro-models using Genetic Programming Techniques: A User Manual for the GP-HEM toolbox. [No known commissioning body]