Smart Systems and Energy Informatics Research Group

Organization profile

Profile Information

The Smart Energy Systems and Energy Informatics Research Group carries out a range of research and enterprise activities centred around the themes of intelligent sensing, control and informatics for energy-related applications. Focus areas of research include applications of Information Modelling, Machine Learning and Optimization for smart grid and the built environment. The research interests and backgrounds of staff members are multi-disciplinary and varied in nature, and include specialisms in construction, control and instrumentation, power systems, artificial intelligence and ICT. The work of the group has been underpinned by numerous EU H2020 research grants and UK/Overseas Government investments, and research outputs have been recognised as world-leading or internationally excellent in terms of quality and impact.

Fingerprint Dive into the research topics where Smart Systems and Energy Informatics Research Group is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.

Creep Engineering & Materials Science
Industry Engineering & Materials Science
Planning Engineering & Materials Science
Precast concrete Engineering & Materials Science
Electricity Engineering & Materials Science
Water Engineering & Materials Science
Electrostatics Engineering & Materials Science
Pulverized fuel Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2014 2023

Research Output 2000 2019

3D printing of intricate sand cores for complex copper castings

Hughes, D., Sutherland, L. & Amalu, E., 2019.

Research output: Contribution to conferenceAbstractResearchpeer-review

Foundry sand
Printing
Binders
Copper
Sand

A combined model for PV system lifetime energy prediction and annual energy assessment

Georgitsioti, T., Pearsall, N., Forbes, I. & Pillai, G., 1 May 2019, In : Solar Energy. 183, p. 738-744 7 p.

Research output: Contribution to journalArticleResearchpeer-review

Degradation
Potential energy
Sensitivity analysis
Economics
Uncertainty

A low-error calibration model for an electrostatic gas-solid flow sensor fusion obtained via machine learning techniques with experimental data

Kidd, A., Zhang, J. & Cheng, R., 26 Jun 2019, (Accepted/In press).

Research output: Contribution to conferencePaperResearchpeer-review

Flow of solids
Learning systems
Electrostatics
Fusion reactions
Calibration

Press / Media

Partnership aiming to build on expertise

Nashwan Dawood

14/09/12

1 item of Media coverage

Press/Media: Press / Media

Experts come together at PLM meet

Nashwan Dawood

19/10/15

1 item of Media coverage

Press/Media: Press / Media

Student theses

A review of project controls in the UK and methodologies to improve the processes

Author: Mackenzie, D., 1 Feb 2010

Supervisor: Dawood, N. (Supervisor)

Student thesis: Doctoral Thesis

Development of simulation-based genetic algorithms model for crew allocation in the precast industry

Author: Al-Bazi, A. F. J., 11 Jun 2010

Supervisor: Dawood, N. (Supervisor) & Dean, J. T. (External person) (Supervisor)

Student thesis: Doctoral Thesis

File

Development of a methodology for analysing and quantifying delay factors affecting construction projects in Libya

Author: Shebob, A., 22 Oct 2012

Supervisor: Dawood, N. (Supervisor)

Student thesis: Doctoral Thesis

File