Projects per year
Personal profile
Academic Biography
Dr Chris Ogwumike is a Senior Lecturer in Electrical and Electronic Engineering in the School of Computing, Engineering and Digital Technologies (SCEDT), Teesside University. Chris holds a BEng degree in Electrical and Electronic Engineering (2006, Enugu State University of Science and Technology, Nigeria), MSc Information Technology Management (2010, Teesside University) and a PhD degree (2018, Teesside University) awarded following successful completion of research and development of ‘An Intelligent Decision Support System (IDSS) for Efficient Scheduling of Smart Home Appliances in a Smart Grid’.
Following the award of his PhD, Chris spent three years working on H2020 funded research and innovation projects – Demand Response in Blocks of Buildings (DR-BoB) and the inteGRIDy projects in the SCEDT, Teesside University, first as a Postdoc Research Assistant, and then a Research Associate. Chris’s previous academic roles includes Part time Tutor at Teesside University during his PhD, Lecturer in Electrical & Electronic Engineering at Bishop Auckland College – South West Durham Training; and a Module tutor, Teesside University Open Learning Engineering (TUOLE).
Chris is a Member of Institution of Engineering and Technology (MIET), a Fellow of Higher Education Academy (FHEA) and a Guest editor of Special Issue ‘Integrating Smart Energy Systems for Sustainable Development’. Chris is research active and has peer-reviewed publications in journals and conferences.
Summary of Research Interests
Dr Chris Ogwumike’s main research interest is focused on Demand Side Integration (Demand Response in built environment, Renewable/Distributed Generations integration, Load forecasting using Machine Learning techniques, and development of Decision-making systems); Techno-economic assessment and evaluation; and Decarbonisation of industrial sector (strategies and framework development).
Areas of research application includes Smart Grids and Smart Energy Systems, Energy Efficiency and Optimisation.
Chris is open for PhD Research supervision and keen to establish further collaboration with Industry.
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Projects
- 2 Finished
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IDRIC: The UK Industrial Decarbonisation Research and Innovation Centre
Dawood, N., Dawood, H., Pinedo-Cuenca, R., Ogwumike, C. & Abugchem, F.
1/07/21 → 30/06/23
Project: Research
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inteGRIDy: integrated Smart GRID Cross-Functional Solutions for Optimized Synergetic Energy Distribution, Utilization & Storage Technologies H2020 Grant Agreement Number: 731268
Dawood, N., Dawood, H., Ogwumike, C., Gudlaugsson, B., Ahmed, T. G., Short, M. & Abugchem, F.
1/01/17 → 30/06/21
Project: Research
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Cost and Environmental Benefit Analysis: An Assessment of Renewable Energy Integration and Smart Solution Technologies in the InteGRIDy project.
Gudlaugsson, B., Ahmed, T. G., Dawood, H., Ogwumike, C., Short, M. & Dawood, N., 30 May 2023, In: Cleaner Energy Systems. 5, 100071.Research output: Contribution to journal › Article › peer-review
Open AccessFile16 Downloads (Pure) -
Evaluation Framework for Techno-economic Analysis of Energy System Retrofit Technologies
Ahmed, T. G., Gudlaugsson, B., Ogwumike, C., Dawood, H., Short, M. & Dawood, N., 1 May 2023, In: Energy and Buildings. 286, 112967.Research output: Contribution to journal › Article › peer-review
Open Access -
Application of Cost Benefits Analysis for the Implementation of Renewable Energy and Smart Solution Technologies: A Case Study of InteGRIDy Project †
Gudlaugsson, B., Ahmed, T. G., Dawood, H., Ogwumike, C. & Dawood, N., 3 Dec 2021, In: Environmental Sciences Proceedings. 11, 1, 6 p.Research output: Contribution to journal › Conference article › peer-review
Open AccessFile51 Downloads (Pure) -
KPI Evaluation Framework and Tools Performance: A Case Study from the inteGRIDy Project
Ogwumike, C., Dawood, H., Ahmed, T. G., Gudlaugsson, B. & Dawood, N., 1 Dec 2021, Environmental sciences proceedings. 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile53 Downloads (Pure) -
Machine learning and data segmentation for building energy use prediction—a comparative study
Mounter, W., Ogwumike, C., Dawood, H. & Dawood, N., 18 Sept 2021, In: Energies. 14, 18, 5947.Research output: Contribution to journal › Article › peer-review
Open AccessFile55 Downloads (Pure)
Thesis
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An Intelligent Decision Support System for Efficient Scheduling of Smart Home Appliances in a Smart Grid
Author: Ogwumike, C., 10 Jan 2018Supervisor: Short, M. (Supervisor)
Student thesis: Doctoral Thesis
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