Adenuga, Olukorede Tijani
Publications
(Articles)
Results 1-2 of 2 (Search time: 0.003 seconds).
| Issue Date | Title | Author(s) | |
|---|---|---|---|
| 1 | 2025 | A grey wolf optimization approach for solving constrained economic dispatch in power systems | Adenuga, Olukorede Tijani ; Krishnamurthy, Senthil |
| 2 | 2025 | An MINLP optimization method to solve the RES-hybrid system economic dispatch of an electric vehicle charging station | Adenuga, Olukorede Tijani ; Krishnamurthy, Senthil |
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Full Name
Adenuga, Olukorede Tijani
Email
olukorede.adenuga@gmail.com
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ORCID
Biography
Dr. Olukorede Tijani Adenuga is an Associate Professor (Reader) and Head of the Department of Mechatronics Engineering, with expertise in artificial intelligence (AI)-driven optimization, control systems, automation, and sustainable energy engineering. He holds a Doctor of Engineering (D.Eng.) in Electrical Engineering from the Cape Peninsula University of Technology (2024), a Doctor of Technology (D.Tech.) in Industrial Engineering from the Tshwane University of Technology (2018), an M.Tech. in Industrial Engineering (2014), and a B.Eng. in Electronic and Electrical Engineering from the University of Sunderland (2010).
His research focuses on the application of AI, optimization algorithms, intelligent control systems, and energy management techniques to improve renewable energy integration, power system performance, industrial automation, and sustainable manufacturing systems. His work spans areas such as economic dispatch, hybrid renewable energy systems, electric vehicle charging infrastructure, HVAC optimization, robotics, mechatronics, and Industry 4.0 technologies.
Dr. Adenuga has participated in international academic and research collaborations, including research engagements associated with institutions in the United States and Europe. He has also contributed extensively to multidisciplinary projects in advanced manufacturing, intelligent energy systems, and industrial engineering.
With more than 40 peer-reviewed publications and over a decade of teaching, research, and postgraduate supervision experience, he has supervised and mentored students in industrial engineering, mechatronics, energy systems, and automation-related disciplines. His research contributions include publications in energy optimization, manufacturing systems, AI-based predictive modelling, and sustainable engineering applications.
In addition to his academic career, Dr. Adenuga brings extensive industry experience gained from work across the oil and gas, automotive, manufacturing, construction, and process industries, including engagements with organizations such as Shell Petroleum Development Company, Volkswagen, and UTC PLC. His current research and professional activities are centered on AI-enabled intelligent energy management systems designed to enhance grid reliability, optimize renewable energy penetration, improve energy efficiency, and support the transition toward resilient and low-carbon energy infrastructures.
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