Prof. Mahmoud Dhimish
Department of Electronic Engineering, University of York, Heslington, YO10 5DD, UK
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Academic Career Length
11Years (2016-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 March 2018 in Renewable Energy
Journal Article
Mahmoud DhimishVHVioleta Holmes
Violeta HolmesBMBruce Mehrdadi
Bruce Mehrdadi
MDMark Dales
Mark Dales
Journal Article
RVRomenia Vieira
Romenia VieiraFAFábio M. U. de Araújo
Fábio M. U. de AraújoMahmoud DhimishMGMaria I. S. Guerra
Maria I. S. GuerraSolar photovoltaic (PV) energy has shown significant expansion on the installed capacity over the last years. Most of its power systems are installed on rooftops, integrated into buildings. Considering the fast development of PV plants, it has becoming even more critical to understand the performance and reliability of such systems. One of the most common problems faced in PV plants occurs when solar cells receive non-uniform irradiance or partially shaded. The consequences of shading generally are prevented by bypass diodes. A significant number of studies and technical reports have been published as of today, based on extensive experience from research and field feedbacks. However, such material has not been cataloged or analyzed from a perspective of the technological evolution of bypass diodes devices. This paper presents a comprehensive review and highlights recent advances, ongoing research, and prospects, as reported in the literature, on bypass diode application on photovoltaic modules. First, it outlines the shading effect and hotspot problem on PV modules. Following, it explains bypass diodes’ working principle, as well as discusses how such devices can impact power output and PV modules’ reliability. Then, it gives a thorough review of recently published research, as well as the state of the art in the field. In conclusion, it makes a discussion on the overview and challenges to bypass diode as a mitigation technique.
15 February 2024 in IEEE Transactions on Transportation Electrification
Journal Article
MCMengyu Cheng
Mengyu Cheng
Xing ZhaoMahmoud DhimishQWQiu Wangde
Qiu WangdeSNShuangxia Niu
Shuangxia NiuElectric motor is one of the core components of electronic propulsion systems and plays an essential role in the industry. The optimal design of an electric motor poses a complex nonlinear problem, often challenging traditional methods to strike a balance between accuracy and efficiency. Achieving accurate analysis and holistic optimization typically entails significant computational requirements, particularly when dealing with massive individuals. As a result, researchers begun to explore the utilization of data-driven surrogate models to resolve this dilemma. This review paper focuses on investigating the leading techniques employed for constructing data-driven surrogate models to assist and facilitate the design optimization process of electric motors. These techniques encompass statistical models, machine learning models, deep learning models, and other artificial intelligence-based technologies. The paper provides a comprehensive survey of the underlying principles and offers detailed examples of studies that have utilized these diverse models. Besides, the performances and potentials of these models are highlighted with comments, shedding light on their respective strengths and limitations. Furthermore, the research challenges that lie ahead and promising avenues for future improvements under this topic are discussed.
1 December 2017 in Energy
Journal Article
Mahmoud DhimishVHVioleta Holmes
Violeta HolmesBMBruce Mehrdadi
Bruce Mehrdadi
MDMark Dales
Mark Dales
PMPeter Mather
Peter Mather1 November 2016 in Solar Energy
Journal Article
Mahmoud DhimishVHVioleta Holmes
Violeta Holmes6 February 2019 in IEEE Transactions on Electron Devices
Journal Article
Mahmoud DhimishHot-spotting is a reliability problem influencing photovoltaic (PV) modules, where a mismatched solar cell/cells heat up significantly and reduce the output power of the affected PV module. Therefore, in this paper, a succinct comparison of seven different state-of-the-art maximum power point tracking (MPPT) techniques are demonstrated, doing useful comparisons with respect to amount of power extracted, and hence calculate their tracking accuracy. The MPPT techniques have been embedded into a commercial off-the-shelf MPPT unit, accordingly running different experiments on multiple hot-spotted PV modules. Furthermore, the comparison includes real-time long-term data measurements over several days and months of validation. Evidently, it was found that both fast changing MPPT and the modified beta techniques are best to use with PV modules affected by hot-spotted solar cells as well as during partial shading conditions, on average, their tracking accuracy ranging from 92% to 94%. Ultimately, the minimum tracking accuracy is below 93% obtained for direct pulsewwidth modulation voltage controller MPPT technique.
About Me
Mahmoud Dhimish is an Assistant Professor in Electrical Engineering, at
the Department of Electronic Engineering, University of York. He received an
M.Sc. degree in Electronics and Communication Engineering (Distinction) from
the University of Huddersfield in 2016 and a Ph.D. in Renewable Energy from the
same University in 2018. From 2018 to August 2021, he worked as a Senior Lecturer
in Electronics and Control Engineering and was the Head of the Photovoltaic
Laboratory at the University of Huddersfield. In September 2021, he joined the
Department of Electronic Engineering at York University as a Lecturer
(Assistant Professor) in Electrical Engineering, working on developing
cutting-edge research in the area of photovoltaics/renewables and power
electronics. In November 2020, he was named one of the top 15 young scientists
in Great Britain, according to a leading index of scientific academics
published by Stanford University. He is a member of the Institute of
Engineering and Technology (IET), a member of the Institute of Electrical and
Electronics Engineering (IEEE), and a fellow of the Higher Education Academy
(FHEA). He has published 73 papers with 1939 citations and an h-index of 23
(Scopus, 11 December 2023). His research topics mainly include: renewable
energy technologies power systems analysis, photovoltaic (PV) solar energy
systems: prediction, forecasting and data analysis techniques: sensitivity,
risk and uncertainty analysis: climatology.