Browsing by Author "Hossain, Md Moinul"

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    Artificial intelligence and bio-inspired soft computing-based maximum power plant tracking for a solar photovoltaic system under non-uniform solar irradiance shading conditions - a review
    (MDPI, 2021-09-23) Ali, Amjad; Irshad, Kashif; Khan, Mohammad Farhan; Hossain, Md Moinul; Al-Duais, Ibrahim N. A.; Malik, Muhammad Zeeshan
    Substantial progress in solar photovoltaic (SPV) dissemination in grid-connected and standalone power generation systems has been witnessed during the last two decades. However, weather intermittency has a non-linear characteristic impact on solar photovoltaic output, which can cause considerable loss in the system’s overall output. To overcome these inevitable losses and optimize the SPV output, maximum power point tracking (MPPT) is mounted in the middle of the power electronics converters and SPV to achieve the maximum output with better precision from the SPV system under intermittent weather conditions. As MPPT is considered an essential part of the SPV system, up to now, many researchers have developed numerous MPPT techniques, each with unique features. A Google Scholar survey from 2015–2021 was performed to scrutinize the number of published review papers in this area. An online search established that on different MPPT techniques, overall, 100 review articles were published; out of these 100, seven reviews on conventional MPPT techniques under shading or partial shading and only four under non-uniform solar irradiance are published. Unfortunately, no dedicated review article has explicitly focused on soft computing MPPT (SC-MPPT) techniques. Therefore, a comprehensive review of articles on SC-MPPT techniques is desirable, in which almost all the familiar SC-MPPT techniques have to be summarized in one piece. This review article concentrates explicitly on soft computing-based MPPT techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram. It will not only be helpful for academics and researchers to provide a future direction in SC-MPPT optimization research, but also help the field engineers to select the appropriate SC-MPPT for SPV according to system design and environmental conditions.
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    ItemOpen Access
    OxyCAP UK: Oxyfuel Combustion - academic Programme for the UK
    (Elsevier, 2014-12-31) Chalmers, Hannah L.; Al-Jeboori, Mohamad J.; Anthony, Ben; Balusamy, Saravanan ; Black, Stuart K.; Cavallo Marincola, F.; Clements, Alastair G.; Darabkhani, Hamidreza Gohari ; Dennis, John S.; Farrow, Timipere S.; Fennell, Paul S.; Franchetti, Benjamin; Gao, Lingjun; Gibbins, Jon R.; Hochgreb, Simone; Hossain, Md Moinul; Jurado Pontes, Nelia; Kempf, Andreas M.; Liu, Hao; Lu, Gang; Ma, Lin; Navarro-Martinez, Salvador; Nimmo, William; Oakey, John E.; Pranzitelli, Alessandro; Scott, Stuart A.; Snape, Colin E.; Sun, Chenggong; Sun, Duo; Szuhánszki, Janos; Trabadela, Ignacio; Wigley, Fraser; Yan, Yong; Pourkashanian, Mohamed M.
    The OxyCAP-UK (Oxyfuel Combustion - Academic Programme for the UK) programme was a £2 M collaboration involving researchers from seven UK universities, supported by E.On and the Engineering and Physical Sciences Research Council. The programme, which ran from November 2009 to July 2014, has successfully completed a broad range of activities related to development of oxyfuel power plants. This paper provides an overview of key findings arising from the programme. It covers development of UK research pilot test facilities for oxyfuel applications; 2-D and 3-D flame imaging systems for monitoring, analysis and diagnostics; fuel characterisation of biomass and coal for oxyfuel combustion applications; ash transformation/deposition in oxyfuel combustion systems; materials and corrosion in oxyfuel combustion systems; and development of advanced simulation based on CFD modelling.