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Maximum power point tracking (MPPT) control of pressure retarded osmosis (PRO) salinity power plant : development and comparison of different techniques
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He, Wei, Luo, Xing, Kiselychnyk, Oleh, Wang, Jihong and Shaheed, Mohammad Hasan (2016) Maximum power point tracking (MPPT) control of pressure retarded osmosis (PRO) salinity power plant : development and comparison of different techniques. Desalination, 389 . pp. 187-196. doi:10.1016/j.desal.2016.01.022 ISSN 0011-9164.
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WRAP_1473759-es-060516-mppt_paper.pdf - Accepted Version - Requires a PDF viewer. Download (1629Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.desal.2016.01.022
Abstract
This paper presents two new methods for the maximum power point tracking (MPPT) control of a pressure retarded osmosis (PRO) salinity power plant, including mass feedback control (MFC) and fuzzy logic control (FLC). First, a brief overview of perturb & observe (P&O) and incremental mass resistance (IMR) control is given as those two methods have already demonstrated their merit in good control performance. Then, two new methods employing variable-step strategy, MFC and FLC, are proposed to address the trade-off relationship between rise-time and oscillation of P&O and IMR. Genetic algorithm (GA) is used for finding the optimum parameters of membership functions of FLC. From the case-study of start-up of the PRO adopting MPPT control, MFC and FLC have shown faster convergence to the target performance without oscillation compared with P&O and IMR. These four MPPT techniques are further evaluated in case-studies of state transitions of the PRO due to operational fluctuations. It is proven that the MPPT using FLC and modified MFC has better performance than the other two methods. Finally, the paper reports a comparison of major characteristics of the four MPPT methods, which could be considered as guidance for selecting a MPPT technique for the PRO in practice.
Item Type: | Journal Article | ||||||||||
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Subjects: | Q Science > QH Natural history | ||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||||
Library of Congress Subject Headings (LCSH): | Osmosis, Genetic algorithms | ||||||||||
Journal or Publication Title: | Desalination | ||||||||||
Publisher: | Elsevier BV | ||||||||||
ISSN: | 0011-9164 | ||||||||||
Official Date: | 1 July 2016 | ||||||||||
Dates: |
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Volume: | 389 | ||||||||||
Number of Pages: | 10 | ||||||||||
Page Range: | pp. 187-196 | ||||||||||
DOI: | 10.1016/j.desal.2016.01.022 | ||||||||||
Status: | Peer Reviewed | ||||||||||
Publication Status: | Published | ||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||
Date of first compliant deposit: | 9 May 2016 | ||||||||||
Date of first compliant Open Access: | 1 February 2017 | ||||||||||
Funder: | Engineering and Physical Sciences Research Council (EPSRC), Henry Lester Trust, Great Britain-China Educational Trust | ||||||||||
Grant number: | EP/L014211/1 (ESPRC), EP/K002228/1 (EPSRC) |
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