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New hybrid meta-heuristic algorithm for reliable and cost-effective designing of photovoltaic/wind/fuel cell energy system considering load interruption probability

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F21%3APU138529" target="_blank" >RIV/00216305:26210/21:PU138529 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S095965262033451X?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S095965262033451X?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.jclepro.2020.123406" target="_blank" >10.1016/j.jclepro.2020.123406</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    New hybrid meta-heuristic algorithm for reliable and cost-effective designing of photovoltaic/wind/fuel cell energy system considering load interruption probability

  • Original language description

    In this paper optimal and cost-effective design of a photovoltaic/wind turbine/fuel cell (PV/WT/FC), the renewable energy system is proposed with the objective of lifespan cost of hybrid system (LSCS) minimisation and considering reliability constraint as a maximum of load interruption probability (LIP) as LIPmax to supply the demand of residential-commercial centres (RCC) located in Iran based on real data of irradiance and wind speed of this region. A new hybrid meta-heuristic algorithm named hybrid grey wolf optimiser-sine cosine algorithm (HGWOSCA) based on the exponential decreasing function (EDF) with high accuracy and speed of optimisation in achieving to the global solution is applied to determine the optimal size of system components. The superiority of the proposed HGWOSCA is compared with SCA, GWO and particle swarm optimisation (PSO) methods in designing of different combinations of the hybrid system and under varying reliability constraint. The results showed that the PV/WT/FC combination is the best combination in view of LSCS and LIPmax for supplying the RCC as a cost-effective and reliable combination. The superiority of the HGWOSCA in designing different combinations of the hybrid system is proved with fewer LSCS and LIP than the other methods with more convergence speed and accuracy. The results clearly showed that the use of hydrogen storage as a reserve power has well compensated the fluctuations in renewable sources production for meeting the RCC load to achieve optimal reliability. The results cleared that the cost of per kW of RCC supply for LIPmax = 1% and LIPmax = 5% is 0.853 and 0.764 $. The results indicated that increasing the failure rate of the components increases the system cost and weakens the reliability. In addition, the results showed that increased FC efficiency has reduced the level of reserve hydrogen, reduced the LSCS, and improved reliability. © 2020

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20704 - Energy and fuels

Result continuities

  • Project

    <a href="/en/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Sustainable Process Integration Laboratory (SPIL)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Cleaner Production

  • ISSN

    0959-6526

  • e-ISSN

    1879-1786

  • Volume of the periodical

    neuveden

  • Issue of the periodical within the volume

    278

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    13

  • Pages from-to

    123406-123406

  • UT code for WoS article

    000592387000016

  • EID of the result in the Scopus database

    2-s2.0-85089598092