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    Multi-objective day-ahead scheduling of microgrids using modified grey wolf optimizer algorithm

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    Mokryani_Jnl_of_Intelligent_and_Fuzzy_Systems.pdf (917.8Kb)
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    Publication date
    2018
    Author
    Javidsharifi, M.
    Niknam, T.
    Aghaei, J.
    Mokryani, Geev
    Papadopoulos, P.
    Keyword
    Multi objective optimal operation management
    Pareto optimal solution
    Modified grey wolf optimizer
    Micro-grid
    Renewable energy sources
    Rights
    ©2018 IOS Press. Reproduced in accordance with the publisher's self-archiving policy. The final publication is available at IOS Press through https://doi.org/10.3233/JIFS-171688
    Peer-Reviewed
    Yes
    
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    Abstract
    Investigation of the environmental/economic optimal operation management of a microgrid (MG) as a case study for applying a novel modified multi-objective grey wolf optimizer (MMOGWO) algorithm is presented in this paper. MGs can be considered as a fundamental solution in order for distributed generators’ (DGs) management in future smart grids. In the multi-objective problems, since the objective functions are conflict, the best compromised solution should be extracted through an efficient approach. Accordingly, a proper method is applied for exploring the best compromised solution. Additionally, a novel distance-based method is proposed to control the size of the repository within an aimed limit which leads to a fast and precise convergence along with a well-distributed Pareto optimal front. The proposed method is implemented in a typical grid-connected MG with non-dispatchable units including renewable energy sources (RESs), along with a hybrid power source (micro-turbine, fuel-cell and battery) as dispatchable units, to accumulate excess energy or to equalize power mismatch, by optimal scheduling of DGs and the power exchange between the utility grid and storage system. The efficiency of the suggested algorithm in satisfying the load and optimizing the objective functions is validated through comparison with different methods, including PSO and the original GWO.
    URI
    http://hdl.handle.net/10454/16610
    Version
    Accepted Manuscript
    Citation
    Javidsharifi M, Niknam T, Aghaei J et al (2018) Multi-objective day-ahead scheduling of microgrids using modified grey wolf optimizer algorithm. Journal of Intelligent & Fuzzy Systems. 36(3): 2857-2870.
    Link to publisher’s version
    https://doi.org/10.3233/JIFS-171688
    Type
    Article
    Collections
    Engineering and Informatics Publications

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