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    Stochastic Analysis (MCS) for Mitigation of Reliability Indicators of the Power Distribution System

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    Trabalho apresentado em evento
    Date
    2022
    Author
    Neves Neto, João Cardoso das
    Abubakar, Ahmad
    Almeida, Carlos Frederico Meschini
    Delbone, Edval
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    Abstract
    The study aims to indicate the methodology of an algorithm to mitigate the supply reliability indicators through small-scale simulations with the IEEE 34 model through deterministic analysis of the Monte Carlo Method through Matlab, to calculate the SAIDI and SAIFI indicators independent of the problem caused in the distribution. The algorithm consists of analyzing the data and selecting the recloser and/or DG to serve the most consumers. The results show that the best results are with the activation of the DG at bar 890 of the model, where the SAIDI obtained a reduction of 57.88% and the SAIFI a reduction of 57.63%. Thus, the implementation of smart grid and DG systems by distribution system operators will improve the reliability of the power system. Thus, with the methodology applied on a large scale, to exemplify, in the reliability indicators of some South American countries, there are reductions, SAIFI from 17.6 to 7 events/year and SAIDI from 21.6 to 9.18 hours/year. © 2022 IEEE.
    1. Energy Integration
    2. SAIDI
    3. SAIFI
    4. Smart-grid
    5. South American
    6. Electric power distribution
    7. MATLAB
    8. Monte Carlo methods
    9. Reclosing circuit breakers
    10. Reliability analysis
    11. Stochastic systems
    12. % reductions
    13. Energy-integration
    14. Power-distribution system
    15. Reliability indicators
    16. SAIDI
    17. SAIFI
    18. Smart grid
    19. South american
    20. Stochastic analysis
    21. Supply reliability
    22. Smart power grids
    URI
    https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149180146&doi=10.1109%2fIEEEPESGTDLatinAmeri53482.2022.10038302&partnerID=40&md5=20396cefcc0746469ebe956924cf895f
    https://repositorio.maua.br/handle/MAUA/620
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