IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i3p343-d92749.html
   My bibliography  Save this article

Reliability Assessment of Power Generation Systems Using Intelligent Search Based on Disparity Theory

Author

Listed:
  • Athraa Ali Kadhem

    (Department of Electrical and Electronic Engineering, University Putra Malaysia, Selangor 43400, Malaysia)

  • Noor Izzri Abdul Wahab

    (Department of Electrical and Electronic Engineering, University Putra Malaysia, Selangor 43400, Malaysia)

  • Ishak Aris

    (Department of Electrical and Electronic Engineering, University Putra Malaysia, Selangor 43400, Malaysia)

  • Jasronita Jasni

    (Department of Electrical and Electronic Engineering, University Putra Malaysia, Selangor 43400, Malaysia)

  • Ahmed N. Abdalla

    (Department of Engineering Technology, University Malaysia Pahang, Kuantan 26300, Malaysia)

Abstract

The reliability of the generating system adequacy is evaluated based on the ability of the system to satisfy the load demand. In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. Disparity evolution is used to enhance the performance of the probability of mutation in a genetic algorithm (GA) by incorporating features from the paradigm into the disparity theory. The DEGA is based on metaheuristic searching for the truncated sampling of state-space for the reliability assessment of power generation system adequacy. Two reliability test systems (IEEE-RTS-79 and (IEEE-RTS-96) are used to demonstrate the effectiveness of the proposed algorithm. The simulation result shows the DEGA can generate a larger variety of the individuals in an early stage of the next population generation. It is also able to estimate the reliability indices accurately.

Suggested Citation

  • Athraa Ali Kadhem & Noor Izzri Abdul Wahab & Ishak Aris & Jasronita Jasni & Ahmed N. Abdalla, 2017. "Reliability Assessment of Power Generation Systems Using Intelligent Search Based on Disparity Theory," Energies, MDPI, vol. 10(3), pages 1-13, March.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:343-:d:92749
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/3/343/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/3/343/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Akwasi F. Mensah & Leonardo Dueñas-Osorio, 2012. "A Closed-Form Technique for the Reliability and Risk Assessment of Wind Turbine Systems," Energies, MDPI, vol. 5(6), pages 1-17, June.
    2. Lin, Jin & Cheng, Lin & Chang, Yao & Zhang, Kai & Shu, Bin & Liu, Guangyi, 2014. "Reliability based power systems planning and operation with wind power integration: A review to models, algorithms and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 921-934.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Athraa Ali Kadhem & Noor Izzri Abdul Wahab & Ishak Aris & Jasronita Jasni & Ahmed N. Abdalla, 2017. "Advanced Wind Speed Prediction Model Based on a Combination of Weibull Distribution and an Artificial Neural Network," Energies, MDPI, vol. 10(11), pages 1-17, October.
    2. Martin Onyeka Okoye & Junyou Yang & Zhenjiang Lei & Jingwei Yuan & Huichao Ji & Haixin Wang & Jiawei Feng & Tunmise Ayode Otitoju & Weidong Li, 2020. "Predictive Reliability Assessment of Generation System," Energies, MDPI, vol. 13(17), pages 1-13, August.
    3. Lin He & Chang-Ling Li & Qing-Yun Nie & Yan Men & Hai Shao & Jiang Zhu, 2017. "Core Abilities Evaluation Index System Exploration and Empirical Study on Distributed PV-Generation Projects," Energies, MDPI, vol. 10(12), pages 1-18, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chang-Gi Min & Mun-Kyeom Kim, 2017. "Flexibility-Based Evaluation of Variable Generation Acceptability in Korean Power System," Energies, MDPI, vol. 10(6), pages 1-12, June.
    2. Li, Jinghua & Zhou, Jiasheng & Chen, Bo, 2020. "Review of wind power scenario generation methods for optimal operation of renewable energy systems," Applied Energy, Elsevier, vol. 280(C).
    3. Saheed Lekan Gbadamosi & Nnamdi I. Nwulu, 2020. "Optimal Power Dispatch and Reliability Analysis of Hybrid CHP-PV-Wind Systems in Farming Applications," Sustainability, MDPI, vol. 12(19), pages 1-16, October.
    4. Ali Kadhem, Athraa & Abdul Wahab, Noor Izzri & Aris, Ishak & Jasni, Jasronita & Abdalla, Ahmed N., 2017. "Computational techniques for assessing the reliability and sustainability of electrical power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1175-1186.
    5. Shang, Ce & Lin, Teng & Li, Canbing & Wang, Keyou & Ai, Qian, 2021. "Joining resilience and reliability evaluation against both weather and ageing causes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    6. Zendehboudi, Sohrab & Rezaei, Nima & Lohi, Ali, 2018. "Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review," Applied Energy, Elsevier, vol. 228(C), pages 2539-2566.
    7. Abdin, Islam & Li, Yan-Fu & Zio, Enrico, 2017. "Risk assessment of power transmission network failures in a uniform pricing electricity market environment," Energy, Elsevier, vol. 138(C), pages 1042-1055.
    8. Akhavein, Ali & Porkar, Babak, 2017. "A composite generation and transmission reliability test system for research purposes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 331-337.
    9. Shafiee, Mahmood & Sørensen, John Dalsgaard, 2019. "Maintenance optimization and inspection planning of wind energy assets: Models, methods and strategies," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    10. Antonio Casimiro Caputo & Alessandro Federici & Pacifico Marcello Pelagagge & Paolo Salini, 2023. "Scenario Analysis of Offshore Wind-Power Systems under Uncertainty," Sustainability, MDPI, vol. 15(24), pages 1-21, December.
    11. Jaalam, N. & Rahim, N.A. & Bakar, A.H.A. & Tan, ChiaKwang & Haidar, Ahmed M.A., 2016. "A comprehensive review of synchronization methods for grid-connected converters of renewable energy source," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1471-1481.
    12. Zhou, P. & Jin, R.Y. & Fan, L.W., 2016. "Reliability and economic evaluation of power system with renewables: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 537-547.
    13. Memon, Mudasir Ahmed & Mekhilef, Saad & Mubin, Marizan & Aamir, Muhammad, 2018. "Selective harmonic elimination in inverters using bio-inspired intelligent algorithms for renewable energy conversion applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2235-2253.
    14. Caputo, Antonio C. & Federici, Alessandro & Pelagagge, Pacifico M. & Salini, Paolo, 2023. "Offshore wind power system economic evaluation framework under aleatory and epistemic uncertainty," Applied Energy, Elsevier, vol. 350(C).
    15. Eryilmaz, Serkan & Navarro, Jorge, 2022. "A decision theoretic framework for reliability-based optimal wind turbine selection," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    16. Escalera, Alberto & Hayes, Barry & Prodanović, Milan, 2018. "A survey of reliability assessment techniques for modern distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 344-357.
    17. Wilkie, David & Galasso, Carmine, 2020. "A probabilistic framework for offshore wind turbine loss assessment," Renewable Energy, Elsevier, vol. 147(P1), pages 1772-1783.
    18. Fábio Luiz Usberti & Celso Cavellucci & Christiano Lyra, 2023. "Interruption flows for reliability evaluation of power distribution networks," Operational Research, Springer, vol. 23(1), pages 1-23, March.
    19. Lu, H.W. & Pan, H.Y. & He, L. & Zhang, J.Q., 2016. "Importance analysis of off-grid wind power generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 999-1007.
    20. Ashrafi, Maryam & Davoudpour, Hamid & Khodakarami, Vahid, 2015. "Risk assessment of wind turbines: Transition from pure mechanistic paradigm to modern complexity paradigm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 347-355.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:343-:d:92749. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.