IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v100y2017icp35-43.html
   My bibliography  Save this article

A model-based framework for fault estimation and accommodation applied to distributed energy resources

Author

Listed:
  • Allen, James T.
  • El-Farra, Nael H.

Abstract

This paper presents the development and approach of a model-based fault identification and accommodation framework applied to sampled-data controlled distributed energy resources subject to control actuator faults. The main objective of the proposed approach is to handle faults that degrade stability as well as performance, while remaining robust to false alarms. The proposed method allows for dual fault detection and estimation, through the use of an embedded system model that minimizes the residual between the estimated and sampled states at each sampling period by adjusting a fault parameter in the embedded model over a past horizon. The resulting fault parameter estimate is then used by the control system to find an optimal fault accommodation strategy by minimizing a predefined performance metric whilst ensuring closed-loop stability. The developed fault accommodation framework is then applied to a simulated model of a solid oxide fuel cell subject to both stability and performance degrading faults in the control actuators. A discussion of some of the practical implementation issues associated with the developed framework is also included.

Suggested Citation

  • Allen, James T. & El-Farra, Nael H., 2017. "A model-based framework for fault estimation and accommodation applied to distributed energy resources," Renewable Energy, Elsevier, vol. 100(C), pages 35-43.
  • Handle: RePEc:eee:renene:v:100:y:2017:i:c:p:35-43
    DOI: 10.1016/j.renene.2016.05.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148116304104
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2016.05.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ro, K & Rahman, S, 2003. "Control of grid-connected fuel cell plants for enhancement of power system stability," Renewable Energy, Elsevier, vol. 28(3), pages 397-407.
    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. Da Xue & Nael H. El-Farra, 2018. "Forecast-Triggered Model Predictive Control of Constrained Nonlinear Processes with Control Actuator Faults," Mathematics, MDPI, vol. 6(6), pages 1-20, June.
    2. Costa, Vinicius Braga Ferreira da & Bonatto, Benedito Donizeti, 2023. "Cutting-edge public policy proposal to maximize the long-term benefits of distributed energy resources," Renewable Energy, Elsevier, vol. 203(C), pages 357-372.

    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. Irfan, Muhammad & Iqbal, Jamshed & Iqbal, Adeel & Iqbal, Zahid & Riaz, Raja Ali & Mehmood, Adeel, 2017. "Opportunities and challenges in control of smart grids – Pakistani perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 652-674.
    2. Lund, H & Münster, E, 2003. "Modelling of energy systems with a high percentage of CHP and wind power," Renewable Energy, Elsevier, vol. 28(14), pages 2179-2193.
    3. Niknam, Taher & Fard, Abdollah Kavousi & Seifi, Alireza, 2012. "Distribution feeder reconfiguration considering fuel cell/wind/photovoltaic power plants," Renewable Energy, Elsevier, vol. 37(1), pages 213-225.
    4. Reddy, K.S. & Kumar, Madhusudan & Mallick, T.K. & Sharon, H. & Lokeswaran, S., 2014. "A review of Integration, Control, Communication and Metering (ICCM) of renewable energy based smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 180-192.
    5. Kaundinya, Deepak Paramashivan & Balachandra, P. & Ravindranath, N.H., 2009. "Grid-connected versus stand-alone energy systems for decentralized power--A review of literature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2041-2050, October.
    6. Chen, Scarlett & Kumar, Anikesh & Wong, Wee Chin & Chiu, Min-Sen & Wang, Xiaonan, 2019. "Hydrogen value chain and fuel cells within hybrid renewable energy systems: Advanced operation and control strategies," Applied Energy, Elsevier, vol. 233, pages 321-337.
    7. Deshmukh, M.K. & Deshmukh, S.S., 2008. "Modeling of hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(1), pages 235-249, January.
    8. Lund, H., 2006. "Large-scale integration of optimal combinations of PV, wind and wave power into the electricity supply," Renewable Energy, Elsevier, vol. 31(4), pages 503-515.
    9. Joseph Oyekale & Mario Petrollese & Vittorio Tola & Giorgio Cau, 2020. "Impacts of Renewable Energy Resources on Effectiveness of Grid-Integrated Systems: Succinct Review of Current Challenges and Potential Solution Strategies," Energies, MDPI, vol. 13(18), pages 1-48, September.
    10. Bazmi, Aqeel Ahmed & Zahedi, Gholamreza & Hashim, Haslenda, 2011. "Progress and challenges in utilization of palm oil biomass as fuel for decentralized electricity generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 574-583, January.
    11. Lund, Henrik, 2005. "Large-scale integration of wind power into different energy systems," Energy, Elsevier, vol. 30(13), pages 2402-2412.
    12. Bazmi, Aqeel Ahmed & Zahedi, Gholamreza, 2011. "Sustainable energy systems: Role of optimization modeling techniques in power generation and supply—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 3480-3500.

    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:eee:renene:v:100:y:2017:i:c:p:35-43. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.