IDEAS home Printed from https://ideas.repec.org/a/bjc/journl/v11y2024i11p978-1001.html
   My bibliography  Save this article

Parallel Mode Estimation Improvement in Power Networks based on Optimal ANFIS Approach

Author

Listed:
  • Meisam Arabpour

    (Department of Electrical Engineering, Kerman Branch, Islamic Azad University, Kerman, Iran)

  • Alimorad Khajehzadeh

    (Department of Electrical Engineering, Kerman Branch, Islamic Azad University, Kerman, Iran)

  • Mehdi Jafari Shahbazzadeh

    (Department of Electrical Engineering, Kerman Branch, Islamic Azad University, Kerman, Iran)

  • Mahdiyeh Eslami

    (Department of Electrical Engineering, Kerman Branch, Islamic Azad University, Kerman, Iran)

Abstract

In this research, the issue of non-technical losses in the distribution network was addressed, which should have been detected. Distribution networks and transmission lines have different parameters, so their state estimation and modeling are completely different. This problem causes the detection of non-technical losses in the distribution network by mode conversion to suffer a series of computational complications. Therefore, an attempt has been made to improve the parameters of voltage, primary current, passing current and bus energy along with error estimation after estimating the state of the distributed network so that non-technical losses can be detected. Therefore, a hybrid approach based on observer-based fuzzy neural network filter and genetic algorithm is used. Due to the existence of errors, the fuzzy neural network filter has been used, the reason for its three-dimensionality is that the system is non-linear and the errors and states may be different at different times. This research, in one case, has estimated the state of the distribution network with the aim of detecting non-technical losses. The observer can check these different situations at different times. Also, because the problem of detecting non-technical losses in the distribution network based on state estimation is assumed as a hard problem, therefore, the distribution network environment can be assumed as a main platform as a search environment for optimization algorithms. . Therefore, the use of intelligent algorithms from the family of fuzzy neural network and evolutionary algorithms and crowd intelligence can be interesting for estimating the optimal state with the aim of detecting non-technical losses in the distribution network. Hence, genetic algorithm is also used for optimization. After considering the main parameters to estimate the system state with the proposed approach, the results obtained from the simulation indicate the improvement of the state estimation and the detection of non-technical losses in the distribution network along with the minimization of the error estimation compared to the initial state.

Suggested Citation

  • Meisam Arabpour & Alimorad Khajehzadeh & Mehdi Jafari Shahbazzadeh & Mahdiyeh Eslami, 2024. "Parallel Mode Estimation Improvement in Power Networks based on Optimal ANFIS Approach," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(11), pages 978-1001, November.
    • Handle: RePEc:bjc:journl:v:11:y:2024:i:11:p:978-1001
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrsi/digital-library/volume-11-issue-11/978-1001.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrsi/articles/parallel-mode-estimation-improvement-in-power-networks-based-on-optimal-anfis-approach/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yoldaş, Yeliz & Önen, Ahmet & Muyeen, S.M. & Vasilakos, Athanasios V. & Alan, İrfan, 2017. "Enhancing smart grid with microgrids: Challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 205-214.
    2. Sreedharan, P. & Farbes, J. & Cutter, E. & Woo, C.K. & Wang, J., 2016. "Microgrid and renewable generation integration: University of California, San Diego," Applied Energy, Elsevier, vol. 169(C), pages 709-720.
    Full references (including those not matched with items on IDEAS)

    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. Jurasz, Jakub & Beluco, Alexandre & Canales, Fausto A., 2018. "The impact of complementarity on power supply reliability of small scale hybrid energy systems," Energy, Elsevier, vol. 161(C), pages 737-743.
    2. Robledo, Carla B. & Oldenbroek, Vincent & Abbruzzese, Francesca & van Wijk, Ad J.M., 2018. "Integrating a hydrogen fuel cell electric vehicle with vehicle-to-grid technology, photovoltaic power and a residential building," Applied Energy, Elsevier, vol. 215(C), pages 615-629.
    3. C. K. Woo & K. H. Cao & H. Qi & J. Zarnikau & R. Li, 2024. "Price responsiveness of solar and wind capacity demands," Post-Print hal-04597188, HAL.
    4. Lucas Cuadra & Miguel Del Pino & José Carlos Nieto-Borge & Sancho Salcedo-Sanz, 2017. "Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms," Energies, MDPI, vol. 10(8), pages 1-31, July.
    5. Chen, Weidong & Zeng, Yu & Xu, Chongqing, 2019. "Energy storage subsidy estimation for microgrid: A real option game-theoretic approach," Applied Energy, Elsevier, vol. 239(C), pages 373-382.
    6. Jin, Tao & Liu, Siyi & Flesch, Rodolfo C.C. & Su, Wencong, 2017. "A method for the identification of low frequency oscillation modes in power systems subjected to noise," Applied Energy, Elsevier, vol. 206(C), pages 1379-1392.
    7. Bhattacharjee, Vikram & Khan, Irfan, 2018. "A non-linear convex cost model for economic dispatch in microgrids," Applied Energy, Elsevier, vol. 222(C), pages 637-648.
    8. Pan, Pengcheng & Sun, Yuwei & Yuan, Chengqing & Yan, Xinping & Tang, Xujing, 2021. "Research progress on ship power systems integrated with new energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    9. Vinny Motjoadi & Pitshou N. Bokoro & Moses O. Onibonoje, 2020. "A Review of Microgrid-Based Approach to Rural Electrification in South Africa: Architecture and Policy Framework," Energies, MDPI, vol. 13(9), pages 1-22, May.
    10. Joseph Nyangon & Ruth Akintunde, 2024. "Anomaly Detection in California Electricity Price Forecasting: Enhancing Accuracy and Reliability Using Principal Component Analysis," Papers 2412.07787, arXiv.org.
    11. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Challenges, opportunities, and strategies for undertaking integrated precinct-scale energy–water system planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    12. Deetjen, Thomas A. & Vitter, J. Scott & Reimers, Andrew S. & Webber, Michael E., 2018. "Optimal dispatch and equipment sizing of a residential central utility plant for improving rooftop solar integration," Energy, Elsevier, vol. 147(C), pages 1044-1059.
    13. Semaria Ruiz & Julian Patiño & Alejandro Marquez-Ruiz & Jairo Espinosa & Eduardo Duque & Paola Ortiz, 2019. "Optimal Design of a Diesel-PV-Wind-Battery-Hydro Pumped POWER system with the Integration of ELECTRIC vehicles in a Colombian Community," Energies, MDPI, vol. 12(23), pages 1-19, November.
    14. Kolasa, Piotr & Janowski, Mirosław, 2017. "Study of possibilities to store energy virtually in a grid (VESS) with the use of smart metering," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1513-1517.
    15. Sujie Shao & Qingtao Zeng & Shaoyong Guo & Xuesong Qiu, 2018. "Random Violation Risk Degree Based Service Channel Routing Mechanism in Smart Grid," Energies, MDPI, vol. 11(11), pages 1-18, October.
    16. Guillermo Tapia-Tinoco & David Granados-Lieberman & David A. Rodriguez-Alejandro & Martin Valtierra-Rodriguez & Arturo Garcia-Perez, 2020. "A Robust Electric Spring Model and Modified Backward Forward Solution Method for Microgrids with Distributed Generation," Mathematics, MDPI, vol. 8(8), pages 1-32, August.
    17. Molavi, Anahita & Shi, Jian & Wu, Yiwei & Lim, Gino J., 2020. "Enabling smart ports through the integration of microgrids: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 258(C).
    18. Zidane, Tekai Eddine Khalil & Muis, Zarina Ab & Ho, Wai Shin & Zahraoui, Younes & Aziz, Ali Saleh & Su, Chun-Lien & Mekhilef, Saad & Elia Campana, Pietro, 2025. "Power systems and microgrids resilience enhancement strategies: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    19. Liu, Cheng-Yi & Huang, Chun-Kai & Huang, Yen-Yu & Chang, Kun-Chieh & Yu, Kun-Lin & Chiang, Chien-Hung & Wu, Chun-Guey & Lee, Shih-Chang & Yen, Wei-Yu & Sheu, Jinn-Kong & Shi, Jin-Wei, 2022. "Flexible multijunction solar cells embedded inside smart dust modules for outdoor applications to Smart Grids," Applied Energy, Elsevier, vol. 306(PA).
    20. Wang, Richard & Hsu, Shu-Chien & Zheng, Saina & Chen, Jieh-Haur & Li, Xuran Ivan, 2020. "Renewable energy microgrids: Economic evaluation and decision making for government policies to contribute to affordable and clean energy," Applied Energy, Elsevier, vol. 274(C).

    More about this item

    Statistics

    Access and download statistics

    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:bjc:journl:v:11:y:2024:i:11:p:978-1001. 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: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrsi/ .

    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.