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Wind Power Monitoring and Control Based on Synchrophasor Measurement Data Mining

Author

Listed:
  • Mario Klarić

    (Manufacturing and Construction, Dalekovod JSC for Engineering, Zagreb 10000, Croatia)

  • Igor Kuzle

    (Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb 10000, Croatia)

  • Ninoslav Holjevac

    (Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb 10000, Croatia)

Abstract

More and more countries and utilities are trying to develop smart grid projects to make transformation of their power infrastructure towards future grids with increased share of renewable energy production and near zero emissions. The intermittent nature of solar and wind power can in general cause large problems for power system control. Parallel to this process, the aging of existing infrastructure also imposes requirements to utility budgets in the form of a need for large capital investments in reconstruction or maintenance of key equipment. Synchrophasor and other synchronized measurement technologies are setting themselves as one of the solutions for larger wind power integration. With that aim, in this paper one possible solution for wind power control through data mining algorithms used on a large quantity of data gathered from phasor measurement units (PMU) is described. Developed model and algorithm are tested on an IEEE 14 bus test system as well as on real measurements made on wind power plants currently in operation. One such wind power plant is connected to the distribution grid and the other one to the transmission grid. Results are analyzed and compared.

Suggested Citation

  • Mario Klarić & Igor Kuzle & Ninoslav Holjevac, 2018. "Wind Power Monitoring and Control Based on Synchrophasor Measurement Data Mining," Energies, MDPI, vol. 11(12), pages 1-23, December.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3525-:d:191400
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    References listed on IDEAS

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    Cited by:

    1. Thomas I. Strasser & Sebastian Rohjans & Graeme M. Burt, 2019. "Methods and Concepts for Designing and Validating Smart Grid Systems," Energies, MDPI, vol. 12(10), pages 1-5, May.
    2. Goran Petrovic & Juraj Alojzije Bosnic & Goran Majic & Marin Despalatovic, 2019. "A Design of PWM Controlled Calibrator of Non-Sinusoidal Voltage Waveforms," Energies, MDPI, vol. 12(10), pages 1-14, May.
    3. Zoran Zbunjak & Igor Kuzle, 2019. "System Integrity Protection Scheme (SIPS) Development and an Optimal Bus-Splitting Scheme Supported by Phasor Measurement Units (PMUs)," Energies, MDPI, vol. 12(17), pages 1-21, September.
    4. Gyul Lee & Do-In Kim & Seon Hyeog Kim & Yong-June Shin, 2019. "Multiscale PMU Data Compression via Density-Based WAMS Clustering Analysis," Energies, MDPI, vol. 12(4), pages 1-17, February.

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