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Anticipating and Coordinating Voltage Control for Interconnected Power Systems

Author

Listed:
  • Mohammad Moradzadeh

    (Electrical Energy Laboratory, Department of Electrical Energy, Systems and Automation (EESA),Ghent University, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium)

  • René Boel

    (SYSTeMS Research Group, EESA, Technologiepark 914, 9052 Zwijnaarde, Belgium)

  • Lieven Vandevelde

    (Electrical Energy Laboratory, Department of Electrical Energy, Systems and Automation (EESA),Ghent University, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium)

Abstract

This paper deals with the application of an anticipating and coordinating feedback control scheme in order to mitigate the long-term voltage instability of multi-area power systems. Each local area is uniquely controlled by a control agent (CA) selecting control values based on model predictive control (MPC) and is possibly operated by an independent transmission system operator (TSO). Each MPC-based CA only knows a detailed local hybrid system model of its own area, employing reduced-order quasi steady-state (QSS) hybrid models of its neighboring areas and even simpler PV models for remote areas, to anticipate (and then optimize) the future behavior of its own area. Moreover, the neighboring CAs agree on communicating their planned future control input sequence in order to coordinate their own control actions. The feasibility of the proposed method for real-time applications is explained, and some practical implementation issues are also discussed. The performance of the method, using time-domain simulation of the Nordic32 test system, is compared with the uncoordinated decentralized MPC (no information exchange among CAs), demonstrating the improved behavior achieved by combining anticipation and coordination. The robustness of the control scheme against modeling uncertainties is also illustrated.

Suggested Citation

  • Mohammad Moradzadeh & René Boel & Lieven Vandevelde, 2014. "Anticipating and Coordinating Voltage Control for Interconnected Power Systems," Energies, MDPI, vol. 7(2), pages 1-21, February.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:2:p:1027-1047:d:33300
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    Citations

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    Cited by:

    1. Izaskun Garrido & Aitor J. Garrido & Stefano Coda & Hoang B. Le & Jean Marc Moret, 2016. "Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV)," Energies, MDPI, vol. 9(8), pages 1-14, August.
    2. Feras Alasali & Stephen Haben & Victor Becerra & William Holderbaum, 2017. "Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems," Energies, MDPI, vol. 10(10), pages 1-18, October.

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