Damping Adaptive Neural Controller Design in HVDC based on Offshore Wind Turbine to Improve Power System Stability

نوع مقاله : علمی-پژوهشی

نویسندگان

Department of Electrical Engineering, Shabestar Branch, Islamic Azad University, Shabestar, Iran

چکیده

Because of low losses and voltage drop, fast control of power, the limitless connection distance and isolation issues, using the High Voltage Direct Current (HVDC) transmission system based on Voltage Source Converters (VSC) is recommended to the power transfer in the electrical power networks included the offshore wind power plants (OWPP). The OWPPs are expected to meet the grid code necessities when requested to maintain stability. Utilization of the VSC HVDC along with the OWPP, can improve the control of power flow and the power system dynamic stability. In this paper, the impact of control of VSC HVDC based OWPP, on the dynamic stability of power systems is evaluated.  In this way, the dynamic modeling of power system equipped by the VSC HVDC and OWPP are proposed. In the proposed model, using the concepts of controllability and observability of electromechanical modes of power systems, a new approach to the design a supplementary damping controller in VSC HVDC based OWPP is presented. The damping controller is designed based on the nonlinear adaptive neural networks concepts and trained by a proposed online method. The simulation results which are done in MATLAB, show the effectiveness of the proposed control strategy.

کلیدواژه‌ها

عنوان مقاله [English]

Damping Adaptive Neural Controller Design in HVDC based on Offshore Wind Turbine to Improve Power System Stability

نویسندگان [English]

  • A. Hamidi
  • J. Beiza
  • T. Abedinzadeh
  • A. Daghighi
Department of Electrical Engineering, Shabestar Branch, Islamic Azad University, Shabestar, Iran
چکیده [English]

Because of low losses and voltage drop, fast control of power, the limitless connection distance and isolation issues, using the High Voltage Direct Current (HVDC) transmission system based on Voltage Source Converters (VSC) is recommended to the power transfer in the electrical power networks included the offshore wind power plants (OWPP). The OWPPs are expected to meet the grid code necessities when requested to maintain stability. Utilization of the VSC HVDC along with the OWPP, can improve the control of power flow and the power system dynamic stability. In this paper, the impact of control of VSC HVDC based OWPP, on the dynamic stability of power systems is evaluated.  In this way, the dynamic modeling of power system equipped by the VSC HVDC and OWPP are proposed. In the proposed model, using the concepts of controllability and observability of electromechanical modes of power systems, a new approach to the design a supplementary damping controller in VSC HVDC based OWPP is presented. The damping controller is designed based on the nonlinear adaptive neural networks concepts and trained by a proposed online method. The simulation results which are done in MATLAB, show the effectiveness of the proposed control strategy.

کلیدواژه‌ها [English]

  • Offshore wind turbine
  • VSC HVDC systems
  • damping adaptive neural controller
  • control configuration analysis

مراجع

[1] P.C. Carlos, D. Greaves, G. Iglesias, “A review of combined wave and offshore wind energy”, Renewable and Sustainable Energy Reviews, vol. 42, no. 9, pp. 141-153, 2015.
[2] M. Shafiee, “Maintenance logistics organization for offshore wind energy: current progress and future perspectives”, Renewable Energy, vol. 77, pp. 182-193, 2015.
[3] S. Cavazzi, A.G. Dutton, “An Offshore Wind Energy Geographic Information System (OWE-GIS) for assessment of the UK's offshore wind energy potential”, Renewable Energy, vol. 87, pp. 212-228, 2016.
[4] E. Mohamed, Kwok L. Lo, and O. Anaya-Lara, “Impacts of high penetration of  DFIG wind turbines on rotor angle stability of power systems”, Transactions on Sustainable Energy, vol. 63, pp. 759-76,2015.
[5] H. Ertong, and C. Liu, “Impacts of high penetration of  DFIG wind turbines on rotor angle stability of power systems”, Ocean Engineering, vol. 130, pp. 218-227,2017.
[6] D.García, José Luis, Carlos E. Ugalde-Loo, Fernando Bianchi, and Oriol Gomis-Bellmunt, “Input–output signal selection for damping of power system oscillations using wind power plants”, International Journal of Electrical Power & Energy Systems, vol. 58, pp. 75-84,2014.
[7] J-F. Adri, Y. Pipelzadeh, and Tim C. Green, “Blending HVDC-link energy storage and offshore wind turbine inertia for fast frequency response”, Transactions on Sustainable Energy, vol. 63, pp. 1059-1066,2015.
[8] C. Miguel Jiménez, et al, “Optimal power flow in multi-terminal HVDC grids with offshore wind farms and storage devices”, International Journal of Electrical Power & Energy Systems, vol. 65, pp. 291-298,2015.
[9] L. Hongzhi, and Z. Chen, “Contribution of VSC-HVDC to frequency regulation of power systems with offshore wind generation”, Transactions on Energy Conversion, vol. 30.3, pp. 918-926,2015.
[10] N. Sotirios, I. Georgios N. Patsakis, and Stavros A. Papathanassiou, “Assessment of communication-independent grid code compatibility solutions for VSC–HVDC connected offshore wind farms”, Electric Power Systems Research, vol. 121, pp. 38-51,2015.
[11] N.Taheri, and M. Banaei, “A supplementary neural controller for novel modeling of VSC HVDC to enhance dynamic stability in a power system”, In 2010 1st Power Electronic & Drive Systems & Technologies Conference (PEDSTC), pp. 7-12,2010.
[12] M_ R_, Banaei and N. Taheri, “An adaptive neural damping controller for HVDC transmission systems”, European Transactions on Electrical Power, vol. 21, pp. 910-923,2011.
[13] M.Rahimi, M.R.Esmaeili, “Power controller design and damping improvement of torsional oscillations in the 710 kW DFIG based wind turbine installed at the Binalood site”, Tabriz Journal of Electrical Engineering, vol. 46, no. 4, pp. 123-134, 2016 (in persian).
[14] R. Sayyad, A. Khodabakhshian, R. Hooshmand, “A New Systematic Design of Power System Stabilizer Using Classical and Genetic Algorithm Techniques for Wind Power Systems”, Tabriz Journal of Electrical Engineering, vol. 39, no. 1, pp. 13-23, 2009 (in persian).
[15] N.Shafaghatian, A.Kiani, N. Taheri, Z. Rahimkhani, and S- S. Masoumi, “Damping controller design based on FO-PID-EMA in VSC HVDC system to improve stability of hybrid power system”, Journal of central south university, vol. 2, pp. 403-417,2020.
[16] Y.ao, W.ei, et al, “Wide-area damping controller for power system interarea oscillations: a networked predictive control approach”, Transactions on Control Systems Technology, vol. 23.1, pp. 27-36,2015.
[17] P. Manuel, G. Robledo, “Controllability and observability for a linear time varying system with piecewise constant delay”, Acta Applicandae Mathematicae, vol. 136.1, pp. 193-216,2015.
[18] L.iu, Yan-Jun, et al, “Neural controller design-based adaptive control for nonlinear MIMO systems with unknown hysteresis inputs”, transactions on cybernetics, vol. 46.1, pp. 9-19,2016.
[19] M. Arefi, M-R.Jahed-Motlagh, H- R. Karimi, “Adaptive neural stabilizing controller for a class of mismatched uncertain nonlinear systems by state and output feedback”, transactions on cybernetics, vol. 45.8, pp. 1587-1596, 2015.
[20] L.iu, Yan-Jun, et al, “Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems”, Transactions on Neural Networks and Learning Systems, vol. 26.5, pp. 1007-1018,2015.
[21] Yu, Lei, et al, “Design of robust adaptive neural switching controller for robotic manipulators with uncertainty and disturbances”, Journal of Intelligent & Robotic Systems, vol. 77.3, pp. 571,2015.

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