Total views : 325

Quantitative Frequency Security Assessment for Multi-Machine Power System based on COI frequency

Affiliations

  • Centre for Advanced Power and Energy Research (CAPER), Department of Electrical and Electronic Engineering, University Putra Malaysia, 43400, Selangor, Malaysia

Abstract


The frequency is one of the instruments for measuring the health status of the power system, due to its ability to anticipate any imbalance between generations and loads. If the generated power is adequate for the system load and losses, then, the system will be in a steady state, otherwise frequency deviates from nominal value due to the mismatch between the generation and load. If the frequency continues to deviate from nominal value, the system may collapse. The assessment of frequency stability level becomes an essential aspect of power system operation and also for projecting the ability of the power system to maintain nominal frequency when subjected to any disturbance. In this paper, a method is proposed to evaluate frequency security of multi-machine power system using transient frequency deviation index (TFDI) which is based on Center of Inertia (COI) referred frequency. The proposed method has been tested on the New England 39- bus test system. Results show that the proposed method takes the advantage of TFDI in accumulating the effect of frequency trajectory deviations. These frequency trajectories may be obtained from the time domain simulation or Wide Area Measurement System (WAMS). The results also show the advantages of COI referred frequency in representing the equivalent frequency of the system. The method would provide a reliable and efficient base for load shedding relays adjustment and operation control.

Keywords

COI Frequency, Frequency Stability Assessment, Transient Frequency Deviation Index, Quantitative Security Assessment.

Full Text:

 |  (PDF views: 249)

References


  • Kundur P. Power system stability and control; 1994.
  • Fouad A, Stanton S. Transient stability of a multi-machine power system Part I: Investigation of system trajectories. IEEE Trans Power Appar Syst. 1981; PAS-100(7):3408–16.
  • Cai ZX. A direct method for frequency stability assessment of power systems; 2000 Oct. p. 285–9.
  • Taishan XYX. Quantitative assessments of transient frequency deviation acceptability. chines; 2002. p. 1–4.
  • Zhang H, Liu Y. New index for frequency deviation security assessment. 2010 9th Int Power Energy Conf, IPEC 2010; 2010. p. 1031–4.
  • Zhang H, Hou Z, Liu Y. Online security assessment of power system frequency deviation. 2012 Asia-Pacific Power Energy Eng Conf; 2012. p. 1–4.
  • Terzija VV. Adaptive under frequency load shedding based on the magnitude of the disturbance estimation. IEEE Trans Power Syst. 2006; 21(3):1260–6.
  • Seethalekshmi K, Singh SN, Srivastava SC. WAMS assisted frequency and voltage scheme. 2009. p. 1–8.
  • Xu Y, Dai Y, Dong ZY, Xue Y, Wong KP. Load shedding and its strategies against frequency instability in power systems. IEEE Power Energy Soc Gen Meet. 2012. p. 1–7.
  • Xu X, Zhang H, Chai Y, Shi F, Li Z, Li W. Trajectory sensitivity -based emergency load shedding optimal algorithm. Prepr 5th Int Conf Electr Util Deregul Restruct power Technol; Changsh, China. 2015 Nov.
  • Nedic DP. Simulation of large system disturbances. Electr Eng Electron; 2003 Dec.
  • Rudez U, Mihalic R. Monitoring the first frequency derivative to improve adaptive underfrequency load-shedding schemes. IEEE Trans Power Syst. 2011; 26(2):839–46.
  • Li A. A method for frequency dynamics analysis and load shedding assessment based on the trajectory of power system simulation. System; 2008 Apr. p. 1335–9.
  • Djukanovic MB, Popovic DP, Sobajic DJ, Pao Y-H. Prediction of power system frequency response after generator outages using neural nets. IEE Proc C Gener Transm Distrib. 1993; 140(5):389.
  • Mokhlis H, Laghari JA, Bakar AHBA, Karimi M. A fuzzy based under-frequency load shedding scheme for islanded distribution network connected with DG. Int Rev Electr Eng. 2012; 7(4):4992–5000.
  • Lalor GR. Frequency control on an island power system with evolving plant mix; 2005 Sep. p. 221.
  • Meegahapola L, Flynn D. Impact on transient and frequency stability for a power system at very high wind penetration. IEEE PES Gen Meet; 2010. p. 1–8.
  • Frequency Control Workstream; 2011. p. 1–11.
  • Doherty R, Mullane A, Nolan G, Burke DJ, Bryson A, O’Malley M. An assessment of the impact of wind generation on system frequency control. IEEE Trans Power Syst. 2010; 25(1):452–60.
  • Lei X, Lerch E, Xie CY. Frequency security constrained short-term unit commitment. Electr Power Syst Res. 2002; 60(3):193–200.
  • Hong YY, Wei SF. Multiobjective under frequency load shedding in an autonomous system using hierarchical genetic algorithms. IEEE Trans Power Deliv. 2010; 25(3):1355–62.
  • Lawrence EO, Martinez C, Xue S, Martinez M. Review of the recent frequency performance of the Eastern, Western and ERCOT Interconnections; 2010 Dec.
  • Yan R, Saha T. Frequency response with significant wind power penetration: Case study of a realistic power system. 2014 IEEE PES General Meeting, Conference and Exposition; 2014. p. 1–5.
  • Nahid-Al-Masood, Yan R, Saha TK. A new tool to estimate maximum wind power penetration level: In perspective of frequency response adequacy. Appl Energy. 2015; 154:209– 20.
  • Yan R, Saha TK. A probabilistic index for estimating frequency response of a power system with high wind power penetration. International Conference on Electrical and Computer Engineering (ICECE); 2014. p. 583–6.
  • Akorede MF, Hizam H, Aris I, Kadir MZAA. Qualitative and quantitative analysis of system stability and power quality in networks with DG of different penetration levels. Int Rev Electr Eng. 2010; 5(5):2366–77.
  • Zhang XY, Hengxu, Yutian LIU. Quantitative assessment of transient frequency deviation security considering cumulative effect. Chines J. 2010.
  • Zhang H, Li C, Liu Y. Quantitative frequency security assessment method considering cumulative effect and its applications in frequency control. Int J Electr Power Energy Syst. 2015; 65:12–20.
  • IEEE 10 Generator 39 Bus System. Network. Available from: http://psdyn.ece.wisc.edu/IEEE_benchmarks/ 30. Ye H, Liu Y. Design of model predictive controllers for adaptive damping of inter-area oscillations. Int J Electr Power Energy Syst. 2013; 45(1):509–18.
  • Transient Security Assessment Tool (TSAT) user manual; 2011.

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.