Impacts of Tie-Lines and Wind Generator Location on Small Signal Stability of a Power System

Abstract

This paper analyses the impact of tie-lines connecting different areas of power system and the location of wind farms on the small signal stability of a power system. The analysis is conducted using Monte Carlo simulation via modal analysis. The random samples are generated from two-parameter Weibull distribution to obtain possible representation of wind speed needed for the generation of wind power using Latin hypercube sampling techniques. The sampling technique allows the usage of a small sample size, which helps in reducing the simulation cost without jeopardising the accuracy of the result. Different scenarios are created and the oscillatory modes are calculated for different operating condition. The changes in modal characteristic of the system due to different operating conditions are evaluated by observing the movement on the complex plane. The results of the modal analysis for each scenario are validated using time domain simulation. Some of the key results show that wind power can have either positive or negative impact on the oscillation of a power system depending on the location in which it is integrated into the power system. It is also found out that strengthening the weak tie-lines can greatly improve the inter-area mode. This paper is useful in the planning stage of wind power projects.

Keywords

• Wind power; Tie-lines; Power systems; Small signal stability; Wind power location; Monte Carlo simulation

References

1. G. Papaefthymiou, et al., "Integration of stochastic generation in power systems," International Journal of Electrical Power & Energy Systems, vol. 28, pp. 655- , 2006.
2. T. R. Ayodele, et al., "The Challenges of Integrating Intermittent Renewable Energy sources on the Power System grid Integrity:A review," presented at the 1st International Conference on Green and Sustainable Technology: Research and Workforce Development, Greensboro, North Carolina, USA, 2010.
3. P. Kundur, Power System Stability and Control,The EPRI Power System Engineering Series vol. 1: McGraw- Hill,Inc, New York, 1994.
4. A. Mendonca and J. A. P. Lopes, "Impact of large scale wind power integration on small signal stability," in International Conference on Future Power Systems,, Amsterdam, 2005, pp. 5 pp.-5.
5. J. G. Slootweg and W. L. Kling, "The Impact of Wind Power Generation on Power System Oscillations," Electric Power System Research, vol. 67, pp. 9-20, 2003.
6. D. J. Vowles, et al., "Effect of wind generation on small- signal stability ; A New Zealand Example," in Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008
7. IEEE, Pittsburgh, Pennsylvania, USA, 2008, pp. 1-8.
8. J. Stenzel, et al., "Impact of Large Scale Wind Power on Power System Stability," in 5th International Workshop on Large-Scale Integration of Wind and Transmission Network for Offshore Wind Farm., Glascow, Scotland, L. B. Shi, et al., "Analysis of Impacts of Grid-Connected Wind Power on Small Signal Stability," Wind Energy (Wiley online), 2010.

9. S. Ghosh and N. Senroy, "Effect of generator type on the participation of adjacent synchronous machines in electromechanical oscillations," in Joint International Conference on Power Electronics, Drives and Energy Systems (PEDES) India, 2010, pp. 1-3.
10. T. R. Ayodele, et al., "Performance Evaluation of Sampling Techniques in Monte Carlo Simulation-Based Probabilistic Small Signal Stability Ananlysis," presented at the The 23rd IASTED International Conference on Modelling and Simulation (MS 2012), Banff, Canada,
11. H. Yu, et al., "Probabilistic Load Flow Evaluation With Hybrid Latin Hypercube Sampling and Cholesky Decomposition," IEEE Transaction on Power Systems, vol. 24, 2009.
12. J. C. Helton and F. J. Davis, "Latin Hypercube Sampling and the Propagation of Uncertainty in Analysis of Complex System," Reliability Engineering & System Safety, vol. 81, pp. 23-69, 2003.
13. T. R. Ayodele, et al., "Probabilistic Small Signal Stability Analysis of a Power System Consisting Intermittent Wind Generation " in 12th International conference on Probabilistic Methods Applied to Power System, Istanbul, Turkey, 2012.
14. J. Chow, "Power System Toolbox 2.0- Dynamic Tutoria and Functions," Cherry Tree Scientific Software, Appendix Table 3. Wind distribution parameters Parameters Values 24 61m/s Scale, (c) Time (s) (b)