Transient stability probability of a power system incorporating a wind farm
Source abstract
Abstract
An analytical approach for probabilistic evaluation of transient stability of a power system incorporating a wind farm is presented in this study. Based on the fact that the boundary of practical dynamic security region (PDSR) of a power system with double fed induction generators (DFIG) can be approximated by one or few hyper-planes in nodal power injection space, transient stability criterion for given configurations of pre-fault, fault-on and post-fault of a power system is to be expressed by certain expressions of linear combination of nodal injection vector and the transient stability probability (TSP) is further obtained with a much more simplified expression than the complex integral. Furthermore, considering uncertainties of nodal injection power including wind power and load, TSP is calculated analytically by Cornish-Fisher expansion, which can provide reliable evaluation results with high accuracy and much less computing time compared with Monte Carlo simulation. TSP and its visualization can further help operators and planners be aware of the degree of stability or instability and find critical components to monitor and reinforce. Test results on the New England 10-generators and 39-buses power system show the method’s effectiveness and significance for probabilistic security assessment.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Wind Turbine Control Systems · Power System Optimization and Stability · Wind Energy Research and Development
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (25)
Show source-provided references
1. Li J F, Cai F B, Qiao L M, et al. 2014 China Wind Power Review and Outlook. Beijing: China Environmental Science Press, 2014
2. Li J F, Cai F B, Qiao L M, et al. 2013 China Wind Power Review and Outlook. Beijing: China Environmental Science Press, 2013
3. Vittal E, O’Malley M, Keane A. Rotor angle stability with high penetrations of wind generation. IEEE T Power Syst, 2012; 27: 353–36210.1109/TPWRS.2011.2161097 ↗
4. Hao Z H, Yu Y X. The influence of doublyfed induction generator on stability of power system. Power Syst Prot Contr, 2011; 39: 7–11
5. Kayikci M, Milanovic J V. Assessing transient response of DFIGbased wind plants-the influence of model simplifications and parameters. IEEE T Power Syst, 2008; 23: 545–55410.1109/TPWRS.2008.919310 ↗
6. Nunes M V A, Peas L J A, Zurn H H, et al. Influence of the variable-speed wind generators in transient stability margin of the conventional generators integrated in electrical grids. IEEE T Energy Conv, 2004; 19: 692–70110.1109/TEC.2004.832078 ↗
7. Faried S O, Billinton R, Aboreshaid S. Probabilistic evaluation of transient stability of a wind farm, IEEE T Energy Conv, 2009; 24: 733–73910.1109/TEC.2009.2016035 ↗
8. Faried S O, Billinton R, Aboreshaid S. Probabilistic evaluation of transient stability of a power system incorporating wind farms, IET Renew Power Gener, 2010; 4: 299–30710.1049/iet-rpg.2009.0031 ↗
9. Fang J K, Wen J Y, Cheng S J, et al. Probabilistic assessment of power system transient stability incorporating SMES. http://dx. doi.org/10.1016/j.physc.2012.03.068, 2012
10. Li H Y, Ju P, Chen X Q, et al. Stochastic averaging method for quasi Hamiltonian system of multi-machine power systems. Sci Sin Tech 2015; 45: 766–77210.1360/N092014-00434 ↗
11. Li H Y, Ju P, Yu Y P, et al. Bounded fluctuations region and analytic method of intra-region probability in power system under stochastic excitations. Proc CSEE, 2015; 35: 3561–3568
12. Liu Q, Xue Y S, Dong Z Y, et al. Non-deterministic analysis for transient stability based on transient stability domain and conditional probability. Autom Elec Power Syst, 2007; 31: 1–6
13. Shen C, Fang Y J. Calculation of transient stability margin distribution under random power injection conditions. Autom Elec Power Syst, 2013; 37: 41–48
14. Yu Y X. Review of Study on methodology of security regions of power system. J Tianjin Univ, 2008; 41: 635–646
15. Palo A. Direct Methods for security regions of bulk power system. 1008608. California: EPRI, 2004
16. Qin C, Liu Y L, Yu Y X, et al. Dynamic security region of power systems with double fed induction generator. T China Electrotechnical Soc, 2015; 30: 157–163
17. Clark K, Miller N W, Sanchez-Gasca J J. Modeling of GE Wind Turbine-Generators for Grid Studies. New York: Gener Elec International Inc., 2009
18. User’s manual of transient stability program PSD-BPA (in Chinese). Beijing: China Electric Power Research Institute, 2008
19. Bowden G J, Barker P R, Shestopal V O. The Weibull distribution function and wind power statistics. Wind Eng, 1983; 7: 85–98
20. Wang C S, Zheng H F, Xie Y H. Probabilistic power flow containing distributed generation in distribution system. Autom Elec Power Syst, 2005; 29: 39–44
21. Yuan T J, Chao Q, Li Y Y. Short-term wind power output forecasting model for economic dispatch of power system incorporating large-scale wind farm. P CSEE, 2010; 30: 23–27
22. Zhang P, Stephen T L. Probabilistic load flow computation using the method of combined cumulants and gram-charlier expansion. IEEE T Power Syst, 2004; 19: 676–68210.1109/TPWRS.2003.818743 ↗
23. Ruiz-Rodriguez F J, Hernández J C, Jurado F. Probabilistic load flow for photovoltaic distributed generation using the cornish-fisher expansion. Elec Power Syst Res, 2012; 89: 129–13810.1016/j.epsr.2012.03.009 ↗
24. Wu F F, Tsai Y K. Probabalistic dynamic security assessment of power systems: part I-basic model. IEEE T Circuits Syst, 1983; 30: 148–15910.1109/TCS.1983.1085344 ↗
25. Liu Y L, Yu Y X. Probabilistic steady-state and dynamic security assessment of power transmission system. Sci China Tech Sci, 2013; 56: 1198–120710.1007/s11431-013-5173-x ↗