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Wind Power Integrated Power System Small Signal Stability Analysis Based On Frequency Response Method

Posted on:2020-01-09Degree:DoctorType:Dissertation
Country:ChinaCandidate:P ShiFull Text:PDF
GTID:1362330572973889Subject:Power system and its automation
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The development of interconnected power systems is making the small-signal stability problem of the original weak grid increasingly serious,such as low-frequency oscillation and ultra-low-frequency oscillation,that threaten the safe and stable operation of power systems.Since the 21st century,the small-signal stability of power systems has been challenged with the large-scale new energy power penetration,especially for wind power generation.Taking the wind power for example,the more concerned influencing factors of the small-signal stability of power systems caused by wind power can be summarized as the following two aspects:uncertainty of wind power output,and the difference of the dynamic characteristics between wind power generator and synchronous generator.The above two factors can correspondingly come down to the robust small-signal stability analysis of the system with parametric uncertainty,and the small-signal stability analysis of the system with determined parameters.So far,the analysis methods for power systems with parametric uncertainty are relatively limited,then it can not fully meet the needs of power system stability analysis.As for the stability analysis of power systems with determined parameters,such as the effect of dynamic characteristics of wind power generators on the power system low-frequency oscillation,it is difficult to obtain general conclusions based on the existing methods.Therefore,it may be helpful to develop new methods.This dissertation mainly proposes a combination of frequency response analysis methods including "new value set approach" and "vector margin method".And from the two aspects of parametric uncertainty and parameter determination,the frequency response analysis methods are applied to the small-signal stability analysis of wind power integrated power systems.The main contributions of this dissertation are as follows.1.A method,called new value set approach is proposed for robust small-signal stability analysis of power systems with wind power uncertainties.And the results of the new value set approach is intuitive and easy to analyze,and it is also applicable for parameter analysis.The new method mainly improves some shortcomings of the previous value set approach,such as large number problem and the conservativeness caused by the results of mapping theorem.Therefore,the new method further improves the value set approach.Moreover,by applying damping ratio constraints to robust stability evaluation,the new method can be applied to the robust D stability analysis,and make it more suitable for the analysis of power system oscillation mode.2.A rational fractional representation method is proposed for wind power integrated power system robust small-signal stability analysis.Comparing to the traditional polynomial model,the advantage of the rational fractional representation model is that,it takes use of the fractional characteristics of the parameters in the power system state matrix(including controller parameters and power flow parameters),so that the rational fractional representation is more close to the real parametric model of power systems.And the comparison between the results of the above two fitting models also indicates that the low-order rational fractional fitting is more accurate than the low-order polynomial fitting.Especially for the controller parameter uncertainties,the fitting error of the rational fractional representation becomes zero.Therefore,based on the proposed rational fractional fitting technique,the applicable occasions of the value set approach for power system robust stability analysis can become wider.3.For analysis of the low-frequency oscillation of the power systems with wind power penetration,a method based on the vector margin theory is proposed mainly for analyzing the effect of wind generation characteristics.Comparing to the traditional modal analysis method and damping torque method,the new method proposed here does not need the calculation of the eigenvectors and the residue.And the approximate "rank equals to one" property of the generalized frequency response of multi-machine power system transfer function matrix at the low-frequency oscillation frequency,is proved.According to this property,the determinant of the return difference matrix can be simplified to a sum of vector components,and each vector component respectively represents the effect of the corresponding wind generation.Based on the simplified analysis criterion of the vector margin method,the vector plot of the determinant of the return difference matrix directly shows the effect of the wind generation on the power system low-frequency oscillation.The results also indicate that,the phase of the generalized frequency response of multi-machine power system transfer function matrix,mainly determines the direction of change of oscillation mode damping,before and after the wind power integration.4.The ultra-low-frequency oscillation of power systems with wind power penetration is modeled and analyzed in this dissertation.The uniform-frequency model is widely used for ultra-low-frequency oscillation analysis.However,the strict mathematical proof of this simplified model has not been widely reported.Therefore,based on our previous proof work for synchronous generator power systems,and the obtained Phillips-Heffron model considering wind generation dynamics,a proof is given that the wind power integrated power systems also have the approximate uniform-frequency characteristic during the ultra-low-frequency range.And based on the proved uniform-frequency characteristic,the uniform-frequency model of the Yunnan power grid with integrated wind powers,is built.Then the effect of the wind power on the ultra-low-frequency oscillation is analyzed by using the vector margin method based on the built uniform-frequency model.
Keywords/Search Tags:small-signal stability, parametric uncertainty, robust small-signal stability, vector margin, low-frequency/ultra-low-frequency oscillation, value set approach, frequency response
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