Analysis of voltage stability uncertainty using stochastic response surface method related to wind farm correlation

Wind speed follows the Weibull probability distribution and wind power can have a significant influence on power system voltage stability. In order to research the influence of wind plant correlation on power system voltage stability, in this paper, the stochastic response surface method (SRSM) is applied to voltage stability analysis to establish the polynomial relationship between the random input and the output response. The Kendall rank correlation coefficient is selected to measure the correlation between wind farms, and the joint probability distribution of wind farms is calculated by Copula function. A dynamic system that includes system node voltages is established. The composite matrix spectral radius of the dynamic system is used as the output of the SRSM, whereas the wind speed is used as the input based on wind farm correlation. The proposed method is compared with the traditional Monte Carlo (MC) method, and the effectiveness and accuracy of the proposed approach is verified using the IEEE 24-bus system and the EPRI 36-bus system. The simulation results also indicate that the consideration of wind farm correlation can more accurately reflect the system stability.

[1]  Zhaoxing Ma Non-member,et al.  Study on power system small-disturbance uncertainty stability considering wind power , 2014 .

[2]  F. Silvestro,et al.  A Gas Turbine Model for Studies on Distributed Generation Penetration Into Distribution Networks , 2011, IEEE Transactions on Power Systems.

[3]  Huang Xiaojing,et al.  Quantitative Uncertainty Analysis for Power System Dynamic Simulation Based on Stochastic Response Surface Method , 2008 .

[4]  Roy Billinton,et al.  Probabilistic evaluation of transient stability of a power system incorporating wind farms , 2010 .

[5]  R. Billinton,et al.  Probabilistic Power Flow Analysis Based on the Stochastic Response Surface Method , 2016, IEEE Transactions on Power Systems.

[6]  Evangelos Farantatos,et al.  A measurement-based approach for power system instability early warning , 2016 .

[7]  Lin Feng,et al.  Cost reduction of a hybrid energy storage system considering correlation between wind and PV power , 2016 .

[8]  Cai De-f,et al.  Probabilistic load flow considering correlation between input random variables based on Copula theory , 2013 .

[9]  Wei Gu,et al.  Study on power system small‐disturbance uncertainty stability considering wind power , 2014 .

[10]  J. Milanović,et al.  Probabilistic Small-Disturbance Stability Assessment of Uncertain Power Systems Using Efficient Estimation Methods , 2014, IEEE Transactions on Power Systems.

[11]  H. F. Wang,et al.  Probabilistic Analysis of Small-Signal Stability of Large-Scale Power Systems as Affected by Penetration of Wind Generation , 2012, IEEE Transactions on Power Systems.

[12]  Xiong Haoqing,et al.  Dynamic Consistency Test for Power System Time-domain Simulation , 2010 .

[13]  Mahmud Fotuhi-Firuzabad,et al.  Impact of correlation on reserve requirements of high wind-penetrated power systems , 2015 .

[14]  Roy Billinton,et al.  Adequacy assessment of generating systems containing wind power considering wind speed correlation , 2009 .

[15]  G. T. Heydt,et al.  Probabilistic Methods For Power System Dynamic Stability Studies , 1978, IEEE Transactions on Power Apparatus and Systems.

[16]  J. Driesen,et al.  A Probabilistic Formulation of Load Margins in Power Systems With Stochastic Generation , 2009, IEEE Transactions on Power Systems.

[17]  Zhi Li,et al.  Short-term wind power prediction based on extreme learning machine with error correction , 2016, Protection and Control of Modern Power Systems.

[18]  Wen Fushuan,et al.  A Multi-round Negotiation Model for Bilateral Contracting Considering Spot Price Risks in Electricity Market Environment , 2010 .

[19]  Gyu-Hong Kang,et al.  Prediction of torque characteristic on barrier-type SRM using stochastic response surface methodology combined with moving least square , 2004 .

[20]  Roy Billinton,et al.  Bibliography on power system probabilistic analysis (1962-88) , 1990 .

[21]  Qian Ai,et al.  Optimal scheduling strategy for virtual power plants based on credibility theory , 2016 .

[22]  Chen Wang,et al.  Modelling analysis in power system small signal stability considering uncertainty of wind generation , 2010, IEEE PES General Meeting.

[23]  H Miao,et al.  One novel control strategy of the AC / DC bi-directional power converter in micro-grid , 2013 .

[24]  Haibo,et al.  A Stochastic Response Surface Method for Probabilistic Evaluation of the Voltage Stability Considering Wind Power , 2012 .

[25]  Long Zhang,et al.  Impact of Wind Speed Correlation on Transient Stability of Power System , 2013 .

[26]  Li Jun,et al.  Reliability models of wind farms considering wind speed correlation and WTG outage , 2015 .