Stochastic Estimation of Voltage Sag Considering Output Correlation of Renewable Energy Sources

doi:10.3969/j.issn.1000-7229.2018.10.009

Abstract

Abstract: For the electric power system with renewable energy sources such as wind power and photovoltaic power, a stochastic estimation method for voltage sag considering output correlation of renewable energy sources is proposed. Firstly, the stochastic models of short circuit fault information and the output stochastic models of renewable energy sources are established. Secondly, the fault information samples are obtained using the Latin hypercube sampling （LHS）. The correlation coefficient of the renewable energy sources output of the same type is determined by the Pearson correlation analysis method, and then the output samples of renewable energy sources are obtained through the Nataf transformation and LHS. Thirdly, through the fault simulation, a series of voltage sag events can be got, the sag indices of each node can be calculated, and sags at each node can be estimated. The IEEE 30-bus system is taken as an example, the influences of the renewable energy sources output under the change of correlation coefficient and different types of renewable energy sources on the voltage sag are studied.

Key words: voltage sag, renewable energy sources, output correlation, Latin hypercube sampling（LHS）, Pearson correlation analysis method, Nataf transformation

CLC Number:

TM 712

LU inbing，WEI Pengfei，LIU Yali，WANG Xudong，LI Shupeng，XU Yonghai. Stochastic Estimation of Voltage Sag Considering Output Correlation of Renewable Energy Sources[J]. Electric Power Construction, 2018, 39(10): 71-81.

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