Probabilistic-Interval Power Flow and Sensitivity Analysis Using Double Layer Surrogate Method
Wang Chenxu1, Tang Fei1, Liu Dichen1, Gao Xin1, Zhou Yixi2
1. School of Electrical Engineering and Automation Wuhan University Wuhan 430072 China; 2. Hangzhou Power Supply Company State Grid Zhejiang Electric Power Co. Ltd Hangzhou 310000 China
Abstract：With the increasing complexity of uncertainties in power systems, the co-existence of random and interval variables makes it challenging to accurately obtain systems’ operating states by using probabilistic or interval power flow calculations. To cope with this issue, this paper proposes a double layer surrogate method for probabilistic-interval power flow analysis. The proposed method can obtain the upper and lower surrogate models based on a few times deterministic power flow calculations. Then, the surrogate models are used to solve a large number of deterministic power flow calculations required in the conventional probabilistic-interval power flow method, and the probability boxes of output variables can be obtained with high efficiency. In addition, a sensitivity index is proposed to describe the characteristics of output variables, and the sensitivity analysis is performed using the proposed method to identify the importance of input interval variables that affect output variables. The accuracy and efficiency of the proposed method are validated on the IEEE 118-bus test system by comparing the existing methods. The sensitivity analysis can identify the key interval variables for the output variables and reveal the relationship between the operating states and the input interval variables.
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2022, Vol. 37 
