DOI:10.35833/MPCE.2019.000106 |
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Data-driven Probabilistic Static Security Assessment for Power System Operation Using High-order Moments |
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Page view: 117
Net amount: 454 |
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Author:
Guanzhong Wang1,Zhiyi Li1,Feng Zhang2,Ping Ju1,Hao Wu1,Changsen Feng3
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Author Affiliation:
1.Department of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;2.State Grid Zhejiang Electric Power Research Institute, Hangzhou 310014, China;3.College of Information Engineering, Zhejiang University of Technology, Hangzhou 310008, China
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Foundation: |
This work was supported by the National Natural Science Foundation of China (No. 52007163) and in part by China Postdoctoral Science Foundation (No. 2020M671718). |
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Abstract: |
In this letter, a new formulation of Lebesgue integration is used to evaluate the probabilistic static security of power system operation with uncertain renewable energy generation. The risk of power flow solutions violating any pre-defined operation security limits is obtained by integrating a semi-algebraic set composed of polynomials. With the high-order moments of historical data of renewable energy generation, the integration is reformulated as a generalized moment problem which is then relaxed to a semi-definite program (SDP). Finally, the effectiveness of the proposed method is verified by numerical examples. |
Keywords: |
Data-driven analysis ; probabilistic static security assessment ; power system operation ; distributionally robust approach |
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Received:October 16, 2019
Online Time:2021/09/28 |
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