Fast Confidence Evaluation of Operation Mode of Power Grid Based on Gaussian Process Regression

被引：0
|
作者：
Liu J. [1 ]
Liu Y. [1 ]
Qiu G. [1 ]
Wang J. [2 ]
Ding M. [3 ]
Liu J. [1 ]
机构：
[1] College of Electrical Engineering, Sichuan University, Chengdu
[2] Northwest Branch of Sated Grid Corporation of China, Xi'an
[3] State Grid Ningxia Electric Power Co., Ltd., Yinchuan
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2022年 / 46卷 / 11期
关键词：
Analytic hierarchy process; Artificial intelligence; Gaussian process regression; Multi-dimensional indices; Operation mode; Power grid;
D O I：
10.7500/AEPS20210630012
中图分类号：
学科分类号：
摘要：
The integration of high penetration of renewable energy makes the power grid operation more uncertain, the operation mode adjustment more frequent, and the number of evaluation indices much more. However, the multi-dimensional complex and related indices change with the operation mode, and it is difficult to accurately grasp the advantages and disadvantages of the operation mode only depending on manual work. Furthermore, the repeated safety checking can easily lead to the slow calculation of the evaluation indices. Therefore, to improve the efficiency of operation mode adjustment, fast and accurate operation mode evaluation is essential. Firstly, the indices based on the voltage-reactive DC power flow and transient stability assessment are extracted from three dimensions of security, stability, and economy. Secondly, the entropy weight-fuzzy analytic hierarchy process is adopted to fuse and calibrate the multi-dimensional indices to enhance the observability of operation mode evaluation. Finally, the Gaussian process regression with certain interpretability and confidence resolution is introduced to construct the evaluation model to realize the fast evaluation of operation modes. The modified IEEE 39-bus system and a provincial power grid in Northwest China are used for verification. The results show that the proposed method can evaluate the operation mode quickly, accurately, and flexibly, and can provide rapid adjustment feedback results during the operation mode compilation process, helping improve the efficiency of the operation mode preparation. © 2022 Automation of Electric Power Systems Press.
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页码：181 / 190
页数：9
相关论文
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