首页|Knowledge-Based Efficient N-1 Analysis Calculation Method for Urban Distribution Networks with CIM File Data

Knowledge-Based Efficient N-1 Analysis Calculation Method for Urban Distribution Networks with CIM File Data

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The N-l criterion is a critical factor for ensuring the reliable and resilient operation of electric power distribution networks. However, the increasing complexity of distribution networks and the associated growth in data size have created a significant challenge for distribution network planners. To address this issue, we propose a fast N-l verification procedure for urban distribution networks that combines CIM file data analysis with MILP-based mathematical modeling. Our proposed method leverages the principles of CIM file analysis for distribution network N-1 analysis. We develop a mathematical model of distribution networks based on CIM data and transfer it into MILP. We also take into account the characteristics of medium voltage distribution networks after a line failure and select the feeder section at the exit of each substation with a high load rate to improve the efficiency of N-1 analysis. We validate our approach through a series of case studies and demonstrate its scalability and superiority over traditional N-l analysis and heuristic optimization algorithms. By enabling online N-1 analysis, our approach significantly improves the work efficiency of distribution network planners. In summary, our proposed method provides a valuable tool for distribution network planners to enhance the accuracy and efficiency of their N-1 analyses. By leveraging the advantages of CIM file data analysis and MILP-based mathematical modeling, our approach contributes to the development of more resilient and reliable electric power distribution networks.

MILPCIMfast analytical methodN-ldistribution networksknowledge-based method

Lingyu Liang、Xiangyu Zhao、Wenqi Huang、Liming Sun、Ziyao Wang、Yaosen Zhan

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Digital Grid Research Institute of China Southern Power Grid, China Southern Power Grid Co., Ltd., Guangzhou, 510640, China

Software Development Department, Guangzhou Shuimu Qinghua Technology Co., Ltd., Guangzhou, 510640, China||College of Electric Power, South China University of Technology, Guangzhou, 510640, China

College of Electric Power, South China University of Technology, Guangzhou, 510640, China

Software Development Department, Guangzhou Shuimu Qinghua Technology Co., Ltd., Guangzhou, 510640, China

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2023

10.32604/ee.2023.042042

Energy engineering

Energy engineering

ISSN：0199-8595
年,卷(期)：2023.120(12)