基于多源数据融合算法的配电网外破风险识别与定位方法
A Method for Identifying and Locating the Risk of External Damage in Distribution Networks Based on Multi-source Data Fusion Algorithm
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摘要: 配电网作为电力供应的重要组成部分,其运行安全对于保障电力供应的稳定性至关重要。通过对外破风险的筛查,可及时处理并发现潜在的风险性问题,从而保障电网的运行稳定性。为实现上述目的,提出基于多源数据融合算法的配电网外破风险识别与定位方法。利用多源数据融合算法模型,量化外破风险,进而在定义外力破坏等级的同时,完善定位流程,从而完成基于多源数据融合算法的配电网外破风险识别与定位方法的设计。实验结果表明,所提方法能在外破风险的情况下准确识别出配电网的故障电压,且对于风险线路的定位偏差也相对较小,有助于保障配电网的运行稳定性。Abstract: As an important component of power supply, the safe operation of the distribution network is crucial to ensuring the stability of power supply. Through the screening of external damage risks, potential risk issues can be dealt with and identified in a timely manner, thereby ensuring the operational stability of the power grid. To achieve the above goals, this study proposes a method for identifying and locating the external damage risk of distribution networks based on multi-source data fusion algorithms. By using the multi-source data fusion algorithm model, the risk of external damage is quantified. Then, while defining the level of external force damage, the positioning process is improved to complete the design of the identification and positioning method of the risk of external damage in the distribution network based on the multi-source data fusion algorithm. The experimental results show that the application of the above method can accurately identify the fault voltage of the distribution network in the case of external damage risk, and the positioning deviation of the risky lines is relatively small, which is helpful to ensure the operational stability of the distribution network.
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