基于区间权重和改进云模型的变压器状态评估

摘要

For the randomness and fuzziness problem of condition level boundary information in the power transformers, a new assessment method based on normal cloud theory is proposed. Given a full consideration to the limitation of data use for condition assessment, the limited data collected of the power transformers would be handled to establish the data normal cloud. For the issue of power transformers level boundary ambiguity, it proposes to properly expand each level and establish the level normal cloud. Depending on the different probabilities of cloud droplets in clouds, the cloud association degree is then calculated between the data normal cloud and the level normal cloud. Secondly, the operation data of power transformer is represented the range form. As for volatility for each interval data of performance indicators, it calculates the variance and average interval data and gives different weights index. The result of condition level of the power transformers is finally obtained. Through the analysis of a power transformer station operating data, the simulation example demonstrates that proposed method is efficient and practical to apply to assess the power transformers.%针对变压器状态等级边界信息随机性和模糊性的问题，提出建立基于正态云理论的变压器状态评估模型。考虑变压器状态评估数据的有限性，提出对变压器少数运行数据进行正态云处理。对于变压器等级边界模糊性问题，提出对变压器各等级进行适度扩展，建立变压器指标等级正态云。根据不同云滴在数据正态云出现的不同概率，计算变压器数据正态云云滴与各评估指标等级正态云之间的关联度，得到评判矩阵。其次，对变压器运行数据进行区间表示。针对各指标区间数据的波动性，计算区间数据的方差和平均差，进而赋予指标不同的权重，在此基础上进行变压器状态评估。通过分析某台变压器运行数据，验证了该方法应用于变压器状态评估中的有效性。