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Research on multi-attribute decision-making in condition evaluation for power transformer using fuzzy AHP and modified weighted averaging combination

机译:基于模糊层次分析与改进加权平均组合的电力变压器状态评估多属性决策研究

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摘要

Power transformers are of vital importance for the stable operation of power system. Hence, to grasp transformers' health condition is of imminent importance. However, the evaluation of transformers' health condition is bound with fuzzy, uncertainty, and even conflict information. To address these problems, a novel evaluation model for transformer, by integrating the merits of fuzzy set theory, fuzzy analytical hierarchical process (AHP), and modified weighted averaging combination, is proposed in this study. The evaluation model contains four factors: dissolved gas analysis, electrical testing, oil testing, and miscellaneous factors, as well as 20 indices. The evaluation process consists of three steps. First, the fuzzy set theory is used to obtain assessment grades for each quantified indices. Second, the fuzzy AHP using fuzzy preference programming, which extends classical AHP and can better tackle the uncertainty existed in the comparison matrix given by experts, is introduced to calculate the weights of indices. Finally, the assessment is processed through the modified weighted averaging combination, which is able to handle the conflicts among evidences. The proposed method is verified by evaluating a realistic transformer, and the results of field examples indicate that the method can evaluate the transformer health condition effectively.
机译:电力变压器对于电力系统的稳定运行至关重要。因此,掌握变压器的健康状况至关重要。但是,对变压器健康状况的评估会受到模糊,不确定性甚至冲突信息的限制。为解决这些问题,本研究提出了一种结合模糊集理论,模糊层次分析法和改进的加权平均组合的优点的变压器评估模型。评估模型包含四个因素:溶解气体分析,电气测试,机油测试和其他因素,以及20个指标。评估过程包括三个步骤。首先,模糊集理论用于获得每个量化指标的评估等级。其次,介绍了采用模糊偏好规划的模糊层次分析法,对经典层次分析法进行了扩展,可以更好地解决专家给出的比较矩阵中存在的不确定性,从而计算出指标的权重。最后,通过修改后的加权平均组合来处理评估,该组合能够处理证据之间的冲突。通过对实际变压器的评估,验证了该方法的有效性,现场实例结果表明,该方法可以有效评估变压器的健康状况。

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