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高危用户的用电安全不仅关系到自身的经济利益,也关系到社会稳定的大局和电网的安全稳定运行。对此,对用户侧安全隐患进行了梳理和分类,建立包含环境、设备、人为和管理隐患的安全隐患评价体系。评价体系具有模糊性、随机性、突发性、非线性和动态性等特点,而且四个子系统的特点也各不相同。环境隐患的影响因素多为定量指标,采用熵权法方法,充分利用隐患状态的数据来确定评价指标的权重以避免主观确定权重的不足,建立基于熵权法的环境隐患评价模型;针对人为隐患的评价指标多为定性指标,且指标值的确定有很大的随意性,所以首先利用集值统计原理确定评价指标值,建立基于神经网络的人为隐患评价模型;考虑到设备和管理隐患的实际情况,建立了设备和管理隐患的模糊综合评价模型。通过建立综合评价体系,对用户侧的安全隐患进行最终评估。
The electricity safety of high-risk users is not only related to their own economic interests, but also the overall social stability and the safe and stable operation of the power grid. In this regard, the user side of the security risks were sorted and classified, the establishment of environmental, equipment, man-made and management of potential safety hazard evaluation system. The evaluation system has such characteristics as ambiguity, randomness, suddenness, nonlinearity and dynamics, and the four subsystems also have different characteristics. Most of the influencing factors of environmental hidden dangers are quantitative indicators. Entropy method is used to make full use of hidden state data to determine the weight of evaluation index so as to avoid the subjective determination of the weight deficiencies. The evaluation model of environmental hidden dangers based on entropy method is established. Of the evaluation indicators are mostly qualitative indicators, and the index value is determined a lot of randomness, so the first set of statistical principles to determine the value of the evaluation index, the establishment of artificial neural network-based evaluation of hidden risks; taking into account the actual equipment and management of hidden dangers Situation, established a fuzzy comprehensive evaluation model of equipment and management risks. Through the establishment of a comprehensive evaluation system, the user side of the security risks for the final assessment.