A risk assessment method for distribution stations using multi-source data fusion

The distribution station is an important component of the distribution network, and its safe and reliable operation is crucial for ensuring power supply. Considering the problems of single evaluation data and high manpower consumption in traditional methods for evaluating the operation status of distribution stations, this paper proposes a risk assessment method for the safe and reliable operation of distribution stations based on multi-source information fusion and fuzzy analytic hierarchy process. Multi source data fusion is performed on environmental, device status, and gas data obtained from different intelligent perception devices. The Analytic Hierarchy Process is used to determine the weights of twelve evaluation factors, and the membership degree is calculated based on the trapezoidal triangle membership function. A fuzzy algorithm is used to establish a comprehensive evaluation model for the status of the distribution station. Based on Python software, the engineering instance data is calculated to obtain the risk assessment results for the safe and reliable operation of the distribution station, and the effectiveness of the proposed method is verified. The proposed method can improve the efficiency of evaluating the operation status of distribution stations, and the research results can provide decision-making basis for operation and maintenance personnel.