Based On Multi-source Information Fusion Analysis Of Station Power Efficiency And Equipment Failure

Substation is an important part of the power grid.Its energy consumption and reliability of operation are very important for the safe and stable operation of the power grid.The electrical equipment of the substation station is the basis for the stable operation of the substation.In addition,as a part of the network loss,the energy consumption of the electrical equipment in the substation has a great impact on the energy saving and consumption reduction of the power grid.Therefore,it is of great significance to improve the reliability of substation electrical equipment and reduce the level of power consumption.The thesis first designs the power consumption collection system of the substation station,and determines the power consumption collection target and implementation plan of the substation station.Taking "STATCOM water cooling system energy consumption,500kV main transformer high voltage side power consumption,power equipment energy consumption,indoor environment power consumption,35kV main transformer low voltage side power consumption" as the main typical loads,a station power consumption data collection system was constructed.The collection parameters and communication methods of each typical load of station power are clarified.Secondly,the idea of block and layering is adopted to construct a three-layer substation energy efficiency evaluation system of conclusion layer,block layer and index layer.The conclusion layer is the comprehensive evaluation score of the power efficiency of the substation station;the block layer includes the energy efficiency indicators of the station power equipment,the power quality technical indicators,the measurement and monitoring indicators of the power supply system,and the building and environmental energy efficiency indicators;the indicator layer has determined 16 Specific index parameters for power efficiency evaluation of each station.Combining the three weighting methods of "subjective weighting method,entropy weighting method,and comprehensive integration weighting method",a weight analysis method based on "multi-source information fusion" is proposed.A comprehensive evaluation and analysis of energy efficiency were carried out on the power consumption of three substation stations.The evaluation results found that of the three substations,T1 has lower energy efficiency overall,substation T3 has higher energy efficiency overall,and substation T2 has the highest energy efficiency overall.Finally,a multi-source information fusion BP neural network-D-S station power failure analysis method is proposed to diagnose whether there are faults or abnormalities in the station power equipment.This method first uses a BP neural network based on multi-source information fusion to predict the station power consumption of the equipment under normal operating conditions,and then compares it with the measured power consumption of the equipment to determine whether the equipment power consumption is abnormal,and then diagnose whether the equipment is abnormal.And by constructing the fault identification collection of the electrical equipment of the station,and then integrating the improved D-S evidence theory,it is judged whether the equipment is faulty and the fault type.Field tests show that this method can correctly determine equipment faults and fault types,and can improve the reliability of safe and stable operation of substations.