Design And Implementation Of Dynamic Capacity Increase Of Transmission Line Based On Micro Power Sensor

With the rapid development of China’s economic and social,the increasing demand for electricity,transmission line damage because of the long time continuous work and burned the fault cause serious damage to the normal operation of the power industry,the traditional way of human patrol work efficiency is low,but most of the existing intelligent monitoring system based on Zigbee,bluetooth and WIFI wireless transmission way,It often has the defects of short communication distance and high power consumption,which can not meet the actual demand.At the same time,the damage of transmission lines makes the analysis and calculation of real-time load of transmission lines not reasonable and accurate,resulting in power shortage in some areas during peak periods.Although new energy power generation can alleviate the problem of power shortage,new energy power stations are often far away from the existing transmission lines,resulting in high transmission loss.The reconstruction of transmission lines is restricted by many factors and cannot be realized in the short term.To solve the above problems,this paper designed and implemented a line status monitoring system based on Long Range transmission,which can monitor the running status of transmission lines online in real time.Based on the theoretical analysis of the calculation model of the line ampacity under each standard,the neural network is used to train the source data and make the prediction,and the dynamic capacity increase model of the transmission line based on the meteorological parameter prediction is established,and the field test is carried out,and the ampacity increase is realized.The specific work content is as follows:In this paper,temperature and micrometeorological monitoring systems are designed and optimized using Long Range as transmission mode.Select low-power microcontroller and other devices to design the hardware circuit,and draw PCB circuit board,based on LoRaWAN protocol design system software part.System optimization,to join a group of MOS tube,data acquisition circuit and data circuit,successively in the software part design reasonable work and sleep time,sends the data cycle is set to 10 minutes,every time before sending time to 1 minute from sleep mode into the working mode,the hardware and software,under the function of each node dormancy of current is less than 10 uA,The effective data transmission distance can reach 1km.Secondly,the paper analyzes three kinds of current current-carrying calculation models at home and abroad,compares the advantages and disadvantages of each current-carrying calculation model,and simulates the parameters that affect the current-carrying size based on CTM model.Draw the relationship diagram of wind speed,heat dissipation coefficient(thermal radiation coefficient),wind direction Angle,light intensity,wire temperature,ambient temperature and other factors with the current,and find out the parameters with greater influence.Then,convolutional neural network(CNN),Long Short-term Memory neural network(LSTM)and Gate Recurrent Unit(GRU)are used to train and predict wind speed,ambient temperature and light intensity data respectively.The predicted data are inserted into the current-carrying capacity prediction model for calculation.According to the predicted results,The gated cyclic unit with the highest accuracy is selected as the network model of ampacity calculation.In view of the problem that the large amount of source data causes the neural network to run for a long time and cannot calculate the load in time,this paper adds the Extreme Learning Machine(ELM)on the basis of GRU network and combines it into the GRU-ELM model to train and predict the data.Experiments show that the combined model can shorten the network running time by 90%,and the prediction accuracy can be increased by about 1%.The source and forecast data are substituted into the dynamic capacitive model based on wire temperature measurement for calculation,and the real-time ampacities of the line are compared.The results show that the micro-power sensor based on LoRa wireless transmission can realize the real-time online monitoring of transmission lines and ensure the smooth and safe operation of the lines.The dynamic capacity increasing technology based on GRU-ELM can quickly calculate the line load according to the meteorological parameters measured by the designed sensor,effectively increase the line load from the original about 400A to the maximum about 1200A,and alleviate and solve the problem of power shortage in the peak period.