Intelligent Evaluation Of Cable Loss Considering Power Quality Problems

Power quality problems such as harmonics,three-phase imbalance,and voltage deviation in the distribution network are becoming more and more serious.At present,the research on cable line loss that takes into account the above power quality problems is not thorough enough,and there is no systematic development of cables under the combined effects of complex power quality problems.The quantitative evaluation of line loss lacks corresponding theoretical research on cable field test data under the interference of power quality.Starting from the composition of cable loss,this article quantitatively analyzes their respective effects on cable loss for power quality problems such as harmonics,three-phase unbalance,and voltage deviation,and establishes a physical formula calculation model for cable additional loss under their individual actions.For the composite power quality problem,an assessment model of the additional loss of the cable line under the combined effect of the composite power quality problem based on the combination of subjective and objective weights of the analytic hierarchy process and the coefficient of variation method is proposed.In order to test the physical formula calculation model of cable power quality loss under the action of various power quality problems,this paper designs the power quality disturbance test of the cable on the large-capacity power quality comprehensive disturbance platform,aiming at the different loads connected to the cable line in the actual power grid.Type and size,completed the cable field test under the interference of power quality problems such as harmonics,three-phase unbalance,voltage deviation,etc.,collected and summarized the cable power quality interference test data set under various load conditions.Through the processing and analysis of the cable test data,the accuracy of the cable power quality loss physical formula model is first verified,and then the cable power quality additional loss increase rate index is used to detect the cable under the action of harmonics,three-phase unbalance,and voltage deviation.Quantitative analysis of line power loss.Due to the complex structure of the cable and the special laying method,it is difficult to accurately obtain electrical parameters such as resistance and capacitance,and different power quality problems will have related interaction effects,resulting in the use of traditional physical formula models to evaluate the cable line loss that takes into account power quality problems.Large deviations make the calculation process complicated.Considering that the operating electrical parameters such as voltage,current,and power quality indicators in cable operation can be accurately measured and stored,this article will take the key operating electrical parameters that affect the cable line loss as the input of the intelligent evaluation model,and establish a calculation based on artificial intelligence algorithms.The intelligent evaluation model of cable line loss for power quality problems,so as to more accurately and quickly evaluate the cable line loss when the combined power quality problems are combined.When considering power quality issues,there are many operating electrical parameters that affect cable loss,and there are complex interactions between different parameters.In this paper,a convolutional neural network(CNN)with powerful feature processing and extraction capabilities is selected for intelligent evaluation and modeling.In this paper,a large number of experimental data obtained from the cable power quality disturbance test are used as training samples,and the operating electrical parameters of the cable line in each data sample,such as the voltage,current,and various power quality index values,are used as the input of the convolutional neural network.The loss evaluation value is used as the output target of the network,and an intelligent evaluation model of cable line loss based on deep learning algorithm that takes into account power quality problems is established.Through simulation analysis in two data sets of 120 k W resistive load and 80 A current source load,the final evaluation results show that the comparison does not take into account the power quality problem of the intelligent evaluation model,the traditional machine learning intelligent evaluation model and the weighting method formula evaluation model,application The intelligent evaluation model of cable line loss established by convolutional neural network that takes into account power quality problems can more accurately and stably evaluate the cable line loss under the action of compound power quality problems.