Development Of Online Monitoring System For Distribution Network Ring Main Unit

Nowadays,with the expansion of the use of electric energy,the use of Ring Main Unit in our country has increased sharply,and ensuring the safe and stable operation of Ring Main Unit is a necessary condition for ensuring the safe operation of the distribution network system.According to market research,our country’s current Ring Main Unit of 10 k V and below are widely distributed and large in number,with imperfect monitoring systems and single functions.Maintenance requires relatively large labor and economic costs.In order to solve the above problems,we design a set of online monitoring system suitable for Ring Main Unit.The high-frequency sensor and transient ground voltage sensor and its conditioning circuit suitable for partial discharge monitoring of the Ring Main Unit are designed.Non-intrusive high-frequency sensors and transient ground voltage sensors are used to effectively collect the Partial discharge information;we designed a cable terminal insulation surface temperature monitoring program suitable for Ring Main Unit,using a wristband temperature measurement design,based on 433 MHz wireless data transmission,making the temperature measurement method more convenient and reliable;We have designed a current fault monitoring and voltage live monitoring program suitable for Ring Main Unit.The optical fiber transmission and optocoupler isolation methods effectively isolate the high-voltage system from the low-voltage system;we use the GPRS wireless transmission program to transmit the data of the Ring Main Unit.Information is effectively transmitted in real time.For the pattern recognition of partial discharge signals in Ring Main Unit,this paper builds three common partial discharge models in cable terminal heads,and collects partial discharge information through the above systems.Hilbert-VMD using frequency analysis of the partial discharge signal,to obtain an effective modal partial discharge signal,and obtains the respective multi-scale entropy permutation modal component corresponding to the calculated feature matrix of the partial discharge signal using the PCA algorithm The optimal feature vector set was screened out,and the feature set was used for pattern recognition using BP neural network and support vector machine respectively.The recognition effect of evaluation indicators such as precision,accuracy,recall and F1 are used to evaluate the results.The results show that the accuracy of the support vector machine is higher than that of the BP neural network for the pin plate discharge and the surface discharge,and the recognition F1 score of the three discharges is higher than the BP neural network algorithm,indicating that the support vector machine is more suitable for solving small samples and practical engineering problems.Based on Code Composer Studio and Lab VIEW,we designs the upper and lower computer programs of the system,completes the system debugging,and installs and tests it in the 10 k V Ring Main Unit.Based on the upper computer software,the remote online monitoring of the Ring Main Unit is realized,and the operation and maintenance of the Ring Main Unit is intelligentized.By simulating the occurrence of failures in the laboratory environment,the effectiveness of the monitoring of each sensor and the whole machine is verified.Then,through on-site testing,the developed system can effectively collect the operating status information of the Ring Main Unit,and perform state diagnosis on the Ring Main Unit according to the information data of the Ring Main Unit,which verifies the effectiveness of the monitoring system.