Online Measurement Method of Intelligent Energy Meter Based on Heuristic Q-Learning Algorithm

In order to study the quality analysis method of key links in smart energy meters, the author proposes a data fusion based quality analysis and prediction method for smart energy meters. This method is based on the relevant data of key links in the electric energy meter, and selects the data of the electric energy meter in research and development design, material procurement, production and manufacturing, acceptance testing, installation and operation, dismantling and scrapping as the sample data for model construction. The XGBoost algorithm classification method is used to establish an intelligent electric energy meter quality analysis model. Taking the dismantled electricity meter data of a certain power company as an example, this paper conducts modeling analysis and prediction of various quality issues of smart electricity meters, and conducts on-site verification. Based on the verification results, the model is continuously optimized. The results indicate that: The model was optimized using cross validation and grid search methods, and the final model achieved an accuracy rate of 0.74 and a recall rate of 0.82 on the validation set. This method can meet the actual needs of power grid business and objectively reflect the quality situation of key links in smart energy meters.

In order to solve the problems of heavy workload, weak planning, and repetitive maintenance in the periodic rotation of smart energy meters, the author proposes a verification cycle optimization method based on the evaluation results of energy meter status. This method first obtains data on six indicators of smart energy meters: regional factors, reliability, full event, abnormal metering events, battery overload, and clock battery undervoltage; Subsequently, on the one hand, the coefficient of variation assignment method is used to obtain the status score of each electricity meter, and on the other hand, these six indicator data are used as input data, and the K means clustering algorithm is used to classify and obtain the corresponding categories. Finally, the two algorithms are combined to obtain a new method for evaluating the status of smart energy meters, and the final evaluation result is output. The experimental results indicate that: The number of electricity meters scored below 80 points obtained by this method accounts for 22.08% of the total number of electricity meters, while electricity meters scored above 80 points account for 77.93% of the total number of electricity meters. This indicates that this method is in line with the actual situation and objective laws. Constructing a state evaluation model for electric energy meters, using historical data and on-site calibration data as state variables, analyzing the annual operational quality of electric energy meters, and providing reference basis for adjusting the calibration cycle of electric energy meters.

In recent years, with the State Grid Corporation's vigorous construction of smart grids, smart meters have been rapidly promoted in the power system. After several years of online operation, the operating reliability of smart meters has also stabilized. However, in the process of widespread use of smart electric energy meters, the quality problems of clock chips, batteries and other components have also been exposed. This article takes the component failures encountered in the detection and operation of the smart electric energy meter as an example, analyzes the causes of the failures based on the four typical abnormal phenomena, and then conducts the opening detection for the above reasons and determines the nature of the failure based on the test conclusions. Finally, a corresponding fault management platform is established through the collection of electric energy meter fault data, which realizes all-round management and control of the fault handling process and selection of the qualifications of smart meter suppliers, thereby ensuring the quality of components and improving the operation of smart electric meters reliability.

In recent years, smart electric energy meters are demand at 70 million to 90 million with the strong smart grid construction every year in China. However, there are some issues in smart electric energy meters data collection such as the interference of environment, low collection efficiency and inability to work when the power is off. In order to solve these issues above, it uses the RFID communication technology to collect the numbers and electric energy information of smart electric energy meters on the basis of the existing smart electric energy meters, and the related data collection communication experiments were made. The experimental result shows that the electric information and other data batch collection of RFID smart electric energy meters are realized in power and power off. It improves the efficiency and the overall success rate is 99.2% within 2 meters. It provides a new method for smart electric energy meters data collection.

The analysis and record of data for traditional in-field calibration of electric energy meter relies on artificial work, which will easily lead to data error due to human factors and unable to realize standardization of calibration. The complete sets of mobile operation software for in-field calibration of electric energy meter is embedded the process of in-field standardized operation, which can standardize the in-field calibration of electric energy meter and realize automatic identification of wiring mode and calibration methods of electric energy meter. It establishes the multiple data intelligent diagnostic model based on information such as current cutoff、 lose of phase、 voltage-loss and severe three-phase unbalance. By analyzing and comparing with the user data of Power User Electric Energy Data Acquire System, the model can automatically identify and diagnose abnormal power consumption behavior like stealing electricity. It also establishes a model for distinguishing the abnormal operating state of electric energy meter, which can realize automatic distinction of abnormal operating state of electric energy meter. Introduction Electric energy meter is a metrology apparatus for commercial exchange between electric power enterprises and customers, and calibration of electric energy meter is the duty of electric power marketing management which is very important to electric safety and power management. For a long time, the calibration personnel took the calibration instrument to the scene of the electric meter calibration, recorded the calibration data in the notebook, analyzed and screened the calibration data artificially, and then went back to the office to put the calibration data into the computer. The in-field calibration and background jobs in the office was performed separately, which cannot realize standardization of calibration and high-efficient work and analyzing and screening the calibration data artificially can easily lead to the data error of calibration. The complete sets of mobile operation software for in-field calibration of electric energy meter is embedded the process of in-field standardized operation, which can standardize the in-field calibration of electric energy meter. It also uses a variety of encryption technology to access intranet system securely, realizing a seamless connection with the Marketing Information System. The software employs an intelligent recognition and matching technology of calibration methods and establishes database of calibration methods of electric power meter to realize automatic identification of wiring mode and calibration methods of electric energy meter. It establishes the multiple data intelligent diagnostic model based on information such as current cutoff、 lose of phase、 voltage-loss and severe three-phase unbalance. By analyzing and comparing with the user data of Power User Electric Energy Data Acquire System, the model can automatically identify and diagnose abnormal power consumption behavior like stealing electricity. It also establishes a model for distinguishing the abnormal operating state of electric energy meter, which can realize automatic distinction of abnormal operating state of electric energy meter. 3rd International Conference on Machinery, Materials and Information Technology Applications (ICMMITA 2015) © 2015. The authors Published by Atlantis Press 1184 Fig.1. system architecture diagram

Based on the technical specifications of smart meters, the electrical performance evaluation methods of single-phase smart meters are studied, and the accuracy, stability and safety of smart meters are analyzed and studied through specific data verification. Analysis the basic characteristics of the electrical performance of the smart energy meter, and evaluate the electrical performance based on the basic characteristics. Collect the specific working characteristic data of the intelligent electric energy meter, accurately measure the parameters of the intelligent electric energy meter, and analysis the electrical performance. Analysis the influence of the harmonic components of the power system on the measurement of the electric energy meter, study the power consumption of the smart electric energy meter, and the accuracy and stability of the operation.

The communication protocol structure of digital substation in smart grid has changed greatly, and the electrical energy metering system is changed greatly too. In this paper, an all-digital electrical energy metering system based on pure optical voltage transducer (OVT) and optical current transducer (OCT) is introduced. The advanced communication protocol IEC618509-2 is adopted in the all-digital electrical metering system firstly. And in this paper, the difference between traditional electrical energy metering system and all-digital electrical energy metering system is analyzed and compared in principle, and the benefits of all-digital electrical energy metering system are described. The realization of the proposed all-digital electrical energy metering system on a 220 kV voltage grade power system is described. The results of running show that the developed all-digital electrical energy metering has the performances of high accuracy, high reliability and high safety.

In view of the low measurement accuracy of traditional mechanical energy meters, the inability to charge by time, and the inability to display relevant parameters, a smart energy meter was designed. The smart energy meter takes the single chip microcomputer as the main control chip, adopts the ADE7755 module to realize the collection and calculation of the electric energy, and combines the 12864 display module, the independent button module, the clock DS1302 module, the storage 24C02 module, etc. to improve the electric energy measurement accuracy, realize time-sharing billing and Parameter display function. Completed the hardware design, software design and physical development of the smart energy meter. The physical test results show that the smart energy meter can realize dual-rate charging, reduce resource waste, and the rate range can be adjusted according to the actual situation, and can display data such as electric energy, electricity cost, time, and date.

In the application process of smart electric energy meter, not all components are in working state all the time. According to the working stress to predict its reliability index will lead to the conservatism of the predicted results. Therefore, it is necessary to consider the non-stress state of the intermittent mode unit, so as to make a more reasonable and accurate prediction. In this paper, a reliability prediction method considering non-stress state of components in intermittent operation mode is proposed, and a practical reliability prediction model of electric energy meter is established, which realizes the accurate reliability prediction of intelligent electric energy meter in intermittent mode. Based on the theory of reliability prediction and life cycle cost of electric energy meter, a comprehensive evaluation model of reliability and economy of smart electric energy meter is established, which provides a theoretical basis for the formulation of reliability index and related management policies of smart electric energy meter.

Although smart meters bring convenience to people’s lives, they also bring unnecessary losses to grid operations due to intrinsic defects. Compared with traditional electric meters, the smart meters are susceptible to interference from external magnetic fields, and may stop charging when strong interference occurs, which reduce its reliability. This also brings opportunities for lawbreakers, and the phenomenon of electricity leakage occurs from time to time. In order to overcome the shortcomings of electric meters, this project makes an in-depth research on high frequency electromagnetic field monitoring technology, and carries out the antenna simulation technique, the envelope detection technique and the alarming control system design based on the experimental data of high frequency electromagnetic field environmental parameter monitoring. A technical solution that can quickly detect external high-frequency interference sources and give alarm when stealing occurs is proposed, and a high frequency electromagnetic field monitoring module is designed to protect the operating environment of the meter.

In view of the manufacturing dispersion of smart electric energy meters in China, the products quality of various manufacturers varies greatly, the low efficiency of manual supervision and other problems, this paper describes a RFID-based smart electric energy meter monitoring technology program. RFID tags were implanted in smart electric energy meters, monitors and RFID readers were added to the production line, collected data was properly formulated. Smart electric energy meter production environment, equipment and key process steps were monitored. While uploading data to the monitoring system platform, key data was stored in meters. The whole process monitoring and full record of smart electric energy meter production process have formed, the efficiency of supervision has been improved, and the products quality has been guaranteed. At the same time, it makes up for the lack of data on manufacturing supervision in the life cycle management of smart electric energy meters.

Analysis and study the reliability theory of smart electric energy meters, as well as reliability analysis indicators and fault distribution rules. Starting from the distribution law of fault data and reliability indicators of fault life, the reliability of electric energy meters is analyzed by collecting field maintenance data. The reliability model is used to study the failure modes, causes and effects of smart electric energy meters. The research and analysis of the reliability of the smart electric energy meter ensure the normal operation of the intelligent electric energy meter and improve the stability and reliability of the intelligent electric energy meter.

This paper analyzes the inspection error of the traditional electric energy meter constant inspection method. It is believed that the inspection error of the electric energy meter constant is mainly caused by the manual control pulse when the inspector carries out the last digit of the liquid crystal meter of the electric energy meter during the constant inspection. The time difference between the start and stop of the counter is not synchronized and the truncation error of the pulse counter recorded pulse. Based on the establishment of a smart energy meter image detection system with C# and Halcon as the software platform, the Blob analysis algorithm is used to extract the ROI (region of interest) from the image, and the histogram equalization is used to process the extracted image to enhance the contrast between the background and the target area can obtain a high-quality electric energy meter picture, and the Canny edge detection algorithm is improved by the OTSU algorithm to improve the adaptability of the image threshold range to obtain a more complete image appearance outline. Character segmentation processing to obtain the rated parameter information of the electric energy meter. According to the regulations of OIML and NE standards, through analysis and demonstration, an optimized solution for fast inspection of electric energy meter constants that not only meets the inspection error requirements specified in the standard but also shortens the test time is proposed.

With the continuous changes of the working environment of the electric energy meter, the dynamic detection method of the electric energy meter becomes more and more important. Therefore, in recent years, the IEC 62052-11 Standards Committee has proposed to add a rapid change test of electric energy meter load current. This article proposes an effective dynamic test method according to the requirements of this regulation standard, builds an electric energy meter dynamic error test platform and develops a software test system. An anti-submarine mechanism is proposed for the electric energy measurement algorithm of the smart meter, and the load current rapid change test of various electric energy meters from different manufacturers at home and abroad is tested, and the correctness of this test method is verified.

At present, China’s smart electric energy meter life management is started from the procurement and acceptance. The related monitoring and management of the manufacturing sector has not yet been carried out. This article applies RFID technology and network cloud platform to full life cycle management system of smart electric energy meters, builds this full life cycle management system including design and manufacturing, process control, measurement and calibration testing, storage management, user acceptance, site operation, maintenance scrap and other aspects. Exploring smart electric energy meters on-line and off-line communication by the application of active RFID communication functions, and the actual functional application such as local data exchange and instrument calibration. This system provides technical supports on power demand side management and the improvement of smart electric energy meter reliability evaluation system.