Pseudorandom Dynamic Test Signal Modeling And Dynamic Error Test Method Of Electricity Meter

In the twenty-first century,in order to solve the contradiction between energy and environment,great changes have taken place in the supply side and demand side of energy grid.In 13th five year plan outline of the China,it is clearly proposed that "further promote the energy revolution and strive to promote the transformation of energy production and utilization mode".After years of technological innovation and application,by implementing the five development concepts of "innovation,coordination,green,openness and sharing" put forward by general secretary Xi Jinping,our energy production and utilization patterns have changed significantly,at the same time,it has also brought challenges to the accurate measurement of electrical energy.The output power of large scale renewable energy generation on the supply side of energy grid has strong uncertainty,intermittent and random volatility.The wide application of large power nonlinear dynamic loads on the demand side leads to the complex and rapid dynamic fluctuation of load current,which leads to the serious over tolerance of electrical energy measurement for smart electricity meters.According to the statistics of nation energy administration,in 2019,the industrial power consumption dominated by nonlinear dynamic loads accounts for 67.1%of the total social electrical energy consumption Therefore,the 1%error of electrical energy measurement caused by the rapid random fluctuation of dynamic loads may cause several billion yuan of economic loss.However,at present,there is no corresponding theory and technology for the dynamic error testing of smart electricity meter under the condition of rapid fluctuation at home and abroadGuided by the above problems in the implementation of the national strategy,the scientific problems for the dynamic error testing of smart electricity meter are found and refined in this paper,theory and method of the smart electricity meter dynamic error test are researched and explored.The original research results are formed,which mainly including(1)The typical intrinsic characteristics of actual dynamic load singals in the grid are studied and analyzed.On this basis,aiming.at the problem that the existing test signals for electricity meter error testing can not reflect the fast and random fluctuation characteristics of actual dynamic load signals,a new structual parameter model of distorted waveform m-sequence pseudorandom dynamic test signal is established,and the signal generation method is proposed.The test signal model meets the requirements of the dynamic error test signal modeling for smart electricity meter,and provides an effiective solution for the dynamic error testing of smart electricity meter.(2)In order to improve the efficiency of the smart electricity meter dynamic error testing,according to the linear code modulation theory of measurement matrix in the compressive sensing theory,an orthogonal pseudorandom measurement matrix is constructed by using the structural method,the orthogonal pseudorandom amplitude modulation function is generated by matrix mapping,and the distorted waveform orthogonal pseudorandom dynamic test signal model is proposed.It can reflect the typical intrinsic characteristics of actual dynamic load signals,at the same time,it has compactness,which improves the efficiency of smart electricity meter dynamic error test.Meanwhile,the problem of the application using compressive sensing theory in engineering field is solved.(3)The windowed algorithm,which is widely used in the field of electrical parameter measurment at home and abroad,has the problem that the measurement accuracy is obviously reduced under fast random dynamic conditions.Based on the compressive measurement signal processing theory,the frequency-domain spareness of pseudorandom dynamic instantaneous power test signal is analyzed.By constructing a minimum error active power measurment filter,a nonoverlapping moving compressive measurement(NOLM-CM)algorithm is proposed for the dynamic electrical energy accurate measurement.In the simulation and experimental conditions,the NOLM-CM algorithm is verified to have higher accuracy.It can provide guidance for the accurate measurement of dynamic electrical energy measurement under fast random dynamic conditions.(4)Aiming at the smart electricity meter dynamic error test,based on the two kinds of distorted waveform pseudorandom dynamic test signals,the run length likelihood functions of test signals are defined,and a dynamic error likelihood function indirect test method of smart electricity meter is establised,which solves the traceability from dynamic reference electrical energy to steady-state reference electrical energy.Meanwhile,the dynamic error test system of smart electricity meter is builted.Experimental results verify the validity of the distorted waveform pseudorandom dynamic test signal models and dynamic error likelihood function indirect test method.The measurement uncertainty is significantly reduced.In this paper,from theoretical research to simulation analysis,then to experimental verifications,a complete theorectical system of smart electricity meter dynamic error test has been formed,and the key technologies have been solved.The research results have broad application propects to ensure the accurate measurment and fair trading of electrical energy under the condition of rapid random dynamic fluctuations,and promote the green development and innovation development of electrical energy substitution.