Research On The Influence Of Electric Vehicle Charging Load On Electric Energy Measurement Accuracy

There are a large number of non-linear components in the charging system of electric vehicle,which results in a large number of harmonic(ripple),sudden change and unsteady signals in the charging load of electric vehicle,showing obvious non-linearity,seriously affecting the accuracy of electric energy measurement.In order to improve the accuracy of electric vehicle charging energy measurement,AC and DC charging load characteristics are studied.Based on the equivalent circuit,the charging load model of electric vehicle is established.A new electric energy measurement algorithm based on the charging load characteristics of electric vehicle is proposed and simulated.Aiming at the shortcomings of on-site operation state evaluation of electric energy measurement devices,an evaluation method of electric vehicles charging electric energy measurement accuracy based on fuzzy comprehensive strategy is proposed.The experiment on the influence of charging load on electric energy measurement error is designed.The accuracy of the proposed measurement algorithm and the effectiveness of the evaluation method are verified by the results of field operation and the evaluation case of electric vehicle charging energy measurement accuracy.The main contents of this paper are as follows:(1)The AC and DC charging load curve of electric vehicle is analyzed to extract the non-linear characteristics of harmonic(ripple),sudden change and unsteady signal.Combining with the charging load characteristics of electric vehicles,the charging load of electric vehicles is modeled based on equivalent circuit theory,so as to determine the impact of charging load on charging energy measurement of electric vehicles.(2)The measurement principle and characteristics of measurement instruments are studied.According to the non-linear characteristics of electric vehicles charging load,a new energy measurement algorithm based on variable step size adaptive Kalman and modified wavelet packet is proposed.The algorithm optimizes the recognition accuracy and convergence speed of harmonic(ripple)by adaptive selection of noise covariance coefficient and step size and introduction of forgetting factor,and improves the accuracy of extracting sudden and unsteady signals by modifying the layering and threshold parameters of wavelet packet transform.The simulation results show that the proposed algorithm can accurately extract the fundamental wave(including sudden change signal),harmonic wave(ripple)and unsteady wave of electric vehicles charging signal adaptively and accurately,and then the relative accuracy of electric vehicles AC and DC charging energy measurement is 67.6% and 75% higher than that of full power energy measurement algorithm respectively.(3)In view of the shortcomings of the current evaluation of electric vehicle charging electric energy measurement status,a method of evaluating charging electric energy measurement accuracy of electric vehicles based on fuzzy comprehensive strategy is proposed.The multiple factors affecting the accuracy of electric vehicle charging energy measurement are analyzed,and the accuracy evaluation model is established to overcome the defect that the true value can not be obtained effectively and the accuracy of electric energy measurement can not be evaluated by the measured electric energy data.(4)The electric energy measurement algorithm based on variable step size adaptive Kalman and modified wavelet packet is burned into the formal prototype.Under the specified reference conditions,the influence test of harmonic(ripple)on measurement error and the influence test of current amplitude on measurement error are set.The accuracy and the ability to anti-harmonic(ripple)interference of proposed measurement algorithm are verified by the field operation results.A case study on accuracy assessment of electric vehicle charging electric energy measurement was conducted to verify the effectiveness of the proposed evaluation method.