The Impact Of Electric Vehicles Charging Load On Distribution System And Optimization Method

Nowadays, since the world confronts increasingly serious problems ofenvironmental pollution and global climate change, governments, businesses andconsumers pay great attention to the EVs (electric vehicles) for their low pollution andlow carbon emission characteristics. With great strides in high-performance batteryand motor technology, EVs have reached the practical stage and will be used in largescale in the near future. When a large number of EVs are available in the market, thehuge charging load will have adverse effects on distribution network. Therefore, it isnecessary to quantitatively analyze the impact of the charging load on distributionnetwork and propose the corresponding optimization strategies to minimize itsnegative impact.Accurate calculation of the charging load serves as the basis of quantitativeanalysis of the impact of charging load on distribution network. Firstly, this paperanalyzes the method of calculation of the EVs charging load. It build the charging loadmodel considering randomness with several influencing factors and propose thecharging load calculation method based on statistical principles. This method iscompared with the charging load calculation method based on Monte Carlo simulationwith the same accuracy and higher computational efficiency.Secondly, it sets several scenarios according to different EVs penetrations andseasons and analyzes the impact of charging load on power loss, voltage deviation,maximum load, peak and valley difference under different scenarios. The simulationresults show that the penetration level is related to the impact of charging load on thedistribution network which means the higher penetration rate cause more severe effect.Finally, the time-of-use (TOU) scheme with optimized time period partition isproposed to realize the EVs optimized charging. The method of exhaustion is chosen toget two different optimal time period partitions with minimum peak and valleydifference or smallest standard deviation by calculating peak and valley differencesand standard deviations of system daily load curve respectively under every timeperiod partitions which achieve the goals of minimum peak and valley difference andlowest system load fluctuation of distribution system.This paper focuses on the analysis of the impact of charging load on thedistribution network and corresponding optimization measures. It proposes thecalculation method of charging load, analyzes the charging load impact on the distribution network, and develops optimized charging scheme which serves as areference for further comprehensive and detailed analysis of charging load impact onsystem and formulation better optimized charging scheme.