Prediction on the charging demand for electric vehicles in Chengdu

The development of the electric vehicle charging station facilities speed directly affect the development of electric vehicle speed. And the charging demand of electric vehicles is one of the main factors influencing the electric vehicle charging facilities. The paper collected and collated car ownership in recent years, the use of elastic coefficient to predict Chengdu electric vehicle ownership, further modeling to give electric vehicle charging demand.


1.Introduction
Electric vehicle charging and switching facilities are an important facility for electric vehicles and are the main factors influencing the development and promotion of the electric vehicle, however, electric vehicle charging demand is one of the main factors which affect the effect of charging station layout, only by accurately predicting the charging demand, can rational layout of the electric vehicle charging station be achieved. There are many kinds of predicting methods for electric vehicle charging demand. In this paper, a systematic method is used to predict the charging demand of electric vehicles in Chengdu.

2.Prediction Idea
The elastic coefficient method is used to predict the number of cars in Chengdu city by 2020, and then establishes the model and combines the current situation to analyze and predict the annual car ownership and charging demand of the private cars, taxis and buses and electric vehicles.

Prediction of the car ownership 3.1 The Introduction of the Methods
The Elastic Coefficient Method is an indirect prediction method which is based on the prediction of the development and change of a factor and predicts the development of another , means elastic coefficient, that is the limit of ratio of the relative increment of the function and the relative increment of the independent variable is the elastic coefficient of the function . It is seen that the elastic coefficient of the function is the ratio of the relative change of function and relative change of independent variable, which correctly reflects sensitivity of the changes between them, elastic coefficient shows the relative change between the two and is called a single elasticity, the elastic coefficient means that the relative change of Y is greater than the relative change of X, which is called elasticity, the coefficient of elasticity means that the relative change of Y is less than the relative change of X, which is called inelasticity.
Based on the definition of the elastic coefficient method here, we take the current GDP data change and predict the growth rate of car ownership, and the formula is as follows: In the formula, R-Annual growth rate of car ownership -GDP Growth rate E-Elastic coefficient -car ownership in N year -car ownership in N-1 year

3.2Prediction of the car ownership
Although in the new energy vehicles plan of Sichuan province and put forward our electric car development goal, but because of the charging infrastructure, and the limitation of charging technology, for the development of it will be hard to achieve our goals. Therefore, this paper combines relevant theoretical models and analyses the actual status quo to predict the car ownership of Chengdu in the future. The number of automobile grew slowly due to the slow development of the national economy a few years earlier ago, however, in recent years, the rapid economy develops rapidly, the growth of car ownership has become rapidly, showing explosive trend. But according to the slow growth of GDP, it will make domestic car ownership tend to saturation in the next few years, the growth rate will gradually decline in the future. According to the GDP growth prediction of the National Statistical Bureau respectively 9%, 8% and 7% during "11th Five-  Table 3 below. Here, the paper predicts the number of electric vehicles in Chengdu according to the three high, middle and low ratio schemes . Among high, low and middle ratio schemes, 2012, 2015 and 2020, respectively, 0.6%, 2%, 9%, 0.3%, 1.2%, 6%, 0.1%, 0.3% and 3%. Taking into account the electric vehicle due to national policy and its various aspects will certainly present increasing trend of rapid growth during 2014 to 2020 and fully consider the study and take the proportion of electric vehicles from 2012 to 2020. The prediction is shown in Table 5 below. Taking into account the actual situation, choosing the data of the low scheme to calculate. According to the introduction of the development stage, in the early stage ,there is the development of the bus, taxi and other fields, the slow development of private cars; but for the long-term, private cars lies in a stage of rapid development and will show explosive growth, while buses and taxis is steadily developing. Based on this situation, this paper hypotheses taxi, bus and private cars accounted for the proportion of electric car ownership as in Table 6 shown in 2014 to 2020, taking into account the actual situation, the paper chooses electric vehicle ownership to predict low scheme to calculate the number of private cars and taxis, table 7 can be obtained.

Prediction of Charging Demand
The charging demand for electric vehicles is to prepare the layout of the electric charging station, so the prediction of its demand should firstly consider the layout and facilities of the charging station.

Predicting Premise
1) Now, the average mileage of batteries for electric vehicles is 180 kilometers , But as time goes on, the relevant experts predict that in the next 5 years, electric vehicle mileage will reach 300 km or more, but because the mature time of the technology is full of uncertainty, and Considering the deep discharge of the automobile, the service life of the battery will be affected .
2) the main charging mode of the private car is regular charging, which is supplemented by charging in the public fast charging station. So supposing that the car is charged at the public quick charging station, once from Monday to Friday and once at the weekend.
3) Taking into account the battery life problems and high depreciation costs, and now the technology and other issues, the construction of the public rapid charging station is based on the principle that the main battery replacement is considered, DC fast charge is supplemented , that is, when the vehicle comes to charge, the battery is replaced under normal conditions, and secondly, the fast charge is selected. This will not only reduce the battery load, but also improve the utilization rate of vehicles.

Normal Charging Demand
Normal charging is usually aimed at private cars. Now, in order to solve the energy and environmental problems, the government has vigorously promoted the development of electric vehicles as a means of green transportation. So as to introduce a variety of policies to promote the popularization of electric vehicles, so for the private users of electric vehicles, the construction of charging facilities should be funded by the government to build charging facilities. For private electric vehicles, charging facilities should be equipped with charging piles in accordance with the ratio 1:1.
The formula for charging demand is as follows: Q=N*S mileage/S available mileage In the formula, Q-Actual charging demand of every day N-the number of the charging cars S Mileage-average daily mileage S Available mileage -Battery mileage available Regular charging mostly aims at the private cars. The average daily mileage is 60 kilometers, and the battery mileage is 150 kilometers. Therefore, a private car charge 0.4 times a day / day. For buses, environmental sanitation vehicles and vehicles of other groups usually charge by the battery replacement. If the bus is full of electricity, available mileage is 260 kilometers, while the bus in Chengdu run 230 kilometers per day on average. Therefore, the bus is full of electricity, basically it can run one day, that is, the bus charge per day is 1 times / day. Battery replacement mode is more suitable for buses and other special vehicles to charge, the size of the battery replacement station to meet the jurisdiction of the vehicle battery supply of the second day within the station.

Electricity demand of public fast charging station
The main service object of public fast charging station is the taxi and the private car that needs temporary power supply. According to the survey, the daily mileage of taxis is about 400 kilometers, while the available mileage of the taxi is 150 kilometers, and the number of charging is 2.67 times per day. Since taxis are sometimes required to maintain and attendance rates are unlikely to be 100%, the attendance rate is 90%. The formula for charging demand for taxis can be derived by formula 3-1.
Q=N*S mileage/S available*C For private cars, the normal charging mode is chose in most cases, and only when the power needs to be temporarily added, the public fast charge can be chose. According to the hypothesis, private cars need temporarily public recharging from Monday to Friday, at least once a week, or 2 times a week at public charging from Monday to Friday . Considering the outside factors such as private car temporary maintenance, the attendance rate of private cars is also 90%. Therefore, the formula for charging electricity demand of private car in public fast charging station is as follows: Q=N*q*C In the formula：Q-charging demand(car/day)； q-average daily charging demand of every car(from Monday to Friday1/5times every day， weekends 1/2times every day)； N-the number of the charging private car ； C-attendance rate； From the above, you can know that the charging demand on the weekend is significantly greater than Monday to Friday charging demand, In order to avoid too many traveling owners on the weekends and waiting in line too long when charging, when planning the scale of the charging facilities, the requirements of the weekend should be considered to meet the vehicle's electricity demand as a target construction. Due to the driving characteristics of the normal charging service objects, it is possible to build AC charging piles in the special-purpose parking areas and public parking places, and the construction of battery replacement stations in fixed parking areas is suitable for group cars. In view of the location of these two kinds of charging facilities, the existing parking spaces and parking lots can be assured, while the public fast charging stations can not be assured and need to be calculated by prediction. Therefore, this thesis regards the public fast charging station as the main object of the study. For the taxi, according to the formula 3-2, the formula of the taxi charging demand can be gained: Q=N*2.67*90%; according to the formula 3-3, the formula of the private car charging demand can be gained : Q=N*0.5*90%, charging demand of the taxi and the private electric cars are given from 2014 to 2020 in table 8. Table8

5.Conclusion
This paper combines the development of electric vehicles in Chengdu. In the last few years, the number of car ownership has been collected to predict the number of electric vehicles in Chengdu's 13th five-year plan, and its products are predicted. The model is further established to predict the charging demand of one of the main factors influencing the layout of electric vehicle charging stations. A good setup is provided for the distribution of charging stations for electric vehicles.