Studies On The Electric Vehicles Charging Load Forecasting Of Guangdong Province

Low-carbon economy has become the main theme of China’s economic development, as an important part of the new energy strategy and smart grid, electric vehicles (EVs) will become the focus of future development of China’s auto industry and energy industry. As the vanguard of China’s economic development, Guangdong province is striving to the forefront in EV industry. However, after large-scale EVs will be put into use in Guangdong Province, the charging characteristics have some uncertainty. It may cause some negative effects to the power grid, so it is necessary to do some researches on Guangdong’s charging load forecasting.Firstly, this paper combines the US NHTS statistics data, the trip data of other cities and the actual EVs operation data of Shenzhen. And considering several major factors that affect charging load, which including the vehicle mileage, start time, charging time and frequency of charging. Then the paper establishes charging load models with EV cars, taxis, buses and official vehicles.Secondly, the contrasts in economy, convenience, environmental protection and other aspects between EV cars and traditional fuel cars are considered in this paper. The Logit model is used to establish the function between charge price and market share of EVs. Considering the Tripartite Game of government, electric charging infrastructure operators and EV users, and then using the method of Game analysis to predict the population of electric cars in Guangdong Province in 2020. The paper also refers to the government’s documents and planning to predict the population of electric taxis, electric buses and official EVs in Guangdong Province in 2020.Then, on the basis of charging load model and forecasting of the population, the Monte Carlo simulation method is used to predict the daily charging curve of EV cars, taxis, buses and official vehicles in Guangdong Province in 2020. The four types of electric vehicles’ charging curves are accumulated to obtain the total daily charging curve of electric vehicles in Guangdong Province.Finally, a distribution network of a typical residential area is built, and with the limited of the capacity of the transformer, the paper has considered the maximum capability of the residential area on accessing EVs. Take the IEEE 33 nodes model system as the basic studies, and combined with the distribution network of the residential area. Then load fluctuation of the original system is considered to research the node voltage offset, voltage over limit and line losses after the accessing of electric vehicles at different numbers.This paper has established the charging model in Guangdong Province from the reality, and predicted the population of electric vehicles in Guangdong Province in 2020 based on the method of Game analysis. Monte Carlo simulation method has been used to predict charging load of the electric vehicles in Guangdong Province. This study can provide a reference for the the future transformation of Guangdong power grid, electric vehicle charging load management and the electric vehicles’ pricing mechanism.