A Controlled Electric Vehicle Charging Strategy Considering Regional Wind And PV

With the declining quality of the environment around the world, people are increasingly advocating the concept of green living. As is in response to the country's energy conservation policy, electric vehicle is developing rapidly. On the other hand, the traditional fossil fuel resources are depleted, wind and solar energy is widely studied and utilized as promising renewable energy.First, it will produce a corresponding power fluctuation of wind, solar and other renewable energy power generation, when large-scale renewable energy connected to the grid, how to stabilize its power fluctuations on the grid and increase its absorptive capacity of the grid is the urgent problem. Secondly, large-scale electric vehicle charging will result in localized tension load, especially during peak hours, it will increase the burden on the power grid, and how to reduce their impact on the power grid by coordinating control of electric vehicle charging process is worthy of studying. Combining these two problems, we propose the following research ideas: by directing the electric vehicle charging order to reduce the impact of large-scale disorder charging on the grid, through the control of the charging time and the amount of load, we can stabilize the fluctuations caused by wind, light and other new energy in the power grid and optimize the regional peak and valley difference.The main work is as follows: First, based on probabilistic law a probabilistic output model of regional wind farm and PV generation is established and a method to assess the peak to load difference in uncertain load curve is put forward; Second, a two-stage model for peak and valley electricity price is built and through this model the peak and load electricity price can be used to guide the ordered charging of EV; Third, an optimization model for the beginning and ending time of the valley electricity price in the two-stage peak and valley electricity price model and the peak and valley electricity price is established and solved by genetic algorithm; Finally, in response to a substation supply area including wind farm and photovoltaic generation, regional EV sharing control strategy is proposed to take advantage of electric vehicles to complete new energy consumption.