The latest policy on solar container charging piles

How many charging piles are there?

The demand for slow charging piles is only 18. Its total number is 30. There is a reduction of 80% compared with the 153 charging piles obtained from the charging demand forecast. Assume that the time cost of electric vehicles to queue or transfer to a new charging station is the same as the time cost of fuel vehicles.

How to optimize the configuration of electric vehicle charging piles?

When optimizing the configuration of electric vehicle charging piles, it’s necessary to consider the limited number of charging piles in the parking lot. We assume that the charging information can be shared with EVs in real-time to provide decisions for charging decisions and path planning. 3.11.2.

How to build charging piles in China?

The Chinese government has made great efforts to build charging piles. At present, the most popular construction mode is to build charging piles on a fixed proportion of spaces in existing parking lots. The proportions of charging piles recommended by the government, which is known as a one-size-fits-all strategy.

Do redundant charging piles increase the time cost of electric vehicles?

Assume that the time cost of electric vehicles to queue or transfer to a new charging station is the same as the time cost of fuel vehicles. It can be concluded that redundant charging piles will increase the time cost of GVs and reduce the travel cost of EVs, thus increasing the time cost of all vehicles when the number of EVs is small.

What is the proportion of charging pile demand and construction?

Therefore, the initial trial construction proportion of fast charging piles in the area is 3%, the proportion of slow charging piles is 6% and the total proportion of charging piles is 9%, which are as shown in Table 1 below. Table 1. The proportion of charging pile demand and construction.

What is the optimization model for charging piles?

The optimization model aims to design the configuration of charging piles to minimize the sum of electric vehicle queueing time, gasoline vehicle queueing time, and vehicle transfer time to idle parking lots. The model is solved by the genetic algorithm. This paper takes the Wulin Square business district in Hangzhou as a real-world example.