Electric vehicle charging optimization method based on day-ahead load prediction value
An electric vehicle and optimization method technology, applied in the direction of electric vehicle charging technology, electric vehicles, charging stations, etc., can solve the problems of not being able to control the initiative of power regulation and the large amount of calculation of charging stations
Pending Publication Date: 2022-04-26
GUANGZHOU CITY UNIV OF TECH
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[0009] In this way, the load optimization of the charging station requires a large amount of computation, and it is impossible to control the initiative of power regulation
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[0066] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.
[0067] Such as Figure 1-Figure 2 As shown, an electric vehicle charging optimization method based on a day-ahead load forecast value is used for charging an electric vehicle at a charging station, and the optimization method includes the following steps:
[0068] (S1) Obtain the total loss power of the transformer in the charging station and the economic equivalent of reactive power K q .
[0069] When the transformer is running, the total power loss of the transformer includes the no-load loss P 0 and load loss P K , then the expression of active power loss ΔP is:
[0070] ΔP=P 0 +β 2 P K (1).
[0071] In the expression (1), ΔP is the active power loss of the transformer, P 0 is the no-load loss of the transformer, β is the load factor of the transformer, P k is the short-circuit active power loss of the transformer; ΔP, ...
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The invention discloses an electric vehicle charging optimization method based on a day-ahead load prediction value. The method comprises the following steps: obtaining a charging station transformer parameter and a reactive economic equivalent; calculating the optimal comprehensive operation efficiency of the charging station transformer; one day is divided into 24 time periods, each hour is one time period, the charging power of the charging pile of the charging station in each time period is optimized in real time, the reference optimization coefficient of each time period is defined as ki, and the power reference optimization coefficient ki of the electric vehicle in each time period is obtained; obtaining the number of electric vehicles being charged in the charging station in a certain period of time and the battery remaining capacity SOC of each electric vehicle; obtaining the number of electric vehicles being charged in the charging station in a certain period of time and the battery remaining capacity SOC of each electric vehicle; according to the method, real-time power optimization can be carried out on the electric vehicle connected to the charging station in each time period of one day, and optimization is carried out by using the reference optimization coefficient of each time period, so that the operand is greatly reduced, and the transformer is enabled to operate at the optimal comprehensive efficiency.
Description
technical field [0001] The invention relates to the technical field of electric vehicle charging, in particular to an electric vehicle charging optimization method based on a day-ahead load forecast value. Background technique [0002] In recent years, people have higher and higher requirements for energy and the environment. Insufficient reserves of fossil fuels and global warming have attracted increasing attention. The improvement of environmental protection concepts has made people strongly demand to reduce oil consumption in transportation. Due to its special energy drive mode, electric vehicles have good energy-saving and low-emission potentials, and have been widely developed. Electric vehicles can improve energy efficiency and reduce environmental pollution. Its popularization and promotion has become a future trend. Countries have also adopted active policy measures to encourage the development of electric vehicles. [0003] The electrification of the transportatio...
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IPC IPC(8): H02J3/00B60L53/63
CPCH02J3/0075H02J3/003B60L53/63Y02T10/70Y02T10/7072Y02T90/12
Inventor 周星月王智东张紫凡王玕吴灿郭琳
Owner GUANGZHOU CITY UNIV OF TECH