Electric vehicle charging network chance constraint planning method considering random charging load
A technology for electric vehicles and charging networks, applied in the field of electric vehicle charging network planning, can solve problems such as providing references and difficult construction of electric vehicle charging networks, and achieve the effect of reducing network loss and electricity
Inactive Publication Date: 2021-04-30
JIANGSU ELECTRIC POWER CO +1
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Problems solved by technology
However, the existing planning methods do not consider the impact of the random characteristics of electric vehicle charging load on the operating conditions of the power distribution system, which has certain limitations and is difficult to provide reference for the construction of electric vehicle charging network
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[0055] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. Of course, the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0056] Such as figure 1 As shown, the present invention proposes a chance constrained programming method for electric vehicle charging network considering random charging load, specifically as follows:
[0057] S1: given planning boundary conditions, including: distribution system topology parameters, distribution system planning typical day load, electric vehicle charging station planning typical day charging load probability scenario set, distributed photovoltaic planning typical day output probability scenario set , the candidate addresses of charging stations, the total number of charging stations, the construc...
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The invention provides an electric vehicle charging network chance constraint planning method considering a random charging load. The method comprises the following steps: 1, giving a planning boundary condition; 2, establishing an electric vehicle charging network stochastic programming model based on opportunity constraints; 3, designing a chromosome coding scheme and crossover and mutation operators, and solving the electric vehicle charging network stochastic programming model by adopting a genetic algorithm. The method has the advantages that the electric vehicle charging network stochastic programming model based on chance constraint is adopted, the construction address and capacity of the electric vehicle charging station can be optimized on the premise of considering charging load stochastic characteristics, and the network loss electric quantity of a power distribution system planning typical day is reduced; by designing a chromosome coding scheme and crossover and mutation operators in a genetic algorithm and combining distribution system probabilistic load flow analysis, an optimal planning scheme of an electric vehicle charging network can be quickly and accurately obtained.
Description
technical field [0001] The invention relates to the field of electric vehicle charging network planning, in particular to a chance-constrained programming method for electric vehicle charging networks considering random charging loads. Background technique [0002] In recent years, with the gradual depletion of fossil fuels and the increasing environmental pollution, clean energy vehicles represented by electric vehicles have become increasingly popular. At present, the charging power of a single electric vehicle can reach tens of kilowatts. Therefore, as an important place for electric vehicle charging, the charging load of electric vehicle charging stations can reach hundreds or even thousands of kilowatts, becoming one of the most important loads in the power distribution system. one. An unreasonable electric vehicle charging network will not only hinder the development of electric vehicles, but also deteriorate the operating conditions of the power distribution system. ...
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Login to View More IPC IPC(8): G06N3/12G06Q10/04G06Q10/06
CPCG06N3/126G06Q10/04G06Q10/06315Y02E40/70Y04S10/50
Inventor 李亚飞钱科军刘乙谢鹰郑众张晓明张新松曹书秀徐杨杨陆胜男卢成郭云翔
Owner JIANGSU ELECTRIC POWER CO