Cluster electric vehicle charge-discharge power optimization management method

Abstract

The invention discloses a cluster electric vehicle charge-discharge power optimization management method, and belongs to the technical field of electric vehicle charging and discharging management. The method comprises the steps of: the step A, collecting target dispatching power information and basic information of electric vehicles (EV) to be dispatched; the step B, establishing a convex optimization model of EV charge-discharge power dispatching according to the target dispatching power information and the basic information of the EVs to be dispatched; and the step C, issuing an EV charge-discharge power dispatching plan to EV charge-discharge control devices to control the charge-discharge of each EV. A dispatching mechanism collects the information of each EV through an EV collectionsupplier, then publishes a power command to be dispatched to the EV collection supplier and allows the EV collection supplier to send a charge-discharge power command to each EV charge-discharge control device to perform charge and discharge for the EVs. The cluster electric vehicle charge-discharge power optimization management method avoids the problem caused by non-convex constraint on solvingthe EV charge-discharge model. The method does not need any application condition, has wide application range and is easy to be popularized to the electric automobile or the peak regulation and frequency regulation field participating in energy storage.

Description

technical field [0001] The invention belongs to the field of charging and discharging management systems for electric vehicles, and in particular relates to a method for optimizing the charging and discharging power of clustered electric vehicles. Background technique [0002] With the popularization of electric vehicles (electric vehicle, EV) and the development of electric vehicle network (vehicle to Grid, V2G) technology, more and more charging and discharging power optimization management methods of cluster electric vehicles have been proposed to avoid the disorder of electric vehicles. The adverse impact of charging behavior on the grid can solve problems such as load fluctuations and intermittent renewable energy. [0003] Since the electric vehicle charging and discharging scheduling model considering V2G needs to include constraints to avoid simultaneous charging and discharging of electric vehicles (the product of EV charging power and discharging power is 0), this ...

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Problems solved by technology

[0003] Since the charging and discharging scheduling model of electric vehicles considering V2G needs to include constraints to avoid simultaneous charging and discharging of electric vehicles (the product of EV charging power and discharging power is 0), this non-convex constraint makes the model difficult to solve directly

In the existing cluster electric vehicle charging and discharging optimization scheduling scheme, integer variable modeling is often introduced, or iterative methods (such as smoothing method, precise penalty method, etc.), or intelligent algorithms (such as cross-entropy algorithm, cross-genetic particle swarm algorithm, simulated annealing algorithm, etc.) to solve the optimization model, but the above methods require a long solution time, which is difficult to meet the needs of actual optimization scheduling

At present, there are also some fast optimal scheduling methods based on convex optimization models, but they generally have the following limitations: (1) the method lacks generality; (2) the scope of application of the method is limited; (3) it is difficult to promote

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