Electric vehicle ordered charging and discharging dynamic optimization strategy based on particle swarm optimization
A particle swarm algorithm, electric vehicle technology, applied in the field of vehicle-network interaction, can solve the problem of increasing the peak-to-valley difference of the load curve
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[0084] The invention is further illustrated below with reference to the accompanying drawings and examples.
[0085] Refer Figure 1 ~ 5 An electric vehicle based on particle group algorithm based on particle group algorithm, including the following steps:
[0086] 1. Establish an electric vehicle charging load model
[0087] According to NHTS2017 travel data, "Home, H)" is the starting point, "Work, W)" is the starting point of the "Work, W)" and the starting point at "Workspace", with "home" For Gaussian fittings (WH), the probability density function (PROBILITY DENSITY FUNCTION, PDF) is obtained by Electronic Vehicle, EV. Simplifies the Gaussian probability density function to observe the results of the fitting result.
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[0089] In the formulas A, B, and C are the peak, peak position, and semi-width information of the Gaussian curve, respectively.
[0090] It is divided into 96 time sections a day 24 hours, and the relationship between EV access grid time and the time ...
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