Multi-objective scheduling method for wind power-electric vehicle-thermal power joint operation model
An electric vehicle and thermal power combined technology, applied in the field of power system, can solve problems such as not considering the effect of joint optimal scheduling, few multi-objective optimization research, and not considering the impact research.
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Embodiment 1
[0042] Embodiment 1: An implementation of the multi-objective scheduling method for the joint scheduling of wind power-electric vehicles-thermal power;
[0043] Such asfigure 1 As shown, the method includes the following steps:
[0044] S1. Randomly generate multiple groups of 24-period wind speed values through the Weibull distribution function;
[0045] It is characterized in that the Weibull distribution function adopted in the step S1 is:
[0046] F ( v ) = 1 - exp [ - ( v c ) k ]
[0047] Among them: k is the shape parameter; c is the scale parameter, reflecting the average wind speed of the wind farm;
[0048] The probability density function of wind speed v is:
[0049] f ( ...
Embodiment 2
[0077] Embodiment 2: the comparison of several model equivalent load curves;
[0078] (1) First introduce the free charging model of electric vehicles:
[0079] Since electric vehicles are still in the stage of trial operation and promotion, a large number of electric vehicle daily mileage and other relevant reliable historical data are relatively scarce. Based on the family vehicle driving survey data of the U.S. Department of Transportation, using the maximum likelihood parameter estimation method, the cumulative distribution function of the daily driving mileage of the family car is fitted with the lognormal cumulative distribution function, and the daily driving mileage obeys the pairwise distribution function. The number of normal distribution, its probability density function is:
[0080] f d = 1 d σ 2 π ...
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