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Genetic-algorithm

于 2015-11-05 发布文件大小:8KB

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代码说明：

用MATLAB程序语言实现最优控制的遗传算法( Genetic algorithm)

文件列表：

遗传优化算法 (2)
................\AsyLnCPSO.m,1085,2008-09-04
................\BreedPSO.m,1829,2008-09-10
................\CLSPSO.m,2413,2008-09-13
................\LinWPSO.m,1028,2008-09-02
................\LnCPSO.m,1017,2008-09-04
................\PSO.m,971,2008-09-02
................\RandWPSO.m,1116,2008-09-03
................\SAPSO.m,1156,2008-09-11
................\SecPSO.m,1073,2008-09-03
................\SecVibratPSO.m,1438,2008-09-03
................\SelPSO.m,1173,2008-09-10
................\SimuAPSO.m,1584,2008-09-04
................\YSPSO.m,1175,2008-09-02

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The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

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Genetic-algorithm

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