CN109815618B - Photovoltaic power generation tracking method under shading based on physical model and particle swarm algorithm - Google Patents

Abstract

The invention discloses a photovoltaic power generation tracking method under shading based on a physical model and a particle swarm algorithm. The engineering model is simplified according to the condition that the photo-generated current is far larger than the reverse saturation current of an internal diode and the parallel resistance is infinite to obtain the model. The particle swarm algorithm search range is each peak value range determined by the engineering model; and finally, the tracking of the photovoltaic power generation global optimum point under the shading based on a physical model and a particle swarm algorithm is realized through the comparison of experimental data.

Description

Photovoltaic power generation tracking method under shade based on physical model and particle swarm algorithm

technical field

The invention relates to the technical field of photovoltaic power generation systems, in particular to a photovoltaic power generation tracking method under shade based on a physical model and a particle swarm algorithm.

Background technique

Photovoltaic arrays generate several peaks under shading conditions. To obtain the maximum output power of the photovoltaic power generation system, a solution needs to be found. In order to solve this problem, many scholars proposed the maximum power point tracking method under shading conditions [Hu Keyong, Xu Fang, Ai Qinglin, et al. Improved particle swarm optimization algorithm for photovoltaic multi-peak power tracking [J]. Journal of Xi'an Jiaotong University, 2015, 49(4). Yu Xiaopeng, Xiao Wenbo, Wu Huaming, et al. Research on photovoltaic cell engineering model and several maximum power point tracking algorithms [J]. Journal of Nanchang Hangkong University (Natural Science Edition), 2017(03):45-55.]. The goal pursued by all methods is fast and high-accuracy tracking of the maximum power point of photovoltaic cells under shaded conditions.

SUMMARY OF THE INVENTION

The problem to be solved by the present invention is to provide a photovoltaic power generation tracking method under shade based on a physical model and a particle swarm algorithm. According to the photovoltaic cell mathematical engineering model, the photo-generated current is much larger than the reverse saturation current of the internal diode, and the parallel resistance is infinitely lower. The simplified model pre-estimates the peak range, and searches for the particle swarm algorithm according to the set voltage range, so as to achieve fast and high-precision tracking of the global maximum power point.

The technical solution provided by the present invention to solve the above problems is: a method for tracking photovoltaic power generation under shade based on a physical model and a particle swarm algorithm, characterized in that the method includes the following steps:

(1) The engineering model calculates the P-V characteristic curve of photovoltaic cells under different light intensities according to the simplified model obtained when the photo-generated current is much larger than the reverse saturation current of the internal diode and the parallel resistance is infinite;

(2) Combined with the P-V characteristic curves of photovoltaic cells under different light intensities, pre-estimate the approximate position of the multi-peak value of photovoltaic power generation under shading; by setting the peak voltage ±3V search interval, determine the search range of the particle swarm algorithm, using the particle swarm Algorithm to search for each peak power;

(3) Comparing the above search results using particle swarm algorithm to obtain the maximum power point of photovoltaic power generation.

Preferably, in the step (1), the engineering model determines each peak position according to the model obtained when the photogenerated current is much larger than the reverse saturation current of the internal diode and the parallel resistance is infinite.

Preferably, in the step (2), the search range of the particle swarm algorithm is determined according to the peak position determined by the engineering model in the step (1), so that the particle swarm algorithm can achieve faster and more accurate tracking.

Compared with the prior art, the advantages of the present invention are: the present invention is based on the engineering model based on the fact that the photo-generated current is much larger than the reverse saturation current of the internal diode and the model obtained by simplification when the parallel resistance is infinite; Determine the approximate range of the local peak value of the photovoltaic cell; then use the particle swarm algorithm to track within the voltage range set by the particle swarm algorithm, and finally determine the maximum power point of the photovoltaic cell by comparing the experimental data to achieve the maximum power point of the photovoltaic cell, which can achieve a fast and high-precision global maximum For the tracking of the power point, the present invention can realize the tracking of the maximum power point of the photovoltaic power generation system more quickly and accurately under the shading condition, and provides an effective way for the photoelectric conversion efficiency of the current solar cell.

Description of drawings

The accompanying drawings described herein are used to provide further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention.

1 is an equivalent circuit diagram of two photovoltaic cells with bypass diodes according to the present invention;

2 is a schematic diagram of the P-V characteristic curve of the photovoltaic array under different shading conditions according to the present invention;

Figure 3 shows the experimental results obtained by the present invention.

Detailed ways

The embodiments of the present invention will be described in detail below with the accompanying drawings and examples, so as to fully understand and implement the implementation process of how the present invention applies technical means to solve technical problems and achieve technical effects.

A method for tracking photovoltaic power generation under shade based on a physical model and a particle swarm algorithm, the method includes the following steps:

(1) The engineering model calculates the P-V characteristic curve of photovoltaic cells under different light intensities according to the simplified model obtained when the photo-generated current is much larger than the reverse saturation current of the internal diode and the parallel resistance is infinite;

(2) Combined with the P-V characteristic curves of photovoltaic cells under different light intensities, pre-estimate the approximate position of the multi-peak value of photovoltaic power generation under shading; by setting the peak voltage ±3V search interval, determine the search range of the particle swarm algorithm, using the particle swarm Algorithm to search for each peak power;

(3) Comparing the above search results using particle swarm algorithm to obtain the maximum power point of photovoltaic power generation.

In the step (1), the engineering model determines each peak position according to the model obtained when the photo-generated current is much larger than the reverse saturation current of the internal diode and the parallel resistance is infinite.

In the step (2), the search range of the particle swarm algorithm is determined according to the peak position determined by the engineering model in the step (1), so that the particle swarm algorithm can achieve faster and more accurate tracking.

According to the current change of each battery in Figure 1, it is analyzed whether the bypass diode connected in parallel with each battery is turned on, and thus the output voltage of each battery under different light intensities can be obtained. The two batteries are at the same working current, and their bypass diodes are in blocking state. However, under non-uniform light intensity, the two batteries will be at different working currents, and some batteries will be affected by the bypass diode. does not work, the analysis is as follows:

If the light intensity received by the first battery is S ₁ , the short-circuit current is I _ph1 ; the light intensity received by the second battery is S ₂ , and the short-circuit current is I _ph2 , if S ₁ < S ₂ , then I _ph1 <I _ph2 .

When the current I<I _ph1 in the two series-connected batteries, then the two series-connected batteries output together, the output voltage V is:

When the battery component current I _ph1 < I, only the second battery is output to the outside; the reason is that the bypass diode of the first battery is turned on, causing the first battery to fail and not output to the outside, and the output voltage V is:

Parameters in the above formulas (1) and (2): I _ph —— photo-generated current; I _o —— reverse saturation current of internal diode of battery; q—— electron charge constant; R _s —— internal series resistance of battery; n ——the internal diode ideality factor of the battery; k——Boltzmann constant; T——the battery temperature during the test.

The battery characteristics under shaded conditions were analyzed, and the output voltages of the series-connected batteries under different output current conditions were obtained. Fit the volt-ampere characteristic curve of the solar cell under illumination.

和

的搜索区间段，通过工程模型计算得到的峰值范 围后利用粒子群算法进行搜索，搜索得到两个局部峰值P3和P4分别为92.87162W和 93.79569W，横坐标电压分别为15.52917V和28.68385V。最后通过对比每个峰值的大小得出 P4为最大功率点，结果如图3所示。因此自适应惯性权重粒子群算法完全可以完成局部荫影 条件下对光伏阵列最大功率点的全局寻优，并且算法搜寻到的最大功率点值十分接近理论 值，验证了该算法的准确性。 The specific operation of the present invention is: firstly, according to the mathematical engineering model of photovoltaic cells, pre-estimate the approximate position of the multiple peaks of photovoltaic power generation under the shade; secondly, search for the specific size of each peak value of the photovoltaic power generation under the shade according to the particle swarm algorithm; The size of the peak value obtains the maximum power of photovoltaic power generation. As shown in Figure 2, using the engineering model to calculate the output voltage power characteristic curve of the solar cell, it can be known that the two local peaks P1 and P2 are 81.85925W and 85.30249W respectively, and the abscissa voltages are 14.21392V and 26.96348V respectively. Set by pre-estimated peak approximate location

and

The search interval segment of , and the peak range calculated by the engineering model is used to search by particle swarm algorithm. The search obtains two local peaks P3 and P4, which are 92.87162W and 93.79569W, respectively, and the abscissa voltages are 15.52917V and 28.68385V, respectively. Finally, by comparing the size of each peak, P4 is obtained as the maximum power point, and the result is shown in Figure 3. Therefore, the adaptive inertial weight particle swarm optimization algorithm can completely complete the global optimization of the maximum power point of the photovoltaic array under local shadow conditions, and the maximum power point value found by the algorithm is very close to the theoretical value, which verifies the accuracy of the algorithm.

Therefore, it shows that the photovoltaic power generation tracking method under shade based on the physical model and particle swarm algorithm proposed by us can track the global optimal value of the photovoltaic power generation system more quickly and accurately.

The beneficial effects of the present invention are as follows: the present invention uses an engineering model to simplify the model based on the fact that the photo-generated current is much larger than the reverse saturation current of the internal diode and the parallel resistance is infinite; Then use the particle swarm algorithm to track within the voltage range set by the particle swarm algorithm, and finally determine the maximum power point of the photovoltaic cell by comparing the experimental data to achieve the maximum power point of the photovoltaic cell, which can achieve fast and high-precision tracking of the global maximum power point. The invention can track the maximum power point of the photovoltaic power generation system more quickly and accurately under shading conditions, and provides an effective way for the current photovoltaic conversion efficiency of solar cells.

The above only describes the best embodiments of the present invention, but should not be construed as limiting the claims. The present invention is not limited to the above embodiments, and the specific structure thereof can be changed. All changes made within the protection scope of the independent claims of the present invention are all within the protection scope of the present invention.

Claims (3)

1. A photovoltaic power generation tracking method under shading based on a physical model and a particle swarm algorithm is characterized in that: the method comprises the following steps:

(1) the engineering model calculates the P-V characteristic curve of the photovoltaic cell under different illumination intensities according to a model obtained by simplifying the condition that the photoproduction current is far larger than the reverse saturation current of the internal diode and the parallel resistance is infinite;

(2) pre-estimating the approximate position of the photovoltaic power generation multi-peak value under shading by combining the P-V characteristic curves of the photovoltaic cells under different illumination intensities; setting a search interval through a peak value, determining a particle swarm algorithm search range, and searching each peak power by using a particle swarm algorithm;

(3) and comparing the results obtained by utilizing the particle swarm algorithm to obtain the maximum power point of the photovoltaic power generation.

2. The physical model and particle swarm algorithm-based photovoltaic power generation tracking method under shade according to claim 1, characterized in that: in the step (1), the engineering model determines the position of each peak value according to a model obtained when the photo-generated current is far larger than the reverse saturation current of the internal diode and the parallel resistance is infinite.

3. The physical model and particle swarm algorithm-based photovoltaic power generation tracking method under shade according to claim 1, characterized in that: in the step (2), the particle swarm algorithm searching range is determined according to the peak position determined by the engineering model in the step (1), so that the particle swarm algorithm can realize tracking more quickly and accurately.

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