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Photovoltaic system MPPT method based on leapfrog and pattern search neural network

A pattern search algorithm and neural network technology, applied in the field of photovoltaic system MPPT based on leapfrog and pattern search neural network, can solve the problems of low quality of neural network sample data sets, inaccurate maximum power point tracking, etc., and achieve high tracking Efficiency, response speed and precision are superior, and the effect of fast response time

Pending Publication Date: 2021-06-29
HUAIYIN INSTITUTE OF TECHNOLOGY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] Purpose of the invention: This invention aims to provide a photovoltaic system MPPT method based on leapfrog and pattern search neural network, to solve the problems of low quality of neural network sample data set and inaccurate maximum power point tracking

Method used

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  • Photovoltaic system MPPT method based on leapfrog and pattern search neural network

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Embodiment 1

[0131] In order to simulate the condition that the cloud passes quickly through the solar panel, under the constant temperature condition of 25° C., this embodiment considers different radiation conditions on the photovoltaic panel. Step changes occur at every second interval as shown below.

[0132] State 1: 200W / m 2 And 0

[0133] State 2: 400W / m 2 And 3

[0134] State 3: 600W / m 2 And 6

[0135] State 4: 800W / m 2 And 9

[0136] State 5: 300W / m 2 And 11

[0137] State 6: 1000W / m 2 And 12

[0138] Among them, the maximum irradiance value of 12 to 14 seconds is 1kW / m 2 , the minimum irradiance value for 0-3 seconds is 0.2kW / m 2 .

[0139] Figure 7 The performance of the proposed maximum power point tracking method at maximum available power at different irradiances is described. It can be seen that, compared with different maximum power point tracking technologies, the performance of the maximum power point tracking method propos...

Embodiment 2

[0143] The purpose of the simulation is to assume an isolation constant of 1000W / m 2 When , the effect of temperature change on the operating point of the photovoltaic system is studied. The performance of photovoltaic systems is evaluated in the following states.

[0144] State 1: 57°C and 0

[0145] State 2: 48°C and 2.5

[0146] State 3: 41°C and 7

[0147] Figure 13 A comparison of power and amplified power in the instantaneous case is given. It can be seen that the method reaches the maximum power point with high accuracy and can track accurately even under changing weather conditions. However, the disadvantage of solar energy system is that it is very dependent on weather conditions, to solve this problem, storage devices are introduced that can provide more reliability and stability under steady state and dynamic conditions. The combination of photovoltaic system and battery BES can form a stable and reliable hybrid power system, such as Figur...

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Abstract

The invention discloses a photovoltaic system MPPT (Maximum Power Point Tracking) method based on a leapfrog and pattern search neural network, which comprises the following steps of: (1) obtaining the temperature and irradiance of a photovoltaic module, and obtaining a maximum power point reference voltage by adopting a neural network; (2) enabling the controller to obtain an output quantity according to an error between the reference voltage and the measurement voltage of the photovoltaic module; (3) enabling an enhanced disturbance observer P& Q to obtain the control quantity of the chopper circuit according to the measured voltage, the measured current and the output quantity of the controller, so that the photovoltaic system stably works at the maximum power point along with the illumination change. According to the method, a hybrid recombination leapfrog and pattern search algorithm is adopted to optimize the maximum power point tracking based on the neural network in the photovoltaic system; the method has excellent performance in response speed and precision, and can provide the highest tracking efficiency and the fastest response time under the condition that the steady state and the irradiance are continuously changed, and the response time is 11 seconds.

Description

technical field [0001] The invention relates to a photovoltaic system MPPT method, in particular to a photovoltaic system MPPT method based on leapfrog leap and pattern search neural network. Background technique [0002] In recent years, researches on the maximum power point tracking (MPPT) of photovoltaic PV power stations have emerged in an endless stream, and many control methods have also been proposed in various literatures. Research and evaluation of reliability under environmental conditions, etc. Among various maximum power point tracking methods, the artificial neural network ANN maximum power point tracking method is famous for its strong anti-noise ability and no need for prior information of the solar system's physical parameters. [0003] The samples used in the neural network are divided into training samples and test samples, and the quality of the training samples determines the prediction accuracy to a certain extent. If the training samples are not selec...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06G06K9/62G06N3/00G06N3/04G06N3/08
CPCG06Q10/063114G06Q50/06G06N3/006G06N3/08G06N3/045G06F18/214Y04S10/50Y02E40/70
Inventor 姜明新王文豪贾银洁王海燕
Owner HUAIYIN INSTITUTE OF TECHNOLOGY
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