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Extreme value tracking method of self-adaptive weighted modulation signal based on photovoltaic system

An adaptive weight and adaptive weighting technology, which is applied in photovoltaic power generation, control/regulation systems, and electrical variable adjustment, to achieve the effects of preventing misjudgment, speeding up dynamic response time, and accurately tracking

Active Publication Date: 2019-06-21
SHANGHAI MARITIME UNIVERSITY
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Problems solved by technology

The contradiction between system tracking dynamic response and power oscillation is not fundamentally resolved

Method used

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  • Extreme value tracking method of self-adaptive weighted modulation signal based on photovoltaic system
  • Extreme value tracking method of self-adaptive weighted modulation signal based on photovoltaic system
  • Extreme value tracking method of self-adaptive weighted modulation signal based on photovoltaic system

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Embodiment Construction

[0023] attached figure 1 It is a system block diagram of the present invention based on the extreme value tracking method of the adaptive weighted modulation signal of the photovoltaic system, with figure 2 It is a system flow chart of the present invention. The implementation of the method mainly has the following five steps:

[0024] Step 1: Obtain the real-time output voltage and current of the system to obtain the real-time output power P of the system;

[0025] Step 2: Apply the modulation signal asin(wt) of the adaptive weight to the output power P, a is the adaptive weight of the modulation signal, adjust the size of the adaptive weight a by determining the real-time working position of the photovoltaic system, when the photovoltaic system When the operating point is far from the maximum power point, use a larger modulation signal weight to track the maximum power point to speed up the dynamic response time. When the photovoltaic system operating point is near or at ...

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Abstract

The invention discloses an extreme value tracking method of a self-adaptive weighted modulation signal based on a photovoltaic system. The method comprises the steps of obtaining system output power P; applying a modulation signal with an adaptive weight to the output power P to obtain a power ripple Rho; after passing through a high-pass filter, multiplying the power ripple by a modulation signalwith a self-adaptive weight value to complete a demodulation process, to obtain the ripple Zeta; after an alternating current part signal of the signal Zeta is filtered out through the low-pass filter, outputting a reference value of the duty ratio through an integrator, to control the system to track the maximum power. The contradiction between the steady-state precision and the dynamic trackingspeed in maximum power tracking control of the photovoltaic system is balanced, and the method can be widely applied to control of the photovoltaic system and is not limited to the photovoltaic system.

Description

[0001] Technical field: [0002] The invention relates to the fields of photovoltaic power generation technology, maximum power tracking technology, automatic control technology and the like, and in particular to an extreme value tracking method based on an adaptive weighted modulation signal of a photovoltaic system. [0003] Background technique: [0004] With the rapid development of the economy, the shortage of traditional energy sources such as coal and oil has become increasingly serious, and the environmental pollution has become increasingly serious. It is necessary to vigorously develop and apply various new renewable energy sources. Compared with the lifespan of the sun, solar energy can be said to be inexhaustible. Relevant authoritative departments predict that by 2050, 22% of global energy output will come from solar energy, of which more than 50% of solar energy output will come from photovoltaic system power generation. Therefore, vigorously developing photovolt...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05F1/67
CPCY02E10/56
Inventor 程宇涛王天真姚君琦谢涛张米露
Owner SHANGHAI MARITIME UNIVERSITY
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