CN105870972A - Intelligent control system of photovoltaic microgrid PWM (pulse-width modulation) inverter - Google Patents
Intelligent control system of photovoltaic microgrid PWM (pulse-width modulation) inverter Download PDFInfo
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- CN105870972A CN105870972A CN201610422868.XA CN201610422868A CN105870972A CN 105870972 A CN105870972 A CN 105870972A CN 201610422868 A CN201610422868 A CN 201610422868A CN 105870972 A CN105870972 A CN 105870972A
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- 238000005457 optimization Methods 0.000 claims description 12
- 239000004531 microgranule Substances 0.000 claims description 9
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- H02J3/383—
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/01—Arrangements for reducing harmonics or ripples
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/40—Arrangements for reducing harmonics
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Abstract
The invention discloses an intelligent control system of a photovoltaic microgrid PWM (pulse-width modulation) inverter in the field of photovoltaic power generation. The intelligent control system comprises an outer ring voltage controller, wherein the signal output end of the outer ring voltage controller is connected with the signal input end of an inner ring current controller; the signal output end of the inner ring current controller is connected with the signal input end of a disturbance controller; the signal output end of the disturbance controller is connected with the signal input end of a reference coordinate system conversion module; the signal output end of the reference coordinate system conversion module is connected with the signal input end of a PWM inverter; the signal output end of the reference coordinate system conversion module is also in feedback connection with the signal input end of the inner ring current controller; the PWM inverter is connected into a power grid through a rear-mounted filter; the signal output end of the rear-mounted filter is also in feedback connection with the signal input end of the reference coordinate system conversion module. The intelligent control system has the advantages that the electric energy quality of the photovoltaic power generation is improved; the utilization rate of the photovoltaic microgrid electric energy is improved; the electric energy waste is reduced; the intelligent control system can be used in photovoltaic power generation.
Description
Technical field
The present invention relates to a kind of photovoltaic control system, particularly to a kind of photovoltaic inverter control system.
Background technology
In recent years, the energy internet development with intelligent grid, distributed energy as framework is rapid, and photovoltaic microgrid is at electric power
In supply, role gradually highlights, and increasing photovoltaic micro-grid power generation system is linked in electrical network, also to photovoltaic generation
Cutting-in control technology has had higher requirement, and before photovoltaic micro-grid connection, the electric energy guarantee of outputting high quality is grid-connected to electrical network
Adverse effect minimum.In order to efficiently complete photovoltaic micro-grid connection, and effectively reduce the combining inverter impact to electrical network, some
Advanced combining inverter intelligent control method has become urgent demand.
At present, double-loop control is a kind of mode commonly used in combining inverter, and this control method is at voltage
Increase a current inner loop in ring, the dynamic responding speed of system can be significantly improved in this way, cut down load timely
The impact that disturbance causes, but system is the best to the inhibition of nonlinear load disturbance, thus cause combining inverter harmonic wave
And DC component inhibition is limited.
Summary of the invention
It is an object of the invention to provide the intelligence control system of a kind of photovoltaic microgrid PWM inverter, to solve existing harmonic wave
And the problem low to the effect of the suppression of nonlinear load disturbance in DC component process of inhibition, thus photovoltaic generation is greatly improved
The quality of power supply, improve photovoltaic microgrid utilization rate of electrical, reduce waste of energy.
The object of the present invention is achieved like this: the intelligence control system of a kind of photovoltaic microgrid PWM inverter, including:
Reference frame modular converter, for controlling PWM inverter output electric current, carries out d-q coordinate transform by dynamic coordinate system and turns
Changing d-q reference frame into, d axle is used for controlling active power and PWM inverter DC terminal voltage, and q axle is used for controlling idle
Power and grid-connected support voltage；
Outer shroud voltage controller, utilize PI control method respectively to gaining merit based on d-q reference frame, reactive power, PWM inverse
Become device DC voltage and grid-connected support voltage is adjusted controlling；
Internal ring current controller, utilizes artificial neural network accurately to control output electric current when PWM inverter is incorporated into the power networks, presses down
DC component processed；
Disturbance controller, carrys out the Voltage unbalance caused by control and compensation grid disturbances by P control method；
Postfilter, suppresses, with inductance capacitance hybrid filter, the higher harmonic components that PWM inverter produces；
The signal output part of described outer shroud voltage controller is connected with the signal input part of internal ring current controller, interior circular current control
The signal output part of device processed is connected with the signal input part of disturbance controller, and the signal output part of disturbance controller is joined through d-q
After examining coordinate system inverse transformation, the signal input part with PWM inverter is connected, and in check line voltage component passes through phase delay
With phase calculation after d-q reference frame converts with the signal input part feedback link of disturbance controller, in check electricity
Net current component passes through the phase delay signal input part feedback link through d-q reference frame Yu internal ring current controller,
Described PWM inverter accesses electrical network through postfilter, the signal output part of postfilter also with reference frame modulus of conversion
The signal input part feedback link of block.
As the further restriction of the present invention, the input of described internal ring current controller is 4 input quantities, respectively d axle
The error of electric current, the error intergal of d shaft current, the error of q shaft current and the error intergal of q shaft current；Interior circular current controls
Device is output as 2 outputs, the control voltage of respectively d axle and the control voltage of q axle.
As the further restriction of the present invention, described postfilter is through phase delay module, voltage phase angle computing module
Being connected with reference frame modular converter, component of voltage is connected with disturbance controller after d-q reference frame is changed, rearmounted filter
Ripple device is connected with reference frame modular converter through phase delay module, with electric current after the conversion of current component d-q reference frame
Controller is connected.
As the further restriction of the present invention, the artificial neural network in described internal ring current controller possess non-linear soon
Speed optimization neural network ONLINE RECOGNITION self-learning function, this function utilizes particle swarm optimization algorithm to realize, self study process mesh
Scalar functions is defined as: the square value sum of d-q shaft current error and error intergal is minimum.
As the further restriction of the present invention, described particle swarm optimization algorithm is realized by below equation:
Wherein, w is inertia weight, c1And c2It is respectively cognitive aceleration pulse and society's aceleration pulse, rand1And rand2It it is two
Random number between [0 1]；xiPosition for i-th microgranule；xpThe desired positions lived through by this microgranule；xgFor colony
The desired positions that all microgranules live through；viFor particle speed, this limited speed is in vimin≤vi≤vimax.
As the further restriction of the present invention, the voltage caused by described disturbance controller control and compensation grid disturbances
Imbalance, described disturbance controller input quantity is d-q axle electrical network virtual voltage, electrical network nominal voltage, and controls voltage.
Compared with prior art, the beneficial effects of the present invention is, the present invention utilizes artificial neural network technology to control
Output electric current when grid-connected inverters runs, and artificial neural-network control device online intelligent recognition self study process is by grain
Subgroup optimized algorithm realizes；Neural Network Online identification self study setting controller and outer ring controller are combined with each other, altogether
The same output affecting system, thus ensure that system output waveform has good error to follow the tracks of ability, have again and the most dynamically ring
Answer performance, the quality of power supply of photovoltaic generation is greatly improved, improve photovoltaic microgrid utilization rate of electrical, decrease waste of energy.
The present invention can be used in photovoltaic generation.
Accompanying drawing explanation
Fig. 1 is control principle block diagram of the present invention.
Fig. 2 is internal ring current controller schematic diagram based on artificial neural network in the present invention.
Fig. 3 is Neural Network Self-learning flow chart based on particle swarm optimization algorithm in the present invention.
Fig. 4 is disturbance controller schematic diagram in the present invention.
Fig. 5 is the harmonic component inhibition comparison diagram of the present invention and conventional photovoltaic inverter control method.
Detailed description of the invention
The intelligence control system of a kind of photovoltaic microgrid PWM inverter as shown in Figure 1, including:
Reference frame modular converter, for controlling PWM inverter output electric current, carries out d-q coordinate transform by dynamic coordinate system and turns
Changing d-q reference frame into, d axle is used for controlling active power and PWM inverter DC terminal voltage, and q axle is used for controlling idle
Power and grid-connected support voltage；
Outer shroud voltage controller, utilize PI control method respectively to gaining merit based on d-q reference frame, reactive power, PWM inverse
Become device DC voltage and grid-connected support voltage is adjusted controlling；
Internal ring current controller, utilizes artificial neural network accurately to control output electric current when PWM inverter is incorporated into the power networks, presses down
DC component processed, the input of described internal ring current controller is 4 input quantities, the error of respectively d shaft current, d shaft current
Error intergal, the error of q shaft current and the error intergal of q shaft current；Internal ring current controller is output as 2 outputs,
Be respectively d axle controls voltage and the control voltage of q axle, and the artificial neural network in described internal ring current controller possesses non-thread
Property rapid Optimum Neural Network Online identification self-learning function, this function utilizes particle swarm optimization algorithm to realize, self study
Journey object function is defined as: the square value sum of d-q shaft current error and error intergal is minimum, and described particle swarm optimization algorithm leads to
Cross below equation to realize:
Wherein, w is inertia weight, c1And c2It is respectively cognitive aceleration pulse and society's aceleration pulse, rand1And rand2It it is two
Random number between [0 1]；xiPosition for i-th microgranule；xpThe desired positions lived through by this microgranule；xgFor colony
The desired positions that all microgranules live through；viFor particle speed, this limited speed is in vimin≤vi≤vimax；
Disturbance controller, comes the Voltage unbalance caused by control and compensation grid disturbances, described disturbance control by P control method
Voltage unbalance caused by device control and compensation grid disturbances processed, described disturbance controller input quantity is that d-q axle electrical network is real
Border voltage, electrical network nominal voltage, and control voltage；
Postfilter, suppresses, with inductance capacitance hybrid filter, the higher harmonic components that PWM inverter produces；
The signal output part of described outer shroud voltage controller is connected with the signal input part of internal ring current controller, interior circular current control
The signal output part of device processed is connected with the signal input part of disturbance controller, and the signal output part of disturbance controller is joined through d-q
After examining coordinate system inverse transformation, the signal input part with PWM inverter is connected, and in check line voltage component passes through phase delay
With phase calculation after d-q reference frame converts with the signal input part feedback link of disturbance controller, in check electricity
Net current component passes through the phase delay signal input part feedback link through d-q reference frame Yu internal ring current controller,
Described PWM inverter accesses electrical network through postfilter, the signal output part of postfilter also with reference frame modulus of conversion
The signal input part feedback link of block, described postfilter is sat with reference through phase delay module, voltage phase angle computing module
Mark system modular converter is connected, and component of voltage is connected with disturbance controller after d-q reference frame is changed, and postfilter is through phase
Position time delay module is connected with reference frame modular converter, with current controller phase after the conversion of current component d-q reference frame
Even.
The present invention utilizes interior circular current to control and outer shroud voltage-controlled double loop Compound Control Strategy controls inverse simultaneously
Become grid-connected current when device runs and voltage；Wherein electric current controls to be realized by current controller based on artificial neural network,
This nerve network controller basic structure proposed by the invention is as in figure 2 it is shown, controller input is the error of d-q shaft current
And error intergal, it is output as d-q axle and controls voltage.The present invention proposes to utilize particle swarm optimization algorithm non-linear the most excellent to realize
Changing Neural Network Online identification self study process, this nerve network controller self study process goal function is defined as: d-q axle
The square value sum of current error and error intergal is minimum.
Particle group optimizing (Particle Swarm Optimization, PSO) algorithm is to see according to animal social behavior
A kind of nonlinear optimization algorithm examining Theoretical Evolution and come；PSO algorithm based on colony, according to the fitness of environment by group
The region that individuality in body moves to；But it does not uses evolutive operators to individuality, but regard each individuality as multidimensional
A microgranule not having volume in search volume, with certain speed flight in search volume, this speed is according to it originally
The flying experience of body and the flying experience of companion dynamically adjust；Renewal equation is as follows:
Wherein, w is inertia weight, c1And c2It is respectively cognitive aceleration pulse and society's aceleration pulse, rand1And rand2It it is two
Random number between [0 1]；xiPosition for i-th microgranule；xpThe desired positions lived through by this microgranule；xgFor colony
The desired positions that all microgranules live through；viFor particle speed, this limited speed is in vimin≤vi≤vimax.
PSO algorithm starts and the parametric procedure of optimized artificial neural network is as it is shown on figure 3, according to different its exterior environment
Arrange, adjust through a series of News Search, can quickly obtain optimized neural network parameter and carry out optimization neural network
The control effect of current controller.
As shown in Figure 4, proposition disturbance controller of the present invention carrys out compensation network voltage disturbance as predistorter and is drawn
The Voltage unbalance risen, it is actual defeated with nominal voltage and current controller that disturbance controller input quantity is respectively d-q axle electrical network
The d-q axle gone out controls voltage.
The intelligent control scheme utilizing the present invention to propose can solve existing PWM inverter harmonic wave and DC component suppressed
Problem low to the effect of the suppression of nonlinear load disturbance in journey, compares with traditional inverter control method, such as Fig. 5 institute
Showing, the system schema that the present invention proposes quickly can determine the change of phase by responsive electricity grid, shields the noise in line voltage and high order
Harmonic wave, thus the quality of power supply of photovoltaic generation is greatly improved.
The invention is not limited in above-described embodiment, on the basis of technical scheme disclosed by the invention, the skill of this area
Art personnel are according to disclosed technology contents, it is not necessary to some of which technical characteristic just can be made one by performing creative labour
A little replacements and deformation, these are replaced and deformation is the most within the scope of the present invention.
Claims (6)
1. the intelligence control system of a photovoltaic microgrid PWM inverter, it is characterised in that including:
Reference frame modular converter, for controlling PWM inverter output electric current, carries out d-q coordinate transform by dynamic coordinate system and turns
Changing d-q reference frame into, d axle is used for controlling active power and PWM inverter DC terminal voltage, and q axle is used for controlling idle
Power and grid-connected support voltage；
Outer shroud voltage controller, utilize PI control method respectively to gaining merit based on d-q reference frame, reactive power, PWM inverse
Become device DC voltage and grid-connected support voltage is adjusted controlling；
Internal ring current controller, utilizes artificial neural network accurately to control output electric current when PWM inverter is incorporated into the power networks, presses down
DC component processed；
Disturbance controller, carrys out the Voltage unbalance caused by control and compensation grid disturbances by P control method；
Postfilter, suppresses, with inductance capacitance hybrid filter, the higher harmonic components that PWM inverter produces；
The signal output part of described outer shroud voltage controller is connected with the signal input part of internal ring current controller, interior circular current control
The signal output part of device processed is connected with the signal input part of disturbance controller, and the signal output part of disturbance controller is joined through d-q
After examining coordinate system inverse transformation, the signal input part with PWM inverter is connected, and in check line voltage component passes through phase delay
With phase calculation after d-q reference frame converts with the signal input part feedback link of disturbance controller, in check electricity
Net current component passes through the phase delay signal input part feedback link through d-q reference frame Yu internal ring current controller,
Described PWM inverter accesses electrical network through postfilter, the signal output part of postfilter also with reference frame modulus of conversion
The signal input part feedback link of block.
The intelligence control system of a kind of photovoltaic microgrid PWM inverter the most according to claim 1, it is characterised in that described
The input of internal ring current controller is 4 input quantities, the error of respectively d shaft current, the error intergal of d shaft current, q shaft current
Error and the error intergal of q shaft current；Internal ring current controller is output as 2 outputs, the control electricity of respectively d axle
Pressure and the control voltage of q axle.
The intelligence control system of a kind of photovoltaic microgrid PWM inverter the most according to claim 1 and 2, it is characterised in that institute
State postfilter to be connected with reference frame modular converter through phase delay module, voltage phase angle computing module, component of voltage
Being connected with disturbance controller after d-q reference frame is changed, postfilter turns with reference frame through phase delay module
Die change block is connected, and is connected with current controller after the conversion of current component d-q reference frame.
The intelligence control system of a kind of photovoltaic microgrid PWM inverter the most according to claim 1 and 2, it is characterised in that institute
State the artificial neural network in internal ring current controller and possess non-linear rapid Optimum Neural Network Online identification self-learning function,
This function utilizes particle swarm optimization algorithm to realize, and self study process goal function is defined as: d-q shaft current error and error value product
The square value sum divided is minimum.
The intelligence control system of a kind of photovoltaic microgrid PWM inverter the most according to claim 4, it is characterised in that described
Particle swarm optimization algorithm is realized by below equation:
Wherein, w is inertia weight, c1And c2It is respectively cognitive aceleration pulse and society's aceleration pulse, rand1And rand2It it is two
Random number between [0 1]；xiPosition for i-th microgranule；xpThe desired positions lived through by this microgranule；xgFor colony
The desired positions that all microgranules live through；viFor particle speed, this limited speed is in vimin≤vi≤vimax.
The intelligence control system of a kind of photovoltaic microgrid PWM inverter the most according to claim 1 and 2, it is characterised in that institute
Stating the Voltage unbalance caused by disturbance controller control and compensation grid disturbances, described disturbance controller input quantity is d-q
Axle electrical network virtual voltage, electrical network nominal voltage, and control voltage.
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Cited By (2)
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| CN113241807A (en) * | 2021-05-17 | 2021-08-10 | 中国南方电网有限责任公司 | Distributed photovoltaic inverter self-adaptive robust adjusting method for low-voltage treatment of power distribution network |
| CN116632926A (en) * | 2023-07-25 | 2023-08-22 | 苏州阿诗特能源科技有限公司 | Phase-locked grid-connected method based on communication |
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