CN108346811A - Active tracking Optimal Control System for grid type solid oxide fuel cell - Google Patents
Active tracking Optimal Control System for grid type solid oxide fuel cell Download PDFInfo
- Publication number
- CN108346811A CN108346811A CN201810082385.9A CN201810082385A CN108346811A CN 108346811 A CN108346811 A CN 108346811A CN 201810082385 A CN201810082385 A CN 201810082385A CN 108346811 A CN108346811 A CN 108346811A
- Authority
- CN
- China
- Prior art keywords
- fuel cell
- solid oxide
- oxide fuel
- value
- time point
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 239000000446 fuel Substances 0.000 title claims abstract description 142
- 239000007787 solid Substances 0.000 title claims abstract description 83
- 238000005070 sampling Methods 0.000 claims description 46
- 238000013461 design Methods 0.000 claims description 24
- 239000011159 matrix material Substances 0.000 claims description 24
- 239000013598 vector Substances 0.000 claims description 24
- 230000006870 function Effects 0.000 claims description 21
- 238000000034 method Methods 0.000 claims description 17
- 238000004519 manufacturing process Methods 0.000 claims description 12
- 238000005457 optimization Methods 0.000 claims description 10
- 238000012546 transfer Methods 0.000 claims description 10
- 230000005611 electricity Effects 0.000 claims description 7
- 230000003044 adaptive effect Effects 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 claims description 6
- 230000001681 protective effect Effects 0.000 claims description 5
- 239000000126 substance Substances 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims description 3
- XCWPUUGSGHNIDZ-UHFFFAOYSA-N Oxypertine Chemical compound C1=2C=C(OC)C(OC)=CC=2NC(C)=C1CCN(CC1)CCN1C1=CC=CC=C1 XCWPUUGSGHNIDZ-UHFFFAOYSA-N 0.000 claims 1
- 238000005516 engineering process Methods 0.000 description 4
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 3
- 230000033228 biological regulation Effects 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000002485 combustion reaction Methods 0.000 description 3
- 230000006378 damage Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 3
- 239000001257 hydrogen Substances 0.000 description 3
- 229910052739 hydrogen Inorganic materials 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 230000001052 transient effect Effects 0.000 description 2
- 206010008190 Cerebrovascular accident Diseases 0.000 description 1
- 208000006011 Stroke Diseases 0.000 description 1
- 208000027418 Wounds and injury Diseases 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001447 compensatory effect Effects 0.000 description 1
- 230000008602 contraction Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000005034 decoration Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- XLYOFNOQVPJJNP-ZSJDYOACSA-N heavy water Substances [2H]O[2H] XLYOFNOQVPJJNP-ZSJDYOACSA-N 0.000 description 1
- 235000003642 hunger Nutrition 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000002427 irreversible effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 150000002927 oxygen compounds Chemical class 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 239000000700 radioactive tracer Substances 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 230000037351 starvation Effects 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M8/00—Fuel cells; Manufacture thereof
- H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
- H01M8/04298—Processes for controlling fuel cells or fuel cell systems
- H01M8/04992—Processes for controlling fuel cells or fuel cell systems characterised by the implementation of mathematical or computational algorithms, e.g. feedback control loops, fuzzy logic, neural networks or artificial intelligence
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M8/00—Fuel cells; Manufacture thereof
- H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
- H01M8/04298—Processes for controlling fuel cells or fuel cell systems
-
- H02J3/387—
-
- 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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
-
- 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
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/30—Hydrogen technology
- Y02E60/50—Fuel cells
Landscapes
- Engineering & Computer Science (AREA)
- Fuel Cell (AREA)
- Life Sciences & Earth Sciences (AREA)
- Manufacturing & Machinery (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
- Chemical & Material Sciences (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Electrochemistry (AREA)
- General Chemical & Material Sciences (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Automation & Control Theory (AREA)
- Computing Systems (AREA)
- Evolutionary Computation (AREA)
- Fuzzy Systems (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Power Engineering (AREA)
Abstract
The invention discloses the active tracking Optimal Control Systems for grid type solid oxide fuel cell, including setting value optimizer SPO, voltage source inverter VSI, solid oxide fuel cell SOFC systems and L1 MPC tracking control units.Setting value optimizer receives the active power output order of dispatching of power netwoks, and solves optimal voltage and current value according to the instruction and SOFC mathematics model of stable state, which makes thermal power of the system consumption in internal resistance minimum.Voltage source inverter is using above-mentioned optimal current as its reference value so that the output current of SOFC tracks the reference value.L1 MPC tracking control units are used as using above-mentioned optimal voltage value and SOFC optimum fuel utilization rates with reference to being worth, by controlling anode fuel flow and cathode air flow, by the output voltage of SOFC and fuel availability stability contorting in its reference value.
Description
Technical field
The invention belongs to Thermal power engneerings and automation field, are related to having for solid oxide fuel cell (SOFC)
Work(tracks regulation and control system, especially a kind of to be combined with L1-MPC control algolithms using setting value optimization, for SOFC
The Optimal Control System of active power tracking.
Background technology
Solid oxide fuel cell (Solid Oxide Fuel Cell, abbreviation SOFC) is as a kind of novel energy
Converting apparatus, due to the high efficiency of its chemical energy-electric energy conversion, it is considered to be future can be combined with hydrogen energy storage technology, tool
There is the distributed generation technology of broad prospect of application.
In SOFC main bodys, fuel and air are passed into the anode and cathode of battery, the electricity occurred inside SOFC respectively
Chemical reaction：
Anode:2H2+2O2-→2H2O+4e-
Cathode:O2+4e-→2O2-
Commercial solid oxide fuel cell SOFC systems mainly use two kinds of operational modes at present：Isolated operation and
It is incorporated into the power networks.Isolated operation refers to that load is directly connected on the output end of SOFC and obtains load institute using stable state device or inverter
The direct current or alternating current needed.The cardinal principles of grid type SOFC systems as shown in Figure 1, the system by SOFC main bodys, inverter with
And the part such as SOFC controllers forms.Inverter connects SOFC and power grid, and the DC conversion that SOFC is generated is needed for power grid
Alternating current, while by control electric current size indirect control SOFC external output power.The function of SOFC controllers is
The instruction for generating fuel and air door enters the fuel flow rate and air mass flow of SOFC by controlling opening of valve control, from
And the output voltage of SOFC is adjusted, and maintain the stabilization of fuel availability.The existing SOFC that is incorporated into the power networks passes through inversion
Device is connected with power grid, and uses each parameter such as voltage, electric current, power that stable single operating point is kept to run plan in operation mostly
Slightly.
In fact, rapidities of the SOFC due to its active power regulation, the peaking power source being highly suitable as in micro-capacitance sensor,
To compensatory pause performance source if photovoltaic, wind-powered electricity generation etc. are to frequency fluctuation caused by power grid.Using SOFC as micro-capacitance sensor peak regulation electricity
Source proposes new challenge to SOFC Control System Designs compared to the SOFC systems of traditional single operating point operation.First,
SOFC is as micro-capacitance sensor peaking power source, it is necessary to have and instruct the ability quickly tracked to dispatching the active power of system.The
Two, dynamic characteristic presentation is very strong non-linear, this makes traditional linear PID controllers based on either simplex condition point design
There is showing for performance decline in (Proportion Integration Differentiation. proportional-integral derivative controllers)
As to ensure safety and the stability of system operation, it is necessary to which the more conservative control parameter design of design, this is quick with power
The requirement of tracking contradicts.Easily there is the fuel shortage situation of transient state in SOFC variable parameter operations in third, to fuel electricity
Pond ontology causes permanent irreversible damage, reduces its service life.4th, in variable parameter operation, it is desirable to which SOFC can have to the greatest extent
High economy is measured, that is, wishes that the power consumed in its internal resistance is small as possible.
Invention content
The technical problem to be solved by the present invention is in order to overcome defect present in existing SOFC control systems technology, carry
For one kind when meeting SOFC as micro-capacitance sensor peaking power source active power tracer request, and SOFC is fired at runtime
Expect the Control System Design scheme of utilization rate protection and operating condition optimization.
The active tracking control system of grid type solid oxide fuel cell (SOFC) proposed by the invention includes setting
Set-point Optimizer (SPO, Set Points Optimizer), voltage source inverter (VSI, Voltage Source
Inverter includes controller in inverter), (the present invention is mainly suitable for simultaneously for solid oxide fuel cell SOFC systems
Net type) and L1 it is adaptive-model prediction (L1-MPC, L1adaptive-Model Predictive Controller) tracking
The parts such as controller.
The setting value optimizer SPO receives the active power output order of power network dispatching system, and is asked according to the instruction
The optimal value of voltage, the optimal value of electric current and solid oxide fuel cell SOFC system optimum fuel utilization rates are taken, and will
The optimal value and optimum fuel utilization rate of voltage are transmitted to L1-MPC tracking control units, and the optimal value of electric current is transmitted to voltage source
The optimal value of inverter VSI, the voltage and current make solid oxide fuel cell SOFC system consumptions in internal resistance
Thermal power is minimum；The power network dispatching system is the system that implementation commander, supervision and management power generation run function in power grid.
Power network dispatching system is distributed into power grid power generation task to each electric power and is given birth to according to the electricity consumption total load of power consumer in power grid
Unit is produced, to keep the balance of power generation and consumption.
Voltage source inverter VSI is using the optimal value of the setting value optimizer SPO electric currents acquired as voltage source inverter
The reference value of VSI output currents so that the output current of solid oxide fuel cell SOFC systems tracks the reference value；
L1-MPC tracking control units are most preferably fired using the optimal value and solid oxide fuel cell SOFC systems of voltage
Expect that utilization rate is used as with reference to being worth, by the anode fuel flow and cathode air that control solid oxide fuel cell SOFC systems
Flow, by the output voltage of solid oxide fuel cell SOFC systems and fuel availability stability contorting in its reference value.It examines
Consider difference of above-mentioned SPO, VSI, L1-MPC tracking control unit on the sampling time, while using protection in the controls
Logic, to prevent fuel cell from the fuel shortage of short time occur.
The setting value optimizer by solve following optimization problem obtain the optimal value of voltage, the optimal value of electric current and
Solid oxide fuel cell SOFC system optimum fuel utilization rates：
s.t.Φ(Vout, I)=0
VoutI=Pref
Fu=Fu *
Wherein, s.t. full name are subject to, indicate the constraint in optimization problem, Vout,refFor the optimal value of voltage,
IrefFor the optimal value of electric current, Φ ()=0 is the steady-state model of solid oxide fuel cell SOFC systems；VoutFor solid oxygen
Compound fuel cell SOFC system output voltages, I are solid oxide fuel cell SOFC system output currents, subscript ref generations
The corresponding reference value of table, qchemThe chemical energy released by the fuel of solid oxide fuel cell SOFC system consumptions, PrefFor
Electric network active instructs, FuFor solid oxide fuel cell SOFC system fuel utilizations,For solid oxide fuel cell
SOFC system optimum fuel utilization rates.
The control that the L1-MPC tracking control units obtain solid oxide fuel cell SOFC systems by following formula inputs
Vector：
WhereinFor the control input vector of solid oxide fuel cell SOFC systems,And Mair
The respectively fuel flow rate and air mass flow of solid oxide fuel cell SOFC systems,For L1 compensation control components,
uMPC(t) it is MPC tracing control components, L1 compensation control components are by an output feedback L1 compensators calculating acquisition, MPC tracking
It controls component and acquisition is calculated by a MPC controller.
The design method of the output feedback L1 compensators includes the following steps：
Step A1：The steady running condition point of optional solid oxide fuel cell SOFC systems, is rung by Open loop step
It should test and linear least squares method method, establish the dynamic model of following solid oxide fuel cell SOFC systems：
Y (s)=G (s) (u (s)+σ (s)),
Wherein, y (s), u (s), σ (s) are respectively signal vector y (t), the Laplace transform of u (t), σ (t), and y (t)=
[Vout,Fu]TFor the output quantity of solid oxide fuel cell SOFC systems, σ (t) is solid oxide fuel cell SOFC systems
Lump indeterminate, G (s) is 2 × 2 transfer function matrix；
Step A2：The following output fallout predictor of design：
Wherein subscript i and j representation vectors or the element numbers of matrix, n are the dimension of transfer function matrix G (s), Gi,i(s)
Corresponding transmission function, G are arranged for G (s) i rows ii,j(s) it is that G (s) i rows j arranges corresponding transmission function,To export fallout predictor
Prediction output vectorI-th of element, ui(s),uj(s) i-th of element of input vector u (s) and the in order to control respectively
J element,For the estimated value of solid oxide fuel cell SOFC system lump indeterminates；ForI-th
A element.
Step A3：Design the estimated value more new law of following indeterminate：
Sign is sign function, and t indicates time signal, and Proj is projection operator, and Γ is designing gain, gi,iTo transmit letter
Number Gi,i(s) steady-state gain,yi(t) i-th of element for being output signal y (t),For
Corresponding time-domain signal,ForTo the derivative of time；
Step A4：Calculate L1 adaptive equalization components：
C (s) is a low-pass filter vector with control input vector u with same dimension, Ci(s) it is the of C (s)
I element,WithRespectivelyI-th of element and j-th of element,ForLaplce
Transformation.
The design method of the MPC controller includes the following steps：
Step B1：Convert transfer function matrix G (s) described in step A1 to following equivalent separate manufacturing firms mould
Type：
Y (k)=cx (k),
X (k+1)=Ax (k)+Bu (k)；
X (k), y (k), u (k) indicate respectively the quantity of state at separate manufacturing firms model present sample time point, output quantity,
Input quantity, x (k+1) indicate separate manufacturing firms model in the quantity of state of next sampling time point, and A, B, c is that discrete state is empty
Between model sytem matrix；
Step B2：Following on-line optimization problem is solved, obtained solution sequence is an optimal control sequence：
U (k | k), u (k+1 | k) ..., u (k+M+1 | k),
ymin≤y(k+m|k)≤ymax
Wherein k represents present sample time point, and N is prediction time domain, M time domains in order to control, umin、umaxRespectively input is permitted
Perhaps minimum value and maximum value, ymin、ymaxThe minimum value and maximum value respectively exported, L are so that matrix (A+Lc) is all
The real part of characteristic value is less than 1 Arbitrary Matrix, yrefReference value for solid oxide fuel cell SOFC system outputs y (walks
The reference value of y in rapid A1), μrefFor in separate manufacturing firms model with yrefCorresponding stable state input, μref=(c (I-A)- 1B)-1yref,ForIn the value at present sample time point, Q, R are the weight matrix of design, u (k | k), u (k+1 |
K) ..., u (k+M+1 | k) indicates the PREDICTIVE CONTROL amount at present sample time point respectively, and present sample time point is to next sampling
The PREDICTIVE CONTROL amount ... at time point, PREDICTIVE CONTROL amount of the present sample time point to following the M+1 sampling time point；
Y (k+m | k) indicate prediction output quantity of the present sample time point to following m-th of sampling time point,For
Observations of the system state amount x at present sample time point；For system state amount x upper sampling time point observation
Value, u (k-1) are that the control of upper sampling time point inputs, and y (k-1) is the output of upper sampling time point,WithRespectively current sampling point to the predicted value of following m-th of sampling time point observation with
The predicted value of following the m-1 sampling time point observation, u (k+m | k) and u (k+m-1 | k) are respectively current sampling point to not
Carry out the PREDICTIVE CONTROL amount of the PREDICTIVE CONTROL amount and following the m-1 sampling time point of m-th of sampling time point,
Step B3：MPC tracing control components use first element of the controlled quentity controlled variable sequence solved in step B2, i.e.,：
uMPC(k)=u (k | k)；
Within present sample time point to the time between next sampling time point, u is takenMPC(t)=uMPC(k)。
Present system uses following relay protective scheme：When setting value optimizer SPO acquires the optimal value and electricity of new voltage
When the optimal value of stream, the optimal value of the voltage is transmitted at once in L1-MPC tracking control units, and the optimal value of electric current, which is temporarily stored into, to be set
Be not updated at once in voltage source inverter VSI in the memory of Set-point Optimizer SPO, until L1-MPC tracking control units more
After its new MPC tracing control component, then the optimal value of electric current is updated in voltage source inverter VSI.
The present invention has advantageous effect below：
1. the present invention provides a kind of with good active power tracking performance, and can carry out fuel profit in operation
It is protected with rate, prevents fuel shortage, and take into account the grid type SOFC Control System Design schemes of SOFC performance driving economies,
It disclosure satisfy that requirement when grid type SOFC participates in peaking operation.
L1 self adaptive controls are combined by 2.L1-MPC controllers with MPC controls, have both solved SOFC in variable parameter operation
When nonlinear problem, while convenient advantage is constrained using MPC processing systems, to combustions of the SOFC in variable working condition transient process
Each key parameters such as material utilization rate are limited, and ensure that the safety of system.Wherein, output of the invention feedback L1 is adaptive
Controller is to be based on existing feedback of status L1 adaptive controllers, is changed for immesurable the beneficial of system progress of internal state
Into.
3. the setting value optimizer (SPO), voltage source inverter (VSI) and L1-MPC tracking control units in system are in object
It can be achieved to work independently from each other in reason, reduce the coupling of control system, and the requirement to unitary part computing capability is not
It is high.
Description of the drawings
The present invention is done with reference to the accompanying drawings and detailed description and is further illustrated, it is of the invention above-mentioned or
Otherwise advantage will become apparent.
Fig. 1 is grid type SOFC systematic schematic diagrams.
Fig. 2 is the active tracking Optimal Control System principle frame for grid type solid oxide fuel cell SOFC systems
Figure.
Fig. 3 is fuel availability relay protective scheme figure.
Fig. 4 is SOFC output powers and voltage curve.
Fig. 5 is the electric current and fuel availability curve graph of SOFC.
Fig. 6 is the fuel and airflow rate curve figure of SOFC.
Specific implementation mode
The present invention will be further described with reference to the accompanying drawings and embodiments.
The invention discloses the active tracking Optimal Control System for grid type solid oxide fuel cell, the controls
The structure diagram of system processed is as shown in Figure 2.From a structural point, which is divided into two layers, and upper layer is setting value optimizer
SPO, lower layer are SOFC controllers (L1-MPC tracking control units are used in the present invention), solid oxide fuel cell SOFC systems
And voltage source inverter (wherein including VSI controllers).
The setting value optimizer SPO receives the active power output order of power network dispatching system, and is asked according to the instruction
The optimal value of voltage, the optimal value of electric current and solid oxide fuel cell SOFC system optimum fuel utilization rates are taken, and will
The optimal value and optimum fuel utilization rate of voltage are transmitted to L1-MPC tracking control units, and the optimal value of electric current is transmitted to voltage source
The optimal value of inverter VSI, the voltage and current make solid oxide fuel cell SOFC system consumptions in internal resistance
Thermal power is minimum；
Voltage source inverter VSI is using the optimal value of electric current as its reference value so that solid oxide fuel cell
The output current of SOFC systems tracks the reference value；
L1-MPC tracking control units are most preferably fired using the optimal value and solid oxide fuel cell SOFC systems of voltage
Expect that utilization rate is used as with reference to being worth, by the anode fuel flow and cathode air that control solid oxide fuel cell SOFC systems
Flow, by the output voltage of solid oxide fuel cell SOFC systems and fuel availability stability contorting in its reference value.It examines
Consider difference of above-mentioned SPO, VSI, L1-MPC tracking control unit on the sampling time, while using protection in the controls
Logic, to prevent fuel cell from the fuel shortage of short time occur.
The setting value optimizer by solve following optimization problem obtain the optimal value of voltage, the optimal value of electric current and
Solid oxide fuel cell SOFC system optimum fuel utilization rates：
s.t.Φ(Vout, I)=0
VoutI=Pref
Fu=Fu *
Wherein, Vout,refFor the optimal value of voltage, IrefFor the optimal value of electric current, Φ ()=0 is solid oxide fuel
The steady-state model of battery SOFC systems；VoutFor solid oxide fuel cell SOFC system output voltages, I is soild oxide
Fuel cell SOFC system output currents, subscript ref represent corresponding reference value, qchemFor solid oxide fuel cell SOFC
The chemical energy that the fuel of system consumption is released, PrefIt is instructed for electric network active, FuFor solid oxide fuel cell SOFC systems
Fuel availability,For solid oxide fuel cell SOFC system optimum fuel utilization rates.In general, it is less than 0.7 combustion
Material utilization rate means excessive waste of fuel, and the fuel availability more than 0.9 will produce so-called " fuel shortage (Fuel
Starvation permanent injury) " is generated to fuel cell.In view of above-mentioned two factor, at present for most of combustions
Expect for battery, generally will in operationIt is taken as 0.8.
Optimal voltage value V is obtained in setting value optimizerout,refAnd optimal current value IrefAfterwards, by Vout,refAndMake
It is passed to L1-MPC tracking control units for reference value, and by IrefIt is passed in VSI controllers as with reference to value.For VSI controllers,
It designs and may be used common PID control method, and simultaneously because the dynamic characteristic of VSI far faster than SOFC dynamic characteristic,
Therefore when carrying out SOFC controller designs, the influence that the dynamic of VSI systems generates it can be ignored.
The control that the L1-MPC tracking control units obtain solid oxide fuel cell SOFC systems by following formula inputs
Vector：
WhereinFor the control input vector of solid oxide fuel cell SOFC systems,And Mair
The respectively fuel flow rate and air mass flow of solid oxide fuel cell SOFC systems,For L1 compensation control components,
uMPC(t) it is MPC tracing control components, L1 compensation control components are by an output feedback L1 compensators calculating acquisition, MPC tracking
It controls component and acquisition is calculated by a MPC controller.
The design method of the output feedback L1 compensators includes the following steps：
Step A1：The steady running condition point of optional solid oxide fuel cell SOFC systems, is rung by Open loop step
It should test and linear least squares method method, establish the dynamic model of following solid oxide fuel cell SOFC systems：
Y (s)=G (s) (u (s)+σ (s)),
Wherein, y (s), u (s), σ (s) are respectively signal vector y (t), the Laplace transform of u (t), σ (t), and y (t)=
[Vout,Fu]TFor the output quantity of solid oxide fuel cell SOFC systems, σ (t) is solid oxide fuel cell SOFC systems
Lump indeterminate, G (s) are 2 × 2 transfer function matrix；
Step A2：The following output fallout predictor of design：
Wherein subscript i and j representation vectors or the element numbers of matrix, n are the dimension of transfer function matrix G (s), Gi,i(s)
Corresponding transmission function, G are arranged for G (s) i rows ii,j(s) it is the corresponding elements of G (s),To export the prediction output of fallout predictor
VectorI-th of element, ui(s),uj(s) i-th of element of input vector u (s) in order to control respectively, j-th of element,For the estimated value of solid oxide fuel cell SOFC system lump indeterminates；ForI-th of element.
Step A3：Design the estimated value more new law of following indeterminate：
Sign is sign function, and t indicates time signal, and Proj is projection operator, and Γ is designing gain, gi,iTo transmit letter
Number Gi,i(s) steady-state gain,yi(t) i-th of element for being output signal y (t),For
Corresponding time-domain signal,ForTo the derivative of time；
Step A4：Calculate L1 adaptive equalization components：
C (s) is a low-pass filter vector with control input vector u with same dimension, Ci(s) it is the of C (s)
I element,WithRespectivelyI-th of element and j-th of element,ForLaplce
Transformation.
The design method of the MPC controller includes the following steps：
Step B1：Convert transfer function matrix G (s) described in step A1 to following equivalent separate manufacturing firms mould
Type：
Y (k)=cx (k),
X (k+1)=Ax (k)+Bu (k)；
X (k), y (k), u (k) indicate respectively the quantity of state at separate manufacturing firms model present sample time point, output quantity and
Input quantity, x (k+1) indicate separate manufacturing firms model in the quantity of state of next sampling time point, and A, B, c is that discrete state is empty
Between model sytem matrix；
Step B2：Following on-line optimization problem is solved, obtained solution sequence is an optimal control sequence：
U (k | k), u (k+1 | k) ..., u (k+M+1 | k),
ymin≤y(k+m|k)≤ymax
Wherein k represents present sample time point, and N is prediction time domain, M time domains in order to control, umin、umaxRespectively input is permitted
Perhaps minimum and maximum value, ymin、ymaxThe minimum and maximum value respectively exported, L are so that matrix (A+Lc) all features
The real part of value is less than 1 Arbitrary Matrix, yrefFor the reference value of solid oxide fuel cell SOFC system outputs y, μrefFor from
Dissipate state-space model in yrefCorresponding stable state input,
μref=(c (I-A)-1B)-1yref,ForIn the value at present sample time point；
Q, R are weight matrix to be designed, u (k | k), u (k+1 | k) ..., u (k+M+1 | k) present sample is indicated respectively
The PREDICTIVE CONTROL amount at time point, present sample time point is to the PREDICTIVE CONTROL amount ... of next sampling time point, present sample time
PREDICTIVE CONTROL amount of the point to following the M+1 sampling time point；
Y (k+m | k) indicate prediction output quantity of the present sample time point to following m-th of sampling time point,For
Observations of the system state amount x at present sample time point；For system state amount x upper sampling time point observation
Value, u (k-1) are that the control of upper sampling time point inputs, and y (k-1) is the output of upper sampling time point,WithRespectively current sampling point to the predicted value of following m-th of sampling time point observation with
The predicted value of following the m-1 sampling time point observation, u (k+m | k) and u (k+m-1 | k) are respectively current sampling point to not
Carry out the PREDICTIVE CONTROL amount of the PREDICTIVE CONTROL amount and following the m-1 sampling time point of m-th of sampling time point；
Step B3：MPC tracing control components use first element of the controlled quentity controlled variable sequence solved in step B2, i.e.,：
uMPC(k)=u (k | k).
Within present sample time point to the time between next sampling time point, u is takenMPC(t)=uMPC(k)。
It is noted that in above-mentioned control system, since setting value optimizer, L1-MPC tracking control units, VSI be not using
The same sampling time, therefore when setting value optimizer provides new voltage and current reference value and gives lower layer's controller, L1-MPC
Controller is likely to be at the gap of double sampling.Since VSI is mostly Millisecond to the control characteristic of electric current, it is much smaller than L1-MPC
Sampling time and SOFC response time.It is quick that it is likely to occur solid oxide fuel cell SOFC system output currents at this time
Increase and SOFC the case where not yet fuel flow rate is adjusted, fuel shortage easily occurs and permanently can not to SOFC generations
Inverse damage.For this purpose, the present invention devises the relay protective scheme of control system, to prevent the above problem.
The relay protective scheme flow is as shown in figure 3, when setting value optimizer acquires new voltage reference value and current reference value
When, above-mentioned voltage reference value is transmitted at once in L1-MPC tracking control units, and current reference value is temporarily stored into setting value optimizer
Memory in, be not updated at once in voltage source inverter VSI, until L1-MPC tracking control units update its MPC tracking control
After component processed, then current reference value is updated in VSI.
Embodiment
Emulation experiment is carried out by taking certain 5KW grades of hydrogen fuel solid oxide fuel cell as an example herein, and illustrates this hair
Bright design method and embodiment.In order to keep the technical problem to be solved in the present invention, technical solution and advantageous effect more clear
Chu, below in conjunction with the accompanying drawings and specific embodiment is described in detail.
First in hydrogen flowing quantity MH2=1.296e-4mol/s, air mass flow MairThe corresponding stable states of=1.957e-4mol/s
Operating point carries out step response experiment, at this time corresponding Vout=163.8 (V), I=20 (A) use linear least squares method, obtain
The corresponding transfer function model of steady state condition point is：
The design parameter of L1-MPC controllers is：
Γ=1e5,C1(s)=C2(s)=0.01/ (s+0.01), Q=diag (5,10), R=diag (100,100),
Predict time domain N=50,
In view of the practical demand for security of SOFC systems, system output and input are respectively set as ymin=[100 0.72
]T,ymax=[150 0.88]T
umin=[1.0e-4 1.0e-4]T,umax=[2.55e-3 24.5e-3]T
In emulation experiment, it is assumed that the inlet pressure of cathode and an anode is 2atm, and the inlet temperature of fuel and air is equal
For 973K.
Respectively in t=100s, t=200s, t=300s, instruct difference step to P active powerref=3500W, Pref
=5000W, Pref=4250W.
The output power and output voltage of system are as shown in Figure 4.As seen from the figure, output power and voltage all reach in 50s
New steady state point is arrived.The performance proves that SOFC can compensate the production of the intermittent energy sources such as power grid apoplexy, light as peaking power source
Raw power swing.Fig. 5 shows the electric current and fuel availability of SOFC.Notice fuel availability FuEven if power is in t=
When 200s, i.e. electric current generate a wide range of step, still preferably maintain near optimal value 0.8.Corresponding is at this time
H2Flow rapid step under the action of L1-MPC controllers, responds the electric current of a wide range of step, to maintain fuel sharp
With rate (such as Fig. 6).It is visible in about 110s, 200s and 210s simultaneously, due to the effect of contraction of MPC controller, air stream
Amount is close to its lower limit (1.0e-4mol/s) and not out-of-limit, ensure that the safe operation of system.
It is specific real the present invention provides the active tracking Optimal Control System for grid type solid oxide fuel cell
Now there are many method of the technical solution and approach, the above is only a preferred embodiment of the present invention, it is noted that for this
For the those of ordinary skill of technical field, without departing from the principle of the present invention, several improvement and profit can also be made
Decorations, these improvements and modifications also should be regarded as protection scope of the present invention.Each component part being not known in the present embodiment is available
The prior art is realized.
Claims (6)
1. the active tracking Optimal Control System for grid type solid oxide fuel cell, which is characterized in that including setting
It is worth optimizer SPO, voltage source inverter VSI, solid oxide fuel cell SOFC systems and L1-MPC tracking control units；
The setting value optimizer SPO receives the active power output order of power network dispatching system, and seeks electricity according to the instruction
The optimal value of pressure, the optimal value of electric current and solid oxide fuel cell SOFC system optimum fuel utilization rates, and by voltage
Optimal value and optimum fuel utilization rate be transmitted to L1-MPC tracking control units, the optimal value of electric current is transmitted to voltage source inverter
The optimal value of device VSI, the voltage and current make hot merit of the solid oxide fuel cell SOFC system consumptions in internal resistance
Rate is minimum；
Voltage source inverter VSI is defeated as voltage source inverter VSI using the optimal value of the setting value optimizer SPO electric currents acquired
Go out the reference value of electric current so that the output current of solid oxide fuel cell SOFC systems tracks the reference value；
L1-MPC tracking control units are sharp using the optimal value and solid oxide fuel cell SOFC systems optimum fuel of voltage
Use rate as value is referred to, by controlling the fuel flow rate and air mass flow of solid oxide fuel cell SOFC systems, by solid
The output voltage and fuel availability stability contorting of oxide fuel cell SOFC systems are in reference value.
2. system according to claim 1, which is characterized in that the setting value optimizer is by solving following optimization problem
Obtain the optimal value of voltage, the optimal value of electric current and solid oxide fuel cell SOFC system optimum fuel utilization rates：
Wherein, s.t. indicates the constraint in optimization problem, Vout,refFor the optimal value of voltage, IrefFor the optimal value of electric current, Φ
()=0 is the steady-state model of solid oxide fuel cell SOFC systems；VoutFor solid oxide fuel cell SOFC systems
Output voltage, I are solid oxide fuel cell SOFC system output currents, and subscript ref represents corresponding reference value, qchemFor
The chemical energy that the fuel of solid oxide fuel cell SOFC system consumptions is released, PrefIt is instructed for electric network active, FuFor solid
Oxide fuel cell SOFC system fuel utilizations,It is utilized for solid oxide fuel cell SOFC system optimum fuels
Rate.
3. system according to claim 2, which is characterized in that the L1-MPC tracking control units obtain solid by following formula
The control input vector of oxide fuel cell SOFC systems：
WhereinFor the control input vector of solid oxide fuel cell SOFC systems,And MairPoint
Not Wei solid oxide fuel cell SOFC systems fuel flow rate and air mass flow,For L1 compensation control components, uMPC
(t) it is MPC tracing control components, L1 compensation control components are by an output feedback L1 compensators calculating acquisition, MPC tracing controls
Component is calculated by a MPC controller and is obtained.
4. system according to claim 3, which is characterized in that the design method of the output feedback L1 compensators includes such as
Lower step：
Step A1：The steady running condition point of optional solid oxide fuel cell SOFC systems is responded real by Open loop step
It tests and linear least squares method method, establishes the dynamic model of following solid oxide fuel cell SOFC systems：
Y (s)=G (s) (u (s)+σ (s)),
Wherein, y (s), u (s), σ (s) are respectively signal vector y (t), the Laplace transform of u (t), σ (t), y (t)=[Vout,
Fu]TFor the output quantity of solid oxide fuel cell SOFC systems, σ (t) is solid oxide fuel cell SOFC system lumps
Indeterminate, G (s) are 2 × 2 transfer function matrix；
Step A2：The following output fallout predictor of design：
Wherein subscript i and j representation vectors or the element numbers of matrix, n are the dimension of transfer function matrix G (s), Gi,i(s) it is G
(s) i rows i arranges corresponding transmission function, Gi,j(s) it is that G (s) i rows j arranges corresponding transmission function,For the pre- of output fallout predictor
Survey output vectorI-th of element, ui(s),uj(s) distinguish i-th of element of input vector u (s) in order to control and j-th
Element,For the estimated value of solid oxide fuel cell SOFC system lump indeterminates,ForI-th
Element；
Step A3：Design the estimated value more new law of following indeterminate：
Sign is sign function, and t indicates time signal, and Proj is projection operator, and Γ is designing gain, gi,iFor transmission function Gi,i
(s) steady-state gain,yi(t) i-th of element for being output signal y (t),ForIt is corresponding
Time-domain signal,ForTo the derivative of time；
Step A4：Calculate L1 adaptive equalization components：
C (s) is a low-pass filter vector with control input vector u with same dimension, Ci(s) it is i-th yuan of C (s)
Element,WithRespectivelyI-th of element and j-th of element,ForLaplace transform.
5. system according to claim 4, which is characterized in that the design method of the MPC controller includes the following steps：
Step B1：Convert transfer function matrix G (s) described in step A1 to following equivalent separate manufacturing firms model：
Y (k)=cx (k),
X (k+1)=Ax (k)+Bu (k)；
X (k), y (k), u (k) indicate the quantity of state at separate manufacturing firms model present sample time point, output quantity, input respectively
Amount, x (k+1) indicate separate manufacturing firms model in the quantity of state of next sampling time point, and A, B, c is separate manufacturing firms mould
The sytem matrix of type；
Step B2：Following on-line optimization problem is solved, obtained solution sequence is an optimal control sequence：
U (k | k), u (k+1 | k) ..., u (k+M+1 | k),
ymin≤y(k+m|k)≤ymax
Wherein k represents present sample time point, and N is prediction time domain, M time domains in order to control, umin、umaxIt respectively inputs permitted
Minimum value and maximum value, ymin、ymaxThe minimum value and maximum value respectively exported, L are so that matrix (A+Lc) all features
The real part of value is less than 1 Arbitrary Matrix, yrefFor the reference value of solid oxide fuel cell SOFC system outputs y, μrefFor from
Dissipate state-space model in yrefCorresponding stable state input,ForIn the value at present sample time point, Q, R are design
Weight matrix, u (k | k), u (k+1 | k) ..., u (k+M+1 | k) indicate the PREDICTIVE CONTROL amount at present sample time point respectively,
Present sample time point, present sample time point was to following the M+1 sampling to the PREDICTIVE CONTROL amount ... of next sampling time point
The PREDICTIVE CONTROL amount at time point；
Y (k+m | k) indicate prediction output quantity of the present sample time point to following m-th of sampling time point,For system shape
Observations of the state amount x at present sample time point；It is system state amount x in the observation of upper sampling time point, u
(k-1) it being inputted for the control of upper sampling time point, y (k-1) is the output of upper sampling time point,WithRespectively predicted value and future m-1 of the current sampling point to following m-th of sampling time point observation
The predicted value of sampling time point observation, u (k+m | k) and u (k+m-1 | k) it is respectively that current sampling point samples following m-th
The PREDICTIVE CONTROL amount of the PREDICTIVE CONTROL amount at time point and following the m-1 sampling time point,
μref=(c (I-A)-1B)-1yref,
Step B3：MPC tracing control components use first element of the controlled quentity controlled variable sequence solved in step B2, i.e.,：
uMPC(k)=u (k | k),
Within present sample time point to the time between next sampling time point, u is takenMPC(t)=uMPC(k)。
6. system according to claim 5, which is characterized in that system uses following relay protective scheme：When setting value optimizer
SPO acquire new voltage optimal value and electric current optimal value when, the optimal value of the voltage is transmitted to L1-MPC tracking controls at once
In device processed, the optimal value of electric current is temporarily stored into the memory of setting value optimizer SPO and is not updated to voltage source inverter at once
In VSI, voltage is updated to after L1-MPC tracking control units update its MPC tracing control component, then by the optimal value of electric current
In source inventer VSI.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810082385.9A CN108346811B (en) | 2018-01-29 | 2018-01-29 | Active power tracking optimization control system for grid-connected solid oxide fuel cell |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810082385.9A CN108346811B (en) | 2018-01-29 | 2018-01-29 | Active power tracking optimization control system for grid-connected solid oxide fuel cell |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108346811A true CN108346811A (en) | 2018-07-31 |
| CN108346811B CN108346811B (en) | 2020-07-14 |
Family
ID=62961419
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810082385.9A Expired - Fee Related CN108346811B (en) | 2018-01-29 | 2018-01-29 | Active power tracking optimization control system for grid-connected solid oxide fuel cell |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108346811B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114527640A (en) * | 2022-02-14 | 2022-05-24 | 北京星辰空间科技有限公司 | Anti-interference high-precision storage and supply flow control method and system based on anode current |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2419968A (en) * | 2004-11-08 | 2006-05-10 | Enecsys Ltd | Regulating the voltage fed to a power converter |
| US20080205096A1 (en) * | 2007-02-22 | 2008-08-28 | Jih-Sheng Lai | Control system and method for a universal power conditioning system |
| CN103828111A (en) * | 2011-06-30 | 2014-05-28 | 康维恩公司 | Method and arrangement for minimizing need for safety gases |
| CN105518962A (en) * | 2013-09-04 | 2016-04-20 | Lg燃料电池系统公司 | A fuel cell unit |
| JP2016189268A (en) * | 2015-03-30 | 2016-11-04 | 三浦工業株式会社 | Fuel battery system |
-
2018
- 2018-01-29 CN CN201810082385.9A patent/CN108346811B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2419968A (en) * | 2004-11-08 | 2006-05-10 | Enecsys Ltd | Regulating the voltage fed to a power converter |
| US20080205096A1 (en) * | 2007-02-22 | 2008-08-28 | Jih-Sheng Lai | Control system and method for a universal power conditioning system |
| CN101842956A (en) * | 2007-02-22 | 2010-09-22 | 弗吉尼亚科技知识产权有限公司 | Control method for a universal power condition system |
| CN103828111A (en) * | 2011-06-30 | 2014-05-28 | 康维恩公司 | Method and arrangement for minimizing need for safety gases |
| CN105518962A (en) * | 2013-09-04 | 2016-04-20 | Lg燃料电池系统公司 | A fuel cell unit |
| JP2016189268A (en) * | 2015-03-30 | 2016-11-04 | 三浦工業株式会社 | Fuel battery system |
Non-Patent Citations (4)
| Title |
|---|
| LEI PAN等: "L1 Adaptive Output Feedback Controller with Operating Constraints for Solid Oxide Fuel Cells", 《11TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS ICINCO 2014》 * |
| LI SUN等: "Coordinated Control Strategies for Fuel Cell Power Plant in a Microgrid", 《IEEE TRANSACTIONS ON ENERGY CONVERSION》 * |
| YONGHUI LI等: "Hierarchical Load Tracking Control of a Grid-Connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation", 《ENERGIES》 * |
| 李勇汇 等: "固体氧化物燃料电池电厂并网最优效率负荷跟踪分层递阶控制策略", 《中国电机工程学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114527640A (en) * | 2022-02-14 | 2022-05-24 | 北京星辰空间科技有限公司 | Anti-interference high-precision storage and supply flow control method and system based on anode current |
| CN114527640B (en) * | 2022-02-14 | 2024-03-15 | 北京星辰空间科技有限公司 | Anti-interference high-precision storage and supply flow control method and system based on anode current |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108346811B (en) | 2020-07-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sun et al. | Coordinated control strategies for fuel cell power plant in a microgrid | |
| Ranjan et al. | A literature survey on load frequency control considering renewable energy integration in power system: Recent trends and future prospects | |
| Xu et al. | A novel adaptive neural network constrained control for a multi-area interconnected power system with hybrid energy storage | |
| Peddakapu et al. | A state-of-the-art review on modern and future developments of AGC/LFC of conventional and renewable energy-based power systems | |
| Zhang et al. | Control strategy for power management, efficiency-optimization and operating-safety of a 5-kW solid oxide fuel cell system | |
| Mishra et al. | Biogeography based optimal state feedback controller for frequency regulation of a smart microgrid | |
| Nabipour et al. | Type-3 fuzzy voltage management in PV/hydrogen fuel cell/battery hybrid systems | |
| Suresh et al. | Decentralized control strategy for fuel cell/PV/BESS based microgrid using modified fractional order PI controller | |
| Mallesham et al. | Automatic generation control of microgrid using artificial intelligence techniques | |
| Kumar et al. | Energy management strategy for integration of fuel cell-electrolyzer technologies in microgrid | |
| Sekhar et al. | Sliding mode based feedback linearizing controller for grid connected multiple fuel cells scenario | |
| Khosravi et al. | Improvement of harmonic conditions in the AC/DC microgrids with the presence of filter compensation modules | |
| Pilla et al. | Design and analysis of search group algorithm-based PD-PID controller plus redox flow battery for automatic generation control problem | |
| Habib et al. | Microgrid management using hybrid inverter fuzzy-based control | |
| Nojavan et al. | Voltage stability constrained OPF in multi-micro-grid considering demand response programs | |
| Nassourou et al. | Economic model predictive control for energy dispatch of a smart micro-grid system | |
| Li et al. | Improvement of energy supply configuration for telecommunication system in remote area s based on improved chaotic world cup optimization algorithm | |
| Xing et al. | Maximum production point tracking of a high-temperature power-to-gas system: A dynamic-model-based study | |
| Xu et al. | CVR-based real-time power fluctuation smoothing control for distribution systems with high penetration of PV and experimental demonstration | |
| Pajares et al. | Methodology for energy management strategies design based on predictive control techniques for smart grids | |
| Zhu et al. | PV/Hydrogen DC microgrid control using distributed economic model predictive control | |
| Du et al. | Energy management and performance analysis of an off-grid integrated hydrogen energy utilization system | |
| Tomberg et al. | Operation strategies for a flexible megawatt scale electrolysis system for synthesis gas and hydrogen production with direct air capture of carbon dioxide | |
| CN108346811A (en) | Active tracking Optimal Control System for grid type solid oxide fuel cell | |
| Chen et al. | Dynamic economic dispatch for CHP-MG system based on mixed logical dynamic model and MPC method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20200714 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |