CN115094482A - Alkali liquor electrolysis hydrogen production control method adapting to wide power fluctuation - Google Patents
Alkali liquor electrolysis hydrogen production control method adapting to wide power fluctuation Download PDFInfo
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- 239000001257 hydrogen Substances 0.000 title claims abstract description 84
- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 84
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 title claims abstract description 79
- 239000003513 alkali Substances 0.000 title claims abstract description 78
- 238000005868 electrolysis reaction Methods 0.000 title claims abstract description 43
- 238000000195 production control method Methods 0.000 title description 2
- 239000001301 oxygen Substances 0.000 claims abstract description 54
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 54
- 238000004519 manufacturing process Methods 0.000 claims abstract description 40
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 31
- 238000000034 method Methods 0.000 claims abstract description 23
- 239000007789 gas Substances 0.000 claims description 27
- 239000007788 liquid Substances 0.000 claims description 17
- 238000003062 neural network model Methods 0.000 claims description 14
- 238000013528 artificial neural network Methods 0.000 claims description 8
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 7
- 239000002245 particle Substances 0.000 claims description 4
- 230000002441 reversible effect Effects 0.000 claims description 4
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000012549 training Methods 0.000 claims description 2
- 230000033228 biological regulation Effects 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 abstract description 2
- 210000004027 cell Anatomy 0.000 description 38
- 230000006870 function Effects 0.000 description 12
- 210000002569 neuron Anatomy 0.000 description 8
- 238000010586 diagram Methods 0.000 description 6
- 150000002431 hydrogen Chemical class 0.000 description 5
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000005457 optimization Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 238000004880 explosion Methods 0.000 description 2
- 239000012528 membrane Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 238000012937 correction Methods 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
- 238000005261 decarburization Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 239000002803 fossil fuel Substances 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000028161 membrane depolarization Effects 0.000 description 1
- 238000006386 neutralization reaction Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 239000008213 purified water Substances 0.000 description 1
- 239000011232 storage material Substances 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
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- C—CHEMISTRY; METALLURGY
- C25—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES; APPARATUS THEREFOR
- C25B—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES FOR THE PRODUCTION OF COMPOUNDS OR NON-METALS; APPARATUS THEREFOR
- C25B15/00—Operating or servicing cells
- C25B15/02—Process control or regulation
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- C—CHEMISTRY; METALLURGY
- C25—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES; APPARATUS THEREFOR
- C25B—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES FOR THE PRODUCTION OF COMPOUNDS OR NON-METALS; APPARATUS THEREFOR
- C25B1/00—Electrolytic production of inorganic compounds or non-metals
- C25B1/01—Products
- C25B1/02—Hydrogen or oxygen
- C25B1/04—Hydrogen or oxygen by electrolysis of water
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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
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/30—Hydrogen technology
- Y02E60/36—Hydrogen production from non-carbon containing sources, e.g. by water electrolysis
-
- 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P20/00—Technologies relating to chemical industry
- Y02P20/10—Process efficiency
- Y02P20/133—Renewable energy sources, e.g. sunlight
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Abstract
The invention discloses a control method for hydrogen production by alkali liquor electrolysis, which is suitable for wide power fluctuation. The invention adopts a gas-liquid-electric multi-field coordinated regulation and control mode, solves the problems of low efficiency, low purity and the like during low-load operation of alkali liquor electrolysis hydrogen production, and expands the operation range of alkali liquor hydrogen production so as to adapt to the occasions with wide power fluctuation such as intermittent renewable energy sources. The invention reduces the mixing degree of hydrogen and oxygen and improves the purity of hydrogen production by dynamically adjusting the pressure of the hydrogen and oxygen side and the circulation speed of the alkali liquor. Meanwhile, the problems of poor consistency, large internal resistance, low efficiency and the like of an electrolysis unit when the electrolysis bath operates at low voltage are solved by using an overvoltage pulse modulation method. The invention can produce hydrogen by high-efficiency and high-purity electrolysis in the full power range of the alkali liquor electrolysis bath, and enlarges the application range of the alkali liquor electrolysis hydrogen production technology.
Description
Technical Field
The invention relates to a control method for hydrogen production by alkali liquor electrolysis, which is suitable for wide power fluctuation, and belongs to the operation control technology of a hydrogen-electricity coupling system in the field of new energy.
Background
The development and utilization of non-fossil energy are main ways for promoting large-scale replacement of fossil fuels, green energy transformation and realization of carbon neutralization, and the intervention of high-proportion and high-density renewable energy sources is a basic form of a future power grid. In recent years, hydrogen energy has attracted much attention, and especially hydrogen production by electrolysis of renewable energy sources becomes an industrial hotspot. Hydrogen energy is an ideal clean secondary energy source, is taken from water, and becomes purified water without any pollution after being combusted, so that the hydrogen energy is called as green energy without an industrial ceiling and having the most potential. The renewable energy source is used for producing hydrogen, the hydrogen storage material is used for storing hydrogen, and the hydrogen fuel cell is used for generating electricity, so that a 'net zero emission' sustainable hydrogen energy system is formed, and an important path for realizing 'deep decarburization' besides the renewable energy source is formed.
However, the hydrogen production by electrolysis of renewable energy sources faces a plurality of problems, and due to the characteristics of intermittency, fluctuation and randomness of the renewable energy sources, the gas purity of hydrogen production by electrolysis of alkaline liquor under a low-load working condition needs to be improved, the hydrogen production efficiency is low, so that the hydrogen production method cannot adapt to the situation with wide power fluctuation, and the problems seriously restrict the future development of hydrogen production by electrolysis of alkaline liquor.
Disclosure of Invention
The invention aims to provide a control method for hydrogen production by alkali liquor electrolysis, which is suitable for wide power fluctuation, aiming at overcoming the defects of the prior art, and effectively solving the problems of hydrogen production purity under a low-load working condition and low efficiency under wide-range power fluctuation, so that hydrogen production by alkali liquor electrolysis can be efficiently and stably operated under the condition of wide-range power fluctuation.
The technical scheme adopted by the invention is as follows:
a control method for hydrogen production by alkali liquor electrolysis adapting to wide power fluctuation controls an alkali liquor electrolysis bath to adopt different alkali liquor circulation speeds and hydrogen-oxygen side pressures to operate under different working conditions so as to adapt to the wide power fluctuation, wherein under the low-load working condition of the alkali liquor electrolysis bath, the alkali liquor electrolysis bath is controlled to reduce the alkali liquor circulation speed and the hydrogen-oxygen side pressure; the circulation speed of the alkali liquor is reduced, and the flow of oxygen and hydrogen dissolved in the solution to the other side along with the alkali liquor is reduced, so that the hydrogen and the oxygen are mixed. While reducing the hydrogen-oxygen side pressure ratio, thereby reducing the likelihood of hydrogen permeation through the alkaline membrane.
In the invention, the alkali liquor electrolytic cell is in a U-shaped state under a low-load working condition cell ＜rU 0 Under conditions of (2) wherein U cell For the cell end voltage, r is the number of electrolysis cells connected in series, U 0 For the reversible voltage of the electrolyzed water, 1.23V is generally adopted. The normal working condition isThe electrolytic cell is in U cell ＞rU 0 Under the conditions of (1). Normally, due to U cell ＜ru 0 In the process, the current of the electrolytic cell is very small, and the power change range of the electrolytic cell is limited, so that only one condition is considered under a low-load working condition.
Further, under the low-load working condition of the alkali liquor electrolytic cell, controlling the alkali liquor electrolytic cell to operate at the optimal alkali liquor circulation speed and hydrogen-oxygen pressure ratio; wherein the optimal alkali liquor circulation speed and hydrogen-oxygen pressure ratio are obtained by optimizing the following method:
(1) collecting gas production purity data of the alkali liquor electrolytic cell under the low-load working condition and under the combined operation of different alkali liquor circulation speeds and the hydrogen-oxygen side pressure;
(2) establishing a neural network model for the relationship among the gas production purity of the alkali liquor electrolytic cell, the circulation speed of the alkali liquor and the hydrogen-oxygen pressure ratio by utilizing the neural network fitting function; the input of the neural network model is the combination of the circulation speed of the alkali liquor and the pressure of the hydrogen-oxygen side, the output is the gas production purity of the alkali liquor electrolytic cell, and the training is carried out by taking the loss of the minimum output and the true value as a target;
(3) and constructing a gas purity objective function based on the trained neural network model, and optimizing the gas purity objective function to obtain the optimal alkali liquor circulation speed and the hydrogen-oxygen pressure ratio.
Further, the gas purity objective function is as follows:
f＝Ay(k)＝AF(u(k))
where F is the neural network model, A is the weighting coefficient matrix, and u (k) is the input to the neural network model at time k.
Further, in the step (3), a particle group control algorithm is used to optimize the gas purity objective function.
Further, in the step (3), the optimized constraint condition includes:
the circulation speed of the alkali liquor is less than the upper limit value of the flow speed of the alkali liquor valve;
the internal pressure value of the hydrogen side gas-liquid separator is smaller than the upper limit value of the pressure;
the internal pressure value of the oxygen side gas-liquid separator is less than the upper limit value of the pressure;
the pressure difference of the hydrogen and oxygen sides is less than the upper limit value of the pressure difference.
Further, under a low-load working condition, if the direct-current voltage applied to the two ends of the electrolytic cell is not enough to conduct all the electrode small chambers, the problems of inconsistent working states of the electrolytic cells, large internal resistance, low hydrogen production efficiency and the like can be caused, and even the problems of hydrogen and oxygen mixing and the like can be caused in a serious condition, so that the danger of explosion is easily caused. Thus, the method of the invention further comprises: under the low-load working condition of the alkali liquor electrolytic tank, the operation of the alkali liquor electrolytic tank is controlled by adopting an overvoltage pulse modulation method, wherein the pulse amplitude value>rU 0 R is the number of electrolytic chambers connected in series in the alkali solution electrolytic cell, U 0 Is the reversible voltage of the electrolyzed water; frequency of pulses>1 kHz. By an overvoltage pulse modulation method, the consistency of the electrolysis unit is enhanced when the electrolysis bath operates at low voltage, the internal resistance is reduced, and the electrolysis efficiency under the low-load working condition is improved.
Further, the gas production rate is adjusted by changing the pulse duty ratio d, and the specific control law is as follows:
wherein
For PI controllers, s is the Laplace operator, k p Is a proportionality coefficient, k i Is an integral coefficient; v. of * V is the real-time hydrogen yield for the nominal hydrogen yield.
The invention has the beneficial effects that:
1) the wide power range work of the hydrogen production by the alkali liquor electrolysis is realized, and the hydrogen production by the alkali liquor electrolysis can work for a long time under the low-load working condition.
2) Can effectively reduce the mixing degree of hydrogen and oxygen and improve the hydrogen production purity of hydrogen production by alkali liquor electrolysis under the low-load working condition.
3) The working states of all the electrolysis cells are kept consistent, and the problem of nonuniform reaction of the electrolysis cells in the traditional direct-current voltage electrolysis under the low-load working condition is solved.
Drawings
FIG. 1 is a control interface diagram of an alkali liquor hydrogen production electrolytic tank device;
FIG. 2 is a schematic diagram of the internal structure of an electrolytic cell for hydrogen production from alkali liquor;
FIG. 3 is a schematic diagram of a neural network architecture;
FIG. 4 is a waveform diagram of the pulse voltage applied across the cell;
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
FIG. 2 is a schematic diagram of the internal structure of a typical alkali liquor hydrogen production electrolytic cell, and the control interface of the alkali liquor hydrogen production electrolytic cell is shown in FIG. 1. the method of the present invention firstly uses a cooperative control strategy of alkali liquor circulation speed and hydrogen-oxygen side pressure to reduce alkali liquor circulation speed and reduce the flow of dissolved oxygen and hydrogen in the solution to the other side with alkali liquor to cause hydrogen-oxygen mixing when the alkali liquor hydrogen production electrolytic cell is in a low load condition. While reducing the hydrogen-oxygen side pressure ratio, thereby reducing the likelihood of hydrogen permeation through the alkaline membrane.
The invention further provides a specific control method based on the cooperative regulation strategy. And (3) constructing a neural network model, and establishing the neural network model for the relation between the gas production purity of the alkali liquor electrolytic tank, the circulation speed of the alkali liquor and the hydrogen-oxygen pressure ratio by using the neural network fitting function.
And selecting the oxygen content in the hydrogen at the moment k, the hydrogen content in the oxygen at the moment k as output, the alkali liquor circulation speed at the moment k, the internal pressure value of the hydrogen side gas-liquid separator at the moment k, and the internal pressure value of the oxygen side gas-liquid separator at the moment k as input.
Wherein, the data of the content of hydrogen in oxygen is obtained by an oxygen hydrogen analyzer on the oxygen side, and the data of the content of oxygen in hydrogen is obtained by a hydrogen oxygen analyzer on the hydrogen side. The circulation speed of the alkali liquor is obtained by a flow meter in the alkali liquor channel, the pressure data of the hydrogen side is obtained by a pressure gauge arranged in the gas-liquid separator of the hydrogen side, and the pressure data of the oxygen side is obtained by a pressure gauge arranged in the gas-liquid separator of the oxygen side.
FIG. 3 is a diagram of an exemplary neural network architecture, which is a four-layer neural network that includes an input layer (D layer), hidden layers (M layer and N layer) and an output layer (P layer), the following is a model of the neural network:
the input layer is as follows:
u(k)＝[u 1 (k),u 2 (k),u 3 (k)] T
in the formula u 1 (k) Is the circulation speed of the alkali solution at time k, u 2 (k) Is the pressure value u inside the gas-liquid separator on the hydrogen side at the time k 3 (k) The pressure value in the oxygen-side gas-liquid separator at time k is set.
The output layer is as follows:
y(k)＝[y 1 (k),y 2 (k)] T
in the formula, y 1 (k) Is the oxygen content in hydrogen at time k, y 2 (k) Is the hydrogen content in oxygen at time k
The number of inputs on the input layer is set to D-3, and u is used for any one input d Here, hidden layer 1 includes M neurons, arbitrary neuron is M, hidden layer 2 includes N neurons, arbitrary neuron is N, output layer is P ═ 2, and arbitrary output is y p And the weight between the input layer and the arbitrary node of the hidden layer 1 is recorded as w dm The weight between the arbitrary nodes of hidden layer 1 and hidden layer 2 is denoted as w mn The weight between the hidden layer 2 and any node of the output layer is w np The input sample set is X ═ X1, X2 …]With Xi for any sample and J for the desired output i ＝{j p } P The actual output is Y i ＝{y p } P Where l is the number of iterations and μ is the learning efficiency, the output of the mth neuron in hidden layer 1 is:
the output of the nth neuron of hidden layer 2 is:
the output of the p-th neuron of the output layer, namely the output of the network, is:
the sum of the error energies of all neurons in the output layer is:
the neural network adopts a gradient descent learning rule, and the weight correction formula is as follows:
the relation between the gas purity (oxygen in hydrogen and hydrogen content in oxygen) and the gas-liquid control system parameters (alkali liquor circulation speed and hydrogen-oxygen pressure ratio) is obtained through the neural network model, further, the gas purity is optimized through a particle swarm control algorithm, the gas purity objective function is optimized, and the optimized set parameters of the gas-liquid control system are obtained.
The input variables are:
u(k)＝[u 1 (k),u 2 (k),u 3 (k)] T
in the formula u 1 (k) Is the circulation speed of the alkali solution at time k, u 2 (k) Is the pressure value u inside the gas-liquid separator on the hydrogen side at the time k 3 (k) The pressure value in the oxygen-side gas-liquid separator at time k is set.
Defining a gas purity objective function as:
f＝Ay(k)＝AF(u(k))
wherein F is a neural network model, A is a weight coefficient matrix, which is the importance degree of different gas purities to the total gas purity objective function:
A＝[β 1 β 2 ]
β 1 is the weight of oxygen content in hydrogen, and the value is 0.8, beta 2 The weight of hydrogen content in oxygen is taken as the value of 0.2, and the purity objective function is obtained as follows:
f＝0.8*y 1 (k)+0.2*y 2 (k)
in the formula, y 1 (k) Is the oxygen content in hydrogen at time k, y 2 (k) Is the hydrogen content in oxygen at time k.
The constraint condition 1 is that the circulation speed of the alkali liquor is less than the upper limit value v of the flow speed of the alkali liquor valve max ：
0<u 1 (k)<v max
The constraint condition 2 is that the internal pressure value of the hydrogen side gas-liquid separator is less than the upper pressure limit value thereof
The constraint condition 3 is that the internal pressure value of the oxygen side gas-liquid separator is less than the upper limit value of the pressure
The constraint condition 4 is that the pressure difference on the hydrogen and oxygen sides is less than the upper limit value P of the pressure difference differmax ：
|u 2 (k)-u 3 (k)|<P differmax
Optimizing the gas purity objective function f by utilizing a particle swarm optimization algorithm, realizing the optimization of the gas purity objective function, and obtaining the optimization setting parameters u (k) of the gas-liquid control system.
Under the low-load working condition, the control system adopts the optimized set parameters u (k) to carry out the hydrogen production by the electrolysis of the alkali liquor, so that the hydrogen production purity under the low-load working condition can be improved.
Further, under a low-load working condition, if the direct-current voltage applied to the two ends of the electrolytic cell is not enough to conduct all the electrode cells, the problems of inconsistent working states of the electrolytic cells, large internal resistance, low hydrogen production efficiency and the like can be caused, and even the problems of hydrogen and oxygen mixing and the like can be caused in a serious condition, so that the danger of explosion is easily caused.
Therefore, under the low-load working condition, hydrogen is produced by electrolyzing alkali liquor by using an overvoltage pulse modulation method. The method specifically comprises applying pulse voltage to make all electrolysis cells in the electrolytic cell conductive in high level time period of pulse, wherein the high level voltage U > ru 0 And all the small electrolysis chambers can be conducted, so that all the small electrolysis chambers are in a state of producing hydrogen by electrolyzing water, and all the small electrolysis chambers are fully utilized. In the low level time period of the pulse, because the electrolysis voltage u is 0, all the small chambers of the electrolytic cell are in the state of stopping working at the moment, the overflow of bubbles and the occurrence of depolarization reaction are facilitated, so that the internal resistance is effectively reduced, and the reaction efficiency is improved. Because all the electrolytic cells can be in an electrolytic or stopped state at the same time, the consistency of the electrolytic cells when the electrolytic cell operates under a low-load working condition is ensured.
Applied pulse voltage, pulse amplitude>rU 0 Wherein r is the number of electrolytic cells connected in series in the electrolytic cell, U 0 The voltage is reversible for electrolyzing water, and all the electrolysis cells can be conducted at the moment; frequency of the pulse voltage>1kHz, as shown in FIG. 4; the gas production is adjusted by changing the pulse duty ratio d through a PI controller, and the control law is as follows:
wherein
For PI controllers, s is the Laplace operator, k p Is a proportionality coefficient with a value of 0.001, k i Is an integral coefficient. The value is 0.1; v. of * V is the real-time hydrogen yield for the nominal hydrogen yield.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. This need not be, nor should all embodiments be exhaustive. And obvious variations or modifications of the invention may be made without departing from the scope of the invention.
Claims (7)
1. A control method for hydrogen production by alkali liquor electrolysis adapting to wide power fluctuation is characterized in that an alkali liquor electrolysis tank is controlled to operate at different alkali liquor circulation speeds and different hydrogen-oxygen side pressures under different working conditions so as to adapt to wide power fluctuation, wherein the alkali liquor electrolysis tank is controlled to reduce the alkali liquor circulation speed and the hydrogen-oxygen side pressure under the low-load working condition of the alkali liquor electrolysis tank.
2. The method of claim 1, wherein the operation of the lye electrolysis cell is controlled at an optimum lye circulation speed and hydrogen-oxygen pressure ratio under a lye electrolysis cell low load condition; wherein the optimal alkali liquor circulation speed and hydrogen-oxygen pressure ratio are obtained by optimizing the following method:
(1) collecting gas production purity data of the alkali liquor electrolytic cell under the low-load working condition and under the combined operation of different alkali liquor circulation speeds and the hydrogen-oxygen side pressure;
(2) establishing a neural network model for the relationship among the gas production purity of the alkali liquor electrolytic cell, the circulation speed of the alkali liquor and the hydrogen-oxygen pressure ratio by utilizing the neural network fitting function; the input of the neural network model is the combination of the circulation speed of the alkali liquor and the pressure of the hydrogen-oxygen side, the output is the gas production purity of the alkali liquor electrolytic cell, and training is carried out by taking the loss of the minimum output and the true value as a target;
(3) and constructing a gas purity objective function based on the trained neural network model, and optimizing the gas purity objective function to obtain the optimal alkali liquor circulation speed and hydrogen-oxygen pressure ratio.
3. The method of claim 2, wherein the gas purity objective function is as follows:
f＝Ay(k)＝AF(u(k))
where F is the neural network model, A is the weighting coefficient matrix, and u (k) is the input to the neural network model at time k.
4. The method of claim 2, wherein in step (3), the gas purity objective function is optimized using a particle group control algorithm.
5. The method of claim 2, wherein in the step (3), the optimized constraint condition comprises:
the circulation speed of the alkali liquor is less than the upper limit value of the flow speed of the alkali liquor valve;
the pressure value in the gas-liquid separator on the hydrogen side is smaller than the upper limit value of the pressure;
the internal pressure value of the oxygen side gas-liquid separator is less than the upper limit value of the pressure;
the pressure difference of the hydrogen-oxygen side is smaller than the upper limit value of the pressure difference.
6. The method of claim 1, further comprising: under the low-load working condition of the alkali liquor electrolytic tank, the operation of the alkali liquor electrolytic tank is controlled by adopting an overvoltage pulse modulation method, wherein the pulse amplitude value>rU 0 R is the number of electrolytic chambers connected in series in the alkali solution electrolytic cell, U 0 Is a reversible voltage for electrolyzing water; frequency of pulses>1kHz。
7. The method of claim 6, wherein the gas production is adjusted by changing the pulse duty cycle, and the specific control law is as follows:
wherein
For PI controllers, s is the Laplace operator, k p Is a proportionality coefficient, k i Is an integral coefficient; v. of * V is the real-time hydrogen yield for the nominal hydrogen yield.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116288452A (en) * | 2023-05-11 | 2023-06-23 | 浙江大学 | Multi-mode self-optimizing electrolytic hydrogen production circuit and control method |
| CN116288452B (en) * | 2023-05-11 | 2023-08-01 | 浙江大学 | Multi-mode self-optimizing electrolytic hydrogen production circuit and control method |
| CN117904675A (en) * | 2024-03-19 | 2024-04-19 | 浙江大学 | Seawater direct hydrogen production control device and control method based on osmotic environment regulation and control |
| CN117904675B (en) * | 2024-03-19 | 2024-05-31 | 浙江大学 | Seawater direct hydrogen production control device and control method based on osmotic environment regulation and control |
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