CN115566706B - Fuzzy control method for alkaline electrolysis hydrogen production system - Google Patents
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Abstract
The invention belongs to the field of automatic control of power systems, and particularly relates to a fuzzy control method for an alkaline electrolysis hydrogen production system. Firstly, fuzzifying input quantity and output quantity by a fuzzy control membership function, and respectively defining the fuzzification of the input quantity and the output quantity into four grades according to the intensity of illumination radiation and the intensity of wind power. And defining the output as five modes according to the operation scheme of the electrolytic hydrogen production system. And secondly, establishing a fuzzy rule, wherein the fuzzy rule is defined as that the stronger the illumination is, the larger the output power is, the stronger the wind power is, and the larger the output power is. And then, carrying out membership calculation on the alkaline electrolytic hydrogen production system applying fuzzy control. And finally, clearly judging the working mode of the electrolytic hydrogen production system at the moment through outputting the membership map. The invention can realize the high-efficiency and economic operation of the alkaline electrolytic hydrogen production system under the condition of randomly fluctuating new energy input, avoids the influence of frequent start-up and shutdown on equipment, prolongs the service life of the system and improves the stability of the system.
Description
Technical Field
The invention belongs to the field of automatic control of power systems, and particularly relates to a fuzzy control method for an alkaline electrolysis hydrogen production system.
Background
Renewable energy electrical hydrogen production (green hydrogen) is an important direction for hydrogen energy development in the future, and researches on optimizing the performance of a new energy electrolytic hydrogen production system, improving the utilization rate of renewable energy and improving the economy of the new energy hydrogen production system are imperative in a new energy electrolytic hydrogen production link.
In the traditional electrolytic hydrogen production technology, most of electrolytic cells adopt a constant current control mode for operation, so that the electrolytic cells are easily opened and closed frequently, the service life of the electrolytic cells is shortened, and the hydrogen production amount is small. In a new energy hydrogen production system, because the wind power intensity and the illumination intensity change along with the change of time in one day, or change along with the change of sunny days and rainy days, the electric energy generated by a wind driven generator has larger fluctuation along with the change of the wind power intensity and the electric energy generated by a photovoltaic array along with the change of the illumination intensity and the environmental temperature. And the process of wind power generation and photovoltaic effect transmission to the electrolytic cell is a nonlinear and time-varying model, and a data model is difficult to establish so as to plan the operation mode of the electrolytic cell.
Disclosure of Invention
In order to solve the problems, the invention provides a fuzzy control method for an alkaline electrolysis hydrogen production system, which can adjust the operation mode of an electrolytic cell according to fuzzy control rules through real-time change of illumination intensity and wind power intensity. The operation mode of the electrolytic hydrogen production system is changed in real time based on the difference of wind power intensity and illumination intensity at different moments or in sunny and rainy days, and the system is suitable for an alkaline electrolytic hydrogen production system which is operated in an environment with random fluctuation of wind power and illumination and needs to improve the hydrogen production efficiency and meet the economical efficiency.
Firstly, the input quantity and the output quantity are fuzzified by a fuzzy control membership function, and are fuzzified and defined into four grades respectively according to the intensity of illumination radiation and the intensity of wind power. And defining the output as five modes according to the operation scheme of the electrolytic hydrogen production system. And secondly, establishing a fuzzy rule, wherein the fuzzy rule is defined as that the stronger the illumination is, the larger the output power is, the stronger the wind power is, and the larger the output power is. And then, calculating the membership degree of the alkaline electrolytic hydrogen production system applying fuzzy control. And finally, clearly judging the working mode of the electrolytic hydrogen production system at the moment by outputting the membership map. The invention is used for the alkaline electrolytic hydrogen production system with the operation modes changed according to different environments, thereby realizing the efficient and economic operation of the alkaline electrolytic hydrogen production system under the condition of randomly fluctuating new energy input, avoiding the influence on equipment caused by frequent start-stop, prolonging the service life of the system and improving the stability of the system.
The technical scheme of the invention is as follows:
a fuzzy control method for an alkaline electrolytic hydrogen production system, comprising the following steps:
s1, fuzzifying input energy of an alkaline electrolytic hydrogen production system through a membership function, simultaneously carrying out fuzzy definition according to energy intensity, and defining a fuzzy definition interval, wherein the input energy has a nonlinear real-time characteristic;
s2, fuzzifying the output power of the alkaline electrolytic hydrogen production system through a membership function, setting a working mode of the alkaline electrolytic hydrogen production system according to the result of the S1, and selecting the membership degree of the fuzzy function to describe the working mode to obtain the membership relation between the real-time input energy and the output power as well as the working mode;
s3, establishing a fuzzy rule that the output power is increased along with the increase of the input energy;
s4, converting real-time input energy into real-time membership through a fuzzy rule;
s5, constructing a membership function according to the real-time membership degree, and solving membership output through an output operation rule;
and S6, controlling the alkaline electrolytic hydrogen production system by defuzzification membership output and selecting a corresponding working mode based on the membership relation.
Further, the input energy in S1 includes solar energy and wind energy, and the fuzzy definition manner of the solar energy is as follows: the input illumination intensity blur is defined as four levels, respectively: first level of over-illumination, defined as EL; second level moderate lighting, defined as PL; the third stage lacks illumination, defined as LL; the fourth-level is free of illumination and is defined as OL;
the fuzzy definition of wind energy is as follows: input wind intensity is defined as four levels, respectively: the first stage of excess wind energy is defined as EW; a second stage of moderate wind energy, defined as PW; the third stage lacks wind energy, defined as LW; the fourth-stage is wind-free and defined as OW;
the range of the solar energy and the wind energy of each grade of the division is set, so that a fuzzy definition interval is defined.
Furthermore, the power supply end of the alkaline electrolysis hydrogen production system comprises solar energy, wind energy, a storage battery and a power grid, wherein the solar energy and the wind energy form a system power generation end, and the storage battery is a system power storage end; the electricity end of the alkaline electrolysis hydrogen production system is an electrolytic cell.
Further, the operation modes in S2 include five, which are respectively: the first working module corresponds to a system, wherein the power generation power of a power generation end is smaller than the power consumption power of a power consumption end, at the moment, the system purchases power from a power grid, and meanwhile, a storage battery supplies power to the system, and the first working module is defined as M1; in the second working mode, the power generation power of the corresponding system power generation end is smaller than the power consumption power of the power consumption end, and at the moment, only the storage battery supplies power to the system, which is defined as M2; in the third working mode, the power generation power of the power generation end of the corresponding system is equal to the power consumption power of the power consumption end, and the power generation power is defined as M3; in the fourth working mode, the power generation power of the power generation end of the corresponding system is larger than the power consumption power of the power consumption end, and the system stores redundant electric energy to the power storage end, which is defined as M4; in the fifth working mode, the power generation power of the power generation end of the corresponding system is larger than the power consumption power of the power consumption end, and after the system stores redundant electric energy into the power storage end, the redundant electric energy is input into a power grid and is defined as M5.
Furthermore, in S2, a triangular membership function is used for representing the membership degree of real-time solar energy, wind energy and an output mode, and a light intensity membership function graph, a wind intensity membership function graph and an output system operation mode membership function graph are drawn.
Further, in S4, the solar energy and wind energy levels defined in S2 are used to represent the membership degrees of the solar energy and the wind energy, specifically: defining the membership degree corresponding to the solar energy x as EL = a1, PL = b1, LL = c1, OL = d1, a1+ b1+ c1+ d1=1; defining the corresponding membership degrees of the wind energy y as EW = a2, PW = b2, LW = c2, OW = d2, a2+ b2+ c2+ d2=1;
and assigning the membership degrees according to the real-time solar energy and the wind energy to obtain the real-time membership degrees, and drawing a membership function graph corresponding to the illumination intensity x and a membership function graph corresponding to the wind intensity y.
Further, in S6, the membership output graph is defuzzified by using an area center method to obtain membership function graphs of corresponding area centers of the membership output graph, and the membership function graphs are respectively used
Representing the area formed by each piecewise function curve and the horizontal axis
The horizontal coordinate of the gravity center of a graph formed by each piecewise function curve and the horizontal axis is represented;
can respectively calculate from left to right
And
can be calculated according to the area center formula:
deducing the center of area of membership function
The abscissa, therefore, the corresponding output Mn can be known through the clarity of the membership function graph of the corresponding area center of the membership output graph, n is more than or equal to 1 and less than or equal to 5, and the control of the alkaline electrolysis hydrogen production system is realized according to the corresponding working mode.
The fuzzy control method for the alkaline electrolysis hydrogen production system has the advantages that fuzzification is carried out on input and output of the electrolysis hydrogen production, different fuzzy definitions are carried out on different scenes, fuzzy rules are established, and finally, the fuzzification is carried out through membership. Thereby obtaining the optimal working mode of the alkaline electrolytic cell under different wind power and illumination intensity scenes. Specifically, the following advantages are provided: (1) The invention provides a fuzzy control method for an alkaline electrolysis hydrogen production system, which can adjust the operation mode of an electrolytic cell according to the time-varying illumination intensity and the wind power intensity, and improves the stability of the system. (2) The invention adopts the variable current control mode to operate, reduces the opening frequency of the electrolytic bath Guan Qiting and prolongs the service life of the electrolytic bath. (3) Compared with the traditional alkaline electrolysis hydrogen production system, the invention uses fuzzy control to ensure that the electrolysis system can automatically use different electrolysis modes to operate the electrolytic cell on the basis of random change of illumination intensity and wind power intensity in different environments at different time, thereby improving the hydrogen production efficiency of the electrolysis hydrogen production system. (4) The invention reasonably utilizes new energy photovoltaic power generation and wind power generation to carry out electrolytic hydrogen production, energy storage and grid connection by using fuzzy control, thereby improving the overall economy of the system.
Drawings
FIG. 1 is a diagram of an electric-hydrogen fusion integrated energy system.
Fig. 2 is a flow chart of the fuzzy control.
FIG. 3 is a graph of membership functions for illumination intensities.
FIG. 4 is a graph of membership functions for wind intensity.
FIG. 5 is a graph of membership functions for the operating modes of the output system.
Fig. 6 is a graph of the intensity of illumination x versus membership function.
FIG. 7 is a graph of wind intensity y versus membership function.
FIG. 8 is a graph of output mode versus membership function.
FIG. 9 is a membership output graph.
FIG. 10 is a graph of membership output plots versus area center membership functions.
FIG. 11 is a block diagram of an electric-hydrogen fusion integrated energy system using fuzzy control.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, so that those skilled in the art can better understand the present invention.
The invention discloses a fuzzy control method for an alkaline electrolysis hydrogen production system. Aiming at the nonlinear and time-varying process of wind power generation and photovoltaic effect and transmission to the electrolytic bath. In order to avoid frequent start-stop of the electrolytic cell, increase economic benefits, maintain stable operation of the electrolytic cell, and improve the efficiency of the electrical hydrogen production, a fuzzy control method for the alkaline electrolytic hydrogen production system is provided. Fuzzy control is a rule-based control that directly uses linguistic control rules without the need to build an accurate mathematical model of the controlled object in the design. Because the robustness of the fuzzy control system is strong, the influence of interference and parameter change on the control effect is greatly weakened, the fuzzy control system is very suitable for objects which are difficult to obtain mathematical models and difficult to master dynamic characteristics or have obvious change, and is particularly suitable for the control of nonlinear and time-varying systems. According to the invention, the input and output of the electrolytic hydrogen production are fuzzified, different fuzzy definitions are carried out on different scenes, a fuzzy rule is established, and finally the fuzzification is carried out through membership. The electrolysis system can automatically operate the electrolysis bath by using different electrolysis modes on the basis of random changes of illumination intensity and wind power intensity in different environments at different time. Therefore, the electrolytic hydrogen production system has high efficiency and economy, and a fuzzy control method for the alkaline electrolytic hydrogen production system is formed.
As shown in fig. 1, the system is an electric-hydrogen fusion comprehensive energy system, wherein a wind turbine generator and a photovoltaic array are solar energy and wind energy power generation ends, and are used for supplying power to an electrolytic cell through a direct current bus after conversion, and meanwhile, the direct current bus is also connected with a power grid and a storage battery and is used for supplying power to the electrolytic cell when the electric energy of the power generation ends is insufficient.
Fig. 2 is a flow chart of fuzzy control, in which fuzzy control is fuzzification input, module reasoning is performed by a fuzzy rule, and control output is obtained by resolving the fuzzy.
Example (b):
the specific steps of the example comprise:
step 1: fuzzifying the input quantity through a membership function to define a fuzzy definition interval:
defining the input illumination intensity ambiguity as four levels EL (excessive illumination), PL (moderate illumination), LL (lack of illumination), OL (no illumination) according to the illumination radiation intensity;
fuzzy definition of input wind strength as four grades EW (excess wind energy), PW (moderate wind energy), LW (lack of wind energy), OW (no wind energy) according to the wind strength;
and defining the range between the illumination intensity and the wind intensity of different grades to define a fuzzy definition interval.
Step 2: fuzzifying the output quantity through a membership function, selecting a fuzzy function, and matching an output mode according to input:
the output is defined as five modes: m1 (the system power generation power is less than the power consumption power, the electricity is purchased from a power grid, and meanwhile, a storage battery also discharges to an electrolytic cell), M2 (the system power generation power is less than the power consumption power and is only supplied by the storage battery), M3 (the system power generation power is equal to the power consumption power, and the power generation power is all used for the operation of the electrolytic cell), M4 (the system power generation power is greater than the power consumption power, and redundant energy is absorbed by the storage battery), M5 (the system power generation power is greater than the power consumption power, and the storage battery has redundant parts after absorbing according to the maximum power, and is connected with the power grid through AC/DC at the moment); and (3) expressing the membership degree (the variation range is 0-1) of the real-time illumination and wind power and output mode by using a triangular membership function, and drawing an illumination intensity membership function graph as shown in figure 3, a wind power intensity membership function graph as shown in figure 4 and an output system operation mode membership function graph as shown in figure 5.
And step 3: establishing a fuzzy rule, which is defined as that the stronger the illumination is, the larger the output power is, the stronger the wind power is, and the larger the output power is, wherein the fuzzy rule of the embodiment is shown in table 1.
TABLE 1 fuzzy rule corresponding table
And 4, step 4: according to the real-time weather condition, converting the wind power intensity and the illumination intensity into real-time membership through a fuzzy rule:
in this example, setting a strong day and breezy weather, the intensity of illumination x corresponds to the membership degree of EL =0.7, PL =0.3; the corresponding membership degree of the wind intensity y is LW =0.4, OW =0.6;
and drawing a graph of the corresponding membership function of the illumination intensity x as shown in FIG. 6 and a graph of the corresponding membership function of the wind intensity y as shown in FIG. 7.
And 5: constructing a membership function according to the step 4, and solving membership output through an output operation rule:
establishing an output operation rule according to the membership function and the fuzzy rule established in the step 4
Obtaining a membership function graph corresponding to the output mode according to the operation rule, as shown in FIG. 8;
and (4) solving a membership output graph by taking a union set of the membership function graphs corresponding to the output modes, as shown in FIG. 9.
Step 6: and (3) clarifying the output membership map to obtain the optimal working mode of the alkaline electrolytic cell suitable for the weather at the moment:
performing defuzzification on the membership output graph by using an area center method to obtain a membership function graph of the corresponding area center of the membership output graph, as shown in FIG. 10, respectively
Representing the area formed by each piecewise function curve and the horizontal axis
The abscissa of the center of gravity of a graph formed by each piecewise function curve and the horizontal axis is represented. Assume M =1;
can respectively calculate from left to right
And
can be calculated according to the area center formula:
deducing the center of area of membership function
The abscissa is 0.519, so the corresponding output is M3 as can be clearly seen by the membership output graph corresponding to the area center membership function graph, and the electrolytic cell should be operated in mode 3 at this time.
As shown in fig. 11, the system is a block diagram of an electro-hydrogen fusion comprehensive energy system adopting fuzzy control, and it can be seen that compared with the prior art, the fuzzy control of the invention realizes the operation mode change according to different environments, thereby realizing the efficient and economic operation of the alkaline electrolytic hydrogen production system under the condition of randomly fluctuating new energy input, avoiding the influence of frequent start-up and shut-down on the equipment, prolonging the service life of the system, and improving the stability of the system.
Claims (6)
1. A fuzzy control method for an alkaline electrolysis hydrogen production system, which is characterized by comprising the following steps:
s1, fuzzifying input energy of an alkaline electrolysis hydrogen production system through a membership function, simultaneously carrying out fuzzy definition according to energy intensity, and defining a fuzzy definition interval, wherein the input energy has a nonlinear real-time characteristic; the input energy comprises solar energy and wind energy, and the fuzzy definition mode of the solar energy is as follows: input illumination intensity blur is defined as four levels, respectively: first level of over-illumination, defined as EL; second level of moderate lighting, defined as PL; the third stage lacks illumination, defined as LL; the fourth-level is free of illumination and is defined as OL;
the fuzzy definition of wind energy is as follows: input wind intensity is defined as four levels, respectively: the first stage of excess wind energy is defined as EW; a second stage of moderate wind energy, defined as PW; the third stage lacks wind energy, defined as LW; the fourth-grade is without wind energy and is defined as OW;
setting the range of the divided solar energy and wind energy of each grade so as to define a fuzzy definition interval;
s2, fuzzifying the output power of the alkaline electrolytic hydrogen production system through a membership function, setting a working mode of the alkaline electrolytic hydrogen production system according to the result of the S1, and selecting the membership degree of the fuzzy function to describe the working mode to obtain the membership relation between the real-time input energy and the output power as well as the working mode;
s3, establishing a fuzzy rule that the output power is increased along with the increase of the input energy;
s4, converting the real-time input energy into real-time membership through a fuzzy rule;
s5, constructing a membership function according to the real-time membership degree, and solving membership output through an output operation rule;
and S6, controlling the alkaline electrolytic hydrogen production system by defuzzification membership output and selecting a corresponding working mode based on the membership relation.
2. The fuzzy control method for the alkaline electrolytic hydrogen production system according to claim 1, wherein the power supply end of the alkaline electrolytic hydrogen production system comprises solar energy, wind energy, a storage battery and a power grid, wherein the solar energy and the wind energy form a system power generation end, and the storage battery is a system power storage end; the electricity end of the alkaline electrolysis hydrogen production system is an electrolytic cell.
3. The fuzzy control method for the alkaline electrolytic hydrogen production system according to claim 2, wherein the operation mode in S2 comprises five modes, which are respectively: the first working module corresponds to a system, wherein the power generation power of a power generation end is smaller than the power consumption power of a power consumption end, at the moment, the system purchases power from a power grid, and meanwhile, a storage battery supplies power to the system, and the first working module is defined as M1; in the second working mode, the power generation power of the corresponding system power generation end is smaller than the power consumption power of the power consumption end, and at the moment, only the storage battery supplies power to the system, which is defined as M2; in a third working mode, the power generation power of the power generation end of the corresponding system is equal to the power consumption power of the power consumption end, and the power generation power is defined as M3; in a fourth working mode, the power generation power of the power generation end of the corresponding system is larger than the power consumption power of the power consumption end, and the system stores redundant electric energy to the power storage end, wherein the power storage end is defined as M4; in the fifth working mode, the power generation power of the power generation end of the corresponding system is larger than the power consumption power of the power consumption end, and after the system stores redundant electric energy into the power storage end, the redundant electric energy is input into a power grid and is defined as M5.
4. The fuzzy control method for the alkaline electrolysis hydrogen production system according to claim 3, wherein a triangular membership function is used in S2 to represent membership degrees of real-time solar energy and wind energy and an output mode, and an illumination intensity membership function graph, a wind intensity membership function graph and an output system operation mode membership function graph are drawn.
5. The fuzzy control method for the alkaline electrolysis hydrogen production system according to claim 4, wherein in S4, the degrees of membership of solar energy and wind energy are represented by the solar energy and wind energy grades defined in S2, and specifically: defining the membership degree corresponding to the solar energy x as EL = a1, PL = b1, LL = c1, OL = d1, a1+ b1+ c1+ d1=1; defining the corresponding membership degrees of the wind energy y as EW = a2, PW = b2, LW = c2, OW = d2, a2+ b2+ c2+ d2=1;
and assigning the membership degrees according to the real-time solar energy and wind energy to obtain the real-time membership degrees, and drawing a membership function graph corresponding to the illumination intensity x and a membership function graph corresponding to the wind intensity y.
6. The fuzzy control method for the alkaline electrolysis hydrogen production system according to claim 5, wherein in S6, the membership output graph is defuzzified by an area center method to obtain a membership function graph corresponding to the area center of the membership output graph, and S is used for each i (i =1, …, 7) represents the area of each piecewise function curve with the horizontal axis, and u represents the area i (i =1, …, 7) represents the barycentric coordinate of a graph formed by each piecewise function curve and the abscissa axis;
from left to right, S can be respectively calculated i (i =1, …, 7) and u i (i =1, …, 7), according to the area center formula:
deducing the area center u of the membership function ov And the abscissa, therefore, the corresponding output is Mn through the clearness of the membership output graph corresponding to the area center membership function graph, n is more than or equal to 1 and less than or equal to 5, and the control of the alkaline electrolytic hydrogen production system is realized according to the corresponding working mode. />
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