MPC predictive control and power purchase cost optimization method of photovoltaic hydrogen production system

Abstract

The invention discloses an MPC predictive control and power purchase cost optimization method for a photovoltaic hydrogen production system, and belongs to the technical field of photovoltaic hydrogen production. After a photovoltaic system in the system passes through a boost converter and a full-bridge circuit, an output direct current passes through a first excitation inductor and is connected with a first winding; after the power grid passes through the rectifier and the full-bridge circuit, output direct current flows through the second excitation inductor and is connected with the second winding; after the fuel cell passes through the boost converter and the full-bridge circuit, the output direct current flows through the third excitation inductor and is connected with the third winding; after the electrolytic tank passes through a buck converter and a full-bridge circuit, the output direct current is connected with a fourth winding through a fourth excitation inductor; the hydrogen storage tank is connected with the electrolytic cell and the fuel cell; based on the system, an MPC predictive control algorithm is added into the electrolytic cell converter, and a Z-score function is carried out when the system purchases electricity from a power grid to calculate the optimal electricity purchase time. According to the invention, the optimization of the hydrogen production efficiency, the hydrogen production amount and the system cost of the system is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic hydrogen production, and in particular to an MPC prediction control and electricity purchase cost optimization strategy for a photovoltaic hydrogen production system. Background Art

[0002] With the development of green energy and hydrogen energy industries, photovoltaic hydrogen production has gradually become an important clean energy conversion and energy storage technology. However, the volatility of photovoltaic power generation, the volatility of grid electricity prices, and the uncertainty of hydrogen demand make the design of optimization control strategies particularly important. The electrolyzer requires the input power and the output power of the photovoltaic system to achieve the minimum error, which can improve the energy utilization of the photovoltaic hydrogen production system, maximize hydrogen production, and improve hydrogen production efficiency. For the photovoltaic hydrogen production system, the error between the output power of the photovoltaic system and the input power of the electrolyzer is required to be as small as possible, so as to maximize the energy utilization of the photovoltaic hydrogen production system and improve the hydrogen production efficiency. At the same time, the photovoltaic hydrogen production system is usually connected to the power grid, which can use the electricity generated by photovoltaic power generation, or purchase electricity from the power grid when photovoltaic power generation is insufficient. Since the power purchase price of the power grid may have peak and valley electricity price differences, it is necessary to purchase electricity when the purchase cost is optimized. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide an MPC predictive control and electricity purchase cost optimization strategy for a photovoltaic hydrogen production system, which can achieve the optimal electricity purchase cost while realizing the synchronous tracking of the electrolyzer input power and the photovoltaic system output power.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0005] A method for MPC prediction control and electricity purchase cost optimization of a photovoltaic hydrogen production system, wherein the photovoltaic hydrogen production system comprises a photovoltaic system, a power grid, an electrolyzer, a hydrogen storage tank and a fuel cell; the photovoltaic system is connected to the power grid, and supplies power to the power grid side through a boost converter, and the remaining power is used as input power to the electrolyzer converter through a transformer, and the hydrogen produced by the electrolyzer is delivered to the hydrogen storage tank. When the photovoltaic system does not supply enough power to the power grid, the hydrogen in the hydrogen storage tank is delivered to the fuel cell, and the fuel cell generates electricity, and the power supply of the photovoltaic system is compensated by the boost converter, so that the overall photovoltaic hydrogen production system is stable.

[0006] The MPC predictive control and electricity purchase cost optimization method of the photovoltaic hydrogen production system includes the following steps:

[0007] Step 1, set the initial iteration cycle number t = 1; the input current i of the electrolytic cell E 、The output current i of the photovoltaic system s , fuel cell input current Output Current Input voltage and output voltage Sampling is performed, and after sampling, the input power P of the electrolyzer is calculated. E 、The output power P of the photovoltaic system S , the charging power of the fuel cell p BS,Chg (t) and discharge power p BS,Dhg (t);

[0008] Step 2: Determine whether the output power of the photovoltaic system can meet the power demand of the grid P G If the demand can be met, the remaining power is input to the electrolyzer converter, and the input current i of the electrolyzer is optimized by performing MPC predictive control on the electrolyzer converter. E The generated hydrogen is stored in the hydrogen storage tank, and the remaining electricity is sold to the grid; if it cannot be met, proceed to step 3;

[0009] Step 3: Determine the discharge power p of the fuel cell BS,Dhg (t) Whether the remaining demand of the power grid can be met G -P S ; If it can be met, the hydrogen in the hydrogen storage tank is used to provide raw materials for the fuel cell; if it cannot be met, proceed to step 4;

[0010] Step 4: Purchase electricity from the power grid, sample historical electricity prices, calculate the Z-score function to obtain the optimal electricity purchase time, and reduce the electricity purchase cost;

[0011] Step 5: Determine whether the cycle time t is equal to 8760, so as to satisfy the cycle within one year.

[0012] A further improvement of the technical solution of the present invention is that the photovoltaic hydrogen production system realizes photovoltaic hydrogen production based on five modules, namely:

[0013] Photovoltaic system module: The photovoltaic system is connected to both ends of the full-bridge circuit through a DC-DC boost converter, and the output DC current is connected to the first winding N1 through the first excitation inductor L1;

[0014] Grid module: The grid outputs direct current through the rectifier and is connected to both ends of the full-bridge circuit. The output direct current is connected to the second winding N2 through the second excitation inductor L2;

[0015] Fuel cell module: The fuel cell is connected to both ends of the full-bridge circuit through a DC-DC boost converter, and the output DC current is connected to the third winding N3 through the third excitation inductor L3;

[0016] Electrolyzer module: The electrolyzer is connected to both ends of the full-bridge circuit through a DC-DC buck converter, and the output DC current is connected to the fourth winding N4 through the fourth excitation inductor L4;

[0017] Hydrogen storage tank module: connects the electrolyzer and the fuel cell module; each module’s full-bridge circuit consists of four sets of switch tubes S a1 -S a4 , S b1 -S b4 , S c1 -S c4 , S d1 -S d4 constitute.

[0018] A further improvement of the technical solution of the present invention is that in step 2, the MPC predictive control specifically includes the following contents:

[0019] Construct the objective function of MPC predictive control:

[0020]

[0021] Where N p is the prediction step size, N p =30;P E (k+1) is the input power of the electrolyzer at time k+1; i E (k+1) is the input current of the electrolytic cell at time k+1; P S (k+l) is the output power of the photovoltaic system;

[0022] The objective function J is minimized by iterative Newton method to obtain the optimal input current of the electrolytic cell in the optimal state;

[0023] Define the error between the electrolyzer input power and the photovoltaic system output power as E G (t) = P E (t)-P s (t), E G (t) is subjected to first-order Taylor approximation, and we get E G (t) The linear expression is: Similarly, the electrolytic cell input current is obtained And the output power of photovoltaic system Further, the error E G (t), electrolytic cell input current and photovoltaic system output power Discretization processing and Newton's method iteration cycle are performed on the error to obtain:

[0024]

[0025] In the objective function, P E (k+l)-P s The essence of (k+l) is the error between the input power of the electrolyzer converter and the maximum output power of the photovoltaic system. Just search for the best result;

[0026] The Newton method iteration equation is:

[0027]

[0028] Therefore, the problem of solving the minimum value of the objective function J is transformed into solving the error by Newton's method iteration;

[0029] The relationship between the input voltage and current of the electrolytic cell is as follows:

[0030]

[0031] Where V rev is the reversible voltage of the electrolytic cell, which is 1.299V; r e The resistance of the electrolytic cell is 6.89×10 -5 Ω·m 2 ;s e Take 0.185v as the overvoltage coefficient of the electrolytic cell, t e is the coefficient of the relationship between the overvoltage and current of the electrolytic cell, which is 0.2596m 2 / A; A is the electrode area, A=0.013m 2 ; Input voltage v to the electrolytic cell E (i E ) expression is substituted into the above formula to perform Newton method iteration of the error function;

[0032] Define the constraints of the control variables: In an ideal state, without considering the constraints of the hydrogen storage capacity of the hydrogen storage tank, when (P E (i E )-P s (t)) 2 When the minimum value is obtained, the input current i of the electrolytic cell can be obtained. E The maximum value of

[0033] Define the function g(i E )=(P E (i E )-P s (t)) 2 , for g(i E ) and we get:

[0034]

[0035] Note that the input power P of the electrolyzer E (i E ) is an increasing function of the electrolytic cell input current, so the input current i of the electrolytic cell is solved E The maximum value, that is, when P E (i E )=Ps When P s is the maximum output power of the photovoltaic system;

[0036] When the iteration result reaches the constraint condition, the iteration process is stopped and the optimal input current i of the electrolyzer converter is obtained. E out , the sampled photovoltaic system output voltage v s , the input current to the electrolyzer converter through the transformer for:

[0037]

[0038] Because the electrolytic cell converter is a step-down converter, the duty cycle of the electrolytic cell converter is calculated as:

[0039]

[0040] A further improvement of the technical solution of the present invention is that in step 4, the power purchase cost function of the power grid is as follows:

[0041]

[0042] In the formula, is the electricity price at time t; is the average of historical electricity prices; is the standard deviation of historical electricity prices;

[0043] For the grid-side rectifier, the SPWM three-phase circuit control strategy is used to adjust the power purchased from the grid by changing the current reference value of the current loop PI controller;

[0044] The following constraints apply to the grid power:

[0045]

[0046] In the formula, The power purchased by the power grid, and are the minimum and maximum power purchase power of the power grid respectively; and Determined by the power supply capacity of the power grid and the equipment requirements;

[0047] When Z-score is less than 0, it means that the electricity price is lower than the historical lowest value. That is, the photovoltaic hydrogen production system should increase the amount of electricity purchased from the grid, at which time the current reference value of the grid rectifier current loop PI control is increased and the grid output power is controlled within the constraint conditions;

[0048] When Z-score>0, it means that the electricity price is higher than the historical lowest value, and the That is, the photovoltaic hydrogen production system should reduce the amount of electricity purchased from the power grid; at this time, the current reference value of the grid rectifier current loop PI control is reduced and the grid output power is controlled within the constraints.

[0049] Due to the adoption of the above technical solution, the technical progress achieved by the present invention is:

[0050] In the present invention, after the photovoltaic system passes through the DC-DC boost converter and the full-bridge circuit, the output DC current is connected to the winding N1 through the excitation inductor L1; after the power grid passes through the rectifier and the full-bridge circuit, the output DC current is connected to the winding N2 through the excitation inductor L2; after the fuel cell passes through the DC-DC boost converter and the full-bridge circuit, the output DC current is connected to the winding N3 through the excitation inductor L3; after the electrolyzer passes through the DC-DC buck converter and the full-bridge circuit, the output DC current is connected to the winding N4 through the excitation inductor L4; the hydrogen storage tank connects the electrolyzer and the fuel cell; based on this structure, an MPC predictive control algorithm is added to the electrolyzer converter, and a Z-score function is used to calculate the optimal power purchase time when the system purchases electricity from the power grid, thereby achieving the optimization of the system hydrogen production efficiency, hydrogen production and system cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 is a circuit diagram of a photovoltaic hydrogen production system provided in an embodiment of the present invention;

[0053] Figure 2 It is a control flow chart of the MPC prediction control and electricity purchase cost optimization method of the photovoltaic hydrogen production system provided in the embodiment of the present invention. DETAILED DESCRIPTION

[0054] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or apparatus.

[0055] The present invention is further described in detail below with reference to the accompanying drawings and embodiments:

[0056] like Figure 1 As shown, a MPC predictive control and electricity purchase cost optimization method for a photovoltaic hydrogen production system specifically includes the following contents:

[0057] The photovoltaic hydrogen production system includes a photovoltaic system, a power grid, an electrolyzer, a hydrogen storage tank and a fuel cell. The specific connection method is: the photovoltaic system is connected to the power grid, and power is supplied to the grid side through a boost converter. The remaining power is used as input power to the electrolyzer converter through a transformer. The hydrogen produced by the electrolyzer is transported to the hydrogen storage tank. When the photovoltaic system does not supply enough power to the power grid, the hydrogen in the hydrogen storage tank is transported to the fuel cell. The fuel cell generates electricity and makes up for the power supply of the photovoltaic system through the boost converter, so that the overall photovoltaic hydrogen production system is stable.

[0058] The constructed photovoltaic hydrogen production system model realizes photovoltaic hydrogen production based on five modules, including photovoltaic system module, power grid module, fuel cell module, electrolyzer module and hydrogen storage tank module. They are:

[0059] Photovoltaic system module: The photovoltaic system is connected to both ends of the full-bridge circuit through a DC-DC boost converter, and the output DC current is connected to the first winding N1 through the first excitation inductor L1;

[0060] Grid module: The grid outputs direct current through the rectifier and is connected to both ends of the full-bridge circuit. The output direct current is connected to the second winding N2 through the second excitation inductor L2;

[0061] Fuel cell module: The fuel cell is connected to both ends of the full-bridge circuit through a DC-DC boost converter, and the output DC current is connected to the third winding N3 through the third excitation inductor L3;

[0062] Electrolyzer module: The electrolyzer is connected to both ends of the full-bridge circuit through a DC-DC buck converter, and the output DC current is connected to the fourth winding N4 through the fourth excitation inductor L4;

[0063] Hydrogen storage tank module: connects the electrolyzer and the fuel cell module; each module’s full-bridge circuit consists of four sets of switch tubes S a1 -S a4 , S b1 -S b4 , S c1 -S c4 , S d1 -S d4 constitute.

[0064] like Figure 2 As shown, the MPC predictive control and electricity purchase cost optimization method of the photovoltaic hydrogen production system includes the following steps:

[0065] Step 1, set the initial iteration cycle number t = 1; sample the input current of the electrolytic cell to obtain i E , the output current of the photovoltaic system is sampled and i s , the fuel cell input current and output current are sampled and The input voltage and output voltage are sampled and After sampling, the input power P of the electrolyzer is calculated E 、The output power P of the photovoltaic system S , the charging power and discharging power p of the fuel cell BS,Chg (t) and p BS,Dhg (t);

[0066] Step 2: Determine the output power P of the photovoltaic system S Can it meet the power demand of the power grid? G If the demand can be met, the remaining power is input to the electrolyzer converter, and the current i of the input electrolyzer is optimized by performing MPC predictive control on the electrolyzer converter. E The generated hydrogen is stored in the hydrogen storage tank, and the remaining electricity is sold to the grid; if it cannot be met, proceed to step 3;

[0067] MPC predictive control specifically includes the following contents:

[0068] Construct the objective function of MPC predictive control:

[0069]

[0070] Among them, N p is the prediction step length. In this photovoltaic hydrogen production system, the prediction step length N p =30;P E (k+1) is the input power of the electrolyzer at time k+1; i E (k+l) is the input current of the electrolytic cell; P S (k+l) is the output power of the photovoltaic system.

[0071] The objective function J is minimized by iterative Newton method to obtain the optimal input current of the electrolytic cell in the optimal state.

[0072] Define the error between the electrolyzer input power and the photovoltaic system output power as E G (t) = P E (t)-P s (t), E G (t) is subjected to first-order Taylor approximation, and we get E G (t) The linear expression is: Similarly, the electrolytic cell input current is obtained And the output power of photovoltaic system Further, the error E G (t), electrolytic cell input current and photovoltaic system output power Discretization processing and Newton's method iteration cycle are performed on the error to obtain:

[0073]

[0074] In the objective function, P E (k+l)-P s The essence of (k+l) is the error between the input power of the electrolyzer converter and the maximum output power of the photovoltaic system, so we can directly Just search for the best solution.

[0075] The Newton method iteration equation is:

[0076]

[0077] Therefore, the problem of solving the minimum value of the objective function J is transformed into solving the error by Newton's method iteration.

[0078] The relationship between the input voltage and input current of the electrolytic cell is as follows:

[0079]

[0080] Where V rev is the reversible voltage of the electrolytic cell, usually 1.299V; r e The resistance of the electrolytic cell is 6.89×10 -5 Ω·m 2 、s e Take 0.185v as the overvoltage coefficient of the electrolytic cell, t e is the coefficient of the relationship between the overvoltage and current of the electrolytic cell, which is 0.2596m 2 / A; A is the electrode area, A=0.013m 2 .

[0081] The electrolytic cell is fed with a voltage v E (i E ) expression into the above formula to perform Newton's method iteration of the error function.

[0082] Define constraints on the control variables:

[0083] In an ideal state, without considering the constraints of the hydrogen storage capacity of the hydrogen storage tank, when (P E (i E )-P s (t)) 2 When the minimum value is obtained, the current i E The maximum value of .

[0084] Define the function g(i E )=(P E (i E )-P s (t)) 2 , for g(i E ) and we get:

[0085]

[0086] Note that the electrolyzer input power P E (i E ) is an increasing function of the electrolytic cell input current, so the solution for the electrolytic cell input current i E The maximum value, that is, when P E (i E )=P s At this time P s is the maximum output power of the photovoltaic system.

[0087] When the iteration result reaches the constraint condition, the iteration process is stopped and the optimal input current i of the electrolyzer converter is obtained. E out , according to the sampled photovoltaic system output voltage v s , the input current to the electrolyzer converter through the transformer for:

[0088]

[0089] Because the electrolytic cell converter is a step-down converter, the duty cycle of the electrolytic cell converter is calculated as:

[0090]

[0091] Step 3: Determine the fuel cell output power p BS,Dhg (t) Whether the remaining demand of the power grid can be met G -P S ; If it can be met, the hydrogen in the hydrogen storage tank is used to provide raw materials for the fuel cell; if it cannot be met, proceed to step 4;

[0092] Step 4: Purchase electricity from the power grid, sample historical electricity prices, calculate the Z-score function to obtain the optimal electricity purchase time, and reduce the electricity purchase cost;

[0093] Specifically, the power purchase cost of the power grid is compared with the lowest power purchase cost at the previous moment, and the best power purchase time and power purchase cost are selected through logical judgment, including:

[0094] The power purchase cost function of the power grid is as follows:

[0095]

[0096] in: is the electricity price at time t; is the average of historical electricity prices; is the standard deviation of the historical electricity price. For the grid-side rectifier, we use the SPWM three-phase circuit control strategy to adjust the power purchased from the grid by changing the current reference value of the current loop PI controller.

[0097] The following constraints apply to the grid power:

[0098]

[0099] in, The power purchased by the power grid, and They are the minimum and maximum power purchase power of the power grid, which is determined by the power supply capacity of the power grid and the equipment requirements.

[0100] When Z-score is less than 0, it means that the electricity price is lower than the historical lowest value. That is, the photovoltaic hydrogen production system should increase the amount of electricity purchased from the grid. At this time, the current reference value of the grid rectifier current loop PI control is increased and the grid output power is controlled within the constraints.

[0101] When Z-score>0, it means that the electricity price is higher than the historical lowest value, and the That is, the photovoltaic hydrogen production system should reduce the amount of electricity purchased from the grid. At this time, the current reference value of the grid rectifier current loop PI control is reduced and the grid output power is controlled within the constraint conditions.

[0102] Step 5, determine whether the cycle time t is equal to 8760, so as to satisfy the cycle within one year.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for MPC prediction control and electricity purchase cost optimization of a photovoltaic hydrogen production system, characterized in that: The photovoltaic hydrogen production system includes a photovoltaic system, a power grid, an electrolyzer, a hydrogen storage tank and a fuel cell. The photovoltaic system is connected to the power grid and supplies power to the power grid through a boost converter. The remaining power is used as input power to the electrolyzer converter through a transformer. The hydrogen produced by the electrolyzer is delivered to the hydrogen storage tank. When the photovoltaic system does not supply enough power to the power grid, the hydrogen in the hydrogen storage tank is delivered to the fuel cell. The fuel cell generates electricity and compensates for the power supply of the photovoltaic system through the boost converter, so that the overall photovoltaic hydrogen production system is stable. The MPC predictive control and electricity purchase cost optimization method of the photovoltaic hydrogen production system includes the following steps: Step 1, set the initial iteration cycle number t = 1; the input current i of the electrolytic cell E 、The output current i of the photovoltaic system s , fuel cell input current Output Current Input voltage and output voltage Sampling is performed, and after sampling, the input power P of the electrolyzer is calculated. E 、The output power P of the photovoltaic system S , the charging power of the fuel cell p BS,Chg (t) and discharge power p BS,Dhg (t); Step 2: Determine whether the output power of the photovoltaic system can meet the power demand of the grid P G If the demand can be met, the remaining power is input to the electrolyzer converter, and the input current i of the electrolyzer is optimized by performing MPC predictive control on the electrolyzer converter. E The generated hydrogen is stored in the hydrogen storage tank, and the remaining electricity is sold to the grid; if it cannot be met, proceed to step 3; Step 3: Determine the discharge power p of the fuel cell BS,Dhg (t) Whether the remaining demand of the power grid can be met G -P S ; If it can be met, the hydrogen in the hydrogen storage tank is used to provide raw materials for the fuel cell; if it cannot be met, proceed to step 4; Step 4: Purchase electricity from the power grid, sample historical electricity prices, calculate the Z-score function to obtain the optimal electricity purchase time, and reduce the electricity purchase cost; Step 5: Determine whether the cycle time t is equal to 8760, so as to satisfy the cycle within one year.

2. The MPC prediction control and electricity purchase cost optimization method of a photovoltaic hydrogen production system according to claim 1 is characterized in that: The photovoltaic hydrogen production system realizes photovoltaic hydrogen production based on five modules, namely: Photovoltaic system module: The photovoltaic system is connected to both ends of the full-bridge circuit through a DC-DC boost converter, and the output DC current is connected to the first winding N1 through the first excitation inductor L1; Grid module: The grid outputs direct current through the rectifier and is connected to both ends of the full-bridge circuit. The output direct current is connected to the second winding N2 through the second excitation inductor L2; Fuel cell module: The fuel cell is connected to both ends of the full-bridge circuit through a DC-DC boost converter, and the output DC current is connected to the third winding N3 through the third excitation inductor L3; Electrolyzer module: The electrolyzer is connected to both ends of the full-bridge circuit through a DC-DC buck converter, and the output DC current is connected to the fourth winding N4 through the fourth excitation inductor L4; Hydrogen storage tank module: connects the electrolyzer and the fuel cell module; each module’s full-bridge circuit consists of four sets of switch tubes S a1 -S a4 , S b1 -S b4 , S c1 -S c4 , S d1 -S d4 constitute.

3. The MPC prediction control and electricity purchase cost optimization method of a photovoltaic hydrogen production system according to claim 1 is characterized in that: In step 2, MPC predictive control specifically includes the following: Construct the objective function of MPC predictive control: Where N p is the prediction step size, N p =30;P E (k+1) is the input power of the electrolyzer at time k+1; i E (k+1) is the input current of the electrolytic cell at time k+1; P S (k+l) is the output power of the photovoltaic system; The objective function J is minimized by iterative Newton method to obtain the optimal input current of the electrolytic cell in the optimal state; Define the error between the electrolyzer input power and the photovoltaic system output power as E G (t) = P E (t)-P s (t), E G (t) is subjected to first-order Taylor approximation, and we get E G (t) The linear expression is: Similarly, the electrolytic cell input current is obtained And the output power of photovoltaic system Further, the error E G (t), electrolytic cell input current and photovoltaic system output power Discretization processing and Newton's method iteration cycle are performed on the error to obtain: In the objective function, P E (k+l)-P s The essence of (k+l) is the error between the input power of the electrolyzer converter and the maximum output power of the photovoltaic system. Just search for the best result; The Newton method iteration equation is: Therefore, the problem of solving the minimum value of the objective function J is transformed into solving the error by Newton's method iteration; The relationship between the input voltage and current of the electrolytic cell is as follows: Where V rev is the reversible voltage of the electrolytic cell, which is 1.299V; r e The resistance of the electrolytic cell is 6.89×10 -5 Ω·m 2 ; s e Take 0.185v as the overvoltage coefficient of the electrolytic cell, t e is the coefficient of the relationship between the overvoltage and current of the electrolytic cell, which is 0.2596m 2 / A; A is the electrode area, A=0.013m 2 ; Input voltage v to the electrolytic cell E (i E ) expression is substituted into the above formula to perform Newton method iteration of the error function; Define the constraints of the control variables: In an ideal state, without considering the constraints of the hydrogen storage capacity of the hydrogen storage tank, when (P E (i E )-P s (t)) 2 When the minimum value is obtained, the input current i of the electrolytic cell can be obtained. E The maximum value of Define the function g(i E )=(P E (i E )-P s (t)) 2 , for g(i E ) and we get: Note that the input power P of the electrolyzer E (i E ) is an increasing function of the electrolytic cell input current, so the input current i of the electrolytic cell is solved E The maximum value, that is, when P E (i E )=P s When P s is the maximum output power of the photovoltaic system; When the iteration result reaches the constraint condition, the iteration process is stopped and the optimal input current i of the electrolyzer converter is obtained. E out , the sampled photovoltaic system output voltage v s , the input current to the electrolyzer converter through the transformer for: Because the electrolytic cell converter is a step-down converter, the duty cycle of the electrolytic cell converter is calculated as:

4. The MPC prediction control and electricity purchase cost optimization method of a photovoltaic hydrogen production system according to claim 1 is characterized in that: In step 4, the power purchase cost function of the grid is as follows: In the formula, is the electricity price at time t; is the average of historical electricity prices; is the standard deviation of historical electricity prices; For the grid-side rectifier, the SPWM three-phase circuit control strategy is used to adjust the power purchased from the grid by changing the current reference value of the current loop PI controller; The following constraints apply to the grid power: In the formula, The power purchased by the power grid, and are the minimum and maximum power purchase power of the power grid respectively; and Determined by the power supply capacity of the power grid and the equipment requirements; When Z-score is less than 0, it means that the electricity price is lower than the historical lowest value. That is, the photovoltaic hydrogen production system should increase the amount of electricity purchased from the grid, at which time the current reference value of the grid rectifier current loop PI control is increased and the grid output power is controlled within the constraint conditions; When Z-score>0, it means that the electricity price is higher than the historical lowest value, and p should be reduced. t Grd , that is, the photovoltaic hydrogen production system should reduce the amount of electricity purchased from the grid; at this time, the current reference value of the grid rectifier current loop PI control is reduced and the grid output power is controlled within the constraints.

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