CN115986720A - New energy hydrogen production system coordination control method and device adaptive to hydrogen load fluctuation, electronic equipment and storage medium - Google Patents

New energy hydrogen production system coordination control method and device adaptive to hydrogen load fluctuation, electronic equipment and storage medium Download PDF

Info

Publication number
CN115986720A
CN115986720A CN202211474082.4A CN202211474082A CN115986720A CN 115986720 A CN115986720 A CN 115986720A CN 202211474082 A CN202211474082 A CN 202211474082A CN 115986720 A CN115986720 A CN 115986720A
Authority
CN
China
Prior art keywords
new energy
hydrogen
power
hydrogen production
production system
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202211474082.4A
Other languages
Chinese (zh)
Inventor
张潇桐
刘志力
袁铁江
苗帅
李家珏
戈阳阳
董鹤楠
孙广宇
马欣彤
姚红雨
谭捷
付尧
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Dalian University of Technology
State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Liaoning Electric Power Co Ltd
Original Assignee
Dalian University of Technology
State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Liaoning Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Dalian University of Technology, State Grid Corp of China SGCC, Electric Power Research Institute of State Grid Liaoning Electric Power Co Ltd filed Critical Dalian University of Technology
Publication of CN115986720A publication Critical patent/CN115986720A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315—Needs-based resource requirements planning or analysis
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J15/00—Systems for storing electric energy
    • H02J15/008—Systems for storing electric energy using hydrogen as energy vector
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/58—The condition being electrical
    • H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Physics & Mathematics (AREA)
  • Power Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Theoretical Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Game Theory and Decision Science (AREA)
  • Educational Administration (AREA)
  • General Business, Economics & Management (AREA)
  • Development Economics (AREA)
  • Marketing (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Tourism & Hospitality (AREA)
  • Pure & Applied Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Algebra (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Fuel Cell (AREA)

Abstract

The invention relates to a new energy hydrogen production system coordination control method, a device, electronic equipment and a storage medium adaptive to hydrogen load fluctuation, which comprises the following steps: determining a new energy hydrogen production system structure, and establishing an equivalent model of a vanadium redox flow battery, an electrolytic cell, a hydrogen storage tank and a super capacitor; constructing a state equation in a difference form, converting the equation into a matrix form, and obtaining a rolling optimization model through a state space expression; constructing an objective function, setting constraint conditions, and establishing a mathematical model for optimizing the operation of the hydrogen energy system; initializing a system, and performing minimum optimization on an objective function based on rolling optimization control to provide a system coordination control method; and (3) verifying an analysis example, and obtaining a new energy hydrogen production system coordination control method with optimal control performance for coordination control by changing the control performance and system robustness of the parameter analysis system. The method provided by the invention can be self-adaptive to hydrogen load fluctuation, and the optimal control method of the new energy hydrogen production system is solved by using rolling optimization control.

Description

New energy hydrogen production system coordination control method and device adaptive to hydrogen load fluctuation, electronic equipment and storage medium
Technical Field
The invention relates to the field of coordination control of a new energy hydrogen production system, in particular to a coordination control method and device of a new energy hydrogen production system, electronic equipment and a storage medium, wherein the coordination control method and device are adaptive to hydrogen load fluctuation.
Background
The new energy hydrogen production system generates hydrogen through new energy so as to achieve the purposes of improving the utilization rate of the new energy and meeting the hydrogen load requirement and the power grid load requirement of system design.
For a new energy hydrogen production system, firstly, the electrolytic cell control should safely and reliably cope with the output fluctuation of new energy and track the maximum power working point of the new energy, and secondly, the problem of power coordination needs to be considered to improve the power supply reliability of a power system. In addition, factors such as the efficiency of hydrogen production by electrolysis, technical and economic problems, and the fluctuation of hydrogen load need to be considered.
With the rapid increase of the demand of hydrogen energy, the structure and the application of an energy system can be greatly changed, and the influence of uncertainty caused by the fluctuation of hydrogen load on the safe and economic operation of the energy system cannot be ignored. Different from the overall response of the active frequency modulation of the power system, the uncertain hydrogen load fluctuation can cause the large-amplitude change of the working point of the electrolytic cell, the deterioration of the working condition of the local electrolytic cell can cause the overload and the stop of the electrolytic cell, the service life of the electrolytic cell is influenced, the safety of a gas storage tank and the reliability of hydrogen energy supply are endangered, and the safety and the stability of the power system are threatened by the power impact caused by the start and the stop of a large-scale electrolytic cell. In recent years, many scholars conduct research on power coordination control and economic dispatch, but optimal control of a new energy hydrogen production system adapting to hydrogen load fluctuation needs to be solved urgently.
Disclosure of Invention
In order to solve the technical problems, the invention provides a coordination control method, a coordination control device, electronic equipment and a storage medium for a new energy hydrogen production system adaptive to hydrogen load fluctuation, which are suitable for a hydrogen load fluctuation scene, based on a rolling optimization control principle, the hydrogen load flow rate, the actual maximum output of new energy, the start-stop state of an electrolytic cell and the like are used as system uncertainty interference, and the rolling optimization method is used for realizing the real-time tracking of the SOC of a vanadium redox flow battery, the air pressure of a hydrogen storage tank, the power grid load and the power of a super capacitor. The invention meets the hydrogen load requirement with the best working state and the minimum power regulating quantity through a rolling optimization method, optimizes the working states of the battery and the electrolytic cell, and reduces the shutdown time of the electrolytic cell.
In order to achieve the purpose, the invention adopts the technical scheme that:
the coordination control method of the new energy hydrogen production system capable of self-adapting to hydrogen load fluctuation comprises the following steps:
step S1: determining a new energy hydrogen production system structure, and establishing a new energy hydrogen production system equipment characteristic equation of the vanadium redox flow battery, the electrolytic cell, the hydrogen storage tank and the super capacitor according to the equipment operation characteristics;
step S2: constructing a state equation in a differential form through a dynamic model of a hydrogen energy system, establishing a model of the new energy hydrogen production system, converting the equation into a matrix form, and directly obtaining a rolling optimization model through a state space expression;
and step S3: determining a control target of the hydrogen energy system, determining a parameter value and a reference track, constructing an objective function, and establishing a mathematical model for optimizing the operation of the hydrogen energy system;
and step S4: initializing a reference track and system variables, adjusting the working state of each electrolytic cell in real time based on a rolling optimization method, adopting constant power control to adjust a super capacitor so as to meet the energy supply requirement of medium-long and short-time energy storage, and providing a new energy hydrogen production system coordination control method for iteratively controlling the electrolytic cells;
step S5: and verifying and analyzing an example, changing parameters such as an output variable weight factor, a control variable change increment weight factor, a reference time domain and the like, analyzing the change of the control performance of the system and the robustness of the system, and obtaining the new energy hydrogen production system coordination control method with the optimal control performance, thereby carrying out coordination control on the new energy hydrogen production system.
Further, the step S1 specifically includes:
step S11: determining a new energy hydrogen production system structure, wherein the new energy hydrogen production system structure comprises a new energy power supply, an external power grid, a vanadium redox flow battery, an electrolytic cell, a hydrogen storage tank, a super capacitor and a hydrogen load;
step S12: establishing a dynamic model of a new energy hydrogen production system, wherein the dynamic equivalent model of the vanadium redox flow battery is shown as a formula (1):
Figure SMS_1
wherein S is cell Is the charge quantity, P, of the vanadium redox flow battery cell For discharge power, Q, of vanadium flow battery cell The energy storage capacity of the vanadium redox flow battery is represented, and sigma is a self-decay time coefficient related to the charge capacity of the vanadium redox flow battery;
establishing an electrolytic cell model as shown in formula (2):
Figure SMS_2
wherein the content of the first and second substances,
Figure SMS_3
to produce the hydrogen rate, P elec For the input of power to the cell, A 1 And A 2 Is a linear approximation coefficient;
establishing a hydrogen storage tank model as shown in formula (3):
Figure SMS_4
wherein the content of the first and second substances,
Figure SMS_5
for the pressure change rate of the hydrogen storage tank>
Figure SMS_6
In order to produce hydrogen rate, R is an ideal gas constant, T is the thermodynamic temperature of the ideal gas, and V is the volume of the ideal gas;
establishing a super capacitor model as shown in formula (4):
Figure SMS_7
wherein E is the energy absorbed/released by the super capacitor, A and B are the serial and parallel numbers of the super capacitors, C f Is the individual capacitance of a supercapacitor, U 1 And U 2 The initial voltage and the state voltage of the super capacitor.
Further, the step S2 specifically includes:
step S21: constructing a state equation in a differential form according to a dynamic model of a hydrogen energy system;
according to the formula (1), establishing a state difference equation of the SOC of the vanadium redox flow battery, as shown in the formula (5):
Figure SMS_8
wherein, the delta tau is a time step;
according to the formulas (2) to (3), a state difference equation of the hydrogen storage tank gas pressure is established as shown in the formula (6):
Figure SMS_9
wherein the content of the first and second substances,
Figure SMS_10
is the hydrogen load flow rate, is based on>
Figure SMS_11
And &>
Figure SMS_12
Hydrogen change rates influenced by hydrogen production power and working state of each electrolytic cell are respectively set;
Figure SMS_13
and &>
Figure SMS_14
Expressed by functional, as shown in equations (7) to (8):
Figure SMS_15
/>
Figure SMS_16
wherein f is P (d elec ) As a function of the hydrogen production power of the electrolyzer, f d (d elec ) As a function of the operating conditions of the cell, P elec The hydrogen production power for each cell, delta being the Dirac function, P heat Heating power for cold standby, P sp Activating power for hot standby; d elec For the operating state of each cell, d elec.i E { l, s, w } represents normal operation, cold standby and hot standby respectively;
in consideration of the system power balance, the grid output power is expressed as formula (9):
P grid (t)＝P quit (t-1)+||P elec (t-1)|| 1 -P cell (t-1)-P renw (t-1) (9)
wherein, P quit Abandoning electric power for new energy, P renw The output power is new energy;
step S22: dividing the system variables into a state variable x, an output variable y, a control variable u and a disturbance variable p, wherein the state variable x is expressed as shown in a formula (10):
Figure SMS_17
wherein S is cell Is a vanadium flow battery SOC, p tank Is the gas pressure of the hydrogen storage tank, P grid Is the load of the power grid;
and (3) performing a series of transformations on the control variable u and the disturbance variable p, as shown in formulas (11) to (12):
Figure SMS_18
Figure SMS_19
wherein, P sc Is the power of a supercapacitor, U dsc Is the terminal voltage of the supercapacitor;
the following equation of state is then obtained:
Figure SMS_20
/>
the system state variables can be directly output, so the system output equation is shown in equation (14):
Figure SMS_21
step S23: the system state equation and the output equation are converted into a matrix form as shown in equation (15):
Figure SMS_22
wherein, A is a system state coefficient matrix, B is a control coefficient matrix, C is an output coefficient matrix, D is a disturbance coefficient matrix, and the matrixes are specifically expressed as formulas (16) to (19):
Figure SMS_23
Figure SMS_24
Figure SMS_25
Figure SMS_26
step S24: the rolling optimization model is directly obtained from the state space expression, as shown in equation (20):
Figure SMS_27
wherein the content of the first and second substances,
Figure SMS_28
the output variable value at the t + k moment is obtained according to the available information at the t moment in a prediction mode; u (t + k-1) denotes a control instruction acquired at the moment t; p (t + k-1 luminance t) represents the perturbation signal acquired at time t.
Further, the step S3 specifically includes the following steps:
step S31: determining a control target of a hydrogen energy system to ensure energy supply reliability on a time scale of medium and short time, ensuring that the SOC of the vanadium redox flow battery, the air pressure of a hydrogen storage tank, the power output of a power grid and the power of a super capacitor are required to track a scheduling plan, reducing the power adjustment amount of primary equipment as much as possible, and improving the energy conversion efficiency; constructing an objective function as shown in equation (21):
Figure SMS_29
wherein N is 1 Evaluating the upper bound for the prediction domain, N 2 Evaluating the lower bound for the prediction domain, N u Evaluating the boundaries for the control domain, t and j being different times, δ (j) being the weight of the output variable at time j, λ (j) being the weight of the control variable at time j, Q y As a matrix of output variable weight coefficients, Q u In order to control the variable weight coefficient matrix,
Figure SMS_30
for the expected output track of the system in a specific time range in the future, w (t + k | t) is a reference track, and Δ u is a variation value of a control variable;
step S32: determining prediction domain evaluation upper and lower bounds N 1 ，N 2 The parameter value of (2) ensures that the reference track w (t + j) is consistent with the dimension of the output variable;
step S33: setting the constraint condition of each specific element of the control variable, as shown in formula (22):
Figure SMS_31
wherein, P cell.charge And P cell.discharge Respectively the maximum charging and discharging power of the vanadium redox flow battery and the abandoned new energy power P quit (t) should be lower than the maximum theoretical output P of new energy renw (t)，P elec.min And P elec.max Minimum and maximum hydrogen production power, P, of the cell sc.c，max And P sc.d，max Maximum charge and discharge power for the supercapacitor;
setting the change rate of each element of the control variable, as shown in equation (23):
Figure SMS_32
wherein the content of the first and second substances,
Figure SMS_34
and &>
Figure SMS_37
Respectively regulating the response speed of the vanadium redox flow battery; />
Figure SMS_38
And
Figure SMS_35
the output of the new energy is down-regulated and the response speed of the new energy is up-regulated, and the output of the new energy is limited by the MPPT strategy of the new energy; />
Figure SMS_36
And &>
Figure SMS_39
Response speed is adjusted up and down for hydrogen production power of the electrolytic cell; />
Figure SMS_40
And &>
Figure SMS_33
Down-regulating and up-regulating response speed of the output of the super capacitor;
expanding the constraint condition of the change rate of the system output variable, as shown in the formula (24):
Figure SMS_41
wherein S is cell.min And S cell.max Minimum and maximum state of charge, p, of the vanadium redox flow battery respectively tank.min And p tank.max Respectively, the minimum and maximum pressure values, P, of the hydrogen storage tank grid.min And P grid.max Respectively, minimum and maximum power values for purchasing power from the power grid.
Further, the step S4 specifically includes:
step S41: adjusting the electrolytic cell in real time based on rolling optimization control, inputting a future reference track w (t + j), a control variable and current disturbance information, and repeatedly solving a quadratic programming problem to obtain a control signal u (t + 1) at the next moment;
step S42: calculating the power of the electrolytic cell, changing a working state change disturbance variable p of the electrolytic cell until all electrolytic cells are in a normal power state or all electrolytic cells which normally work at the current control moment are in a hot standby state, and stopping iterative solution to meet the energy supply requirement of medium-and-long-term energy storage;
step S43: the working state of the super capacitor is adjusted based on constant power control, a current deviation value is obtained through reference power, and the PI controller is adopted to realize rapid charging and discharging of the super capacitor so as to meet the energy supply requirement of short-time energy storage.
Further, the step S5 specifically includes:
step S51: setting a specific new energy hydrogen production system, and analyzing a simulation result;
step S52: varying the output variable weighting factor Q y1 、Q y2 、Q y3 Incremental weighting factor Q of control variables u1 、Q u2 、Q u3 And a reference time domain N 1 、N 2 Analyzing the change of the control performance of the system;
step S53: changing standard deviation sigma of new energy power day-ahead prediction error wind Standard deviation of prediction error before day of hydrogen load power
Figure SMS_42
And analyzing the robustness of the system to obtain the new energy hydrogen production system coordination control method with the optimal control performance.
The invention also provides a device for realizing the coordination control method of the new energy hydrogen production system, which is divided into a hydrogen energy system framework module, a system rolling optimization module, a system operation planning module, an energy supply requirement calculation module and a verification analysis module.
Wherein the hydrogen energy system frame module: determining a new energy hydrogen production system structure, and establishing a new energy hydrogen production system equipment characteristic equation of the vanadium redox flow battery, the electrolytic cell, the hydrogen storage tank and the super capacitor according to the equipment operation characteristics;
a system rolling optimization module: constructing a differential state equation through a dynamic model of a hydrogen energy system, establishing a model of a new energy hydrogen production system, converting the equation into a matrix form, and obtaining a rolling optimization model through a state space expression;
a system operation planning module: determining a control target of the hydrogen energy system, determining a parameter value and a reference track, constructing an objective function, and establishing a mathematical model for optimizing the operation of the hydrogen energy system;
energy supply demand calculation module: initializing a reference track and system variables, adjusting the working state of each electrolytic tank in real time based on a rolling optimization method, adopting constant power control to adjust a super capacitor so as to meet the energy supply requirements of medium-long and short-time energy storage, and providing a new energy hydrogen production system coordination control method for iteratively controlling the electrolytic tanks;
a verification analysis module: and verifying and analyzing an example, changing parameters such as an output variable weight factor, a control variable change increment weight factor, a reference time domain and the like, analyzing the change of the control performance of the system and the robustness of the system, and obtaining the new energy hydrogen production system coordination control method with the optimal control performance, thereby carrying out coordination control on the new energy hydrogen production system.
The invention also provides electronic equipment which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, and is characterized in that the processor executes the program to realize the steps of the coordination control method for the new energy hydrogen production system adaptive to the hydrogen load fluctuation.
The invention also provides a non-transitory computer readable storage medium, on which a computer program is stored, wherein the computer program is executed by a processor to implement the steps of the above method for coordinately controlling a new energy hydrogen production system that is adaptive to hydrogen load fluctuations.
Compared with the prior art, the invention has the following advantages:
1. the invention discloses a new energy hydrogen production system coordination control method adaptive to hydrogen load fluctuation, and provides a method for establishing a dynamic model for a hydrogen energy system, constructing a state equation in a differential form and obtaining a rolling optimization model by adopting a state space expression in order to improve the accuracy of output prediction at a future moment.
2. The invention provides a coordination control method of a new energy hydrogen production system, which aims to ensure the reliability of energy supply on a time scale of medium and short time, simultaneously ensure that the SOC of a vanadium redox flow battery, the air pressure of a hydrogen storage tank, the output of a power grid and the power of a super capacitor should be tracked and scheduled as control targets, and use the air pressure of an electrolytic bath, the charge capacity of the vanadium redox flow battery, the output of the power grid and the like as constraint conditions to solve a quadratic scheduling problem and perform minimum optimization on a target function based on rolling optimization control.
3. The invention adopts a specific example to verify the effectiveness of the control method, changes parameters such as an output variable weight factor, a control variable change increment weight factor, a reference time domain and the like, researches the influence of parameter change on the control performance, and analyzes the robustness of the control performance under new energy and hydrogen load fluctuation.
Drawings
FIG. 1 is a flow chart of a coordination control method of a new energy hydrogen production system adaptive to hydrogen load fluctuation in an embodiment of the invention;
FIG. 2 is a structural diagram of a new energy hydrogen production system in an embodiment of the invention;
FIG. 3 is a flowchart of an algorithm for roll optimization control in an embodiment of the present invention;
FIG. 4 is a schematic diagram of a new energy daily power curve according to an embodiment of the present invention;
FIG. 5 is a graph showing a daily power curve of a hydrogen load according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a state of charge change curve of a vanadium redox flow battery in an embodiment of the present invention;
FIG. 7 is a schematic view showing a pressure change curve of the hydrogen storage tank in the embodiment of the present invention;
fig. 8 is a schematic diagram of a load variation curve of the power grid in the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The invention provides a new energy hydrogen production system coordination control method capable of adapting to hydrogen load fluctuation, which utilizes rolling optimization control to meet the requirements of power grid load and hydrogen load in an optimal working state and minimum power regulation quantity under a hydrogen load fluctuation scene.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings.
As shown in fig. 1, the coordination control method for a new energy hydrogen production system adaptive to hydrogen load fluctuation provided by the embodiment of the present invention specifically includes the following steps:
step S1: determining a new energy hydrogen production system structure, and establishing a new energy hydrogen production system equipment characteristic equation of the vanadium redox flow battery, the electrolytic cell, the hydrogen storage tank and the super capacitor according to the equipment operation characteristics;
step S2: constructing a differential state equation through a dynamic model of a hydrogen energy system, establishing a model of a new energy hydrogen production system, converting the equation into a matrix form, and directly obtaining a rolling optimization model through a state space expression;
and step S3: determining a control target of the hydrogen energy system, determining a parameter value and a reference track, constructing an objective function, and establishing a mathematical model for optimizing the operation of the hydrogen energy system;
and step S4: initializing a reference track and system variables, adjusting the working state of each electrolytic cell in real time based on a rolling optimization method, adopting constant power control to adjust a super capacitor so as to meet the energy supply requirement of medium-long and short-time energy storage, and providing a new energy hydrogen production system coordination control method for iteratively controlling the electrolytic cells;
step S5: and verifying and analyzing the example, changing parameters such as an output variable weight factor, a control variable change increment weight factor, a reference time domain and the like, and analyzing the change of the control performance of the system and the robustness of the system to obtain the new energy hydrogen production system coordination control method with the optimal control performance. The device of the coordination control method of the new energy hydrogen production system provided by the invention is divided into a hydrogen energy system framework module, a system rolling optimization module, a system operation planning module and an energy supply requirement calculation module, and the modules are stored on a computer, and parameters of different variables are input into corresponding modules through sensors so as to realize a control target.
In an embodiment, the step S1: determining a new energy hydrogen production system structure, and establishing a new energy hydrogen production system equipment characteristic equation of the vanadium redox flow battery, the electrolytic cell, the hydrogen storage tank and the supercapacitor according to equipment operation characteristics, wherein the new energy hydrogen production system equipment characteristic equation specifically comprises the following steps:
step S11: determining a new energy hydrogen production system structure, which comprises a new energy power supply, an external power grid, a vanadium redox flow battery, an electrolytic cell, a hydrogen storage tank, a super capacitor and a hydrogen load. When the system normally operates, the new energy is used for generating electricity to prepare hydrogen, and the hydrogen load requirement and the power grid load requirement of system design are met by self-adapting to the fluctuation of the new energy and the hydrogen load. Since no fuel cell is needed to guarantee the electric energy, a vanadium redox flow battery is arranged to guarantee the power supply safety of the system in the new energy underestimation period, as shown in fig. 2;
step S12: establishing a dynamic model of the new energy hydrogen production system, wherein the dynamic equivalent model of the vanadium redox flow battery is shown as a formula (1):
Figure SMS_43
wherein S is cell Is the charge quantity, P, of the vanadium redox flow battery cell For discharge power, Q, of vanadium flow battery cell The energy storage capacity of the vanadium redox flow battery is represented, and sigma is a self-decay time coefficient related to the charge capacity of the vanadium redox flow battery;
establishing an electrolytic cell model as shown in formula (2):
Figure SMS_44
wherein the content of the first and second substances,
Figure SMS_45
to produce the hydrogen rate, P elec For the input of power to the cell, A 1 And A 2 Is a linear approximation coefficient;
establishing a hydrogen storage tank model as shown in formula (3):
Figure SMS_46
wherein, the first and the second end of the pipe are connected with each other,
Figure SMS_47
for the pressure change rate of the hydrogen storage tank>
Figure SMS_48
In order to generate hydrogen rate, R is an ideal gas constant, T is the thermodynamic temperature of the ideal gas, and V is the volume of the ideal gas;
establishing a super capacitor model as shown in formula (4):
Figure SMS_49
wherein E is the energy absorbed/released by the super capacitor, A and B are the serial and parallel numbers of the super capacitors, C f Is a single capacitor of a super capacitor, U 1 And U 2 The initial voltage and the state voltage of the super capacitor.
Through the step S1, the structure of the new energy hydrogen production system is determined, and a vanadium redox flow battery equivalent model, an electrolytic cell equivalent model, a hydrogen storage tank equivalent model and a super capacitor equivalent model are established.
In an embodiment, the step S2: the method comprises the following steps of constructing a differential state equation through a dynamic model of a hydrogen energy system, establishing a model of the new energy hydrogen production system, converting the equation into a matrix form, and directly obtaining a rolling optimization model through a state space expression, wherein the method specifically comprises the following steps:
step S21: and constructing a state equation in a differential form according to the dynamic model of the hydrogen energy system. According to the formula (1), establishing a state difference equation of the SOC of the vanadium redox flow battery, as shown in the formula (5):
Figure SMS_50
wherein, delta tau is a time step;
according to the formulas (2) to (3), a state difference equation of the hydrogen storage tank gas pressure is established as shown in the formula (6):
Figure SMS_51
wherein the content of the first and second substances,
Figure SMS_52
is the hydrogen load flow rate, is based on>
Figure SMS_53
And &>
Figure SMS_54
Hydrogen production power and hydrogen change rate influenced by working state of each electrolytic cell are respectively calculated;
Figure SMS_55
and &>
Figure SMS_56
Expressed by functional, as shown in equations (7) to (8):
Figure SMS_57
Figure SMS_58
wherein f is P (P elec ) As a function of the hydrogen production power of the electrolyzer, f d (d elec ) As a function of the operating conditions of the cell, P elec The hydrogen production power for each cell, delta being the Dirac function, P heat Heating power for cold standby, P sp Activating power for hot standby; d elec For the operating state of each cell, d elec.i E { l, s, w } represents normal operation, cold standby and hot standby respectively;
considering the system power balance, the grid output power expression is shown in equation (9):
P grid (t)＝P quit (t-1)+||P elec (t-1)|| 1 -P cell (t-1)-P renw (t-1) (9)
wherein, P quit Abandoning electric power for new energy, P renw The output power is new energy;
step S22: dividing the system variables into a state variable x, an output variable y, a control variable u and a disturbance variable p, wherein the state variable x is expressed as shown in a formula (10):
Figure SMS_59
and (3) performing a series of transformations on the control variable u and the disturbance variable p, as shown in formulas (11) to (12):
Figure SMS_60
Figure SMS_61
wherein, P sc For the power of a super capacitor, U dsc Is the terminal voltage of the supercapacitor;
the following equation of state is then obtained:
Figure SMS_62
the system state variables can be directly output, so the system output equation is shown in equation (14):
Figure SMS_63
step S23: converting the system state equation and the output equation into a matrix form as shown in equation (15):
Figure SMS_64
wherein, a is a system state coefficient matrix, B is a control coefficient matrix, C is an output coefficient matrix, D is a disturbance coefficient matrix, and each matrix is specifically expressed as formulas (16) to (19):
Figure SMS_65
Figure SMS_66
Figure SMS_67
Figure SMS_68
step S24: the rolling optimization model is directly obtained from the state space expression, as shown in equation (20):
Figure SMS_69
wherein the content of the first and second substances,
Figure SMS_70
the output variable value at the t + k moment is obtained according to the available information at the t moment in a prediction mode; u (t + k-1) denotes a control instruction acquired at the time t; p (t + k-1 luminance t) represents the perturbation signal acquired at time t.
Through the step S2, a state equation in a difference form is constructed, a series of transformation is carried out on system variables, and a rolling optimization model is obtained by using a state space expression.
In an embodiment, the step S3: determining a control target of a hydrogen energy system, determining a parameter value and a reference track, constructing an objective function, and establishing a mathematical model for optimizing the operation of the hydrogen energy system, wherein the method specifically comprises the following steps:
step S31: determining a control target of a hydrogen energy system to ensure energy supply reliability on a time scale of medium and short time, ensuring that the SOC of the vanadium redox flow battery, the air pressure of a hydrogen storage tank, the power output of a power grid and the power of a super capacitor are required to track a scheduling plan, reducing the power adjustment amount of primary equipment as much as possible, and improving the energy conversion efficiency; constructing an objective function as shown in equation (21):
Figure SMS_71
wherein N is 1 Evaluating the upper bound, N, for the prediction domain 2 Evaluating the lower bound for the prediction domain, N u Evaluating boundaries for the control domain, t and j being different times, δ (j) being the weight of the output variable at time j, λ (j) being the weight of the control variable at time j, Q y For a matrix of output variable weight coefficients, Q u In order to control the variable weight coefficient matrix,
Figure SMS_72
for the expected output track of the system in a specific time range in the future, w (t + k | t) is a reference track, and Δ u is a variation value of a control variable;
step S32: determining prediction domain evaluation upper and lower bounds N 1 ，N 2 The parameter value of (2) ensures that the reference track w (t + j) is consistent with the dimension of the output variable;
step S33: setting the constraint condition of each specific element of the control variable, as shown in formula (22):
Figure SMS_73
wherein, P cell.charge And P cell.discharge Respectively the maximum charging and discharging power of the vanadium redox flow battery and the abandoned new energy power P quit (t) should be lower than the maximum theoretical output P of new energy renw (t)，P elec.min And P elec.max Minimum and maximum hydrogen production power, P, of the cell sc.c，max And P sc.d，max Maximum charge and discharge power for the ultracapacitor;
setting the change rate of each element of the control variable, as shown in equation (23):
Figure SMS_74
/>
wherein the content of the first and second substances,
Figure SMS_76
and &>
Figure SMS_81
Respectively regulating the response speed of the vanadium redox flow battery; />
Figure SMS_82
And
Figure SMS_77
the output of the new energy is down-regulated and the response speed of the new energy is up-regulated, and the output of the new energy is limited by the MPPT strategy of the new energy; />
Figure SMS_78
And &>
Figure SMS_79
Response speed is adjusted up and down for hydrogen production power of the electrolytic cell; />
Figure SMS_80
And &>
Figure SMS_75
Down-regulating and up-regulating response speed of the output of the super capacitor;
expanding the constraint condition of the change rate of the system output variable, as shown in the formula (24):
Figure SMS_83
wherein S is cell.min And S cell.max Minimum and maximum state of charge, p, of the vanadium redox flow battery respectively tank.min And p tank.max Respectively, the minimum and maximum pressure values, P, of the hydrogen storage tank grid.min And P grid.max Minimum and maximum power values for purchasing power from the grid, respectively.
Through the step S3, a control target of the hydrogen energy system is determined, a target function is constructed by considering parameter values, reference tracks and constraint conditions, and a mathematical model for optimizing the operation of the hydrogen energy system is established.
In an embodiment, the step S4: initializing a reference track and system variables, adjusting the working state of each electrolytic cell in real time based on a rolling optimization method, adjusting a super capacitor by adopting constant power control to meet the energy supply requirement of medium-long and short-time energy storage, and providing a new energy hydrogen production system coordination control method for iteratively controlling the electrolytic cells, which specifically comprises the following steps:
step S41: adjusting the electrolytic cell in real time based on rolling optimization control, inputting a future reference track w (t + j), a control variable and current disturbance information, and repeatedly solving a quadratic programming problem to obtain a control signal u (t + 1) at the next moment;
step S42: calculating the power of the electrolytic cell, changing the working state variation disturbance variable p of the electrolytic cell until all electrolytic cells are in a normal power state or all the electrolytic cells which normally work are in a hot standby state at the current control moment, and stopping iterative solution to meet the energy supply requirement of medium-long time energy storage, wherein the control method is shown in figure 3;
step S43: the working state of the super capacitor is adjusted based on constant power control, a current deviation value is obtained through reference power, and the PI controller is adopted to realize rapid charging and discharging of the super capacitor so as to meet the energy supply requirement of short-time energy storage.
And S4, regarding the optimization problem in the rolling optimization control as a standard quadratic programming problem under linear constraint, solving the quadratic programming problem, repeating optimization calculation to obtain a control signal at the next moment, and providing the new energy hydrogen production system coordination control method for iteratively controlling the states of the electrolytic cells.
In an embodiment, the step S5: verifying and analyzing an example, changing parameters such as an output variable weight factor, a control variable change increment weight factor and a reference time domain, analyzing the change of the control performance of the system and the robustness of the system to obtain the new energy hydrogen production system coordination control method with the optimal control performance, which specifically comprises the following steps:
step S51: the method comprises the following steps of setting a specific new energy hydrogen production system, analyzing a simulation result, and comprising the following steps:
1) Setting specific new energy systemThe total installation of new energy is 10MW, a prediction error in normal distribution is superposed on a prediction power curve of new energy and hydrogen load day ahead, the average value of the prediction errors of the new energy power and the hydrogen load power day ahead is set to be 0, and the standard deviation sigma of the prediction error of the new energy power day ahead is set to be 0 wind Set to 1000kW, the standard deviation of the prediction error of the hydrogen load power day-ahead
Figure SMS_84
Setting the system parameters to be 1000mol/h, wherein the specific parameter settings of the system are shown in Table 1;
TABLE 1
Figure SMS_85
Figure SMS_86
2) Considering that the ultra-short-term prediction accuracy is high, the error of the ultra-short-term prediction value adopted by the rolling optimization control in the embodiment is 0, and the daily power curve of the new energy and the hydrogen load is shown in fig. 4-5;
3) Obtaining a simulation result, wherein a vanadium redox flow battery state-of-charge change curve and a planned reference trajectory thereof are shown in fig. 6, a hydrogen storage tank pressure change curve and a planned reference trajectory thereof are shown in fig. 7, and a power grid load change curve and a planned reference trajectory thereof are shown in fig. 8;
step S52: varying the output variable weighting factor Q y1 、Q y2 、Q y3 Control variable incremental weight factor Q u1 、Q u2 、Q u3 And a reference time domain N 1 、N 2 Analyzing the change of the control performance of the system;
step S53: changing standard deviation sigma of new energy power day-ahead prediction error wind Standard deviation of prediction error before day of hydrogen load power
Figure SMS_87
The robustness of the system is analyzed to obtain the new energy hydrogen production system coordination control method with the optimal control performance and the simulation resultAs shown in table 2.
TABLE 2
Figure SMS_88
/>
Figure SMS_89
Through the step S5, a specific new energy hydrogen production system is set to verify the effectiveness of the method and the control performance under extreme conditions, and the weight parameters are adjusted according to the capacity of system equipment and the control requirement in the process of engineering practical application to obtain the optimal control performance.
The invention also provides a device for realizing the coordination control method of the new energy hydrogen production system, which is divided into a hydrogen energy system framework module, a system rolling optimization module, a system operation planning module, an energy supply requirement calculation module and a verification analysis module.
Wherein the hydrogen energy system frame module: determining a new energy hydrogen production system structure, and establishing a new energy hydrogen production system equipment characteristic equation of the vanadium redox flow battery, the electrolytic cell, the hydrogen storage tank and the super capacitor according to the equipment operation characteristics;
a system rolling optimization module: constructing a state equation in a differential form through a dynamic model of a hydrogen energy system, establishing a model of the new energy hydrogen production system, converting the equation into a matrix form, and obtaining a rolling optimization model through a state space expression;
a system operation planning module: determining a control target of the hydrogen energy system, determining a parameter value and a reference track, constructing an objective function, and establishing a mathematical model for optimizing the operation of the hydrogen energy system;
energy supply demand calculation module: initializing a reference track and system variables, adjusting the working state of each electrolytic cell in real time based on a rolling optimization method, adopting constant power control to adjust a super capacitor so as to meet the energy supply requirement of medium-long and short-time energy storage, and providing a new energy hydrogen production system coordination control method for iteratively controlling the electrolytic cells;
a verification analysis module: and verifying an analysis example, changing parameters such as an output variable weight factor, a control variable change increment weight factor, a reference time domain and the like, analyzing the change of the control performance of the system and the robustness of the system, and obtaining the new energy hydrogen production system coordination control method with the optimal control performance, thereby carrying out coordination control on the new energy hydrogen production system.
The invention also provides electronic equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, and is characterized in that the processor executes the program to realize the steps of the coordination control method of the new energy hydrogen production system adaptive to the hydrogen load fluctuation.
The invention also provides a non-transitory computer readable storage medium, on which a computer program is stored, wherein the computer program is executed by a processor to implement the steps of the above method for coordinately controlling a new energy hydrogen production system that is adaptive to hydrogen load fluctuations.
In order to improve the accuracy of output control at a future moment, the invention provides a method for establishing a dynamic model for a hydrogen energy system, constructing a state equation in a differential form and obtaining a rolling optimization model by adopting a state space expression. The invention provides a coordination control method of a new energy hydrogen production system, which aims to ensure the energy supply reliability on the time scale of medium and short time, simultaneously ensure the tracking and scheduling of the SOC of a vanadium redox flow battery, the air pressure of a hydrogen storage tank, the output of a power grid and the power output of a super capacitor as control targets, and solve the secondary scheduling problem by taking the air pressure of an electrolytic bath, the charge capacity of the vanadium redox flow battery, the output of the power grid and the like as constraint conditions and perform minimum optimization on a target function based on rolling optimization control. The invention adopts a specific example to verify the effectiveness of the control method, changes parameters such as an output variable weight factor, a control variable change increment weight factor, a reference time domain and the like, researches the influence of parameter change on the control performance, and analyzes the robustness of the control performance under new energy and hydrogen load fluctuation.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (9)

1. The coordination control method of the new energy hydrogen production system capable of self-adapting to hydrogen load fluctuation is characterized by comprising the following steps:
step S1: determining a new energy hydrogen production system structure, and establishing a new energy hydrogen production system equipment characteristic equation of the vanadium redox flow battery, the electrolytic cell, the hydrogen storage tank and the super capacitor according to the equipment operation characteristics;
step S2: constructing a differential state equation through a dynamic model of a hydrogen energy system, establishing a model of a new energy hydrogen production system, converting the equation into a matrix form, and directly obtaining a rolling optimization model through a state space expression;
and step S3: determining a control target of the hydrogen energy system, determining a parameter value and a reference track, constructing an objective function, and establishing a mathematical model for optimizing the operation of the hydrogen energy system;
and step S4: initializing a reference track and system variables, adjusting the working state of each electrolytic cell in real time based on a rolling optimization method, adopting constant power control to adjust a super capacitor so as to meet the energy supply requirement of medium-long and short-time energy storage, and providing a new energy hydrogen production system coordination control method for iteratively controlling the electrolytic cells;
step S5: and verifying an analysis example, changing parameters such as an output variable weight factor, a control variable change increment weight factor, a reference time domain and the like, analyzing the change of the control performance of the system and the robustness of the system, and obtaining the new energy hydrogen production system coordination control method with the optimal control performance, thereby carrying out coordination control on the new energy hydrogen production system.
2. The coordination control method for the hydrogen production system from the new energy source with the adaptive hydrogen load fluctuation according to claim 1, wherein the step S1 specifically comprises:
step S11: determining a new energy hydrogen production system structure, wherein the new energy hydrogen production system structure comprises a new energy power supply, an external power grid, a vanadium redox flow battery, an electrolytic cell, a hydrogen storage tank, a super capacitor and a hydrogen load;
step S12: establishing a dynamic model of the new energy hydrogen production system, wherein the dynamic equivalent model of the vanadium redox flow battery is shown as a formula (1):
Figure FDA0003957572580000011
wherein S is cell Is the charge quantity, P, of the vanadium redox flow battery cell For discharge power, Q, of vanadium flow battery cell The energy storage capacity of the vanadium redox flow battery is represented, and sigma is a self-decay time coefficient related to the charge capacity of the vanadium redox flow battery;
establishing an electrolytic cell model as shown in formula (2):
Figure FDA0003957572580000013
wherein the content of the first and second substances,
Figure FDA0003957572580000012
to produce the hydrogen rate, P elec For the input of power to the cell, A 1 And A 2 Is a linear approximation coefficient;
establishing a hydrogen storage tank model as shown in formula (3):
Figure FDA0003957572580000021
wherein the content of the first and second substances,
Figure FDA0003957572580000022
for the pressure change rate of the hydrogen storage tank>
Figure FDA0003957572580000023
In order to produce hydrogen rate, R is an ideal gas constant, T is the thermodynamic temperature of the ideal gas, and V is the volume of the ideal gas;
establishing a super capacitor model as shown in formula (4):
Figure FDA0003957572580000024
wherein E is the energy absorbed/released by the super capacitor, A and B are the serial and parallel numbers of the super capacitors, C f Is the individual capacitance of a supercapacitor, U 1 And U 2 The initial voltage and the state voltage of the super capacitor.
3. The coordination control method for the hydrogen production system from the new energy source with the adaptive hydrogen load fluctuation according to claim 2, wherein the step S2 specifically comprises:
step S21: constructing a state equation in a differential form according to a dynamic model of a hydrogen energy system;
according to the formula (1), establishing a state difference equation of the SOC of the vanadium redox flow battery, as shown in the formula (5):
Figure FDA0003957572580000025
wherein, the delta tau is a time step;
according to the formulas (2) to (3), a state difference equation of the hydrogen storage tank gas pressure is established as shown in the formula (6):
Figure FDA0003957572580000026
wherein the content of the first and second substances,
Figure FDA0003957572580000027
for a hydrogen load flow rate>
Figure FDA0003957572580000028
And &>
Figure FDA0003957572580000029
Are respectively asHydrogen change rate influenced by hydrogen production power and working state of each electrolytic cell;
Figure FDA00039575725800000210
and &>
Figure FDA00039575725800000211
Expressed by functional, as shown in equations (7) to (8):
Figure FDA00039575725800000212
Figure FDA00039575725800000213
wherein f is P (P elec ) As a function of the hydrogen production power of the cell, f d (d elec ) As a function of the operating conditions of the cell, P elec The hydrogen production power for each cell, delta being the Dirac function, P heat Heating power for cold standby, P sp Activating power for hot standby; d elec For the operating state of each cell, d elec.i E { l, s, w } represents normal operation, cold standby and hot standby respectively;
in consideration of the system power balance, the grid output power is expressed as formula (9):
P grid (t)＝P quit (t-1)+||P elec (t-1)|| 1 -P cell (t-1)-P renw (t-1) (9)
wherein, P quit Abandoning electric power for new energy, P renw The output power is new energy;
step S22: dividing the system variables into a state variable x, an output variable y, a control variable u and a disturbance variable p, wherein the state variable x is expressed as shown in a formula (10):
Figure FDA0003957572580000031
wherein S is cell Is a vanadium flow battery SOC, p tank Is the gas pressure of the hydrogen storage tank, P grid Is the load of the power grid;
and (3) performing a series of transformations on the control variable u and the disturbance variable p, as shown in formulas (11) to (12):
Figure FDA0003957572580000032
/>
Figure FDA0003957572580000033
wherein, P sc Is the power of a supercapacitor, U dsc Is the terminal voltage of the supercapacitor;
the following equation of state is then obtained:
Figure FDA0003957572580000041
the system state variables can be directly output, so the system output equation is shown in equation (14):
Figure FDA0003957572580000042
step S23: the system state equation and the output equation are converted into a matrix form as shown in equation (15):
Figure FDA0003957572580000043
wherein, A is a system state coefficient matrix, B is a control coefficient matrix, C is an output coefficient matrix, D is a disturbance coefficient matrix, and the matrixes are specifically expressed as formulas (16) to (19):
Figure FDA0003957572580000044
Figure FDA0003957572580000045
Figure FDA0003957572580000046
/>
Figure FDA0003957572580000047
step S24: the rolling optimization model is directly obtained from the state space expression, as shown in equation (20):
Figure FDA0003957572580000051
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003957572580000052
the output variable value at the t + k moment is obtained according to the available information at the t moment in a prediction mode; u (t + k-1) denotes a control instruction acquired at the moment t; p (t + k-1) denotes the disturbance signal acquired at time t.
4. The coordination control method for the new energy hydrogen production system adaptive to hydrogen load fluctuation according to claim 3, characterized in that the step S3 comprises the following steps:
step S31: determining a control target of the hydrogen energy system, and constructing an objective function as shown in formula (21):
Figure FDA0003957572580000053
wherein N is 1 Evaluating the upper bound for the prediction domain, N 2 Evaluating the lower bound, N, for the prediction domain u Evaluating the boundaries for the control domain, t and for different times, δ (j) being the weight of the output variable at time j, λ (j) being the weight of the control variable at time j, Q y As a matrix of output variable weight coefficients, Q u In order to control the variable weight coefficient matrix,
Figure FDA0003957572580000054
for the expected output track of the system in a specific time range in the future, w (t + k | t) is a reference track, and Δ u is a variation value of a control variable;
step S32: determining prediction domain evaluation upper and lower bounds N 1 ，N 2 The parameter value of (2) ensures that the reference track w (t + j) is consistent with the dimension of the output variable;
step S33: setting the constraint condition of each specific element of the control variable, as shown in formula (22):
Figure FDA0003957572580000055
wherein, P cell.charge And P cell.discharge Respectively the maximum charging power and the maximum discharging power of the vanadium redox flow battery, and the abandoned electric power P of the new energy quit (t) should be lower than the maximum theoretical output P of new energy renw (t)，P elec.min And P elec.max Minimum and maximum hydrogen production power, P, for the cell sc.c，max And P sc.d，max Maximum charge and discharge power for the supercapacitor;
setting the change rate of each element of the control variable, as shown in equation (23):
Figure FDA0003957572580000061
/>
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003957572580000062
and &>
Figure FDA0003957572580000063
Respectively regulating the response speed of the vanadium redox flow battery; />
Figure FDA0003957572580000064
And &>
Figure FDA0003957572580000065
The output of the new energy is down-regulated and the response speed of the new energy is up-regulated, and the output of the new energy is limited by the MPPT strategy of the new energy; />
Figure FDA0003957572580000066
And &>
Figure FDA0003957572580000067
Response speed is adjusted up and down for hydrogen production power of the electrolytic cell; />
Figure FDA0003957572580000068
And &>
Figure FDA0003957572580000069
The output down-regulation and up-regulation response speed of the super capacitor is obtained;
expanding the constraint condition of the change rate of the system output variable, as shown in the formula (24):
Figure FDA00039575725800000610
wherein S is cell.min And S cell.max Minimum and maximum state of charge, p, of the vanadium redox flow battery respectively tank.min And p tank.max Respectively, the minimum and maximum pressure values, P, of the hydrogen storage tank grid.min And P grid.max Respectively the minimum and the maximum of the power purchase from the power gridA large power value.
5. The coordination control method for the hydrogen production system from the new energy source with the adaptive hydrogen load fluctuation according to claim 4, wherein the step S4 specifically comprises:
step S41: adjusting the electrolytic cell in real time based on rolling optimization control, inputting a future reference track w (t + j), a control variable and current disturbance information, and repeatedly solving a quadratic programming problem to obtain a control signal u (t + 1) at the next moment;
step S42: calculating the power of the electrolytic cell, changing the working state variation disturbance variable p of the electrolytic cell until all electrolytic cells are in a normal power state or all the electrolytic cells which normally work are in a hot standby state at the current control moment, and stopping iterative solution;
step S43: and adjusting the working state of the super capacitor based on constant power control, obtaining a current deviation value through reference power, and realizing the rapid charging and discharging of the super capacitor by adopting a PI controller.
6. The coordination control method for the hydrogen production system from the new energy source with the adaptive hydrogen load fluctuation according to claim 5, wherein the step S5 specifically comprises:
step S51: setting a specific new energy hydrogen production system, and analyzing a simulation result;
step S52: varying the output variable weighting factor Q y1 、Q y2 、Q y3 Control variable incremental weight factor Q u1 、Q u2 、Q u3 And a reference time domain N 1 、N 2 Analyzing the change of the control performance of the system;
step S53: changing standard deviation sigma of new energy power day-ahead prediction error wind Standard deviation of prediction error before day of hydrogen load power
Figure FDA0003957572580000071
And analyzing the robustness of the system to obtain the new energy hydrogen production system coordination control method with the optimal control performance.
7. The device for realizing the coordination control method of the new energy hydrogen production system capable of adapting to the hydrogen load fluctuation according to any one of claims 1 to 6, is characterized by comprising the following steps:
a hydrogen energy system frame module: determining a new energy hydrogen production system structure, and establishing a new energy hydrogen production system equipment characteristic equation of the vanadium redox flow battery, the electrolytic cell, the hydrogen storage tank and the super capacitor according to the equipment operation characteristics;
a system rolling optimization module: constructing a state equation in a differential form through a dynamic model of a hydrogen energy system, establishing a model of the new energy hydrogen production system, converting the equation into a matrix form, and obtaining a rolling optimization model through a state space expression;
a system operation planning module: determining a control target of the hydrogen energy system, determining a parameter value and a reference track, constructing an objective function, and establishing a mathematical model for optimizing the operation of the hydrogen energy system;
energy supply demand calculation module: initializing a reference track and system variables, adjusting the working state of each electrolytic cell in real time based on a rolling optimization method, adopting constant power control to adjust a super capacitor so as to meet the energy supply requirement of medium-long and short-time energy storage, and providing a new energy hydrogen production system coordination control method for iteratively controlling the electrolytic cells;
a verification analysis module: and verifying an analysis example, changing parameters such as an output variable weight factor, a control variable change increment weight factor, a reference time domain and the like, analyzing the change of the control performance of the system and the robustness of the system, and obtaining the new energy hydrogen production system coordination control method with the optimal control performance, thereby carrying out coordination control on the new energy hydrogen production system.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method for coordinated control of a new energy hydrogen production system with adaptive hydrogen load fluctuations as defined in any one of claims 1 to 6.
9. A non-transitory computer readable storage medium, having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for coordinated control of a new energy hydrogen production system that adapts to fluctuations in hydrogen load as recited in any one of claims 1-6.
CN202211474082.4A 2022-08-29 2022-11-22 New energy hydrogen production system coordination control method and device adaptive to hydrogen load fluctuation, electronic equipment and storage medium Pending CN115986720A (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202211043879.9A CN115313380A (en) 2022-08-29 2022-08-29 New energy hydrogen production system coordination control method adaptive to hydrogen load fluctuation
CN2022110438799 2022-08-29

Publications (1)

Publication Number Publication Date
CN115986720A true CN115986720A (en) 2023-04-18

Family

ID=83864858

Family Applications (2)

Application Number Title Priority Date Filing Date
CN202211043879.9A Pending CN115313380A (en) 2022-08-29 2022-08-29 New energy hydrogen production system coordination control method adaptive to hydrogen load fluctuation
CN202211474082.4A Pending CN115986720A (en) 2022-08-29 2022-11-22 New energy hydrogen production system coordination control method and device adaptive to hydrogen load fluctuation, electronic equipment and storage medium

Family Applications Before (1)

Application Number Title Priority Date Filing Date
CN202211043879.9A Pending CN115313380A (en) 2022-08-29 2022-08-29 New energy hydrogen production system coordination control method adaptive to hydrogen load fluctuation

Country Status (1)

Country Link
CN (2) CN115313380A (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117153280B (en) * 2023-08-31 2024-05-03 山东大学 Simulation model building method, simulation method and simulation system of alkaline electrolysis hydrogen production system
CN117526374B (en) * 2023-12-28 2024-05-10 国网浙江省电力有限公司电力科学研究院 Control method and device of new energy hydrogen production system matched with real-time output of fluctuation power supply

Also Published As

Publication number Publication date
CN115313380A (en) 2022-11-08

Similar Documents

Publication Publication Date Title
CN105846461B (en) Control method and system for large-scale energy storage power station self-adaptive dynamic planning
WO2020143104A1 (en) Power grid mixing and rolling scheduling method that considers clogging and energy-storing time-of-use price
CN115986720A (en) New energy hydrogen production system coordination control method and device adaptive to hydrogen load fluctuation, electronic equipment and storage medium
CN105375479A (en) Model predicative control based energy management method of distributed energy resource system
CN113285451B (en) Black-start coordination control method based on photovoltaic energy storage system
CN111697578B (en) Multi-target energy storage-containing regional power grid operation control method
CN111934360B (en) Virtual power plant-energy storage system energy collaborative optimization regulation and control method based on model predictive control
CN108711859B (en) Multi-source micro-grid frequency coordination method based on adaptive robust control
CN103248065B (en) Charging-discharging control method of cell energy storing system in wind power plant
CN115000991A (en) Thermal power-flywheel energy storage cooperative frequency modulation control method and system
Badar et al. An autonomous hybrid DC microgrid with ANN-fuzzy and adaptive terminal sliding mode multi-level control structure
CN115133538B (en) Prediction control method for important load voltage model of power distribution network
CN112039092A (en) Island Direct Current (DC) outgoing Automatic Gain Control (AGC) model prediction control method considering energy storage System On Chip (SOC) recovery
CN111654054A (en) Control method for stabilizing short-term wind power fluctuation based on Adaptive Neural Network (ANN) during energy storage
Yin et al. Expandable deep width learning for voltage control of three-state energy model based smart grids containing flexible energy sources
CN114884136A (en) Active power distribution network robust optimization scheduling method considering wind power correlation
Liu et al. A novel adaptive model predictive control for proton exchange membrane fuel cell in DC microgrids
Yang et al. Coordination of generators and energy storage to smooth power fluctuations for multi-area microgrid clusters: A robust decentralized approach
CN106786702A (en) Full range modeling for mixed energy storage system predicts energy dispatching method
CN114374231A (en) Configuration and control integrated optimization method for off-grid multi-energy system
CN111651878B (en) Large power grid static voltage stability optimization decision method and system considering situation assessment
CN111478344A (en) Energy microgrid load frequency control method and system and related products
CN105207220B (en) A kind of tapping voltage regulation and control method based on progressive learning
Wang et al. Multi-objective optimal dispatch of wind-integrated power system based on distributed energy storage
Roy et al. Cost optimization of battery and Supercapacitor Hybrid Energy Storage System for dispatching solar PV Power

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination