Wind-light-hydrogen coupled structure and capacity optimization method and system

Abstract

The invention provides a structure and capacity optimization method and system for a wind-light-hydrogen coupling system, and belongs to the technical field of new energy, and the method comprises the steps: building an upper-layer optimization model of the wind-light-hydrogen coupling system through analyzing the typical structure characteristics of the wind-light-hydrogen coupling system; establishing a lower-layer optimization model of the wind-light-hydrogen coupling system; and solving the upper-layer optimization model and the lower-layer optimization model through a genetic algorithm. The system optimization configuration problem under the condition that the system structure is unknown can be solved, and the method has a wider application scene. According to the method, a double-layer decision framework is adopted, and a planning decision variable and an operation state variable are separated, so that the established optimization model is easier to solve by commercial solution software, and popularization in engineering is more facilitated. In terms of main technical indexes, due to the fact that model selection of the system structure is further considered, structural characteristics and flexibility characteristics can be brought into full play, the economic benefits of the system are further improved, and wind and light absorption is promoted.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy, and particularly relates to a method and system for optimizing the structure and capacity of a wind-solar-hydrogen coupling system. Background Art

[0002] To promote the high-quality development of renewable energy and improve the market competitiveness of wind and solar power generation, from the perspective of the hydrogen production source, using renewable energy to produce hydrogen can alleviate the problems of abandoned wind and light and promote the consumption of new energy; from the perspective of hydrogen demand, hydrogen-powered vehicles have received extensive attention and rapid development in recent years due to their advantages such as fast refueling speed, long cruising range, environmental friendliness, and being more suitable for use in low-temperature environments in winter compared to electric vehicles. Therefore, wind and solar power generation and hydrogen production from electricity have natural complementary characteristics.

[0003] However, the disadvantages of existing wind-solar-hydrogen coupling system planning technologies are as follows: The selection of various equipment composition types is not considered. In reality, wind-solar-hydrogen coupling systems can have various types, such as off-grid / on-grid, with / without electrochemical energy storage, whether to supply power locally, and whether to supply hydrogen locally. Ignoring the structural decision of the system will result in the system being unable to exert its structural and flexibility characteristics, and unable to achieve the optimization of the economic benefits of the system and the consumption of wind and solar energy. Summary of the Invention

[0004] In view of the above problems, the present invention proposes a method and system for optimizing the structure and capacity of a wind-solar-hydrogen coupling system. By optimizing for various equipment types, it can exert its structural and flexibility characteristics to achieve the optimal economic benefits of the system and the consumption of wind and solar energy.

[0005] The present invention provides a method for optimizing the structure and capacity of a wind-solar-hydrogen coupling system, including:

[0006] Analyzing the typical structural characteristics of the wind-solar-hydrogen coupling system, where the structural characteristics are analyzed according to grid connection classification, energy storage type classification, and load type classification;

[0007] According to the classification results, establishing an upper-layer optimization model for the wind-solar-hydrogen coupling system; where the upper-layer optimization model takes the maximum annual average net income R of the wind-solar-hydrogen coupling system as the objective function;

[0008] Establishing a lower-layer optimization model for the wind-solar-hydrogen coupling system; where the lower-layer optimization model takes the maximum annual total income Ia of the system as the objective function;

[0009] Solving the upper-layer optimization model and the lower-layer optimization model through a genetic algorithm.

[0010] Preferably, the establishment of the upper-layer optimization model for the wind-solar-hydrogen coupling system includes:

[0011] Construct an upper - layer objective function based on the annual total revenue of the system, the equivalent annual value of the system investment cost, the system operation and maintenance cost, and the annual average equipment depreciation cost of the system;

[0012] Among them, the annual total revenue of the system is obtained by solving the lower - layer optimization model.

[0013] Preferably, the method further includes:

[0014] Determine the equivalent annual value of the system investment cost according to the total investment cost of each device, the investment cost per unit length of each device, the discount rate, and the operation life;

[0015] Among them, the total investment cost of each device is determined according to the investment capacity of each device and the investment cost per unit length of each device.

[0016] Preferably, the method further includes:

[0017] Determine the annual average operation and maintenance cost of the system according to the percentage of the annual average fixed operation and maintenance cost of each device in the initial investment of the annual average fixed operation and maintenance cost of each device, the operation and maintenance cost coefficient of the electrolyzer, the operation and maintenance cost coefficient related to the hydrogen production / consumption of the fuel cell, the hydrogen production rate of the electrolyzer, the power supply load rate of the fuel cell power generation, and the hydrogen consumption rate of the grid - connected consumption.

[0018] Preferably, the method further includes:

[0019] Determine the annual average equipment depreciation cost of the system according to the total investment cost of the equipment, the equipment residual value, and the operation life.

[0020] Preferably, the method further includes:

[0021] Constrain the upper - layer optimization model;

[0022] Among them, determine whether the wind - solar - hydrogen coupling system is grid - connected according to the grid - connection binary variable, and determine whether the wind - solar - hydrogen coupling system is configured with an electrochemical energy storage according to the configuration electrochemical energy storage binary variable;

[0023] When the value of the grid - connection binary variable is 1, it means that the wind - solar - hydrogen coupling system is grid - connected; when the value of the grid - connection binary variable is 1, it is not grid - connected;

[0024] When the value of the configuration electrochemical energy storage binary variable is 1, it means that the wind - solar - hydrogen coupling system is configured with an electrochemical energy storage, and when the value of the configuration electrochemical energy storage binary variable is not 1, it means that it is not configured with an electrochemical energy storage.

[0025] Preferably, establishing the lower - layer optimization model of the wind - solar - hydrogen coupling system includes:

[0026] Construct the objective function of the lower - layer optimization model according to the revenue from power supply to the grid, the revenue from hydrogen supply to the hydrogen load, the revenue from power supply to the local load, and the penalty cost for abandoning wind and solar;

[0027] Among them, the objective function of the lower-layer optimization model aims at the total annual income Ia of the system.

[0028] Preferably, the method further includes:

[0029] Determine the income from power supply to the power grid according to the total on-grid power of the system, the on-grid electricity price, and the power transmission loss coefficient;

[0030] Determine the income from hydrogen supply to the hydrogen load according to the hydrogen supply rate and the hydrogen supply time for the hydrogen load;

[0031] Determine the income from power supply to the local load according to the power supplied by the wind and photovoltaic units to the local load, the electricity price for in-situ power supply to the electrical load, and the power supply time;

[0032] Determine the curtailment penalty cost of wind and light according to the curtailment penalty price of wind and light, the per-unit wind turbine output at time t of typical day i, and the per-unit photovoltaic unit output at time t of typical day i.

[0033] Preferably, the method further includes:

[0034] Constrain the objective function of the lower-layer optimization model, including: active power balance constraint of the load, transmission power constraint, hydrogen load demand constraint, and hydrogen energy system operation constraint.

[0035] The hydrogen energy system operation constraint includes: power and efficiency constraint of the electrolyzer, power and efficiency constraint of the hydrogen fuel cell, hydrogen storage tank volume constraint, wind and photovoltaic unit output constraint, and electrical and hydrogen load constraint.

[0036] Based on the same inventive concept, an embodiment of the present invention provides a structure and capacity optimization system for a wind-solar-hydrogen coupling system, including:

[0037] A structure classification unit for analyzing the typical structural characteristics of the wind-solar-hydrogen coupling system, where the structural characteristics are analyzed according to whether it is grid-connected, energy storage type, and load type classification;

[0038] A first model unit for establishing an upper-layer optimization model of the wind-solar-hydrogen coupling system according to the classification result; among them, the upper-layer optimization model aims at the maximum annual average net income R of the wind-solar-hydrogen coupling system as the objective function;

[0039] A second model unit for establishing a lower-layer optimization model of the wind-solar-hydrogen coupling system; among them, the lower-layer optimization model aims at the maximum total annual income Ia of the system as the objective function;

[0040] A calculation and solution unit for solving the upper-layer optimization model and the lower-layer optimization model through a genetic algorithm.

[0041] Based on the same inventive concept, an embodiment of the present invention provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus;

[0042] The memory stores a computer program;

[0043] When the processor executes the program stored in the memory, it realizes the structure and capacity optimization method of the aforementioned wind-solar-hydrogen coupling system.

[0044] Based on the same inventive concept, an embodiment of the present invention provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, it realizes the structure and capacity optimization method of the above-mentioned wind-solar-hydrogen coupling system.

[0045] Advantages of the present invention: The present invention can solve the system optimization configuration problem under the condition of unknown system structure and has a wider application scenario. The present invention adopts a two-layer decision-making framework to separate the planning decision variables and the operating state variables, making the established optimization model easier to be solved by commercial solution software and more conducive to popularization in engineering. In terms of the main technical indicators, since this patent further considers the selection of the system structure, it can give full play to the structural characteristics and flexibility characteristics, further improve the economic benefits of the system, and promote the consumption of wind and light.

[0046] Other features and advantages of the present invention will be described in the following description of the specification, and part of them will be obvious from the description of the specification or understood by implementing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the structure pointed out in the specification and the drawings. Description of the Drawings

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings 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 efforts.

[0048] Figure 1 It is a schematic flow chart of a method for optimizing the structure and capacity of a wind-solar-hydrogen coupling of the present invention;

[0049] Figure 2 It is a schematic diagram of a wind-solar-hydrogen coupling structure and capacity optimization system of the present invention;

[0050] Figure 3 It is a schematic diagram of an electronic device applied to the present invention. Detailed Embodiments

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0052] It should be noted that the terms "first", "second", etc. in this application are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances for the embodiments of the present application described herein. In this application, the orientation or positional relationships indicated by the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", etc. are based on the orientation or positional relationships shown in the drawings.

[0053] The embodiments of the present invention provide a method for optimizing the structure and capacity of a wind-solar-hydrogen coupling system. Refer to Figure 1 , including:

[0054] S101: Analyze the typical structural characteristics of the wind-solar-hydrogen coupling system. Among them, classify according to whether it is grid-connected, energy storage type, load type, and analyze the structural characteristics;

[0055] S102: According to the classification results, establish an upper-layer optimization model for the wind-solar-hydrogen coupling system; among them, the upper-layer optimization model takes the maximum annual average net income R of the wind-solar-hydrogen coupling system as the objective function;

[0056] S103: Establish a lower-layer optimization model for the wind-solar-hydrogen coupling system; among them, the lower-layer optimization model takes the maximum annual total income Ia of the system as the objective function;

[0057] S104: Solve the upper-layer optimization model and the lower-layer optimization model through a genetic algorithm.

[0058] It should be noted that the general structure of the wind-solar-hydrogen coupling system has the functions of supplying power to the upper-level power grid, supplying power to local loads, and supplying hydrogen. The system can be divided into several categories according to whether it is grid-connected, the type of energy storage, and the type of load. Among them, according to whether it is grid-connected, the wind-solar-hydrogen coupling system can be divided into off-grid type and grid-connected type. Off-grid type: This mode cancels the grid-connected power transmission and transformation system, and the output of wind and light is consumed through the hydrogen energy system and local electrical loads, and there may also be abandoned wind and light. Grid-connected type: This mode includes a hydrogen energy system and a grid-connected power transmission system, as well as off-grid / grid-connected wind-solar-hydrogen coupling systems. According to the type of energy storage, the wind-solar-hydrogen coupling system can be divided into a system with only hydrogen energy storage and a system with hydrogen energy storage and electrochemical energy storage. According to the type of load, the wind-solar-hydrogen coupling system can be divided into a hydrogen supply-only type, a power supply-only type, and a power supply-hydrogen supply type.

[0059] For the system structure classification, the structure selection process is modeled in the upper-level optimization model, so that the proposed technology can select the most economically optimal mode from various possible structures. The upper-level model simulates the system structure selection process, determines the structure type of the system, and realizes the economic optimality of the system structure; the lower-level model simulates the system operation state and determines the optimal operation strategy. The decision result of the upper level will be transmitted to the lower level, affecting the boundary of the system operation state and thus affecting the overall economy.

[0060] Specifically, the establishment of the upper-level optimization model of the wind-solar-hydrogen coupling system includes:

[0061] Construct the upper-level objective function according to the annual total income of the system, the equivalent annual value of the system investment cost, the system operation and maintenance cost, and the annual average equipment depreciation cost of the system;

[0062] Among them, the annual total income of the system is obtained by solving the lower-level optimization model.

[0063] The upper-level optimization model constructs a system optimization model with the maximum annual average net income R of the wind-solar-hydrogen coupling system as the goal. The objective function is:

[0064] maxR = I a -C Acap -C om -C Y

[0065] Among them, Ia is the annual total income of the system; C Acap is the equivalent annual value of the system investment cost; C om is the annual average operation and maintenance cost of the system; C Y is the annual average equipment depreciation cost of the system. Among them, Ia is the annual total income of the system obtained by solving the lower-level optimization model.

[0066] Specifically, the method further includes:

[0067] Determine the equivalent annual value of the system investment cost based on the total investment cost of each device, the investment cost per unit length of each device, the discount rate, and the operation life.

[0068] Among them, the total investment cost of each device is determined based on the investment capacity of each device and the investment cost per unit length of each device.

[0069] The equivalent annual value C of the system investment cost Acap

[0070]

[0071]

[0072] Among them: C CAP，k is the total investment cost of each device, where k = 1 represents the electrolyzer, k = 2 represents the fuel cell, k = 3 represents the hydrogen storage tank, k = 4 represents the power transmission system, k = 5 represents the electrochemical energy storage, k = 6 represents the wind turbine, k = 7 represents the photovoltaic unit, k = 8 represents the auxiliary equipment; r is the discount rate; m is the operation life: ek is the investment cost per unit length of each device; L is the length of the grid connection line; P ely，max 、P fc，max 、P hs，max 、P trans 、P bat 、P wd 、P pv are the investment capacities of the electrolyzer, fuel cell, hydrogen storage tank, power transmission system, electrochemical energy storage, wind turbine, and photovoltaic unit respectively, and are variables to be optimized.

[0073] In some alternative embodiments, the method further includes:

[0074] Determine the annual average operation and maintenance cost of the system according to the percentage of the annual average fixed operation and maintenance cost of each device in the initial investment of the annual average fixed operation and maintenance cost of each device, the operation and maintenance cost coefficient of the electrolyzer, the operation and maintenance cost coefficient of the fuel cell related to the hydrogen production / consumption amount, the hydrogen production rate of the electrolyzer, the power supply load rate of the fuel cell power generation, and the hydrogen consumption rate of the grid connection.

[0075] The annual average operation and maintenance cost C of the system om

[0076]

[0077] Among them: Q k is the percentage of the annual average fixed operation and maintenance cost of each device in its initial investment; Q h1 and Q h2 are the operation and maintenance cost coefficients of the electrolyzer and the fuel cell related to the hydrogen production / consumption amount respectively; V he，i，t is the hydrogen production rate of the electrolyzer; V hf1，i，t and V hf2，i，tThe rates of hydrogen consumption for supplying electrical loads and feeding electricity into the grid by the fuel cell power generation, respectively.

[0078] In some alternative embodiments, the method further includes:

[0079] Determining the annual average equipment depreciation cost of the system according to the total equipment investment cost, the equipment salvage value, and the operation years.

[0080] The annual average equipment depreciation cost C of the system Y

[0081]

[0082] Where: Ccap is the total investment cost; C R is the salvage value, taking 10% of Ccap.

[0083] In some alternative embodiments, the method further includes:

[0084] Constraining the upper-layer optimization model;

[0085] Among them, it is determined whether the wind-solar-hydrogen coupling system is connected to the grid according to the grid-connected binary variable, and it is determined whether the wind-solar-hydrogen coupling system is configured with an electrochemical energy storage according to the configured electrochemical energy storage binary variable;

[0086] When the value of the grid-connected binary variable is 1, it means that the wind-solar-hydrogen coupling system is connected to the grid; when the value of the grid-connected binary variable is 1, it is not connected to the grid;

[0087] When the value of the configured electrochemical energy storage binary variable is 1, it means that the wind-solar-hydrogen coupling system is configured with an electrochemical energy storage, and when the value of the configured electrochemical energy storage binary variable is not 1, it means that it is not configured with an electrochemical energy storage.

[0088] Upper-layer optimization model constraints

[0089] 0 ≤ P tras,max ≤ I net

[0090] 0 ≤ P bat,max ≤ I bat

[0091] I net , I bat ∈ {0, 1}

[0092] P ely,max , P fc,max , P tan,max ≥ 0

[0093] Where: I net and I bat are binary variables for whether to be connected to the grid and whether to be configured with an electrochemical energy storage. I net= 1 indicates that the wind-solar-hydrogen coupling system is connected to the grid. Conversely, it is not connected to the grid. I bat = 1 indicates that the wind-solar-hydrogen coupling system is configured with electrochemical energy storage. Conversely, it is not configured.

[0094] In some optional embodiments of the present invention, the establishment of the lower-layer optimization model of the wind-solar-hydrogen coupling system includes:

[0095] Construct the objective function of the lower-layer optimization model according to the revenue from supplying power to the grid, the revenue from supplying hydrogen to the hydrogen load, the revenue from supplying power to the local load, and the penalty cost for abandoning wind and light;

[0096] Among them, the objective function of the lower-layer optimization model aims at the annual total revenue Ia of the system.

[0097] Determine the revenue from supplying power to the grid according to the total power of the system fed into the grid, the on-grid electricity price, and the transmission loss coefficient;

[0098] Determine the revenue from supplying hydrogen to the hydrogen load according to the speed of supplying hydrogen to the hydrogen load and the hydrogen supply time;

[0099] Determine the revenue from supplying power to the local load according to the power supplied by the wind and light units to the local load, the electricity price for supplying power to the local load in place, and the power supply time;

[0100] Determine the penalty cost for abandoning wind and light according to the penalty price for abandoning wind and light, the per-unit wind turbine output at time t of typical day i, and the per-unit photovoltaic output at time t of typical day i.

[0101] Specifically, the lower-layer optimization model constructs a system optimization model with the maximum annual total revenue Ia of the wind-solar-hydrogen coupling system as the goal. The objective function is:

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] In the formula: the subscript t represents time, and i represents the typical day number; R e1，i，t is the revenue from supplying power to the grid; R h1，i，t is the revenue from supplying hydrogen to the hydrogen load; R e2，i，t is the revenue from supplying power to the local load; R e3，i is the penalty cost for abandoning wind and light. P net，i，t is the total power of the system fed into the grid; K e1，i，t is the on-grid electricity price; μloss is the transmission loss coefficient; V hsell，i，tis the rate of hydrogen supply for the hydrogen load; K h is the direct hydrogen sales price as a transportation fuel; P wload，i，t 、P pvload，i，t is the power supplied by the wind and photovoltaic units to the local load; P fc1，i，t is the power supplied by the fuel cell to the electrical load; K e2 is the electricity price for supplying the electrical load locally. K e3 is the penalty price for curtailed wind and photovoltaic power. τw,i,t and τp,i,t are the per-unit wind and photovoltaic unit outputs at time t of typical day i respectively.

[0108] Constraints are imposed on the objective function of the lower-layer optimization model, including: active power balance constraint for the load, transmission power constraint, hydrogen load demand constraint, and hydrogen energy system operation constraint.

[0109] Specifically, the active power balance constraint for the load

[0110] P w,i,t +P p,i,t +P fc,i,t =P load,i,t +P net,i,t +P ely,i,t

[0111] In the formula: P w，i，t and P p，i，t are the absorbed wind power and photovoltaic power outputs.

[0112] Transmission power constraint,

[0113] The system's grid-connected power should be less than the transmission system capacity, that is

[0114] 0≤P net，i，t ≤P trans，max

[0115] Hydrogen load demand constraint,

[0116] 0≤V hsell，i，t ≤I hload，i V hload，i，t

[0117] Where: V hload，i，t is the hydrogen load demand value.

[0118] The hydrogen energy system operation constraints include: power and efficiency constraints of the electrolyzer, power and efficiency constraints of the hydrogen fuel cell, hydrogen storage tank volume constraint, wind and photovoltaic unit output constraint, and electrical and hydrogen load constraints.

[0119] Specifically, the power and efficiency constraints of the electrolyzer are as follows

[0120] P ely,i,t =η ely V he,i,t

[0121] m i，t P ely，min ≤P ely，i，t ≤m i，t P ely，max

[0122] P ely,i,t -P ely,i,t-1 ≤α clb P ely,max

[0123] Wherein: P ely，min is the minimum operating power of the electrolyzer; mi,t is the start-stop state of the electrolyzer; η ely is the electric energy consumed to produce unit volume (standard cubic meter) of hydrogen. α clb is the ramp-up coefficient of the electrolyzer.

[0124] The power and efficiency constraints of the hydrogen fuel cell are as follows:

[0125] P fc,i,t =η fc V fc,i,t

[0126] Wherein: η fc is the electric energy generated by the fuel cell consuming unit volume (standard cubic meter) of hydrogen.

[0127] The hydrogen storage tank volume constraint is as follows:

[0128]

[0129] Wherein: V h，i，t and V h，i，t+1 are the hydrogen volumes in the hydrogen storage tank in this time period and the next time period respectively; V h，start and V h，end are the hydrogen volumes in the hydrogen storage tank at the initial and final time periods respectively; V h，max is the maximum volume of the hydrogen storage tank, obtained based on the hydrogen storage tank investment capacity P tan，max (unit kg).

[0130] Output constraint of wind-solar unit

[0131] 0≤P w,i,t ≤τ w,i,t P wd,max

[0132] 0≤P p,i,t ≤τ p,i,t P pv,max

[0133] The electric and hydrogen load constraints are as follows:

[0134] I h load,i , I load,i ∈ {0, 1}

[0135] Based on the same inventive concept, an embodiment of the present invention further provides a structure and capacity optimization system for a wind-solar-hydrogen coupling system. Refer to Figure 2 , including:

[0136] A structure classification unit 201, configured to analyze the typical structural characteristics of the wind-solar-hydrogen coupling system. Among them, the structural characteristics are analyzed according to grid connection classification, energy storage type classification, and load type classification;

[0137] A first model unit 202, configured to establish an upper-layer optimization model of the wind-solar-hydrogen coupling system according to the classification result; wherein, the upper-layer optimization model takes the maximum annual average net income R of the wind-solar-hydrogen coupling system as the objective function;

[0138] A second model unit 203, configured to establish a lower-layer optimization model of the wind-solar-hydrogen coupling system; wherein, the lower-layer optimization model takes the maximum annual total income Ia of the system as the objective function;

[0139] A calculation and solution unit 204, configured to solve the upper-layer optimization model and the lower-layer optimization model through a genetic algorithm.

[0140] The present invention proposes a general optimal structure and capacity decision method for a wind-solar-hydrogen coupling system, which can solve the system optimization configuration problem under the condition of unknown system structure and has a broader application scenario. The present invention adopts a two-layer decision-making framework, separating the planning decision variables and the operating state variables, making the established optimization model easier to be solved by commercial solution software and more conducive to popularization in engineering. In terms of the main technical indicators, since this patent further considers the selection of the system structure, it can give full play to the structural characteristics and flexibility characteristics, further improve the economic benefits of the system, and promote the consumption of wind and solar energy.

[0141] Based on the same inventive concept, the present invention also provides an electronic device 161. Refer to Figure 3 , including a processor 164, a communication interface 165, a memory 162, and a communication bus. Among them, the processor 164, the communication interface 165, and the memory 162 complete communication with each other through the communication bus;

[0142] The memory 162 stores a computer program 163;

[0143] When the processor 164 executes the program stored in the memory 162, it implements the structure and capacity optimization method of the wind-solar-hydrogen coupling system.

[0144] The communication bus described above may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc.

[0145] The communication interface 165 is used for communication between the above-mentioned electronic device 161 and other devices.

[0146] The memory 162 may include a Random Access Memory (RAM), or may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory 162 may also be at least one storage device located far from the aforementioned processor 164.

[0147] The processor 164 described above may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0148] Based on the same inventive concept, the present invention also provides a computer-readable storage medium storing a computer program 163, and when the computer program 163 is executed by the processor 164, the structure and capacity optimization method of the wind-solar-hydrogen coupling system described above is implemented.

[0149] The computer-readable storage medium may be included in the device / device described in the above embodiments; it may also exist alone without being assembled into the device / device. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the structure and capacity optimization method of the wind-solar-hydrogen coupling system according to the embodiments of the present disclosure is implemented.

[0150] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for optimizing the structure and capacity of a wind-solar-hydrogen coupling system, characterized in that, it includes: Analyze the typical structural characteristics of the wind-solar-hydrogen coupling system, where the structural characteristics are analyzed according to grid connection classification, energy storage type classification, and load type classification; According to the classification results, establish an upper-layer optimization model for the wind-solar-hydrogen coupling system; among them, the upper-layer optimization model takes the maximum annual average net income R of the wind-solar-hydrogen coupling system as the objective function; Establish a lower-layer optimization model for the wind-solar-hydrogen coupling system; among them, the lower-layer optimization model takes the maximum annual total income Ia of the system as the objective function; Solve the upper-layer optimization model and the lower-layer optimization model through the genetic algorithm.

2. The method according to claim 1, characterized in that, the establishment of the upper-layer optimization model of the wind-solar-hydrogen coupling system includes: Construct an upper-layer objective function according to the annual total income of the system, the equivalent annual value of the system investment cost, the system operation and maintenance cost, and the annual average equipment depreciation cost of the system; Among them, the annual total income of the system is obtained by solving the lower-layer optimization model.

3. The method according to claim 1 or 2, characterized in that, the method further includes: Determine the equivalent annual value of the system investment cost according to the total investment cost of each device, the unit length investment cost of each device, the discount rate, and the operation life; Among them, the total investment cost of each device is determined according to the investment capacity of each device and the unit length investment cost of each device.

4. The method according to claim 3, characterized in that, the method further includes: Determine the annual average operation and maintenance cost of the system according to the percentage of the annual average fixed operation and maintenance cost of each device in the initial investment of the annual average fixed operation and maintenance cost of each device, the operation and maintenance cost coefficient of the electrolyzer, the operation and maintenance cost coefficient of the fuel cell related to the hydrogen production / consumption amount, the hydrogen production rate of the electrolyzer, the power supply rate of the fuel cell power generation to the electric load, and the hydrogen consumption rate of the grid connection.

5. The method according to claim 4, characterized in that, the method further includes: Determine the annual average equipment depreciation cost of the system according to the total investment cost of the equipment, the equipment residual value, and the operation life.

6. The method according to claim 2, characterized in that, the method further includes: Constrain the upper-layer optimization model; Among them, determine whether the wind-solar-hydrogen coupling system is grid-connected according to the grid connection binary variable, and determine whether the wind-solar-hydrogen coupling system is configured with electrochemical energy storage according to the configured electrochemical energy storage binary variable; When the value of the grid connection binary variable is 1, it means that the wind-solar-hydrogen coupling system is grid-connected; when the value of the grid connection binary variable is 1, it is not grid-connected; When the value of the configured electrochemical energy storage binary variable is 1, it means that the wind-solar-hydrogen coupling system is configured with electrochemical energy storage, and when the value of the configured electrochemical energy storage binary variable is not 1, it means that it is not configured with electrochemical energy storage.

7. The method according to claim 1, characterized in that, the establishment of the lower-layer optimization model of the wind-solar-hydrogen coupling system includes: Construct an objective function of the lower-layer optimization model according to the income from power supply to the grid, the income from hydrogen supply to the hydrogen load, the income from power supply to the local load, and the penalty cost for abandoning wind and light; Among them, the objective function of the lower-layer optimization model takes the annual total income Ia of the system as the objective.

8. The method according to claim 7, characterized in that, the method further includes: Determine the revenue from power supply to the power grid based on the total power of the system connected to the grid, the on-grid electricity price, and the transmission loss coefficient; Determine the revenue from hydrogen supply to the hydrogen load based on the hydrogen supply rate to the hydrogen load and the hydrogen supply time; Determine the revenue from power supply to the local load based on the power supplied by the wind and photovoltaic units to the local load, the electricity price for in-situ power supply to the electrical load, and the power supply time; Determine the curtailment cost of wind and photovoltaic power based on the curtailment penalty price of wind and photovoltaic power, the per-unit wind turbine output at time t of typical day i, and the per-unit photovoltaic unit output at time t of typical day i.

9. According to the method described in claim 8, characterized in that, the method further includes: constraining the objective function of the lower-layer optimization model, including: active power balance constraint of the load, transmission power constraint, hydrogen load demand constraint, and hydrogen energy system operation constraint; The hydrogen energy system operation constraint includes: power and efficiency constraint of the electrolyzer, power and efficiency constraint of the hydrogen fuel cell, hydrogen storage tank volume constraint, wind and photovoltaic unit output constraint, and electrical and hydrogen load constraint.

10. A structure and capacity optimization system for a wind-solar-hydrogen coupling system, characterized in that, including: A structure classification unit for analyzing the typical structural characteristics of the wind-solar-hydrogen coupling system, where the structural characteristics are analyzed according to grid connection classification, energy storage type classification, and load type classification; A first model unit for establishing an upper-layer optimization model of the wind-solar-hydrogen coupling system according to the classification results; where the upper-layer optimization model takes the maximum annual average net revenue R of the wind-solar-hydrogen coupling system as the objective function; A second model unit for establishing a lower-layer optimization model of the wind-solar-hydrogen coupling system; where the lower-layer optimization model takes the maximum annual total revenue Ia of the system as the objective function; A calculation and solution unit for solving the upper-layer optimization model and the lower-layer optimization model through a genetic algorithm.

11. An electronic device, characterized in that, including: A processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus; The memory stores a computer program; When the processor executes the program stored in the memory, it implements a structure and capacity optimization method for a wind-solar-hydrogen coupling system according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, stores a computer program, and when the computer program is executed by a processor, it implements a structure and capacity optimization method for a wind-solar-hydrogen coupling system according to any one of claims 1 to 9.

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