Off-grid ammonia hydrogen micro-grid planning method and system considering mixed electrolytic cell and medium

Abstract

The invention relates to an off-grid ammonia-hydrogen micro-grid planning method and system considering a mixed electrolytic bath and a medium, the method is applied to an off-grid hydrogen-hydrogen micro-grid, and the planning method comprises the following steps: modeling for an electric energy-hydrogen energy conversion process of various types of electrolytic bath modules; modeling for the process of transporting hydrogen produced by an electrolytic cell module to an ammonia production node by using a hydrogen long tube trailer; on the premise of considering constraint conditions, constructing a planning model of the off-grid hydrogen amino micro-grid; and performing linear processing on the constraint condition, and obtaining a planning result by solving the planning model of the off-network hydrogen amino micro-grid. Compared with the prior art, the method has the advantages of integrating the advantages of different types of electrolytic cells, reducing the total investment cost, improving the system elasticity, ensuring efficient and stable operation under different conditions and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrid planning, and in particular to an off-grid ammonia-hydrogen microgrid planning method, system and medium considering a hybrid electrolyzer. Background Art

[0002] Against the backdrop of an increasingly severe energy crisis, the need to develop renewable energy has become increasingly prominent. In view of the intermittent and unevenly distributed characteristics of renewable energy, electrolysis hydrogen production technology has solved this problem to a certain extent. Ammonia-hydrogen-based microgrids usually use electrolyzers as basic units to produce hydrogen. Under the requirements of reducing greenhouse gas emissions and achieving decarbonization of the energy and chemical industries, off-grid ammonia-hydrogen-based microgrids are considered to be a promising paradigm for industrial decarbonization.

[0003] Some solutions focus on the coordinated planning of multiple types of energy. For example, China's patent application publication number CN118100241A focuses on the research on hydrogen energy systems, focusing on energy conversion equipment such as electrolyzers and fuel cells, while ignoring the problem of multiple ways of utilizing hydrogen energy in actual production. Based on P2X demand response and synthetic ammonia systems, combined with the constructed wind and solar output, electrolyzer operation, synthetic ammonia system operation and electric-hydrogen hybrid energy storage system models that take into account uncertainty, an economic operation model of the hydrogen-based energy system is established, and the equipment parameters and operation data of the hydrogen-based energy system are input into the economic operation model of the hydrogen-based energy system to obtain the optimal operating parameters of the hydrogen-based energy system, thereby formulating a scheduling plan for the hydrogen-based energy system. The above application mainly considers scheduling from the perspective of demand response, but does not consider the characteristics of off-grid ammonia-hydrogen microgrid scenarios.

[0004] In addition, some schemes optimize the design of microgrids and propose a variety of microgrid design schemes for different application scenarios and needs, aiming to achieve efficient and stable operation of microgrids; some other schemes make improvements on the establishment of ammonia-hydrogen-based microgrid planning models and the optimal configuration and operation of microgrids. However, these studies only consider specific types of electrolyzer equipment and fail to reasonably organize the application of different electrolyzer equipment and integrate the advantages of each equipment, which may lead to insufficient utilization of renewable energy and thus pay a greater price in microgrid investment decisions.

[0005] In summary, how to make full use of existing large-scale synthetic ammonia plants and realize the combination of distributed hydrogen production and centralized ammonia production is an important issue that needs to be solved in the planning of off-grid ammonia-hydrogen-based microgrids. Summary of the invention

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide an off-grid ammonia-hydrogen microgrid planning method, system and medium considering the hybrid electrolyzer, fully considering the characteristics of different types of electrolyzers to realize the planning of off-grid ammonia-hydrogen microgrid, and ensuring efficient and stable operation under different conditions.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] One aspect of the present invention provides an off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer, which is applied to an off-grid hydrogen-amino microgrid, and the planning method comprises the following steps:

[0009] Modeling of the power-to-hydrogen conversion process for various types of electrolyzer modules;

[0010] Modeling the transport of hydrogen produced in the electrolyser modules to the ammonia production nodes using hydrogen tube trailers;

[0011] Under the premise of considering the constraints, a planning model for off-grid hydrogen-amino microgrid is constructed;

[0012] The constraint conditions are linearized and the planning results are obtained by solving the planning model of the off-grid hydrogen-amino microgrid.

[0013] As a preferred technical solution, the modeling process of the electric energy-hydrogen energy conversion process of the various types of electrolyzer modules is modeled as follows:

[0014]

[0015] in, represents the hydrogen output of the electrolyzer at node j in time t, represents the operating efficiency of the electrolyzer at node j, represents the electricity-to-hydrogen conversion coefficient of the electrolyzer at node j, is the input power of the electrolyzer at node j during time t, b j,k is a binary variable indicating whether an electrolyzer module of type k is installed at node j. represents the operating efficiency of the K-type electrolyzer, Indicates the electricity-to-hydrogen conversion coefficient of the K-type electrolyzer

[0016] As a preferred technical solution, the process of transporting hydrogen produced by the electrolyzer module to the ammonia production node using a hydrogen long tube trailer is modeled as follows:

[0017]

[0018]

[0019] in, is a binary variable, which indicates whether the sth vehicle arrives at node j from node i, n represents the total number of hydrogen transport vehicles, and b j,k is a binary variable indicating whether an electrolyser module of type k is installed at node j.

[0020] As a preferred technical solution, the constraints include vehicle transportation capacity restrictions, node hydrogen storage capacity restrictions, and ammonia production node demand restrictions:

[0021]

[0022] in, is a binary variable, used to indicate whether the sth vehicle arrives at node j from node i. represents the hydrogen output of the electrolyzer at node j within time t, Q is the capacity limit of the hydrogen transport vehicle, and H j is the hydrogen storage capacity of node j, is the demand for ammonia at time t, η Am is the conversion rate of hydrogen to ammonia.

[0023] As a preferred technical solution, the constraints include distribution network constraints:

[0024]

[0025] Among them, P i,j,t and Q i,j,t are the active power flow and reactive power flow of branch (i, j) at time t, respectively, j,t and q j,t are the active power and reactive power of node j at time t, respectively, v j,t is the voltage amplitude of node j at time t, r i,j and x i,j are the resistance and reactance on branch (i, j), respectively. (i, j) represents the branch connecting nodes i and j in a tree distribution network with a total of J nodes. is the set of all child nodes of node j, l i,j,t is the square of the branch current.

[0026] As a preferred technical solution, the constraints include the hybrid electrolyzer power constraint and the binary variable constraint of the electrolyzer operating condition switching:

[0027]

[0028]

[0029] in, is the input power of the electrolyzer at node j in time t, is the installed capacity of the electrolyzer equipment at node j, b j,k is a binary variable indicating whether an electrolyzer module of type k is installed at node j. and They represent the upper and lower limits of the installed capacity of the electrolyzer at node j, K is the set of electrolyzer modules, represents the operating status of the electrolytic cell at node j at time t, Represents the operating state action of the electrolytic cell at node j at time t; Represents the operating state transition of the electrolytic cell at node j from state α to state β at time t.

[0030] As a preferred technical solution, the planning results include electrolytic cell selection information, electrolytic cell capacity information, hydrogen tube trailer capacity information and electrolytic cell site selection information.

[0031] As a preferred technical solution, in the planning model, the objective function is modeled as:

[0032]

[0033] Among them, C TOT is the total cost, Represents the electrolyzer investment cost, Represents the cost of vehicle transportation investment; Represents the electrolyzer operating cost, Represents the cost of vehicle transportation operation, is the conversion factor, is the installed capacity of the electrolyzer equipment at node j, is the annual cost coefficient of the k-type electrolyzer module, C veh is the annual cost of each transport vehicle, C hs is the annual cost factor of hydrogen storage equipment, H j represents the hydrogen storage capacity of node j, ω j represents the equipment maintenance cost of node j, represents the cost coefficient from state α to state β, S is the electrolytic cell state set, c i,j represents the transportation cost from node i to node j, represents the operating state of the electrolytic cell at node j at time t, b j,k is a binary variable indicating whether an electrolyzer module of type k is installed at node j, n represents the total number of hydrogen transport vehicles, is the input power of the electrolyzer at node j in time t, is a binary variable used to indicate whether the sth vehicle arrives at node j from node i.

[0034] Another aspect of the present invention provides an off-grid ammonia hydrogen microgrid planning system considering a hybrid electrolyzer, comprising:

[0035] The power-to-hydrogen conversion process modeling module is used to model the power-to-hydrogen conversion process for various types of electrolyzer modules;

[0036] A hydrogen transportation process modeling module, which is used to model the process of transporting hydrogen produced by the electrolyzer module to the ammonia production node using a hydrogen tube trailer;

[0037] The planning modeling module is used to construct the planning model of the off-grid hydrogen-amino microgrid under the premise of considering the constraints;

[0038] The calculation module is used to perform linear processing on the constraint conditions and obtain the planning results by solving the planning model of the off-grid hydrogen-amino microgrid.

[0039] Another aspect of the present invention provides a computer-readable storage medium comprising one or more programs for execution by one or more processors of an electronic device, wherein the one or more programs include instructions for executing the aforementioned off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer.

[0040] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0041] (1) Fully consider the characteristics of different types of electrolyzers: The present invention takes into account the different working states and conversions of electrolyzers, as well as the characteristics and advantages of different types of electrolyzers, thereby establishing an off-grid ammonia-hydrogen-based microgrid planning model and optimizing the utilization efficiency of renewable energy.

[0042] (2) Ensure efficient and stable operation under different conditions: The vehicle routing problem is used to achieve an effective connection between distributed hydrogen production and centralized ammonia production. By constructing operating constraints on the distribution network and its related equipment, the efficient and stable operation of the system under different conditions is ensured, thus realizing green hydrogen and ammonia production. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Flow chart of the off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer in an embodiment;

[0044] Figure 2 Schematic diagram of planning results of off-grid ammonia-hydrogen-based microgrid in the embodiment;

[0045] Figure 3 A schematic diagram of the operation path of a hydrogen transport vehicle of an off-grid ammonia-hydrogen-based microgrid in an embodiment;

[0046] Figure 4 Schematic diagram of planning results of off-grid ammonia-hydrogen-based microgrid considering only ALK;

[0047] Figure 5 Schematic diagram of planning results of off-grid ammonia-hydrogen-based microgrid considering only PEM;

[0048] Figure 6Schematic diagram of the planning results of the off-grid ammonia-hydrogen-based microgrid considering only SOEC. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0050] Example 1

[0051] Regarding the problems existing in the above prior art, see Figure 1 This embodiment provides a method for planning an off-grid ammonia-hydrogen microgrid considering a hybrid electrolyzer, comprising the following steps:

[0052] Step S1, modeling the electricity-hydrogen energy conversion process of various types of electrolyzer modules under the condition of fully considering the characteristics of different electrolyzers.

[0053] The electrolyzer model in the off-grid ammonia-hydrogen-based microgrid system mainly considers the electrolytic hydrogen production process, as well as the different working states of the electrolyzer and their conversion. The specific process of establishing the electrolyzer model is as follows:

[0054] Step S101, use subscript j to indicate the node sequence, use subscript k to indicate the electrolytic cell type, and use binary variable b j,k To indicate whether a type k electrolyzer is installed at node j, if b j,k =1, then "yes", if b j,k =0, then “No”.

[0055] Step S102, the electrolyzer realizes the conversion of electrical energy into hydrogen energy. This process can be expressed as a steady-state linear function of input power:

[0056]

[0057] Where: represents the hydrogen output of the electrolyzer at node j in time t; represents the operating efficiency of the electrolyzer at node j; represents the electricity-to-hydrogen conversion coefficient of the electrolyzer at node j; is the input power of the electrolyzer at node j during time t.

[0058] Step S103, the operating efficiency and conversion coefficient of each node are related to the type of electrolytic cell installed at the node, and the relationship is established by the binary variable in step S101:

[0059]

[0060] Where: It indicates the operating efficiency of the K-type electrolyzer; It represents the electricity-to-hydrogen conversion coefficient of the K-type electrolyzer;

[0061] Step S104, establish a set of operating conditions S = {ON, OFF, STB} to characterize the operating state of the electrolytic cell: start, shut down and standby. Define three sets of binary variables to represent various states and the transitions between them. The binary variables have the following relationship system:

[0062]

[0063] Where: represents the operating status of the electrolytic cell at node j at time t; Represents the operating state action of the electrolytic cell at node j at time t; represents the operating state transition of the electrolytic cell from state α to state β at node j at time t; τ is a quantity related to the initial state α and the final state β, which represents the number of waiting cycles required to transition from state α to state β, where ∧ and ∨ represent and, or, respectively. Indicates no.

[0064] Step S105: There is a certain relationship between the power and the working state in step S102. The electrolyzer operates at different power levels under different working conditions (i.e., working states):

[0065]

[0066] Where: P M and P m are the upper and lower limits of power in the ON state respectively; P stb Indicates the operating power in the STB state.

[0067] Step S2 is to model the process of transporting hydrogen produced by the electrolyzer module to the ammonia production node using a hydrogen long tube trailer. In this embodiment, a hydrogen pipeline trailer is used as an example of a hydrogen long tube trailer for explanation.

[0068] The hydrogen pipeline trailer transportation model in the off-grid ammonia-hydrogen based microgrid system can be solved with the help of the capacity-constrained vehicle routing problem, thereby realizing the connection between distributed hydrogen production and centralized ammonia production. The specific process of model establishment is as follows:

[0069] Step S201, use subscripts i, j, k to indicate the node sequence, node 0 indicates the node where the ammonia production plant is located, superscript s indicates the vehicle sequence, and binary variables Indicates whether the sth vehicle arrives at node j from node i. If Then "yes", if Then “No”.

[0070] Step S202: To ensure that each vehicle must depart from the ammonia production station and eventually return to the ammonia production station, and that the transport vehicle must arrive at the node where the electrolyzer is installed once a day, and that the vehicle transport trajectory is a continuous trajectory, the following equation is established for the binary variables in step S201:

[0071]

[0072] Where: is a binary variable, indicating whether the sth vehicle arrives at node j from node i; n represents the total number of hydrogen transport vehicles.

[0073] Step S203: In step S202, vehicle transportation is subject to capacity constraints. At the same time, node hydrogen storage is also subject to capacity constraints. The amount of hydrogen delivered in a delivery cycle should meet the needs of the ammonia plant. The following inequality is established:

[0074]

[0075] Where: Q is the capacity limit of hydrogen transport vehicles; H j is the hydrogen storage capacity of node j, is the demand for ammonia at time t; η Am is the conversion rate of hydrogen to ammonia.

[0076] Step S3, constructing a planning model for an off-grid hydrogen-amino microgrid under the premise of considering constraints.

[0077] The off-grid ammonia-hydrogen-based microgrid model considering the hybrid electrolyzer module consists of an objective function and constraints, where the objective function is:

[0078]

[0079] Where: C TOT Represents the total cost of the system; represents the electrolyzer investment cost; Represents the investment cost of vehicle transportation; represents the operating cost of the electrolyzer; Represents the cost of vehicle transportation operation; is a conversion factor used to make investment costs comparable to operating costs; represents the installed capacity of the electrolyzer equipment at node j; is the annual cost coefficient of the k-type electrolyzer module; C veh is the annual cost of each transport vehicle; C hs is the annual cost factor of hydrogen storage equipment; H jrepresents the hydrogen storage capacity of node j; ω j represents the equipment maintenance cost of node j; represents the cost coefficient from state α to state β; S is the set of electrolytic cell states; c i,j represents the transportation cost from node i to node j.

[0080] On the premise of the constraints in step S1, the constraints also include distribution network constraints, power constraints, binary variable constraints and other constraints, specifically including the following:

[0081] Distribution network constraints: Consider a tree-like distribution network with a total of J nodes, where (i, j) represents the branch connecting nodes i and j, and the total number of branches is (J+1)-1=J. Definition is the set of all child nodes of node j. The power and voltage relationship between nodes is established by the distribution network constraint:

[0082]

[0083]

[0084] Where: P i,j,t and Q i,j,t are respectively the active power flow and reactive power flow of branch (i, j) at time t; p j,t and q j,t are the active power and reactive power of node j at time t respectively; v j,t is the voltage amplitude of node j at time t; r i,j and x i,j are the resistance and reactance on branch (i, j), l i,j,t Represents the square of the branch current.

[0085] Power constraint: The input power of the electrolyzer equipment in step S102 is limited by the installed capacity. At the same time, the installed capacity of each node is also subject to upper and lower limits:

[0086]

[0087] Where: is the installed capacity of the electrolyzer at node j; and They represent the upper and lower limits of the installed capacity of the electrolyzer at node j respectively.

[0088] Binary variable constraints: The binary variables used in step S101 and step S104 are subject to relevant constraints:

[0089]

[0090] Other constraints: including restrictions and related constraints in the electrolyzer model and the hydrogen pipeline trailer transportation model in step S1 and step S2.

[0091] Step S4, linearizing the complex constraints in the modeling process, and obtaining the planning results by solving the planning model of the off-grid hydrogen-amino microgrid.

[0092] The complex constraints in an off-grid ammonia-hydrogen based microgrid considering a hybrid electrolyser module are linearized, including:

[0093] Step S401, in step S104, the first constraint includes logical AND and OR operations, which can be linearized as follows:

[0094]

[0095] Where: l is used to indicate the subscript of the inequality constraint;

[0096] In step S402 and step S104, the second constraint includes a logical AND or NOT operation. Since the variables connected by the logical OR operation are limited to only one being 1, the logical OR operation can be directly replaced by an addition operation, and the logical NOT operation can be replaced by a subtraction operation. The formula is equivalent to the following:

[0097]

[0098] Step S403, as shown in step S402, there is still a logical AND operation, and a new binary variable Z is defined to replace the term on the left side of the plus sign, then the formula can be equivalently linearized as follows:

[0099]

[0100] Step S404, shown in step S105, has three sets of equivalent constraints. In order to linearize them, it is necessary to define two new sets of binary variables to describe the expressions on the left side of the equivalent symbols:

[0101]

[0102] Where: m From the set {0,P stb ,P m} traverse the value, ξ M From the set {0,P stb ,P M} to traverse the values;

[0103] Step S405: The conditional constraints in step S404 can be equivalently converted into a set of linear inequalities:

[0104]

[0105] In the formula: ε represents an infinitesimal quantity;

[0106] Step S406: With the help of the two sets of binary variables defined in step S404, the equivalent constraints in step S105 can be linearly transformed into:

[0107]

[0108] Since then, the proposed model is reformulated as a mixed-integer linear programming problem, which can be efficiently solved by off-the-shelf optimization solvers.

[0109] To illustrate the effectiveness of this method, the IEEE-33 node system is taken as a simulation example. The planning period is 1 year, the simulation operation cycle is 24 hours a day, and the scheduling unit is 1 hour. The candidate addresses for the installation of electrolyzers (ELC) include nodes 2 to 33. The candidate electrolyzer types include alkaline electrolyzers (ALK), proton exchange membrane electrolyzers (PEM) and solid oxide electrolyzers (SOEC). The electric-hydrogen conversion coefficients of the three electrolyzers are 0.20kg / kWh, 0.25kg / kWh and 0.43kg / kWh, respectively, and the operating efficiencies are 60%, 79% and 90%, respectively. The unit investment costs are 200$ / kW, 350$ / kW and 500$ / kW, respectively. The waiting period from state OFF to state STB is set to 0, 1 and 2, respectively. The waiting period between other state transitions of the three electrolyzers can be ignored. The upper and lower limits of the power of the electrolyzer in state ON are set to 8MW and 0 respectively, and the operating powers of the three electrolyzers in state STB are 0.03MW, 0.1MW and 0.06MW respectively. The capacity of the hydrogen pipeline trailer transport vehicle is 600kg, the vehicle investment cost is 20,000$ / vehicle, the vehicle transportation cost is 0.015$ / (kg·km), and the hydrogen storage tank (HS) cost is 170$ / kg. The conversion rate of synthetic ammonia is set to 0.65. The upper and lower limits of the electrolyzer installed capacity are set to 6MW and 0 respectively.

[0110] The investment planning results and operation planning results obtained by this method are as follows Figure 2 and Figure 3 shown. Figure 2 The investment planning decisions in this method are presented, mainly in terms of electrolyzer selection, site selection, and capacity determination. Distributed hydrogen production is configured on four different nodes of the IEEE-33 bus system, where node 2 is located on the branch of the network and can be regarded as a hub bus. Therefore, in order to better utilize renewable energy generation, a larger capacity electrolyzer and hydrogen storage facility are installed at this node. Figure 3The diagram shows the route of a typical day's hydrogen pipeline trailer operation. Due to capacity limitations, two vehicles are used for hydrogen transportation. Node 2 is equipped with a larger hydrogen storage facility, so vehicle 1 only transports hydrogen between the ammonia plant and node 2, while vehicle 2 transports hydrogen between nodes 19, 22, 26 and the ammonia plant.

[0111] After obtaining the investment and operation decisions of the off-grid ammonia-hydrogen microgrid considering the hybrid electrolyzer module established by this method, in order to verify the effectiveness and economy of the model, a simplified case considering only a single electrolyzer was used for comparative analysis. The investment planning results of the simplified cases are shown in the figure below. Figures 4 to 6 As shown, Figures 4 to 6 These are the cases where only ALK, PEM and SOEC are considered respectively.

[0112] according to Figures 4 to 6 Considering that nodes closer to power generation nodes are more significantly affected by renewable energy fluctuations, PEM electrolyzers have better adaptability to fluctuations and have obvious advantages in adapting to power fluctuations. However, only considering the cases of ALK and SOEC, there is no choice, resulting in unsatisfactory overall planning results. Secondly, the investment cost of the off-grid ammonia-hydrogen-based microgrid of this method is about $2.62×10 6 , operating costs are about $2.68×10 6 , the total cost is about $5.30×10 6 ; Considering only ALK’s off-grid ammonia-hydrogen-based microgrid, the investment cost is about $3.15×10 6 , operating costs are about $1.86×10 6 , the total cost is about $6.01×10 6 Considering only PEM, the investment cost of an off-grid ammonia-hydrogen-based microgrid is about $4.38×10 6 , operating costs are about $2.35×10 6 , the total cost is about $6.73×10 6 Considering only SOEC, the investment cost of off-grid ammonia-hydrogen-based microgrid is about $5.21×10 6 , operating costs are about $2.56×10 6 , the total cost is about $7.77×10 6 It can be seen that the off-grid ammonia-hydrogen-based microgrid system established by this method has a total system cost reduced by 11.8% compared with the simplified scenario using only a single type of electrolyzer, which is mainly reflected in the reduction of investment planning costs.

[0113] In summary, the off-grid ammonia-hydrogen-based microgrid planning method and system considering the hybrid electrolyzer module established by the present invention have certain practical significance and application prospects.

[0114] This method takes into account the different working states of the electrolyzer and its conversion, the advantages of different electrolyzers in terms of economy and fluctuation adaptability, and the characteristics and advantages of different types of electrolyzers, and establishes an off-grid ammonia-hydrogen-based microgrid system planning model. On the other hand, the vehicle routing problem is used to achieve an effective connection between distributed hydrogen production and centralized ammonia production. By systematically analyzing the operating constraints of the distribution network and its related equipment, the efficient and stable operation of the system under different conditions is ensured, and green hydrogen and ammonia production is achieved.

[0115] Example 2

[0116] Based on Example 1, this example provides an off-grid ammonia-hydrogen microgrid planning system considering a hybrid electrolyzer, including:

[0117] The power-to-hydrogen conversion process modeling module is used to model the power-to-hydrogen conversion process for various types of electrolyzer modules;

[0118] A hydrogen transportation process modeling module, which is used to model the process of transporting hydrogen produced by the electrolyzer module to the ammonia production node using a hydrogen tube trailer;

[0119] The planning modeling module is used to construct the planning model of the off-grid hydrogen-amino microgrid under the premise of considering the constraints;

[0120] The calculation module is used to perform linear processing on the constraint conditions and obtain the planning results by solving the planning model of the off-grid hydrogen-amino microgrid.

[0121] Example 3

[0122] This embodiment provides a computer-readable storage medium, including one or more programs for execution by one or more processors of an electronic device, wherein the one or more programs include instructions for executing the off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer as described in Example 1.

[0123] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for planning an off-grid ammonia-hydrogen microgrid considering a hybrid electrolyzer, characterized in that: Applied to an off-grid hydrogen-amino microgrid, the planning method comprises the following steps: Modeling of the power-to-hydrogen conversion process for various types of electrolyzer modules; Modeling the transport of hydrogen produced in the electrolyser modules to the ammonia production nodes using hydrogen tube trailers; Under the premise of considering the constraints, a planning model for off-grid hydrogen-amino microgrid is constructed; The constraint conditions are linearized and the planning results are obtained by solving the planning model of the off-grid hydrogen-amino microgrid.

2. The off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer according to claim 1, characterized in that: The modeling process of the electricity-hydrogen energy conversion process of the various types of electrolyzer modules is modeled as follows: in, represents the hydrogen output of the electrolyzer at node j in time t, represents the operating efficiency of the electrolyzer at node j, represents the electricity-to-hydrogen conversion coefficient of the electrolyzer at node j, is the input power of the electrolyzer at node j during time t, b j,k is a binary variable indicating whether an electrolyzer module of type k is installed at node j. represents the operating efficiency of the K-type electrolyzer, Indicates the electricity-to-hydrogen conversion coefficient of the K-type electrolyzer.

3. The off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer according to claim 1, characterized in that: The process of transporting hydrogen produced by the electrolyzer module to the ammonia production node using a hydrogen long tube trailer is modeled as follows: in, is a binary variable, which indicates whether the sth vehicle arrives at node j from node i, n represents the total number of hydrogen transport vehicles, and b j,k is a binary variable indicating whether an electrolyser module of type k is installed at node j.

4. The off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer according to claim 1, characterized in that: The constraints include vehicle transport capacity restrictions, node hydrogen storage capacity restrictions, and ammonia production node demand restrictions: in, is a binary variable, used to indicate whether the sth vehicle arrives at node j from node i. represents the hydrogen output of the electrolyzer at node j within time t, Q is the capacity limit of the hydrogen transport vehicle, and H j is the hydrogen storage capacity of node j, is the demand for ammonia at time t, η Am is the conversion rate of hydrogen to ammonia.

5. The off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer according to claim 1, characterized in that: The constraints mentioned include distribution network constraints: Among them, P i,j,t and Q i,j,t are the active power flow and reactive power flow of branch (i, j) at time t, respectively, j,t and q j,t are the active power and reactive power of node j at time t, respectively, v j,t is the voltage amplitude of node j at time t, r i,j and x i,j are the resistance and reactance on branch (i, j), respectively. (i, j) represents the branch connecting nodes i and j in a tree distribution network with a total of J nodes. is the set of all child nodes of node j, l i,j,t is the square of the branch current.

6. The off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer according to claim 1, characterized in that: The constraints include the power constraint of the hybrid electrolyzer and the binary variable constraint of the electrolyzer operating condition switching: in, is the input power of the electrolyzer at node j in time t, is the installed capacity of the electrolyzer equipment at node j, b j,k is a binary variable indicating whether an electrolyzer module of type k is installed at node j. and They represent the upper and lower limits of the installed capacity of the electrolyzer at node j, K is the set of electrolyzer modules, represents the operating status of the electrolytic cell at node j at time t, Represents the operating state action of the electrolytic cell at node j at time t; Represents the operating state transition of the electrolytic cell at node j from state α to state β at time t.

7. The off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer according to claim 1, characterized in that: The planning results include electrolyzer selection information, electrolyzer capacity information, hydrogen tube trailer capacity information and electrolyzer site selection information.

8. The off-grid ammonia-hydrogen microgrid planning method considering hybrid electrolyzers according to claim 1, characterized in that: In the planning model, the objective function is modeled as: Among them, C TOT is the total cost, Represents the electrolyzer investment cost, Represents the cost of vehicle transportation investment; Represents the electrolyzer operating cost, Represents the cost of vehicle transportation operation, is the conversion factor, is the installed capacity of the electrolyzer equipment at node j, is the annual cost coefficient of the k-type electrolyzer module, C veh is the annual cost of each transport vehicle, C hs is the annual cost factor of hydrogen storage equipment, H j represents the hydrogen storage capacity of node j, ω j represents the equipment maintenance cost of node j, represents the cost coefficient from state α to state β, S is the electrolytic cell state set, c i,j represents the transportation cost from node i to node j, represents the operating state of the electrolytic cell at node j at time t, b j,k is a binary variable indicating whether an electrolyzer module of type k is installed at node j, n represents the total number of hydrogen transport vehicles, is the input power of the electrolyzer at node j in time t, is a binary variable used to indicate whether the sth vehicle arrives at node j from node i.

9. An off-grid ammonia-hydrogen microgrid planning system considering a hybrid electrolyzer, characterized in that: include: The power-to-hydrogen conversion process modeling module is used to model the power-to-hydrogen conversion process for various types of electrolyzer modules; A hydrogen transportation process modeling module, which is used to model the process of transporting hydrogen produced by the electrolyzer module to the ammonia production node using a hydrogen tube trailer; The planning modeling module is used to construct the planning model of the off-grid hydrogen-amino microgrid under the premise of considering the constraints; The calculation module is used to perform linear processing on the constraint conditions and obtain the planning results by solving the planning model of the off-grid hydrogen-amino microgrid.

10. A computer-readable storage medium, characterized in that: It includes one or more programs for execution by one or more processors of an electronic device, and the one or more programs include instructions for executing an off-grid ammonia-hydrogen microgrid planning method considering a hybrid electrolyzer as described in any one of claims 1-8.

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