New energy hydrogen storage micro-grid cooperative scheduling method, system and device and storage medium

Abstract

The invention belongs to the technical field of power system scheduling, and provides a distributed cooperative scheduling method, system and device for a new energy hydrogen storage microgrid system and a storage medium, and the method comprises the steps: taking the power consumption of a hydrogen system as a flexible load, and taking the microgrid cost optimization as a target: constructing a power grid side optimization scheduling model under the limited grid-connected capacity; constructing a hydrogen system side optimization scheduling model; based on the power grid side optimization scheduling model and the hydrogen system side optimization scheduling model, constructing a new energy hydrogen storage micro-grid system collaborative scheduling model under the limited grid-connected capacity; and solving the new energy hydrogen storage micro-grid system collaborative scheduling model under the limited grid-connected capacity, and determining a new energy hydrogen storage micro-grid system collaborative scheduling strategy under the limited grid-connected capacity. According to the method and the device, the power grid side and the hydrogen system side are separately modeled and jointly solved, so that the distributed collaborative scheduling of the new energy hydrogen storage micro-grid system can be realized, and meanwhile, the data privacy security is guaranteed.

Description

Technical Field

[0001] The present disclosure belongs to the technical field of power system dispatching, and relates to a method, system, equipment and storage medium for coordinated dispatching of a new energy hydrogen storage microgrid, and in particular to a method for coordinated dispatching of a distributed new energy hydrogen storage microgrid system under limited grid-connected capacity. Background Art

[0002] To build a clean and efficient energy system and implement the "dual carbon" strategy, my country's green and low-carbon transformation of the power industry is accelerating, with a large number of new energy generating units commissioned. However, the centralized development of new energy generating units can lead to excessive power injection, impacting the safe and stable operation of the upstream power grid.

[0003] As a clean, versatile energy source, hydrogen can improve energy resilience and enhance energy security. Integrating new energy generators with hydrogen energy technology to achieve hydrogen production from electricity can promote the efficient utilization of new energy. Therefore, utilizing hydrogen production from electricity, combined with hydrogen storage and hydrogen-to-electricity technologies, to construct a bidirectional hydrogen-electric microgrid system with limited grid connection capacity is a key path to promoting clean power supply and addressing the challenges of new energy consumption. This is of great significance to promoting my country's energy transition.

[0004] However, the current scheduling of bidirectional electric-hydrogen microgrid systems mostly relies on traditional centralized optimization algorithms. These algorithms rely on all system parameter information, which cannot meet current requirements for data privacy protection for different individuals. Separate scheduling of the electric-hydrogen systems, while ensuring data privacy, makes it difficult to achieve coordinated scheduling, reducing overall system flexibility. Furthermore, currently distributed optimization algorithms are mostly targeted at convex optimization problems, and distributed solutions for mixed-integer programming problems remain under investigation.

[0005] Therefore, it is necessary to find an optimized scheduling method that can not only ensure privacy security but also realize distributed collaborative scheduling of electric-hydrogen microgrid systems. Summary of the Invention

[0006] To solve the above problems, the present disclosure provides a new energy hydrogen storage microgrid coordinated scheduling method, system, equipment and storage medium. The method adopts a method of separate modeling and joint solution of the grid side and the hydrogen system side, which can realize distributed coordinated scheduling of the electric hydrogen microgrid system while ensuring data privacy and security.

[0007] This disclosure gives priority to the following solutions for implementation:

[0008] In a first aspect, embodiments of the present disclosure provide a method for coordinated scheduling of a new energy hydrogen storage microgrid, treating the power consumption of the hydrogen system as a flexible load and aiming at optimizing the microgrid cost:

[0009] Construct a grid-side optimal dispatching model under limited grid-connected capacity;

[0010] Construct an optimal scheduling model for the hydrogen system;

[0011] Based on the grid-side optimization scheduling model and the hydrogen system-side optimization scheduling model, a coordinated scheduling model for new energy hydrogen storage microgrid systems with limited grid-connected capacity is constructed;

[0012] Solve the collaborative scheduling model of the new energy hydrogen storage microgrid system under limited grid-connected capacity, and determine the collaborative scheduling strategy of the new energy hydrogen storage microgrid system under limited grid-connected capacity.

[0013] Further,

[0014] The microgrid includes several new energy units, several energy storage systems, several hydrogen production electrolyzers and several hydrogen fuel cells; the new energy units are connected to the external network through grid-connected interconnection lines.

[0015] Further,

[0016] The grid side includes new energy units, energy storage systems, electrical loads and grid-connected interconnection lines.

[0017] Further,

[0018] The hydrogen system side includes a hydrogen production electrolyzer, a hydrogen storage system and a hydrogen fuel cell.

[0019] Further,

[0020] The grid-side costs include the cost of purchasing electricity from the upper-level grid at all times, the maintenance cost of the energy storage system, and the cost of power curtailment.

[0021] Further,

[0022] The operating costs of the hydrogen system include the cost of using the electrolyzer at all times, the start-up and shutdown costs, and the cost of using the hydrogen fuel cell.

[0023] In the second aspect, based on the same inventive concept, the embodiment of the present disclosure further provides a new energy hydrogen storage microgrid coordinated scheduling device, including a grid side modeling module, a hydrogen system side modeling module, a coordinated scheduling modeling module, and a model solving module; wherein,

[0024] The grid-side modeling module is used to build a grid-side optimization scheduling model under limited grid-connected capacity;

[0025] System-side modeling module, used to build a hydrogen system-side optimization scheduling model;

[0026] A collaborative scheduling modeling module is used to build a collaborative scheduling model for new energy hydrogen storage microgrid systems with limited grid-connected capacity based on the grid-side optimization scheduling model and the hydrogen system-side optimization scheduling model;

[0027] The model solving module is used to solve the coordinated scheduling model of the new energy hydrogen storage microgrid system under limited grid-connected capacity, and determine the coordinated scheduling strategy of the new energy hydrogen storage microgrid system under limited grid-connected capacity.

[0028] In a third aspect, based on the same inventive concept, an embodiment of the present disclosure further provides an electronic device, comprising at least one processor and at least one memory electrically connected;

[0029] The memory is electrically connected to the processor, wherein the memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors so that at least one of the processors can execute any of the aforementioned new energy hydrogen storage microgrid coordinated scheduling methods.

[0030] In a fourth aspect, based on the same inventive concept, an embodiment of the present disclosure further provides a computer storage medium, wherein the computer readable storage medium stores a computer program;

[0031] When the computer program is executed by a processor, any of the aforementioned new energy hydrogen storage microgrid coordinated scheduling methods is implemented.

[0032] In a fifth aspect, based on the same inventive concept, an embodiment of the present disclosure further provides a computer program product, wherein the computer program product is stored in at least one storage medium;

[0033] The computer program product includes several instructions for enabling at least one electronic device to execute any of the aforementioned new energy hydrogen storage microgrid coordinated scheduling methods.

[0034] Compared with the prior art, the present disclosure has the following advantages:

[0035] 1. Traditional centralized joint optimization and scheduling requires the establishment of a unified optimization and scheduling model for both the grid and hydrogen systems. This involves exchanging grid and hydrogen system data, which fails to ensure data privacy. This paper, starting with the grid-side power balance equation and the hydrogen system's power consumption, constructs a distributed joint optimization and scheduling model. This model only requires the exchange of hydrogen system power data, protecting the privacy and operational independence of each individual.

[0036] 2. Directly using distributed solvers for mixed integer programming problems can lead to non-convergence or poor-quality solutions. The disclosed solution involves first solving a linear relaxation of the original problem, then using the linear programming solution as a warm-start to solve the original problem with binary variables, and finally solving a linear programming problem based on the original problem with fixed integer variables. This approach can yield high-quality solutions, or even optimal solutions.

[0037] Other features and advantages of the present disclosure will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present disclosure. The purposes and other advantages of the present disclosure can be realized and obtained by the structures indicated in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0039] Figure 1 A schematic diagram showing the structural principle of a new energy hydrogen storage microgrid according to an embodiment of the present disclosure is shown;

[0040] Figure 2 A schematic diagram of a process for collaborative scheduling of a new energy hydrogen storage microgrid according to an embodiment of the present disclosure is shown;

[0041] Figure 3 A schematic structural diagram of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure more clear, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present disclosure without making any creative efforts shall fall within the scope of protection of the present disclosure.

[0043] The embodiment of the present disclosure involves a new energy hydrogen storage microgrid system with limited grid connection capacity, such as Figure 1 shown. Figure 1 The following diagram only shows a schematic diagram of the structural principle including a new energy unit (power station), an energy storage system, an electrolyzer, a hydrogen fuel cell, an electric load, and a grid connection point to facilitate understanding of the technical solution of the embodiment. In actual application, each of the above components is not limited to one. The following discussion is based on actual application scenarios.

[0044] Figure 2 A flow chart of a new energy hydrogen storage microgrid coordinated scheduling method according to an embodiment of the present disclosure is shown.

[0045] like Figure 2As shown, a new energy hydrogen storage microgrid coordinated scheduling method according to an embodiment of the present disclosure specifically includes the following contents:

[0046] S1. Construct a grid-side optimization dispatching model under limited grid-connected capacity.

[0047] Considering the power consumption of the hydrogen system as a flexible load (a load resource that can quickly respond to large fluctuations in power and energy on both the supply and demand sides of the power system, thereby helping the system balance supply and demand and alleviate peak load pressure), the power balance equation on the grid side is:

[0048]

[0049] Where: N res is the index set of new energy units; N bat is the index set of energy storage systems; is the index set of electric load nodes; N T is the index set of the scheduling period; is the output power of new energy unit i at time t; P t tie is the exchange power of the grid-connected tie line of the new energy unit i at time t; is the exchange power of energy storage system k of new energy unit i at time t; is the electric load power of node m of new energy unit i at time t; P t HES is the power consumption of the hydrogen system of new energy unit i at time t;

[0050] P t tie and The value of can be positive or negative: if P t tie >0, indicating that the upper grid provides power support to the microgrid; if P t tie <0, indicating that the microgrid returns power to the upper grid; if It means that the energy storage system is discharging. Indicates that the energy storage system is charging;

[0051] and P t tie Need to meet the following requirements:

[0052]

[0053] in: is the maximum output power of new energy unit i at time t, is the abandoned power of new energy unit i at time t; P ttie is the lower limit of the exchange power capacity allowed by the grid-connected tie line at time t, is the upper limit of the exchange power capacity allowed by the grid-connected tie line at time t.

[0054] For energy storage system i, there are two states: charging and discharging, respectively. and These two binary variables represent the charging and discharging status at the scheduling time t ( Indicates that it is in charging state. Indicates that it is in the discharging state), the energy storage state and charge / discharge power of the energy storage system are:

[0055]

[0056] in: represents the charging power of energy storage system i at time t; represents the discharge power of energy storage system i at time t; P i ch Indicates the lower limit of charging power of energy storage system i; represents the upper limit of charging power of energy storage system i; P i dis Indicates the lower limit of the discharge power of energy storage system i; Indicates the upper limit of the discharge power of energy storage system i; represents the energy storage of energy storage system i; σ represents the self-discharge rate of energy storage system i; η ch represents the charging efficiency of energy storage system i; η dis represents the discharge efficiency of energy storage system i; E bat represents the energy storage capacity of energy storage system i; Δt represents the scheduling time interval, which is 1 hour in this embodiment; represents the lower limit of energy storage of energy storage system i; represents the upper limit of energy storage capacity of energy storage system i; t f is the last index of the scheduling period index set;

[0057] Inequality (4) represents the charge and discharge state constraints of energy storage system i, to prevent energy storage system i from charging and discharging simultaneously; Inequality (5) represents the upper and lower limit constraints that the charging power of energy storage system i should comply with; Inequality (6) represents the upper and lower limit constraints that the discharging power of energy storage system i should comply with; Inequality (8) represents the upper and lower limit constraints that the energy storage of energy storage system i should comply with; Equation (9) ensures the continuity of scheduling and ensures the stability of power grid operation.

[0058] Therefore, the power exchanged from the energy storage system to the microgrid is:

[0059]

[0060] in: represents the power exchanged by energy storage system i to the microgrid at time t; represents the charging power of energy storage system i at time t; Represents the discharge power of energy storage system i at time t.

[0061] For DC power flow, the power flow equation and line constraints are expressed by the following equations (11) and (12):

[0062]

[0063] Where: P t l is the vector consisting of all line powers at time t; is the vector composed of all bus powers at time t; S F is the vector of power transfer distribution factors; is a vector consisting of the maximum power allowed for all lines at time t.

[0064] In order to promote the consumption of new energy, the cost function of abandoned electricity is introduced, which is expressed as follows:

[0065]

[0066] in: represents the cost of power curtailment at time t; It represents the unit power curtailment cost of new energy unit i.

[0067] The cost of purchasing electricity from the upper-level power grid is:

[0068]

[0069] in: represents the electricity purchase cost at time t; represents the revenue from electricity sales at time t; is the unit power price of electricity purchased at time t; is the unit power price of electricity sold at time t.

[0070] The maintenance cost of the energy storage system is:

[0071]

[0072] in: represents the maintenance cost of the energy storage system at time t; represents the maintenance cost per unit power of the energy storage system k.

[0073] For the grid side, the cost includes the cost of purchasing electricity from the upper grid, the maintenance cost of the energy storage system, and the cost of power abandonment at all times. Therefore, the objective function of the grid side cost optimization scheduling is:

[0074]

[0075] So far, the grid-side optimal dispatching model under limited grid connection capacity composed of equations (1)-(16) is obtained.

[0076] S2. Construct an optimization scheduling model for the hydrogen system.

[0077] The hydrogen system consists of multiple electrolyzers and hydrogen fuel cells. The power consumption of the hydrogen system is expressed as:

[0078]

[0079] Where: N EL Represents the index set of electrolytic cells; N HFC An index set representing a hydrogen fuel cell; represents the power consumption of electrolytic cell n at time t; represents the output power of hydrogen fuel cell i at time t, which satisfies the following equations (18) and (19):

[0080]

[0081] Where: β represents the conversion coefficient of hydrogen energy to electrical energy; represents the hydrogen consumption of hydrogen fuel cell i at time t; represents the lower limit of the output power of hydrogen fuel cell i at time t; Represents the upper limit of the output power of hydrogen fuel cell i at time t.

[0082] Considering the three working states of the electrolytic cell, namely production, standby and idle, L n,t 、S n,t , I n,t These three binary variables represent the production, standby, and idle states of electrolytic cell n at time t (L n,t =1 means it is in production state, S n,t =1 means it is in standby state, I n,t =1 indicates idle state). L n,t 、S n,t , I n,t The logical relationship between the three states is:

[0083]

[0084] Formula (20) indicates that electrolytic cell n cannot be in production, standby, or idle state at the same time.

[0085] Use Y n,t and Z n,tThese two binary variables represent the start and shut down actions of electrolytic cell n at time t (Y n,t =1 means start action, Z n,t =1 means closing action), then Y n,t and Z n,t The relationship between it and the working state variables of the electrolytic cell is:

[0086]

[0087] Considering that the restart time of any electrolyzer is 1 hour, continuous start and stop are not allowed. This constraint can be expressed by formula (23):

[0088]

[0089] When the electrolyzer is in production, it produces hydrogen, but the power consumption is subject to the upper and lower limits of the hydrogen production power. When the electrolyzer is in standby mode, its power consumption is equal to the standby power, but it does not produce hydrogen. When the electrolyzer is idle, it does not produce hydrogen and does not consume power. Therefore, the power consumption and hydrogen production of the electrolyzer are expressed as follows:

[0090]

[0091] in: is the standby power of electrolytic cell n; is the lower limit of hydrogen production power of electrolyzer n; are the upper limits of hydrogen production power of electrolyzer n; Indicates the ramp-down rate of hydrogen production power of electrolyzer n; Indicates the ramp rate of hydrogen production power of electrolyzer n; q n,t represents the amount of hydrogen produced by electrolyzer n at time t;

[0092] A1 and A2 are the hydrogen production characteristic coefficients of electrolyzer n; A3 represents the production reduction coefficient due to startup delay; Inequalities (24) and (25) respectively represent the relationship between the electrolyzer power consumption and the electrolyzer working state and the electrolyzer ramp constraint; Equation (26) represents the relationship between the electrolyzer hydrogen production and the working state; W n,t is a binary variable, representing the transition action of electrolytic cell n from standby state to production state at time t, which satisfies equations (27)-(29):

[0093]

[0094] The hydrogen flow balance equation is:

[0095]

[0096] in: is the hydrogen load at time t; is the hydrogen flow rate flowing out of the hydrogen storage system at time t.

[0097] Taking pressure as the hydrogen storage index of the hydrogen storage system, according to the gas state equation, the hydrogen storage system conforms to the equation:

[0098]

[0099] Where: Z c is the compression coefficient used to correct the compression characteristics of hydrogen under actual conditions; R is the universal gas constant; T is the hydrogen storage temperature; V i sto is the hydrogen storage volume capacity of hydrogen storage system i; It is expressed as the pressure state of hydrogen storage system i at time t, which satisfies equations (32) and (33):

[0100]

[0101] in: Indicates the lower limit of gas pressure allowed by hydrogen storage system i; Indicates the upper limit of gas pressure allowed by hydrogen storage system i.

[0102] Equations (32) and (33) can ensure the safe operation of the hydrogen storage system i and the stable and continuous scheduling.

[0103] The total cost of the electrolyzer includes the cost of using the electrolyzer and the cost of starting and stopping the electrolyzer, which can be expressed as:

[0104]

[0105] in: represents the total cost of the electrolytic cell at time t; c EL Indicates the unit cost of electrolytic cell; c su represents the electrolytic cell startup cost; c sd Represents the electrolyzer stopping cost.

[0106] The cost of using hydrogen fuel cells is expressed as:

[0107]

[0108] in: represents the cost of hydrogen fuel cell at time t; c HFC Indicates the unit usage cost of fuel cells.

[0109] The operating cost of the hydrogen system includes the cost of using the electrolyzer at all times, the start-up and shutdown costs, and the cost of using the hydrogen fuel cell. Therefore, the objective function of the cost optimization scheduling on the hydrogen system side is:

[0110]

[0111] At this point, the hydrogen system side optimization scheduling model including equations (17)-(36) is obtained.

[0112] S3. Based on S1 and S2, a coordinated scheduling model for new energy hydrogen storage microgrid systems under limited grid-connected capacity is constructed.

[0113] Note that P in formula (1) t HES In order to connect the coupling variables of the grid side and the hydrogen system side, we “copy” them and make each of the two systems have a copy of the variables, that is, P t HES Divided into the hydrogen system power variable P owned by the grid side t HES,RePSs and the hydrogen system power variable P on the hydrogen system side t HES,HESs Therefore, equations (1) and (17) can be rewritten as equations (37) and (38):

[0114]

[0115] In order to ensure the consistency of the power consumption of the hydrogen system, the following formula needs to be introduced:

[0116]

[0117] The decision variable on the hydrogen system side is denoted as x, and its objective function is denoted as f(x); the decision variable on the grid side is denoted as y, and its objective function is denoted as g(y). The coordinated scheduling model of the new energy hydrogen storage microgrid system under limited grid connection capacity is expressed as:

[0118]

[0119] Among them: st is the abbreviation of "subject to" in mathematical symbols, which means "subject to".

[0120] At this point, a coordinated scheduling model for new energy hydrogen storage microgrid systems under limited grid-connected capacity has been obtained.

[0121] S4, solution of the distributed collaborative scheduling model of the new energy hydrogen storage microgrid system under limited grid-connected capacity.

[0122] The Alternating Direction Method of Multipliers (ADMM) is an efficient distributed solution algorithm. Based on ADMM, the enhanced Lagrangian function required for the optimization process of Equation (40) is:

[0123]

[0124] Where: λ is the Lagrange multiplier vector; ρ is the penalty factor; ||·||2 is the L2 norm.

[0125] Therefore, to solve the coordinated dispatch model of the new energy hydrogen storage microgrid system under the limited grid connection capacity, the general ADMM-based iterative algorithm (solving basic algorithm 1) specifically includes:

[0126] Step 1: Starting from k=1, initialize the Lagrange multiplier vector λ (0) , sub-problem decision x (0) and y (0) , set the penalty factor ρ, the original residual convergence threshold ò pri and dual residual convergence threshold ò dual , the longest running time T max ;

[0127] Step 2: Solve the sub-problems separately according to equations (42) and (43) to obtain x (k) and y (k) :

[0128]

[0129] Step 3: Calculate the original residual and the dual residual according to Equations (44) and (45) and evaluate the convergence properties, where r (k) and d (k) are the primal residual and the dual residual, respectively.

[0130]

[0131] d (k) =||y (k) -y (k-1) ||2 (45).

[0132] If r (k) <ò pri and d (k) <ò dual , it means that the required convergence criterion has been reached and the iteration is exited. Otherwise, go to step 4;

[0133] Step 4: Update the Lagrange multiplier according to equation (46), and k←k+1.

[0134]

[0135] Repeat steps 2, 3, and 4 until the required convergence criteria or runtime limit is reached, and obtain x (k) and y (k) .

[0136] Solving optimization algorithm:

[0137] However, the coordinated scheduling model for new energy hydrogen storage microgrid systems with limited grid-connected capacity represents a mixed integer programming problem, for which the conventional ADMM approach often struggles to converge. Therefore, an improvement based on the ADMM approach was developed. The optimization step involves first solving a linear relaxation of the original problem, then using the linear programming solution as a warm start to explore binary variables in the original problem, and finally solving the linear programming problem based on the original problem with fixed integer variables.

[0138] The decision variables of the grid side and hydrogen system are divided into continuous variables and integer variables, that is, x=(u x ,v x ) and y=(u y ,v y ), where u x and u y represents binary integer variables in x and y, v x and v y represents the continuous variables in x and y. Therefore, the linear relaxation problem corresponding to the coordinated dispatch model of the new energy hydrogen storage microgrid system under the limited grid connection capacity can be expressed as:

[0139]

[0140] Where: r x 、r y u x and u y dimension.

[0141] For a given binary variable and The linear programming problem with fixed integer variables based on the coordinated dispatch model of the new energy hydrogen storage microgrid system under limited grid-connected capacity can be expressed as:

[0142]

[0143] Therefore, the optimization steps for solving the distributed collaborative scheduling model of the new energy hydrogen storage microgrid system under limited grid-connected capacity are:

[0144] Step a: Starting from m=0, set the upper bound UB←+∞, the optimal decision variable Initial penalty factor ρ (0) , penalty reduction factor τ∈(0,1), maximum running time T' max ;

[0145] Step b: Solve the linear relaxation problem (47) using the basic algorithm 1 to obtain the linear relaxation solution x LP and y LP , and the final objective function value is used as the lower bound LB.

[0146] Step c: Given ρ (m) , using x LP 、y LP As a hot start, the basic algorithm 1 is used to solve the coordinated dispatch model of the new energy hydrogen storage microgrid system under the limited grid capacity to obtain the binary variable solution and

[0147] Step d: Given a binary variable and Solve the linear programming problem (48) using the basic algorithm 1 to obtain the optimal decision variable x at this time. (m) and y (m) , and assign the objective function value to Φ (m) ;

[0148] Step e: If LB≤Φ (m) ≤Φ (m-1) , then x o ←x (m) ,y o ←y (m) , UB (m) ←Φ (m) Otherwise, UB (m) =UB (m-1) .

[0149] Step f: According to ρ (m+1) =τρ (m) Update the penalty factor and repeat steps 3-5 until a suitable solution is found or the runtime limit is reached, and thus x can be obtained (o) and y (o) .

[0150] At this point, a high-quality solution or even the optimal solution of the distributed collaborative scheduling model of the new energy hydrogen storage microgrid system under limited grid-connected capacity has been obtained.

[0151] This disclosure adopts a method of separate modeling and joint solution of the power grid side and the hydrogen system side, which can realize distributed collaborative scheduling of the electric-hydrogen microgrid system while ensuring data privacy and security.

[0152] Based on the same inventive concept, the embodiment of the present disclosure also provides a new energy hydrogen storage microgrid coordinated scheduling device corresponding to the above method, including a grid side modeling module, a hydrogen system side modeling module, a coordinated scheduling modeling module, and a model solving module.

[0153] The grid-side modeling module is used to build a grid-side optimization scheduling model under limited grid-connected capacity;

[0154] System-side modeling module, used to build a hydrogen system-side optimization scheduling model;

[0155] A collaborative scheduling modeling module is used to build a collaborative scheduling model for new energy hydrogen storage microgrid systems with limited grid-connected capacity based on the grid-side optimization scheduling model and the hydrogen system-side optimization scheduling model;

[0156] The model solving module is used to solve the coordinated scheduling model of the new energy hydrogen storage microgrid system under limited grid-connected capacity, and determine the coordinated scheduling strategy of the new energy hydrogen storage microgrid system under limited grid-connected capacity.

[0157] Based on the same inventive concept, the present disclosure also provides an electronic device. Figure 3 As shown, the electronic device of an embodiment of the present disclosure includes at least one electrically connected processor and at least one memory, wherein the memory is electrically connected to the processor, wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the new energy hydrogen storage microgrid coordinated scheduling method as described above.

[0158] It should be noted that the electrical connection between the above-mentioned units does not necessarily mean the connection between lines. An indirect connection method can be applied to the embodiments of the present disclosure as long as the purpose of the present disclosure is achieved.

[0159] Based on the same inventive concept, the present disclosure also provides a computer storage medium, in which a computer program is stored. When the computer program is executed by a processor, the new energy hydrogen storage microgrid coordinated scheduling method as described above is implemented.

[0160] Based on the same inventive concept, the present disclosure also provides a computer program product, which is stored in at least one storage medium; the computer program product includes several instructions for enabling at least one computer device to execute the new energy hydrogen storage microgrid coordinated scheduling method as described above.

[0161] Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A new energy hydrogen storage microgrid coordinated scheduling method, characterized in that: The method comprises, The power consumption of the hydrogen system is regarded as a flexible load, and the goal is to optimize the cost of the microgrid: Construct a grid-side optimal dispatching model under limited grid-connected capacity; Construct an optimal scheduling model for the hydrogen system; Based on the grid-side optimization scheduling model and the hydrogen system-side optimization scheduling model, a coordinated scheduling model for new energy hydrogen storage microgrid systems with limited grid-connected capacity is constructed; Solve the collaborative scheduling model of the new energy hydrogen storage microgrid system under limited grid-connected capacity, and determine the collaborative scheduling strategy of the new energy hydrogen storage microgrid system under limited grid-connected capacity.

2. The method according to claim 1, characterized in that The microgrid includes several new energy units, several energy storage systems, several hydrogen production electrolyzers and several hydrogen fuel cells; the new energy units are connected to the external network through grid-connected interconnection lines.

3. The method according to claim 2, characterized in that The grid side includes new energy units, energy storage systems, electrical loads and grid-connected interconnection lines.

4. The method according to claim 2, characterized in that The hydrogen system side includes a hydrogen production electrolyzer, a hydrogen storage system and a hydrogen fuel cell.

5. The method according to claim 1, wherein The grid-side costs include the cost of purchasing electricity from the upper-level grid at all times, the maintenance cost of the energy storage system, and the cost of power curtailment.

6. The method according to claim 1, characterized in that The operating costs of the hydrogen system include the cost of using the electrolyzer at all times, the start-up and shutdown costs, and the cost of using the hydrogen fuel cell.

7. A new energy hydrogen storage microgrid coordinated dispatching device, characterized in that: The device includes a grid-side modeling module, a hydrogen system-side modeling module, a collaborative scheduling modeling module, and a model solving module; wherein: The grid-side modeling module is used to build a grid-side optimization scheduling model under limited grid-connected capacity; System-side modeling module, used to build a hydrogen system-side optimization scheduling model; A collaborative scheduling modeling module is used to build a collaborative scheduling model for new energy hydrogen storage microgrid systems with limited grid-connected capacity based on the grid-side optimization scheduling model and the hydrogen system-side optimization scheduling model; The model solving module is used to solve the coordinated scheduling model of the new energy hydrogen storage microgrid system under limited grid-connected capacity, and determine the coordinated scheduling strategy of the new energy hydrogen storage microgrid system under limited grid-connected capacity.

8. An electronic device, characterized in that: comprising at least one processor and at least one memory electrically connected; The memory is electrically connected to the processor, wherein the memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors so that at least one of the processors can execute the new energy hydrogen storage microgrid coordinated scheduling method as described in any one of claims 1-6.

9. A computer storage medium, characterized in that The computer readable storage medium stores a computer program; When the computer program is executed by a processor, the new energy hydrogen storage microgrid coordinated scheduling method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product is stored in at least one storage medium; The computer program product includes several instructions for enabling at least one electronic device to execute the new energy hydrogen storage microgrid coordinated scheduling method described in any one of claims 1-6.

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