Fuel cell system cluster cooperative performance optimal power distribution method
By establishing a steady-state energy consumption characteristic model and constructing a cost function for a fuel cell system cluster, and using a convex approximation method to achieve optimal power allocation for collaborative performance of the fuel cell system cluster, the problem of balancing fuel economy and system durability in existing technologies is solved, and the comprehensive performance optimization of the fuel cell system cluster is realized.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-28
- Publication Date
- 2026-03-10
AI Technical Summary
Existing energy management methods for fuel cell system clusters struggle to achieve a comprehensive optimization between fuel economy and system durability. These methods primarily rely on engineering experience or involve high computational complexity, making it difficult to balance fuel economy and durability in real time.
The optimal power allocation method for the collaborative performance of fuel cell system clusters is adopted. By establishing a steady-state energy consumption characteristic model, fuel economy and durability cost functions are constructed. The explicit weighted form of the comprehensive cost objective optimization function is established using the convex approximation method, and the optimal power allocation is solved in real time.
It achieves optimal power allocation that balances fuel economy and system durability in fuel cell system clusters, and improves the real-time performance and efficiency of energy management.
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Figure CN121642046A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of optimization control of multi-stack fuel cell systems, specifically relating to a method for optimal power allocation of fuel cell system clusters that takes into account fuel economy and system durability. Background Technology
[0002] Hydrogen energy, characterized by its cleanliness, high efficiency, and wide availability, holds immense potential in addressing climate change and the energy crisis, and is considered a crucial cornerstone for achieving zero carbon emissions and sustainable development. Proton exchange membrane fuel cells (PEMFCs) are power devices that convert the chemical energy of hydrogen into electrical energy, serving as a vital component of the hydrogen economy. With increasing electricity demand, the operating power of rail EMUs can reach hundreds of kilowatts or even megawatts. Current technology makes it difficult for a single fuel cell to meet such massive power requirements. However, fuel cell system clusters, composed of multiple fuel cell power systems connected in parallel, can meet the power demands of heavy-haul trains and have a wider range of applications.
[0003] The complexity of fuel cell system clusters presents challenges to energy management, making rational and efficient energy management methods crucial. Existing power allocation optimization methods for commercial fuel cell system clusters primarily rely on rule-based daisy-chaining and average power allocation, depending on engineering experience to determine the rule logic, making it difficult to achieve optimal fuel economy. Furthermore, optimization-based methods, particularly global optimization, suffer from high computational complexity, requiring offline calculations and struggling to balance real-time performance. Most existing instantaneous optimization methods focus on either fuel economy or system durability, neglecting the interplay between the two, thus failing to achieve comprehensive performance optimization for the fuel cell system cluster. Therefore, comprehensively considering both fuel economy and system durability is of paramount importance in the energy management of fuel cell system clusters. Summary of the Invention
[0004] In view of the above-mentioned technical problems in the prior art, the present invention proposes a power allocation method for optimal collaborative performance of fuel cell system clusters. The method is reasonably designed, overcomes the shortcomings of the prior art, and has good results.
[0005] To achieve the above objectives, the present invention adopts the following technical solution: A method for optimal power allocation in a fuel cell system cluster, comprising the following steps: Step S1: Establish a steady-state energy consumption characteristic model of the fuel cell system. The model includes energy consumption characteristics that characterize the relationship between hydrogen consumption rate and net output power of the fuel cell power system, and energy consumption characteristics that characterize the relationship between stack power and net output power of the fuel cell power system. Step S2: Construct the fuel economy cost function and the system durability cost function of the fuel cell power system; Step S3: Based on the steady-state energy consumption characteristic model and cost function of the fuel cell power system, establish the explicit weighted form of the comprehensive cost objective optimization function through the convex approximation method; Step S4: Solve the optimal power allocation result of the fuel cell system cluster in real time based on the load power demand.
[0006] Preferably, step S1 specifically includes the following steps: S101: The electrochemical energy consumption characteristics of a fuel cell power system reflect the relationship between the system's hydrogen consumption rate and net output power. The electrochemical energy consumption characteristics are expressed as follows: (1); in, This represents the hydrogen consumption rate of the i-th fuel cell power system at time t. This represents the net output power of the i-th fuel cell power system at time t. The coefficients represent the electrochemical energy consumption characteristic function of the i-th fuel cell power system; ; S102: The energy consumption characteristics of a fuel cell power system reflect the relationship between the system's net output power and the system's stack power. The energy consumption characteristics are expressed as follows: (2); in, This represents the stack power of the i-th fuel cell power system at time t. , The coefficients represent the energy consumption characteristic function of the i-th fuel cell power system.
[0007] Preferably, step S2 specifically includes the following steps: S201: The cost function for constructing a fuel cell power system's hydrogen consumption is calculated as follows: (3); In the formula, This represents the hydrogen consumption cost of the i-th fuel cell power system at time t. Indicates the price of hydrogen. This indicates the density of hydrogen gas. Indicates the time step for power allocation; S202: Constructing the durability cost function for the aging of a fuel cell power system; under different operating conditions, the fuel cell power system will experience lifespan loss due to performance degradation. This loss will be converted into cost, expressed as: (4); in, This represents the durability cost of the i-th fuel cell power system at time t. This represents the cost of the i-th fuel cell power system operating in the low-power range at time t. This represents the cost of the i-th fuel cell power system operating in the power load range at time t. This represents the cost of the i-th fuel cell power system operating in the high-power range at time t. This indicates the number of individual cells in a fuel cell. Indicates the rated power of the fuel cell power system; The cost function of a fuel cell power system operating in the low-power range is shown in the following equation: (5); in, This indicates the voltage degradation rate of the fuel cell in the low-power range. This is the initial rated voltage of the fuel cell stack. This refers to the unit price of a fuel cell; The cost function of a fuel cell power system operating in the high-power range is shown in the following equation: (6); in, This indicates the voltage degradation rate of the fuel cell in the high-power range; The cost function of the fuel cell power system operating in the power load range is shown below: (7); in, This indicates the voltage degradation rate of the fuel cell within the power load range. This represents the stack power of the i-th fuel cell power system at time t-1.
[0008] Preferably, step S3 specifically includes the following steps: S301: The explicit weighted form of the overall cost objective optimization function is expressed as: (8); In the formula, This represents the overall cost of the fuel cell at time t. This indicates that the fuel cell system cluster contains n fuel cell power systems. This indicates the weighting of hydrogen consumption costs in a fuel cell power system. The durability-weighted weights represent the performance degradation of the fuel cell power system. S302: Substituting the constructed energy consumption characteristic function and cost function of the fuel cell power system into equation (8), we obtain the comprehensive cost objective function of the fuel cell system cluster, which is expressed as a second-order convex function as follows: (9); in, ; In the formula, , , The coefficients represent the overall cost objective function; ; S303: Setting of constraints. The constraints for the optimal power allocation problem of a fuel cell system cluster include: (10); in, , , , , This indicates the maximum net output power of the fuel cell power system. This indicates the minimum net output power of the fuel cell power system. This represents the power demand of the fuel cell system cluster at time t.
[0009] Preferably, step S4 specifically includes the following steps: S401: Calculate the set of switching parameters for the net output power limit of a fuel cell system cluster. ; Based on the performance indicators of the upper limit of the net output power of fuel cell system clusters Determine the order in which each fuel cell power system reaches its power constraint limit at time t; The performance evaluation index for the power upper limit constraint of the i-th fuel cell power system is calculated as follows: (11); in, This represents the upper limit of the net output power of the i-th fuel cell power system at time t. Let represent the net output power of the fuel cell system cluster when the i-th fuel cell power system reaches its upper limit of net output power at time t. , Let represent the coefficients and constants of the first-order term in the power distribution of the i-th fuel cell power system, respectively; the set of performance indices for the power upper limit constraint is represented as follows: And the performance indicators of power upper limit constraints Arrange the power upper limit constraint sequence set in ascending order. ,in, It is a sorting index; then, based on the power upper limit constraint order set, the cluster power requirement when each fuel cell power system reaches its maximum net output power is determined, thus obtaining the sorted fuel cell system cluster net power output upper limit switching set. ,in, The calculation expression is: (12); In the formula, , They represent the process. The coefficients and constants of the first-order power allocation term for the i-th fuel cell power system, which is used to allocate power among the (n-i+1)-th fuel cell systems after sorting. and They represent the elapsed time t. The upper limit of net output power of the i-th and j-th fuel cell power systems after sorting; the coefficient matrix of the first-order term of the power distribution of the fuel cell system cluster at time t. and power distribution constant term matrix The expressions are as follows: (13); (14); in, , They represent the elapsed time t. After sorting, the power distribution coefficients and constants of the (n-1)th system in the n fuel cell power systems cluster; When there are m sets of adjustable fuel cell power systems, the power distribution coefficient of the i-th set is... and The calculation expressions are as follows: (15); Calculate the switching set of the lower limit of net output power of fuel cell system clusters. According to the performance indicators of the lower limit of the net output power of the fuel cell system cluster. Determine the order in which each fuel cell power system reaches the lower power constraint limit at time t; The performance evaluation index for the power lower limit constraint of the i-th fuel cell power system is calculated as follows: (16); in, This represents the net output power of the fuel cell cluster at time t when the net output power of the i-th fuel cell power system drops to the lower power limit and exits regulation. The set of performance indicators for the lower power limit constraint is represented as follows: And the performance evaluation index of the power lower limit constraint. Sort in descending order It is a sorting index; then, based on the power lower limit constraint order set, the sorted net power output lower limit switching set of the fuel cell system cluster is obtained. ,in, The calculation expression is: (17); In the formula, and All indicated that they had gone through The power allocation coefficient of the i-th fuel cell power system for power allocation among the n-i+1 sets of fuel cell systems after sorting; and They represent the elapsed time t. The lower limit of net output power of the i-th and j-th fuel cell power systems after sorting; the coefficient matrix of the first-order term of the power distribution of the fuel cell system cluster at time t. and power distribution constant term matrix The expressions are as follows: (18); (19); in, , They represent the elapsed time t. After sorting, the power distribution coefficients and constants of the (n-1)th system in the n fuel cell power systems cluster; When there are m sets of adjustable fuel cell power systems, the power distribution coefficient of the i-th set is... and The calculation expressions are as follows: (20); S402: Known real-time load power demand At that time, make a judgment The power switching range of the fuel cell system cluster in which it is located The real-time power allocation expression for a fuel cell system cluster is: (twenty one); In the formula, This represents the i-th column of the power distribution linear coefficient matrix after sorting at time t. Let represent the i-th column of the sorted power allocation constant term matrix at time t, where .
[0010] The beneficial technical effects of this invention are as follows: This invention employs a weighted approach, comprehensively considering the impact of fuel economy and system durability of the fuel cell system cluster during energy management optimization. It also takes into account the differences in energy consumption characteristics of each fuel cell power system during the construction of the fuel cell power system energy consumption characteristic model. By solving the real-time optimal power allocation problem, it achieves the optimal power allocation that combines the fuel economy and system durability of the fuel cell system cluster. Attached Figure Description
[0011] Figure 1 This is a flowchart of the steps in the optimal power allocation method for collaborative performance of fuel cell system clusters in this invention; Figure 2 This is a flowchart of the real-time solution for optimal power allocation in the fuel cell system cluster of this invention. Detailed Implementation
[0012] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments: A method for optimal power allocation in a fuel cell system cluster, comprising the following steps: Step S1: Establish a steady-state energy consumption characteristic model for the fuel cell system. This model includes energy consumption characteristics characterizing the relationship between the hydrogen consumption rate and the net output power of the fuel cell power system, and energy consumption characteristics characterizing the relationship between the stack power and the net output power of the fuel cell power system. Specifically, this includes the following steps: S101: The electrochemical energy consumption characteristics of a fuel cell power system reflect the relationship between the system's hydrogen consumption rate and net output power. The electrochemical energy consumption characteristics are expressed as follows: (1); in, This represents the hydrogen consumption rate of the i-th fuel cell power system at time t. This represents the net output power of the i-th fuel cell power system at time t. The coefficients represent the electrochemical energy consumption characteristic function of the i-th fuel cell power system; ; S102: The energy consumption characteristics of a fuel cell power system reflect the relationship between the system's net output power and the system's stack power. The energy consumption characteristics are expressed as follows: (2); in, This represents the stack power of the i-th fuel cell power system at time t. , The coefficients represent the energy consumption characteristic function of the i-th fuel cell power system.
[0013] Step S2: Construct the fuel economy cost function and the system durability cost function of the fuel cell power system; Specifically, the steps include the following: S201: The cost function for constructing a fuel cell power system's hydrogen consumption is calculated as follows: (3); In the formula, This represents the hydrogen consumption cost of the i-th fuel cell power system at time t. Indicates the price of hydrogen. This indicates the density of hydrogen gas. Indicates the time step for power allocation; S202: Constructing the durability cost function for the aging of a fuel cell power system; under different operating conditions, the fuel cell power system will experience lifespan loss due to performance degradation. This loss will be converted into cost, expressed as: (4); in, This represents the durability cost of the i-th fuel cell power system at time t. This represents the cost of the i-th fuel cell power system operating in the low-power range at time t. This represents the cost of the i-th fuel cell power system operating in the power load range at time t. This represents the cost of the i-th fuel cell power system operating in the high-power range at time t. This indicates the number of individual cells in a fuel cell. Indicates the rated power of the fuel cell power system; The cost function of a fuel cell power system operating in the low-power range is shown in the following equation: (5); in, This indicates the voltage degradation rate of the fuel cell in the low-power range. This is the initial rated voltage of the fuel cell stack. This refers to the unit price of a fuel cell; The cost function of a fuel cell power system operating in the high-power range is shown in the following equation: (6); in, This indicates the voltage degradation rate of the fuel cell in the high-power range; The cost function of the fuel cell power system operating in the power load range is shown below: (7); in, This indicates the voltage degradation rate of the fuel cell within the power load range. This represents the stack power of the i-th fuel cell power system at time t-1.
[0014] Step S3: Based on the steady-state energy consumption characteristic model and cost function of the fuel cell power system, establish the explicit weighted form of the comprehensive cost objective optimization function through the convex approximation method; specifically including the following steps: S301: The explicit weighted form of the overall cost objective optimization function is expressed as: (8); In the formula, This represents the overall cost of the fuel cell at time t. This indicates that the fuel cell system cluster contains n fuel cell power systems. This indicates the weighting of hydrogen consumption costs in a fuel cell power system. The durability-weighted weights represent the performance degradation of the fuel cell power system. S302: Substituting the constructed energy consumption characteristic function and cost function of the fuel cell power system into equation (8), we obtain the comprehensive cost objective function of the fuel cell system cluster, which is expressed as a second-order convex function as follows: (9); in, ; In the formula, , , The coefficients represent the overall cost objective function; ; S303: Setting of constraints. The constraints for the optimal power allocation problem of a fuel cell system cluster include: (10); in, , , , , This indicates the maximum net output power of the fuel cell power system. This indicates the minimum net output power of the fuel cell power system. This represents the power demand of the fuel cell system cluster at time t.
[0015] Step S4: Solve the optimal power allocation result of the fuel cell system cluster in real time based on the load power demand.
[0016] Specifically, the steps include the following: S401: Calculate the set of switching parameters for the net output power limit of a fuel cell system cluster. ; Based on the performance indicators of the upper limit of the net output power of fuel cell system clusters Determine the order in which each fuel cell power system reaches its power constraint limit at time t; The performance evaluation index for the power upper limit constraint of the i-th fuel cell power system is calculated as follows: (11); in, This represents the upper limit of the net output power of the i-th fuel cell power system at time t. Let represent the net output power of the fuel cell system cluster when the i-th fuel cell power system reaches its upper limit of net output power at time t. , Let represent the coefficients and constants of the first-order term in the power distribution of the i-th fuel cell power system, respectively; the set of performance indices for the power upper limit constraint is represented as follows: And the performance indicators of power upper limit constraints Arrange the power upper limit constraint sequence set in ascending order. ,in, It is a sorting index; then, based on the power upper limit constraint order set, the cluster power requirement when each fuel cell power system reaches its maximum net output power is determined, thus obtaining the sorted fuel cell system cluster net power output upper limit switching set. ,in, The calculation expression is: (12); In the formula, , They represent the process. The coefficients and constants of the first-order power allocation term for the i-th fuel cell power system, which is used to allocate power among the (n-i+1)-th fuel cell systems after sorting. and They represent the elapsed time t. The upper limit of net output power of the i-th and j-th fuel cell power systems after sorting; the coefficient matrix of the first-order term of the power distribution of the fuel cell system cluster at time t. and power distribution constant term matrix The expressions are as follows: (13); (14); in, , They represent the elapsed time t. After sorting, the power distribution coefficients and constants of the (n-1)th system in the n fuel cell power systems cluster; When there are m sets of adjustable fuel cell power systems, the power distribution coefficient of the i-th set is... and The calculation expressions are as follows: (15); Calculate the switching set of the lower limit of net output power of fuel cell system clusters. According to the performance indicators of the lower limit of the net output power of the fuel cell system cluster. Determine the order in which each fuel cell power system reaches the lower power constraint limit at time t; The performance evaluation index for the power lower limit constraint of the i-th fuel cell power system is calculated as follows: (16); in, This represents the net output power of the fuel cell cluster at time t when the net output power of the i-th fuel cell power system drops to the lower power limit and exits regulation. The set of performance indicators for the lower power limit constraint is represented as follows: And the performance evaluation index of the power lower limit constraint. Sort in descending order It is a sorting index; then, based on the power lower limit constraint order set, the sorted net power output lower limit switching set of the fuel cell system cluster is obtained. ,in, The calculation expression is: (17); In the formula, and All indicated that they had gone through The power allocation coefficient of the i-th fuel cell power system for power allocation among the n-i+1 sets of fuel cell systems after sorting; and They represent the elapsed time t. The lower limit of net output power of the i-th and j-th fuel cell power systems after sorting; the coefficient matrix of the first-order term of the power distribution of the fuel cell system cluster at time t. and power distribution constant term matrix The expressions are as follows: (18); (19); in, , They represent the elapsed time t. After sorting, the power distribution coefficients and constants of the (n-1)th system in the n fuel cell power systems cluster; When there are m sets of adjustable fuel cell power systems, the power distribution coefficient of the i-th set is... and The calculation expressions are as follows: (20); S402: Known real-time load power demand At that time, make a judgment The power switching range of the fuel cell system cluster in which it is located The real-time power allocation expression for a fuel cell system cluster is: (twenty one); In the formula, This represents the i-th column of the power distribution linear coefficient matrix after sorting at time t. Let represent the i-th column of the sorted power allocation constant term matrix at time t, where .
[0017] When the load power demand is known According to equation (21), the power allocation result of the fuel cell system cluster at time t is calculated in real time. After the allocation is completed at time t, the energy consumption characteristic parameters and optimization objective function parameters of each fuel cell power system need to be updated at the new time T. The power allocation result of the fuel cell system cluster at time T is calculated in real time according to step S4. The above process is repeated until the system stops.
[0018] Of course, the above description is not intended to limit the present invention, and the present invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of the present invention should also fall within the protection scope of the present invention.
Claims
1. A method for optimal power allocation in a fuel cell system cluster, characterized in that, The method comprises the following steps: Step S1: establishing a fuel cell system steady-state energy consumption characteristic model, the model comprising an energy consumption characteristic representing the relationship between the hydrogen consumption rate of the fuel cell power system and the net output power of the system, and an energy consumption characteristic representing the relationship between the stack power of the fuel cell power system and the net output power of the system; Step S2: constructing a fuel economy cost function and a system durability cost function of the fuel cell power system; Step S3: based on the fuel cell power system steady-state energy consumption characteristic model and the cost function, establishing an explicit weighted form of a comprehensive cost target optimization function through a convex approximation method; Step S4: solving the optimal power distribution result of the fuel cell system cluster in real time according to the load power demand.
2. The method of claim 1, wherein, Step S1 specifically comprises the following steps: S101: the electrochemical energy consumption characteristic of the fuel cell power system reflects the relationship between the hydrogen consumption rate of the system and the net output power of the system, and is expressed as: （1）； wherein, represents the hydrogen consumption rate of the i-th fuel cell power system at time t, represents the net output power of the i-th fuel cell power system at time t, represents a coefficient of the electrochemical energy consumption characteristic function of the i-th fuel cell power system; ; S102: the electric energy consumption characteristic of the fuel cell power system reflects the relationship between the net output power of the system and the stack power of the system, and is expressed as: （2）； wherein, represents the stack power of the i-th fuel cell power system at time t, , represents the coefficient of the i-th fuel cell power system electric energy consumption characteristic function.
3. The method of claim 1, wherein, Step S2 specifically comprises the following steps: S201: constructing a cost function of the hydrogen consumption of the fuel cell power system, which is calculated as shown in the following formula: （3）； wherein, represents the hydrogen consumption cost of the i-th fuel cell power system at time t, represents the price of hydrogen, represents the density of hydrogen, represents the time step of power allocation; S202: constructing a durability cost function of the service life aging of the fuel cell power system; the fuel cell power system operates under different working conditions, and the service life loss caused by performance degradation is converted into a cost, which is expressed as: （4）； wherein, Ci(t) represents the durability cost of the i-th fuel cell power system at time t, Ci,low(t) represents the cost of the i-th fuel cell power system operating in the low power interval at time t, Ci, var(t) represents the cost of the i-th fuel cell power system operating in the power variable interval at time t, Ci, high(t) represents the cost of the i-th fuel cell power system operating in the high power interval at time t, N represents the number of single cells in the fuel cell, Pn represents the rated power of the fuel cell power system; The cost function of the fuel cell power system operating in the low-power interval is shown in the following formula: （5）； wherein, represents a voltage degradation rate of the fuel cell in a low power range, is an initial rated voltage of the stack, is a unit price of the fuel cell; The cost function of the fuel cell power system operating in the high-power interval is shown in the following formula: （6）； wherein represents the voltage degradation rate of the fuel cell in the high power region; The cost function of the fuel cell power system operating in the power variable load interval is shown in the following formula: （7）； wherein, represents a voltage degradation rate of the fuel cell in a power variable load section, represents a stack power of the i-th fuel cell power system at t-1.
4. The method of claim 1, wherein, Step S3 specifically comprises the following steps: S301: the explicit weighted form of the comprehensive cost target optimization function is expressed as: （8）； In the formula, represents the comprehensive cost of the fuel cell at time t, represents that the fuel cell power system contains n sets of fuel cell power systems in the fuel cell system cluster, represents the weight of the hydrogen consumption cost of the fuel cell power system, represents the weight of the durability of the performance degradation of the fuel cell power system. S302: the fuel cell power system energy consumption characteristic function and the cost function constructed are substituted into formula (8) to obtain a comprehensive cost target function of the fuel cell system cluster, and are expressed by a second-order convex function as follows: （9）； wherein ; wherein , , denotes a coefficient of the overall cost objective function; ; S303: setting the constraint condition, the optimal power distribution problem of the fuel cell system cluster comprises: （10）； wherein, , , , , represents the maximum net output power of the fuel cell power system, represents the minimum net output power of the fuel cell power system, represents the power demand of the fuel cell system cluster at time t.
5. The method of claim 1, wherein, Step S4 specifically comprises the following steps: S401: Calculate the upper limit of the fuel cell system cluster net output power switching set ; Performance index of upper limit of net output power of fuel cell system cluster Determine the order of each set of fuel cell power system reaching the upper limit of power constraint at time t; The performance advantage and disadvantage index calculation expression of the power upper limit constraint of the i-th set of fuel cell power system is as follows: （11）； wherein, represents the upper limit of the net output power of the i-th fuel cell power system at time t, represents the net output power of the fuel cell system cluster when the i-th fuel cell power system reaches the upper limit of the net output power at time t, respectively represent the first-order term coefficient and the constant term of the power distribution of the i-th fuel cell power system; the performance index set of the power upper limit constraint is represented as , and the performance index of the power upper limit constraint is arranged in ascending order to obtain the power upper limit constraint order set , wherein, is the sorting index; the cluster power demand when each fuel cell power system reaches the maximum net output power is determined according to the power upper limit constraint order set, and the sorted fuel cell system cluster net power output upper limit switching set is obtained , wherein, The calculation expression is: （12）； In the formula, , respectively represent the power distribution first-order term coefficient and constant term of the i-th fuel cell power system after sorting between the n-i+1-th fuel cell system after sorting and respectively represent the upper limit of the net output power of the i-th and j-th fuel cell power system after sorting at time t; the power distribution first-order term coefficient matrix of the upper limit of the cluster power of the fuel cell system at time t and the power distribution constant term matrix The expressions are respectively: （13）； （14）； wherein, , respectively represent the power distribution coefficient of the nth-1th system in the n sets of fuel cell power systems in the fuel cell system cluster at time t and the constant term after sorting, the power distribution coefficient of the nth-1th system in the n sets of fuel cell power systems in the fuel cell system cluster at time t and the constant term after sorting, respectively. When the controllable fuel cell power system is m sets, the power distribution coefficient of the i th set and The calculation expression is respectively: （15）； Computing fuel cell system cluster net output power lower limit switching set ; performance index according to fuel cell system cluster net output power lower limit Determining the order of each set of fuel cell power systems reaching the lower limit of power constraints at time t; The performance advantage and disadvantage index calculation expression of the power lower limit constraint of the i-th set of fuel cell power system is as follows: （16）； wherein, represents the net output power of the fuel cell system cluster at time t when the net output power of the i-th fuel cell power system drops to the lower limit of power and exits the regulation, and the performance index set of the lower limit of power constraint is represented as and the performance index of the lower limit of power constraint is arranged in descending order, is the sorting index; and according to the sequence set of the lower limit of power constraint, the sequence set of the lower limit of the net power output of the fuel cell system cluster after sorting is obtained wherein, The calculation expression is: （17）； In the formula, and All indicated that they had gone through The power allocation coefficient of the i-th fuel cell power system for power allocation among the n-i+1 sets of fuel cell systems after sorting; and They represent the elapsed time t. The lower limit of net output power of the i-th and j-th fuel cell power systems after sorting; the coefficient matrix of the first-order term of the power distribution of the fuel cell system cluster at time t. and power distribution constant term matrix The expressions are as follows: （18）； （19）； in, , They represent the elapsed time t. After sorting, the power distribution coefficients and constants of the (n-1)th system in the n fuel cell power systems cluster; When the controllable fuel cell power system is m sets, the power distribution coefficient of the i-th set and The calculation expressions are respectively: （20）； S402: Known real-time load power demand at the time, determine the fuel cell system cluster power switching interval in which it is located, The real-time fuel cell system cluster power allocation solution expression is: (21); wherein denotes the i-th column of the sorted power allocation constant term matrix at time t, wherein denotes the i-th column of the sorted power allocation constant term matrix at time t, wherein .