CN115763908A - Distributed control method for efficiency optimization of multi-stack fuel cell system - Google Patents
Distributed control method for efficiency optimization of multi-stack fuel cell system Download PDFInfo
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Abstract
The invention discloses a distributed control method for optimizing efficiency of a multi-stack fuel cell system, which considers the difference of efficiency characteristics caused by different fuel cell stack performances, each single-stack cell of the multi-stack fuel cell system firstly obtains an efficiency/power curve of the stack by identification, the incremental hydrogen consumption of the single-stack cell is set as a consistency variable, a consistency algorithm is adopted, information interaction iteration between adjacent fuel cells is realized through a distributed communication topology to achieve the consistency of the incremental hydrogen consumption values, the output power corresponding to each stack is obtained, and different given modes of stack control and DC/DC control reference power in a single-stack fuel cell control layer are designed. The invention can realize that the multi-stack fuel cell system can realize the optimal efficiency operation when the electric pile performance of each single-stack system is inconsistent, so as to avoid the dependence on an integrated controller and the damage to the electric pile performance caused by oxygen starvation, thereby improving the high efficiency and the durability of the multi-stack system operation.
Description
Technical Field
The invention belongs to the field of new energy utilization, and relates to an MFCS efficiency optimization power distribution method based on a consistency algorithm.
Background
A Proton Exchange Membrane Fuel Cell (PEMFC) is an energy conversion device that generates electrical energy through an electrochemical reaction between hydrogen and oxygen, and has the characteristics of high power density, high conversion efficiency, and low noise. Because a single-stack fuel cell has limited output power and low reliability, the overall power level of the system is generally improved by connecting a plurality of single PEMFCs in series and parallel to form a Multi-stack fuel cell system (MFCS), and the system has diversified topological structures such as series connection and parallel connection, and the stability and durability of the system are improved by a Multi-stack cooperative operation mode.
Under the background of large development cost and limited application scale of hydrogen energy, the system efficiency is improved, and the reduction of the whole hydrogen consumption is of great significance to the popularization and the application of the fuel cell. For a multi-stack fuel cell system with different power grades or performances of each single PEMFC, how to distribute the output power of each single stack cell is a problem that currently important research is needed to enable the multi-stack system to participate in the coordinated operation of a multi-state energy system in a high-efficiency operation state. The traditional power distribution mode of the multi-stack fuel cell system comprises average distribution and chain distribution, and the existing literature mainly optimizes the power distribution problem of the multi-stack fuel cell system through two modes. Firstly, the efficiency curve identification accuracy and the real-time performance are improved; secondly, an intelligent algorithm is adopted to improve the rationality of distribution so as to realize the optimization goal.
However, the existing power distribution method of the multi-stack fuel cell system has certain defects and shortcomings, and mainly focuses on:
1. most of the existing power distribution modes are designed on the premise that the characteristics of each single battery pile are consistent. The influence of a plurality of factors such as power, galvanic pile temperature, gas pressure, relative humidity, hydrogen supply and system operation dynamic characteristics on the actual efficiency characteristics of the galvanic pile is not considered, and the subsequent power distribution is not accurate enough.
2. Most efficiency optimization control methods based on power self-adaptive distribution obtain efficiency power curves of different numbers of galvanic piles through offline data fitting to realize the tracking of the overall maximum efficiency of the system; however, the starting number of the galvanic piles needs to be changed synchronously when the power is distributed, frequent starting and stopping of the galvanic piles in an actual system is unreasonable, and the difference of output characteristics of the galvanic piles during actual operation is not considered.
3. The existing various self-adaptive distribution modes belong to centralized control, measured data such as voltage, current and the like of a galvanic pile are sent to a centralized controller, power distribution optimization is carried out by using an intelligent optimization algorithm after identification, and then an instruction is issued to each unit controller. The integrated controller needs to perform information interaction with all single-pile FC controllers, a complete communication network is required to be arranged in the system, the construction cost is high, and meanwhile the integrated controller is required to have strong data processing capacity. When the centralized controller or the communication link fails, the centralized control cannot complete the corresponding control target, and thus the reliability is not high.
Disclosure of Invention
The invention provides a distributed control method for optimizing the efficiency of a multi-stack fuel cell system to overcome the defects of the existing method, so that the multi-stack fuel cell system can realize the optimal efficiency operation when the performance of the electric stacks of each single-stack system is inconsistent, the dependence on an integrated controller and the damage to the performance of the electric stacks caused by oxygen starvation are avoided, and the high efficiency, the durability and the stability of the operation of the multi-stack system can be improved.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention relates to a distributed control method for optimizing efficiency of a multi-stack fuel cell system, which is applied to the multi-stack fuel cell system, wherein the multi-stack fuel cell system comprises n single-stack fuel cell systems, and any j-th single-stack fuel cell system comprises the following steps: the j electric pile, the j DC/DC converter, the j DC/DC controller and the j electric pile controller; the distributed control method is characterized by comprising the following steps:
step 1: the jth electric pile controller collects the voltage v of the electric pile fc,j Current i fc,j Auxiliary system power Paux, j, thereby obtaining the single-pile fuel cell efficiency eta corresponding to the current jth electric pile output power by using the formula (1) fcs,j ：
In the formula (1), P fc,j Representing the output power of the jth electric pile, N is the number of electric pile single bodies, eta s,j Represents the thermal efficiency of the jth cell stack, eta e,j Representing the electrical efficiency, η, of the jth cell stack f,j Representing the fuel utilization rate of the jth electric pile; e coefficient related to PEMFC reaction heat; j =1,2,3, …, n; n is the total number of the galvanic pile; p is aux,j Represents the power consumed by the auxiliary equipment of the jth electric pile in the PEMFC system;
identifying a fitting relation between output power and efficiency of each electric pile in the multi-pile fuel cell through a least square method, and obtaining a fitting function of the characterization curve characteristic of the jth electric pile by using an equation (2):
η fcs,j ＝a 0 +a 1 P fc,j +a 2 (P fc,j ) 2 +a 3 (P fc,j ) 3 +a 4 (P fc,j ) 4 +a 5 (P fc,j ) 5 +a 6 (P fc,j ) 6 (2)
in the formula (2), a 0 ，a 1 ，a 2 ，a 3 ，a 4 ，a 5 ，a 6 Is the coefficient to be identified;
step 2: selecting one electric pile from the multi-pile fuel cells as a leading node, and recording the electric pile as a main electric pile; the other n-1 galvanic piles except the leading node are autonomous nodes;
step 2.1: defining the current updating times as k, and initializing k =1; will lead the output power P of the node fc,main Initial output power P as leading node of k-1 update k-1,main (ii) a The output power P of any nth autonomous node is measured fc,v Initial output power P as the leading node of the k-1 th update k-1,v ；
Step 2.2: the leading node receives the current total command power P from the energy management center ref Then, the leading node updates the output power P according to the k-1 th time k-1,main Obtaining the incremental hydrogen consumption value h of the leading node updated at the k-1 th time by using the formula (3) main (k-1)；
In the formula (3), eta fcs,main Representing the efficiency of the leading node;
step 2.3: the n-1 autonomous nodes also obtain the incremental hydrogen consumption value updated at the k-1 time per se according to the formula (3)
Wherein h is v (k-1) an incremental hydrogen consumption value of the v autonomous node updated at the k-1 st time;
step 2.4: the nth autonomous node obtains the k updated incremental hydrogen consumption value h by using the formula (4) v (k)；
In the formula (4), d v,u Representing the connection state between the v-th autonomous node and the u-th autonomous node for the element of the v-th row and the u-th column in the state transition matrix;
step 2.5: the leading node obtains the increment hydrogen consumption value h updated at the kth time by using the formula (5) main (k)；
In the formula (5), d main,j Represents the connection condition between the main node main and the jth electric pile, h j (k-1) represents the incremental hydrogen consumption value of the jth electric pile of the k-1 iteration, delta P (k-1) represents the difference value of the total output power of the electric pile of the k-1 iteration and the instruction power, and P fc,j (k-1) represents the output power of the jth cell stack for k-1 iterations, P ref Represents the total command power, μ is the convergence factor;
step 2.6: obtaining the updated output power P of the jth electric pile at the kth time by using the formula (6) fc,j (k)；
In the formula (6), P min Representing the minimum output power, P, of the stack max Represents the maximum output power of the stack, h j (k) Represents the increment of hydrogen consumption value h of the jth galvanic pile in the kth iteration j -1 [·]Expression (2) represents the inverse of the function;
step 2.7: obtaining a difference value delta P (k) between the total output power of the galvanic pile and the instruction power of the kth iteration by using a formula (7);
step 2.8: judging the incremental hydrogen consumption values of n electric piles
Whether all are equal and | Δ P (k) & gtnon-<If epsilon is true, if yes, the efficiency of the multi-stack fuel cell is optimal, and the current total command power P is used ref Output power of each corresponding electric pile
To the respective single stack fuel cell systems; otherwise, assigning k to k-1, and returning to the step 2.2 for sequential execution; wherein the content of the first and second substances,
represents the optimal output power of the jth electric pile;
and 3, step 3: the jth single-stack fuel cell system receives the optimal output power
Then, the optimum output power received last time
Make a comparison if
The command power P transmitted to the jth stack controller is obtained using equation (8) fc And the command power P of the jth DC/DC controller dc (ii) a Otherwise, the command power P transmitted to the jth stack controller is obtained by equation (9) fc And the command power P of the jth DC/DC controller at the time t dc (t)；
In the formula (9), τ is the FC dynamic time constant.
The electronic device of the invention comprises a memory and a processor, and is characterized in that the memory is used for storing programs for supporting the processor to execute the distributed control method, and the processor is configured to execute the programs stored in the memory.
The invention relates to a computer-readable storage medium, on which a computer program is stored, characterized in that the computer program executes the steps of the distributed control method when being executed by a processor.
Compared with the prior art, the invention has the beneficial effects that:
1. aiming at the problem of efficiency optimization power distribution of a multi-stack battery system, the distributed control power distribution method based on a consistency algorithm is adopted, information interaction and consistency iteration between adjacent electric stacks are realized through topology, the optimal operation of the system efficiency is realized, the centralized control is not relied on, and the distributed control power distribution method has higher reliability. In distributed control, each pile node only needs to communicate with adjacent nodes, the information transmission quantity is small, the requirement on communication topology is not high, certain robustness is achieved, data identification work and power calculation are carried out in the nodes, and the overall data processing pressure of the system is reduced. The network topology structure is more flexible and changeable, the communication construction cost is reduced, and the system expansibility is higher.
2. Based on the control time scale difference caused by the difference of the fuel cell body and the DC/DC dynamic response speed, the invention designs different given modes of the reference power of the air inlet control and the DC/DC control of the electric pile in the single pile control layer, and avoids the damage of oxygen starvation to the electric pile performance on the basis of finishing the power instruction of the upper layer.
Drawings
FIG. 1 is a highway traffic multi-state energy system architecture of the present invention;
FIG. 2 is a block diagram of a fuel cell gas supply system of the present invention;
FIG. 3 is a block diagram illustrating the air supply control of the air compressor according to the present invention;
FIG. 4 is a block diagram of a fuel cell boost converter control of the present invention;
FIG. 5 is a block diagram of the efficiency optimization of a multi-stack fuel cell system of the present invention;
FIG. 6 is a flow chart of the coherency algorithm of the present invention;
FIG. 7 is a multi-stack fuel cell system topology of the present invention;
FIG. 8 is a graph of the efficiency of four different stacks of the present invention;
FIG. 9a is an iterative graph of incremental hydrogen consumption for each node for a scheduling power of 520KW in accordance with the present invention;
FIG. 9b is a graph of total output power of the multi-stack system at 520KW dispatch power in accordance with the present invention;
FIG. 9c is a graph of the output power of each stack of the multi-stack system when the scheduled power is 520KW in accordance with the present invention;
FIG. 10 is a diagram of three different communication networks of the present invention;
FIG. 11a is a diagram of an iterative process for ring topology consistency of the present invention;
FIG. 11b is a diagram of an iterative process for star topology consistency of the present invention;
FIG. 11c is a diagram of an iterative process of chain topology consistency of the present invention;
FIG. 12 is a diagram of the DC/DC reference power given mode of the present invention;
fig. 13 is a graph of the stack output voltage of the present invention.
Detailed Description
The following describes the embodiments and operation principles of the present invention in further detail with reference to the accompanying drawings.
In the embodiment, the distributed control method for optimizing the efficiency of the multi-stack fuel cell system considers the difference of the efficiency characteristics of the stacks caused by the operation condition of each single-stack fuel cell and the performance of the stacks, considers each single-stack fuel cell of the multi-stack fuel cell system as an intelligent body, sets equivalent incremental hydrogen consumption of each single-stack cell as a consistency variable after an efficiency/power curve of each stack is obtained by identification of each intelligent body, adopts a consistency algorithm to perform distributed control on the multi-stack system, achieves consistency of incremental hydrogen consumption values through information interaction iteration between adjacent topological fuel cells, then obtains output power corresponding to each incremental hydrogen consumption value of each stack, controls the stacks to complete corresponding output, and achieves optimal efficiency operation of the multi-stack fuel cell system. Different given modes of the stack air inlet control and the DC/DC control reference power in the single-stack fuel cell control layer are designed, and the system performance is improved through control cooperation.
Fig. 1 is a structural diagram of a road traffic multi-state energy system, and the system is characterized in that a photovoltaic cell, a fan, a fuel cell, an electrochemical energy storage device and other devices are respectively connected to a direct current bus through a converter, and redundant electric energy is used for producing hydrogen through an electrolytic cell to realize large-scale energy storage. The proton exchange membrane fuel cell has a complex gas supply system and a chemical reaction process, and the dynamic response time is slow, so that a multi-pile fuel cell system consisting of proton exchange membrane fuel cell units operates according to an energy scheduling instruction no matter whether a road traffic multi-state energy system is in a networking state or an island state. The invention selects a multi-stack combined operation mode of connecting a plurality of PEMFCs in parallel, improves the integral power level of the system, and simultaneously, each fuel cell is provided with a DC/DC converter which can independently control the power output.
Aiming at the problem of optimizing power distribution of a multi-stack fuel cell system with different single-stack output characteristics, the invention designs a distributed power optimization distribution control framework of the multi-stack fuel cell system based on a consistency algorithm, which comprises an equipment layer, a single-stack control layer and a multi-stack distribution layer, as shown in figure 5. The multi-stack fuel cell system adopts a parallel topology model, and a ring-shaped distributed communication architecture is adopted among the fuel cell systems.
In a multi-stack distribution layer, each stack performs efficiency-power curve identification work in its own fuel cell controller without transmitting measurement data to a centralized controller. Each single-pile cell system is regarded as an intelligent node for distributed control, and when the total scheduling power P of the multi-pile fuel cell system ref When the system changes, a leading node (shown as a node 1 in fig. 5) is set to replace the centralized controller to receive a total power instruction, consistency variable parameters are interacted among the leading node, the plurality of autonomous nodes and other nodes connected with the communication topology, after the consistency is achieved through multiple iterations, a power optimization distribution instruction considering each single-stack efficiency-power curve is obtained, the target of optimal efficiency operation of the multi-stack fuel cell system is achieved, and each stack reference power instruction is transmitted to the single-stack control layer.
The control of the single-stack fuel cell system comprises stack air inlet control (shown in figure 2), DC/DC control (shown in figure 4), humidity control, temperature control and the like, and based on the control time scale difference caused by the difference of the dynamic response speeds of the fuel cell body and the DC/DC control, the invention designs different given modes of reference power of the stack air inlet control and the DC/DC control in a single-stack control layer, and avoids the damage of oxygen starvation to the performance of the stack on the basis of finishing the power instruction of the upper layer.
On the basis of the power distribution mode of the multi-stack fuel cell, the distributed control method for optimizing the efficiency of the multi-stack fuel cell system is applied to the multi-stack fuel cell system, the multi-stack fuel cell system comprises n single-stack fuel cell systems, and any j-th single-stack fuel cell system comprises the following steps: the j electric pile, the j DC/DC converter, the j DC/DC controller and the j electric pile controller; the distributed control method is characterized by comprising the following steps of:
step 1: the jth electric pile controller collects the voltage v of the electric pile fc,j Current i fc,j Auxiliary system power Paux, j, thereby obtaining the single-pile fuel cell efficiency eta corresponding to the current jth electric pile output power by using the formula (1) fcs,j ：
In formula (1), P fc,j Represents the output power of the jth electric pile, N is the number of electric pile monomers, eta s,j Represents the thermal efficiency of the stack, eta e,j Representing the electrical efficiency, η f,j Represents the fuel utilization rate, and is set to 100% in the present invention; e is related to the reaction heat of the PEMFC, if the reaction heat of the galvanic pile Gao Zeshi is 1.48, and if the reaction heat is low, 1.25 is taken; j =1,2,3, …, n; n is the total number of the galvanic piles; p aux,j Indicating the power consumed by the auxiliary equipment in the PEMFC system includes, among other things, the PEMFC controller, the unidirectional DC/DC converter, and the fuel cell auxiliary system power.
Identifying a fitting relation between output power and efficiency of each electric pile in the multi-pile fuel cell through a least square method, and obtaining a fitting function of the characteristic curve of the jth electric pile by using an equation (2):
η fcs,j ＝a 0 +a 1 P fc,j +a 2 (P fc,j ) 2 +a 3 (P fc,j ) 3 +a 4 (P fc,j ) 4 +a 5 (P fc,j ) 5 +a 6 (P fc,j ) 6 (2)
in the formula (2), a 0 ，a 1 ，a 2 ，a 3 ，a 4 ，a 5 ，a 6 Is the coefficient to be identified;
the overall efficiency of the multi-stack fuel cell system is defined as formula (3):
in the formula (3), eta MFCS Overall efficiency of the multi-stack fuel cell; p fc,j ，η fcs,j The output power and the electric pile efficiency of the jth electric pile are respectively; j =1,2,3, …, n (n is the total number of stacks); p ref Is the total scheduled power; p H2 Is the total equivalent hydrogen consumption.
Step 2: multi-stack fuel cell system distributed power optimization distribution control based on consistency algorithm
A first part: theory of consistency algorithm:
the graph theory and the matrix theory are theoretical bases of a consistency algorithm, local information interaction is realized by all distributed control units through interconnected communication lines, and a communication structure among all units can be described by one graph. For a system with n cells, the communication topology is represented by G = (V, E). Wherein, the node set V = {1, …, n }, which represents the set of all vertices in the graph G; edge set
Representing the set of edges to which the nodes are connected. The graph selected by the invention is an undirected graph, namely the information transfer of two connected units is bidirectional. If there are paths between nodes in the graph G, the graph G is called connected, and the system connectivity can use the premise of a discrete consistency algorithm. In graph theory, two matrixes can be used to describe the connection situation between nodes, namely an adjacent matrix A = [ a ] ij ] n×n And laplace matrix L = [ L ] ij ] n×n They are defined by formula (4) and formula (5), respectively:
the consistency algorithm has two types of discrete type and continuity, and communication transmission has discrete characteristics in distributed control, so the invention adopts a first-order discrete consistency algorithm for research.
For a distributed control system with n nodes, let x i [k]A coherency state variable representing node i, where i =1,2, …, n, k is the number of iterations. Node state variable x i [k]By contact with a neighboring node x j [k]And exchanging state information, updating the state quantity of the nodes, and enabling the state variables of all the nodes to be consistent with the increase of the iteration times. The discrete consistency algorithm can be described as equation (6):
can be written as a matrix form as in equation (7):
X(k+1)＝DX(k) (7)
in the formula (7), X (k) = [ X = [) 1 (k)，x 2 (k)，…，x n (k)] T ，D＝[d ij ] n×n For the state transition matrix, D is a random matrix satisfying a certain condition [19，20] And making the state variables of each node finally tend to be consistent through iteration, and particularly, when D is a dual random matrix and the diagonal element is not 0, the state quantity of each node converges to the average value of the initial state quantity.
The structure mode of the state transition matrix D is various, and has influence on the convergence rate of the consistency iterative algorithm, the invention selects a Metropolis method to construct the D matrix, and the form is as the formula (8):
in the formula (8), n i And n j Representing the number of connected nodes of the node i and the node j; n is a radical of i Representing a collection of nodes connected to node i.
A second part: optimizing an objective function by system efficiency:
the output of each single fuel cell stack is reasonably distributed, so that the optimal operation of the overall efficiency of the multi-fuel cell stack is realized. In the process, the dispatching instruction of the upper control center is required to be reached, and the output power constraint of each single battery pile is also required to be met. The objective function and the constraint condition can be summarized as formula (9) by a mathematical model:
the lagrange function can be constructed according to the target of maximum efficiency and the equality constraint of the system contribution as follows:
to P fci And (3) solving the partial derivatives to obtain an optimal solution:
defining equivalent incremental hydrogen consumption h i Comprises the following steps:
the optimal solution of equation (9) is known as:
h 1 ＝h 2 ＝…＝h n ＝-λ (13)
in the formula (13), n is the number of the stacks. Namely, when the equivalent incremental hydrogen consumption of each single fuel cell stack is equal, the multi-stack fuel cell system achieves the optimal overall efficiency.
And a third part: iterative calculation of incremental hydrogen consumption consistency:
selecting one electric pile from the multi-pile fuel cells as a leading node, and recording the electric pile as a main electric pile; the other n-1 galvanic piles except the leading node are autonomous nodes;
step 2.1: defining the current updating times as k, and initializing k =1; will lead the output power P of the node fc,main Initial output power P as the leading node of the k-1 th update k-1,main (ii) a The output power P of any nth autonomous node is measured fc,v Initial output power P as leading node of k-1 update k-1,v ；
Step 2.2: the leading node receives the current total instruction power P from the energy management center ref Then, the leading node updates the output power P according to the k-1 th time k-1,main Obtaining the incremental hydrogen consumption value h of the leading node updated at the k-1 th time by using the formula (14) main (k-1)；
In the formula (14), eta fcs,main Representing the efficiency of the leading node;
step 2.3: the n-1 autonomous nodes also obtain the incremental hydrogen consumption value updated at the k-1 time per se according to the formula (14)
Wherein h is v (k-1) an incremental hydrogen consumption value of the v autonomous node updated at the k-1 st time;
step 2.4: obtaining the increment hydrogen consumption value h updated at the kth time by the aid of the formula (15) by the aid of the nth autonomous node v (k)；
In the formula (15), d v,j Is a state transitionThe element in the v-th row and the j-th column in the matrix represents the connection condition between the v node and other nodes.
Step 2.5: the leading node obtains the increment hydrogen consumption value h of the kth update by using the formula (16) main (k)；
In the formula (16), d main,j Representing the connection status between the leading node main and other nodes, h j (k-1) represents incremental hydrogen consumption value of each node in k-1 iterations, delta P (k-1) represents difference value of total output power and instruction power of the cell stack in k-1 iterations, and P fc,j (k-1) represents the output power of each cell stack for k-1 iterations, P ref Represents the total command power, μ is the convergence factor;
step 2.6: obtaining the updated output power P of the jth electric pile at the kth time by using the formula (17) fc,j (k)；
In the formula (17), P min Represents the minimum output power, P, of the stack max Represents the maximum output power of the stack, h j (k) Represents the increment of hydrogen consumption value h of the jth galvanic pile in the kth iteration j -1 [·]Expression (2) represents the inverse of the function;
step 2.7: obtaining Δ P (k) of the kth update using equation (18);
step 2.8: judging the incremental hydrogen consumption values of n electric piles
Whether all are equal and | Δ P (k) & gtnon-<If epsilon is true, if yes, the efficiency of the multi-stack fuel cell is optimal, and the current total command power P is used ref Correspond toOutput power of each cell stack
To the respective single stack fuel cell systems; otherwise, after k is assigned to k-1, the step 2.2 is returned to be executed in sequence; wherein the content of the first and second substances,
represents the optimal output power of the jth electric pile;
FIG. 6 is a power distribution flow chart based on a consistency algorithm, in each iteration process, a leading node only needs to exchange an incremental hydrogen consumption value with an adjacent node, then iteration updating is carried out according to the consistency algorithm, and corresponding output power is guaranteed to be within a limit range; the autonomous node needs to receive a total scheduling power instruction of the energy management center, and besides information exchange and consistency iteration with adjacent nodes, the autonomous node also needs to calculate the difference value between the total output power of each multi-stack system and the power of an upper-layer scheduling instruction and substitute the difference value into the consistency iteration. When the consistent variables of all the nodes are iterated to be consistent and the power difference value is smaller than the set deviation value, the dispatching power instruction requirement of the energy center is met, the power distribution with the optimal system efficiency is realized, the output power instruction corresponding to each single stack is issued to the control unit, so that the fuel cell outputs the corresponding power, and the aim of the optimal operation of the multi-stack fuel cell system is fulfilled.
And step 3: single-stack fuel cell system control:
when power change or load fluctuation is scheduled, the high-pressure hydrogen storage tank and the air compressor need to provide sufficient hydrogen and oxygen for the electric pile, so that safe and reliable chemical reaction is ensured. The cathode air inlet system is the key point of air inlet control, air is sent into a supply pipeline at a certain flow and pressure by adjusting the voltage of a compressor and changing the rotating speed of an impeller, and the air compressor and the pipeline enable the cathode air inlet system to have obvious time lag. The dynamic response of the whole stack system is mainly influenced by a cathode air inlet system. The power of the air compressor accounts for about 80% of the power of the auxiliary system, and reasonable control of the air compressor is beneficial to reducing the power consumption of the auxiliary system and improving the efficiency of the pile. Therefore, the invention mainly adjusts the air intake quantity by controlling the air compressor.
Fig. 3 is a block diagram of air supply control of an air compressor, according to the principle of electrochemical reaction of a flow field inside a stack, the air amount required by the reaction of a fuel cell is obtained from the output current of the fuel cell, and meanwhile, in order to avoid adverse effects on the stack performance caused by "oxygen starvation" caused by sudden change of current, a certain excess air is provided into the stack by introducing an oxygen ratio λ, so as to obtain a reference value of the air flow, as shown in formula (19):
in formula (19), N is the number of the stack monomers, I fc For the stack output current, mo 2 Is the molar mass of oxygen, χ O2 F is the faraday constant, the oxygen fraction in air.
And after the reference value of the air flow is obtained, the air flow enters closed-loop control of the air flow to control the voltage of the air compressor, change the rotating speed of the air compressor and provide enough oxygen for the electric pile.
Since the dynamic response time of the stack is in the order of seconds and the DC/DC converter is in the order of milliseconds, when the scheduled power command is increased, the regulation of the stack air intake system has a significant time lag, and a rapid increase in DC/DC output power may result in a rapid increase in stack output current and a significant voltage drop, while the air compressor may not be in time to supply sufficient oxygen, which may cause "oxygen starvation" and damage the stack. Therefore, the electric pile air supply system and the DC/DC converter need to be reasonably matched to ensure the safe and stable operation of the system.
When the instruction power is reduced, the gas in the galvanic pile is sufficient, the DC/DC can immediately output the upper layer required power, when the instruction power is increased, the hydrogen and the oxygen in the galvanic pile do not reach the gas flow corresponding to the required power, and if the DC/DC directly outputs the required power, the oxygen starvation phenomenon may occur, which causes serious damage to the galvanic pile. According to two variation trends of the command power, a coordination strategy of the fuel cell and the DC/DC control is provided.
The jth single-stack fuel cell system receives the optimal output power
Then, the optimum output power received last time
Make a comparison if
The command power P transmitted to the jth cell stack controller is obtained by equation (20) fc And the command power P of the jth DC/DC controller dc (ii) a Otherwise, the command power P transmitted to the jth stack controller is obtained by equation (21) fc And the command power P of the jth DC/DC controller at the time t dc (t)；
In the formula (20), τ is an FC dynamic time constant.
An electronic device of the present invention includes a memory for storing a program that supports a processor to execute the above-described distributed control method, and a processor configured to execute the program stored in the memory.
The present invention is a computer-readable storage medium on which a computer program is stored, the computer program being executed by a processor to perform the steps of the distributed control method described above.
In order to verify the effectiveness of the distributed control strategy, a simulation model that four fuel cell stacks are connected to a direct current bus in parallel through DC/DC is built in a simulation platform Matlab/Simulink, each single fuel cell is regarded as an intelligent node, and a communication line between each node adopts a ring topology as shown in FIG. 7 and is used for information transmission of each node in distributed control. In order to verify the effectiveness of the consistency algorithm on the power distribution and efficiency optimization of the multi-stack system, four electric stacks with different output characteristics are selected for verification, and the efficiency/power curve of each single-stack fuel cell is shown in fig. 8.
Simulation 1: efficiency comparison of different power distribution modes:
in order to verify the effectiveness and superiority of the method provided by the invention, the method is compared and analyzed with the traditional average power distribution method and the chained power distribution method. The average distribution is equal distribution, and the total target power is divided by the total number of the electric piles of the multi-pile system, so that the output force of each single pile can be obtained; the chain type distribution galvanic pile is started step by step, and when the output of the current galvanic pile reaches the maximum value, the next galvanic pile can be started until the total power instruction is reached.
Four 150kw fuel cells are selected for analysis, the initial power values of each single-pile cell are respectively 100kw, 90kw, 100kw and 90kw, the galvanic pile 1 is used as a leading node, and receives a total dispatching power instruction of a multi-pile system of a control center, and the total power instruction is 520kw.
As shown in fig. 9a and 9b, the initial total power does not reach the target value, the consistency variables are unequal, after a certain number of iterations, the consistency variables tend to be consistent, the total power of the multi-stack system also reaches the scheduling command value, and the output of each single stack is as shown in fig. 9 c.
Table 1 shows that different power allocation modes compare and compare system efficiencies corresponding to average allocation, chain allocation, and consistent allocation when the total command power is 520kw, and the consistent allocation has an obvious efficiency improvement compared with the two traditional allocation modes.
TABLE 1 comparison of different power distribution modes for a total command power of 520kw
Compared with the traditional average distribution and chain distribution, the power optimization distribution strategy based on the consistency algorithm has obvious advantages in system efficiency, and the efficiency of a multi-stack fuel cell system is improved by 1.02% and 13.43% respectively. Meanwhile, the power distribution improves the operating efficiency of the multi-stack fuel cell system, reduces the hydrogen consumption of the system and realizes the efficient and economic operation of the multi-stack system.
According to the efficiency curves of the four galvanic piles in fig. 8, the corresponding efficiency is different in different power intervals due to different performance of the galvanic piles. Compared with the two traditional power distribution modes, the power distribution mode provided by the invention considers the performance difference between the galvanic piles, the galvanic piles with high efficiency exert more power in the same power interval, and the operating pressure of the fuel cell with insufficient output capacity or poor performance is reduced, so that the service life and the overall performance of a multi-pile system are prolonged, and the consistency of the performance of the galvanic piles and the long-term operation of the multi-pile system are favorably maintained.
Simulation 2: different communication topologies are compared:
the communication topology has an influence on the iteration speed of the consistency algorithm, three different communication topologies of four nodes are selected for comparison in the section, and the three communication topologies are respectively a ring type, a star type and a chain type, as shown in fig. 10. The initial power values of the single-pile batteries are respectively 60kw, 90kw, 70kw and 80kw, the electric pile 1 is used as a leading node, and the total power instruction of the receiving dispatching center is 360kw.
Fig. 11a is a power distribution consistency iteration process of a ring topology stack fuel cell system, fig. 11b is a power distribution consistency iteration process of a multi-stack fuel cell system of a star topology, fig. 11c is a power distribution consistency iteration process of a multi-stack fuel cell system of a chain topology, the three topologies can reach consistency after a certain number of iterations, the number of iterations of the ring topology is the minimum, and the number of iterations of the chain topology is the maximum. The comparison of the three groups of graphs shows that the type (a) topology has higher iterative convergence speed, and the type (c) topology shows that the type (a) topology has certain fault-tolerant capability, when a certain communication line fails, the communication connection of the whole node is not influenced, and the system can also complete the aim of consistent iteration of the node, but the iteration speed is influenced. Simulation 3: DC/DC power given way comparison:
when the dispatching power changes, the single-pile-layer pile controller and the DC/DC controller need to update respective reference power in time, and the pile controller can directly control the air compressor to provide corresponding air flow according to the new instruction power; the DC/DC dynamic response speed is high, and the power setting mode needs to be considered to be matched with the side of the pile.
As shown in fig. 12, mode 1 is a given mode of the conventional DC/DC reference power, and mode 2 is a given mode of the DC/DC reference power proposed by the present invention. As can be seen from the characteristic curve of the output voltage of the cell stack in fig. 13, when the command power suddenly changes, the conventional power setting method of DC/DC may generate an obvious voltage drop, which may damage the performance and the operation durability of the cell stack.
Claims (3)
1. A distributed control method for optimizing efficiency of a multi-stack fuel cell system is applied to the multi-stack fuel cell system, wherein the multi-stack fuel cell system comprises n single-stack fuel cell systems, and any j-th single-stack fuel cell system comprises the following steps: the j electric pile, the j DC/DC converter, the j DC/DC controller and the j electric pile controller; the distributed control method is characterized by comprising the following steps of:
step 1: the jth electric pile controller collects the voltage v of the electric pile fc,j Current i fc,j Auxiliary system power Paux, j, thereby obtaining the single-pile fuel cell efficiency eta corresponding to the current jth electric pile output power by using the formula (1) fcs,j ：
In the formula (1), P fc,j Representing the output power of the jth electric pile, N is the number of electric pile single bodies, eta s,j Represents the thermal efficiency of the jth cell stack, eta e,j Represents the electrical efficiency, η, of the jth cell stack f,j Representing the fuel utilization rate of the jth cell stack; e coefficient related to PEMFC reaction heat; j =1,2,3, …, n; n is the total number of the galvanic piles; p aux,j Represents the power consumed by the auxiliary equipment of the jth electric pile in the PEMFC system;
identifying a fitting relation between output power and efficiency of each electric pile in the multi-pile fuel cell through a least square method, and obtaining a fitting function of the characteristic curve of the jth electric pile by using an equation (2):
η fcs,j ＝a 0 +a 1 P fc,j +a 2 (P fc,j ) 2 +a 3 (P fc,j ) 3 +a 4 (P fc,j ) 4 +a 5 (P fc,j ) 5 +a 6 (P fc,j ) 6 (2)
in the formula (2), a 0 ，a 1 ，a 2 ，a 3 ，a 4 ，a 5 ，a 6 Is the coefficient to be identified;
step 2: selecting one electric pile from the multi-pile fuel cells as a leading node, and recording the electric pile as a main electric pile; the other n-1 galvanic piles except the leading node are autonomous nodes;
step 2.1: defining the current updating times as k, and initializing k =1; will lead the output power P of the node fc,main Initial output power P as leading node of k-1 update k-1,main (ii) a The output power P of any nth autonomous node is measured fc,v Initial output power P as leading node of k-1 update k-1,v ；
Step 2.2: the leading node receives the current total command power P from the energy management center ref Then, the leading node updates the output power P according to the k-1 th time of the leading node k-1,main Obtaining the incremental hydrogen consumption value h of the leading node updated at the k-1 th time by using the formula (3) main (k-1)；
In the formula (3), the reaction mixture is,η fcs,main representing the efficiency of the leading node;
step 2.3: the n-1 autonomous nodes also obtain the incremental hydrogen consumption value updated at the k-1 time per se according to the formula (3)
Wherein h is v (k-1) an incremental hydrogen consumption value of the v autonomous node updated at the k-1 st time;
step 2.4: obtaining the increment hydrogen consumption value h updated at the kth time by the aid of the formula (4) by the aid of the nth autonomous node v (k)；
In the formula (4), d v,u Representing the connection state between the v-th autonomous node and the u-th autonomous node for the element of the v-th row and the u-th column in the state transition matrix;
step 2.5: the leading node obtains the increment hydrogen consumption value h updated at the kth time by using the formula (5) main (k)；
In the formula (5), d main,j Represents the connection condition between the main node main and the jth electric pile, h j (k-1) represents the incremental hydrogen consumption value of the jth electric pile of the k-1 iteration, delta P (k-1) represents the difference value of the total output power of the electric pile of the k-1 iteration and the instruction power, and P fc,j (k-1) represents the output power of the jth cell stack for k-1 iterations, P ref Represents the total command power, μ is the convergence factor;
step 2.6: obtaining the updated output power P of the jth electric pile at the kth time by using the formula (6) fc,j (k)；
Formula (A), (B) and6) In, P min Represents the minimum output power, P, of the stack max Represents the maximum output power of the stack, h j (k) Represents the increment of hydrogen consumption value h of the jth galvanic pile in the kth iteration j -1 [·]Expression (2) represents the inverse of the function;
step 2.7: obtaining a difference value delta P (k) between the total output power of the galvanic pile and the instruction power of the kth iteration by using a formula (7);
step 2.8: judging the incremental hydrogen consumption values of n electric piles
Whether they are all equal, and | Δ P (k) & gtnon<If epsilon is true, if yes, the efficiency of the multi-stack fuel cell is optimal, and the current total command power P is used ref Output power of each corresponding electric pile
To the respective single stack fuel cell systems; otherwise, assigning k to k-1, and returning to the step 2.2 for sequential execution; wherein the content of the first and second substances,
represents the optimal output power of the jth electric pile;
and 3, step 3: the jth single-stack fuel cell system receives the optimal output power
Then, the optimum output power received last time
Make a comparison if
Then use the formula (8) Obtaining the command power P transmitted to the jth electric pile controller fc And the command power P of the jth DC/DC controller dc (ii) a Otherwise, the command power P transmitted to the jth cell stack controller is obtained by equation (9) fc And the command power P of the jth DC/DC controller at the time t dc (t)；
In the formula (9), τ is an FC dynamic time constant.
2. An electronic device comprising a memory and a processor, wherein the memory is configured to store a program that enables the processor to perform the distributed control method of claim 1, and the processor is configured to execute the program stored in the memory.
3. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the distributed control method according to claim 1.
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