CN117476983A - Battery power supply system output power control method, device, equipment and storage medium - Google Patents

Battery power supply system output power control method, device, equipment and storage medium Download PDF

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CN117476983A
CN117476983A CN202311471229.9A CN202311471229A CN117476983A CN 117476983 A CN117476983 A CN 117476983A CN 202311471229 A CN202311471229 A CN 202311471229A CN 117476983 A CN117476983 A CN 117476983A
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power
battery
output power
fuel cell
fcs
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沈凯
姚海燕
张旭峰
邢海青
夏红军
张甜甜
郭强
陈世喆
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State Grid Zhejiang Electric Power Co Ltd Hangzhou Yuhang District Power Supply Co
Hangzhou Power Equipment Manufacturing Co Ltd
Hangzhou Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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State Grid Zhejiang Electric Power Co Ltd Hangzhou Yuhang District Power Supply Co
Hangzhou Power Equipment Manufacturing Co Ltd
Hangzhou Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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Priority to CN202311471229.9A priority Critical patent/CN117476983A/en
Publication of CN117476983A publication Critical patent/CN117476983A/en
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    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00—Fuel cells; Manufacture thereof
    • H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298—Processes for controlling fuel cells or fuel cell systems
    • H01M8/04992—Processes for controlling fuel cells or fuel cell systems characterised by the implementation of mathematical or computational algorithms, e.g. feedback control loops, fuzzy logic, neural networks or artificial intelligence
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/44—Methods for charging or discharging
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00—Fuel cells; Manufacture thereof
    • H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298—Processes for controlling fuel cells or fuel cell systems
    • H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/04537—Electric variables
    • H01M8/04604—Power, energy, capacity or load
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00—Fuel cells; Manufacture thereof
    • H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298—Processes for controlling fuel cells or fuel cell systems
    • H01M8/04694—Processes for controlling fuel cells or fuel cell systems characterised by variables to be controlled
    • H01M8/04858—Electric variables
    • H01M8/04925—Power, energy, capacity or load
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H01M2010/4271—Battery management systems including electronic circuits, e.g. control of current or voltage to keep battery in healthy state, cell balancing

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Abstract

The invention relates to the battery power supply technology, and discloses a method, a device, equipment and a computer readable storage medium for controlling the output power of a battery power supply system, wherein the battery power supply system comprises a power battery and a fuel battery; the output power control method comprises the following steps: collecting user power in real time, and predicting a user power predicted value; determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the objective function is minimum according to the predicted value of the electric power used by the user and the constraint condition; the objective function is a function which takes the output power of the fuel cell as a variable and represents the operation loss of the fuel cell and the power cell; and determining the output power of the power battery according to the optimal output power of the fuel battery, and controlling the output power of the battery power supply system. The power supply cost of the power supply system is reduced, the hysteresis of output power adjustment is avoided, and the stability of the power supply state of the power supply system formed by the fuel cell and the power cell is ensured.

Description

Battery power supply system output power control method, device, equipment and storage medium
Technical Field
The present invention relates to the field of battery power supply technologies, and in particular, to a method, an apparatus, a device, and a computer readable storage medium for controlling output power of a battery power supply system.
Background
With the development of industrial technologies of various industries, electric energy gradually becomes a foundation stone for promoting the operation of various industries, and the electric energy plays an indispensable role in charging of a production line of factories, medical equipment of hospitals and smart phones. Although various power generation technologies are rapidly developed at present, the generated energy is rapidly improved, and in practical application, a power failure condition is unavoidable.
In order to meet the demand of supplying electric energy when the power grid is in outage, a battery power supply system of a fuel battery and a power battery is used as a standby electric energy source, so that economic losses caused by outage can be reduced to a certain extent. How to reasonably control the output power of the battery power supply system is important to reduce the running cost of the battery power supply system.
Disclosure of Invention
The invention aims to provide a method, a device and equipment for controlling the output power of a battery power supply system and a computer readable storage medium, which can more reasonably control the output power of the battery power supply system and reduce the running cost of the battery power supply system.
In order to solve the technical problems, the invention provides an output power control method of a battery power supply system, wherein the battery power supply system comprises a power battery and a fuel battery; the output power control method includes:
collecting user power in real time, and predicting and obtaining a predicted value of the user power in a second preset time period after the current moment according to the user power in the first preset time period before the current moment;
performing optimization operation on a pre-established objective function according to the predicted value of the electric power consumption of the user and a pre-determined constraint condition, and determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the operation result of the objective function is minimum; wherein the objective function is a function representing the operation loss of the fuel cell and the power cell by taking the output power of the fuel cell as a variable;
determining the power battery output power at the next moment according to the fuel battery optimal output power corresponding to the next moment at the current moment in the fuel battery optimal output powers;
and controlling the output power of the battery power supply system according to the optimal output power of the fuel battery corresponding to the next moment at the current moment and the output power of the power battery at the next moment.
Optionally, the process of creating the objective function in advance includes:
determining a fuel cell degradation cost model taking the output power of the fuel cell as a variable according to the operation rule of the fuel cell;
determining a battery charge state transfer equation of the power battery according to the operation rule of the power battery;
determining the objective function as based on the fuel cell degradation cost model and the battery state of charge transfer equationWherein C is fcs,j Fuel cell degradation cost at the jth time point and is an amount of change associated with the fuel cell output power; d (D) soc,j A power battery penalty term for the j-th time point, and +.>D p Is a constant; SOC (0) =soc 0 The method comprises the steps of carrying out a first treatment on the surface of the SOC (m) is the state of charge of the power battery corresponding to the mth time point; and P is fcs (k)+P b (k)+P 0 ＝P de (k)；P de (k) For the user power prediction value, P at the kth time point fcs (k) The fuel cell output power for the kth time point; p (P) b (k) The power battery output power for the kth time point; p (P) 0 The output power of the power battery supplying power to the fuel cell when the fuel cell is started, P after the fuel cell is started 0 Is 0.
Optionally, the pre-created fuel cell degradation cost model includes:
C fcs,j ＝C low,j +C high,j +C chg,j ,j＝0,1,2…；
Wherein C is fcs,j Fuel cell degradation cost for the j-th time point;
C low,j for the degradation cost caused by the low load at the jth time point,γ low for the fuel cell to output less than 20% of rated powerA voltage decay rate per hour at low load; t (T) low,j For the duration of low load at the jth time point, V fcs,eol M is the voltage of the fuel cell in EOL state fcs For fuel cell cost, M fcs ＝100β fcs ，β fcs Outputting a price per kilowatt of electricity for the fuel cell;
C high,j for the degradation cost caused by the high load at the jth time point,γ high a voltage decay rate per hour at a high load of not less than 80% of a rated power for the fuel cell output power; t (T) high,j A high load duration for the j-th time point;
C chg,j for the degradation cost caused by the load change at the jth time point,γ chg a voltage decay rate per kilowatt during which the output power of the fuel cell is in a transient load change; p (P) fcs (m) fuel cell output power at the mth time point; n is n fcs Is the number of fuel cells.
Optionally, the process of creating the battery state of charge model includes:
calculating the battery charge state of the power battery by adopting an ampere-hour integration method, and determining a battery charge state transfer equation of the power battery Taking the battery charge state transfer equation as the battery charge state model;
wherein Q is m For the battery capacity of the power battery, Δt is the time step of the discrete sampling interval; i b For the current of the power battery,U b,oc open circuit voltage for power battery，R b Is the internal resistance of the power battery; p (P) b And outputting power to the power battery.
Optionally, the constraint includes:
SOC state constraints of the power battery: SOC (State of Charge) min ≤SOC(q)≤SOC max The method comprises the steps of carrying out a first treatment on the surface of the Wherein SOC is max And SOC (System on chip) min The maximum value and the minimum value of the charge state of the power battery are respectively;
output power constraint of the power battery: p (P) b,min ≤P b (k)≤P b,max ；P b,min And P b,max Respectively the minimum output power and the maximum output power of the power battery;
an output power constraint of the fuel cell; p (P) fcs,min ≤P fcs (k)≤P fcs,max ；P fcs,min And P fcs,max Respectively, the minimum output power and the maximum output power of the fuel cell;
the output power variation constraint of the fuel cell: ΔP fcs,min ≤ΔP fcs (k)≤ΔP fcs,max ；ΔP fcs,min And DeltaP fcs,max The minimum output power variation and the maximum output power variation of the fuel cell, respectively.
Optionally, predicting to obtain the predicted value of the electric power of the user in the second preset time period after the current time according to the electric power of the user in the first preset time period before the current time includes:
Inputting the user power in a first preset time period before the current moment into an MLP neural network model obtained by training a neural network in advance, and predicting to obtain a predicted value of the user power in a second preset time period after the current moment.
Optionally, according to the predicted value of the electric power for the user and a predetermined constraint condition, performing an optimization operation on a pre-created objective function, and determining the optimal output power of the fuel cell at each time point in a second preset time period after the current time when the operation result of the objective function is minimum, where the method includes:
and carrying out optimization operation on a pre-established objective function by adopting an MPC optimization algorithm according to the predicted value of the electric power of the user and a pre-determined constraint condition, and optimally determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the operation result of the objective function is minimum.
An output power control device of a battery power supply system, the battery power supply system including a power battery and a fuel battery; the output power control device includes:
The power prediction module is used for acquiring the user power in real time, and predicting and obtaining a predicted value of the user power in a second preset time period after the current moment according to the user power in the first preset time period before the current moment;
the first power operation module is used for carrying out optimization operation on a pre-established objective function according to the predicted value of the electric power used by the user and a pre-determined constraint condition, and determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the operation result of the objective function is minimum; wherein the objective function is a function representing the operation loss of the fuel cell and the power cell by taking the output power of the fuel cell as a variable;
the second power operation module is used for determining the power battery output power at the next moment according to the fuel battery optimal output power corresponding to the next moment at the current moment in the fuel battery optimal output powers;
and the output control module is used for controlling the output power of the battery power supply system according to the optimal output power of the fuel battery corresponding to the next moment at the current moment and the output power of the power battery at the next moment.
An output power control apparatus of a battery-powered system, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method for controlling output power of a battery powered system according to any of the above, when executing the computer program.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method of controlling output power of a battery powered system as claimed in any one of the preceding claims.
The invention provides a method, a device, equipment and a computer readable storage medium for controlling output power of a battery power supply system, wherein the battery power supply system comprises a power battery and a fuel battery; the output power control method comprises the following steps: collecting user power in real time, and predicting and obtaining a predicted value of the user power in a second preset time period after the current moment according to the user power in the first preset time period before the current moment; performing optimization operation on a pre-established objective function according to a predicted value of the electric power used by a user and a pre-determined constraint condition, and determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the operation result of the objective function is minimum; the objective function is a function representing the operation loss of the fuel cell and the power cell by taking the output power of the fuel cell as a variable; determining the power battery output power at the next moment according to the optimal output power of the fuel battery corresponding to the next moment at the current moment in the optimal output power of each fuel battery; and controlling the output power of the battery power supply system according to the optimal output power of the fuel battery corresponding to the next moment at the current moment and the output power of the power battery at the next moment.
In the process of supplying power to users by using a fuel cell and a power cell, an objective function representing the running cost of the fuel cell and the power cell is created, so that the fuel cell output power corresponding to the minimum objective function is obtained by continuously adjusting the fuel cell output power for optimization iteration; in the process of iteratively optimizing the operation result of the objective function, according to the predicted value of the predicted electric power of the user, the output power of the fuel cell corresponding to a series of time points which enable the operation result of the objective function to be minimum in a period of time after the current moment can be determined at the same time, so that on one hand, the hysteresis of the regulation of the output power of the whole power supply system of the battery can be avoided, and on the other hand, the stability of the power supply state of the power supply system formed by the fuel cell and the power cell is ensured on the basis of ensuring the low-cost operation of the fuel cell and the power cell.
Drawings
For a clearer description of embodiments of the invention or of the prior art, the drawings that are used in the description of the embodiments or of the prior art will be briefly described, it being apparent that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from them without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of an output power control method of a battery power supply system according to an embodiment of the present application;
fig. 2 is a block diagram of an output power control device of a battery power supply system according to an embodiment of the present invention.
Detailed Description
The fuel cell means a cell using hydrogen as a main fuel; the source of electrical energy in the power cell can be from a fuel cell or from a grid charging when the grid is not powered off.
In the process of power failure of the power grid and power supply of the power battery, the power battery can be utilized to provide an initial starting electric energy for the fuel battery, and after the fuel battery is started, at least one of the power battery or the fuel battery can be utilized to supply power for a user.
In the conventional battery power supply system formed by the fuel cell and the power cell, the power cell is generally used for supplying power to a user preferentially, and once the output power of the power cell is insufficient to provide the power required by the user, the fuel cell is started, and the fuel cell and the power cell are used for providing the required power for the user together. However, the method cannot achieve the maximization of the economic benefit of power supply, and along with the fluctuation of the power demand of a user, the frequent fluctuation of the output power of the whole power supply system is also easily caused, so that the stable operation of the power supply system is not facilitated.
In order to better understand the aspects of the present invention, the present invention will be described in further detail with reference to the accompanying drawings and detailed description. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, fig. 1 is a schematic structural diagram of an output power control method of a battery power supply system according to an embodiment of the present application.
The battery powered system referred to in this application includes a power cell and a fuel cell. In a specific embodiment of the present application, the method for controlling output power of the battery power supply system may include:
s11: and acquiring the power consumption of the user in real time, and predicting and obtaining a predicted value of the power consumption of the user in a second preset time period after the current moment according to the power consumption of the user in the first preset time period before the current moment.
In this embodiment, the user power consumption in the first preset time period before the current time may be the user power consumption obtained by sampling at each time point within 24 hours before the current time, or may be the user power consumption collected at each time point within one week or even one month before the current time, which is not particularly limited in this application, so long as the accuracy of the predicted value of the user power consumption obtained by the subsequent prediction can be ensured.
In the process of predicting and determining the predicted value of the power consumption of the user, a great amount of historical power consumption of the user can be utilized in advance to carry out neural network learning training, and a neural network model is obtained; therefore, the user power consumption in the first preset time period before the current moment can be input into the neural network model, the neural network model is utilized to learn and train the user power consumption, and the predicted value of the user power consumption in the second preset time period after the current moment is predicted.
In an alternative embodiment of the present application, the process of determining the predicted value of the user power consumption may include:
and inputting the electric power used by the user in a first preset time period before the current moment into an MLP neural network model obtained by training the neural network in advance, and obtaining the predicted value of the electric power used by the user in a second preset time period after the current moment.
It can be understood that the MLP neural network model in this embodiment is obtained by training the neural network by taking a large amount of data of the historical user power as a sample in advance. The MLP neural network model can also be called as an MLP multi-layer perceptron, is one of the neural network models, the collected user power is input into an input layer of the MLP multi-layer perceptron, iterative learning is carried out through a hidden layer, and the output layer can output the predicted value of the user power after the current moment.
Of course, in practical application, the prediction of the electric power of the user is not necessarily realized by adopting the MLP neural network, and the prediction can be performed by adopting a convolutional neural network or a neural network model obtained after learning and training of other types of neural networks, so long as the accuracy of the predicted value of the electric power of the final user can be ensured.
S12: and carrying out optimization operation on the pre-established objective function according to the predicted value of the electric power used by the user and the pre-determined constraint condition, and determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the operation result of the objective function is minimum.
The objective function is a function representing the operation loss of the fuel cell and the power cell by taking the output power of the fuel cell as a variable.
It will be appreciated that the objective function is characterized by the operating costs of both the fuel cell and the power cell, and is theoretically related to not only the fuel cell output but also the power cell output. However, the battery power supply system in the application only comprises two batteries, namely a fuel battery and a power battery, to supply electric energy to users; therefore, theoretically, the sum of the fuel cell output power and the power cell output power should be equal to the electric power required by the user. In the case that the electric power used by the user is predicted and known, the power output of the power battery can be expressed by the power output of the fuel battery, so that the objective function simultaneously determined by the power output of the fuel battery and the power output of the power battery can be converted into a function only related to the power output of the fuel battery, and the optimization operation process of the objective function can be simplified.
On this basis, in an alternative embodiment of the present application, the process of performing the optimization operation on the objective function may include:
and (3) carrying out optimization operation on the pre-established objective function by adopting an MPC optimization algorithm according to the predicted value of the electric power of the user and the pre-determined constraint condition, and optimally determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the operation result of the objective function is minimum.
In this embodiment, an MPC optimization algorithm is adopted, and an objective function is used as a cost function to predict the optimal output power of the fuel cell at each time point in a second preset time period after the current time.
In this embodiment, the optimal output power of the fuel cell at each time point after the current time point can be predicted and determined by performing an optimization operation on the objective function by using the user power consumption value after the current time point predicted by the user power consumption before the current time point, which is equivalent to determining the optimal output powers of the fuel cell and the power cell in advance in future time, so that the output powers of the fuel cell and the power cell are correspondingly adjusted in advance, and the problem of hysteresis of the control adjustment of the output powers of the fuel cell and the power cell is avoided.
On the basis, in the embodiment, the optimal output power of the fuel cell corresponding to a series of time points in a period of time after the current moment is predicted at one time, namely, data of a group of optimal output powers of the fuel cell are obtained; therefore, in the process of optimizing the objective function, the optimal output power of the fuel cell at a series of time points corresponding to the minimum calculation result of the objective function in the second preset time period after the current moment is adopted; compared with the method for only determining the optimal output power of the fuel cell, which enables the operation result of the objective function at the next moment at the present moment to be minimum, the method for optimizing the operation objective function in the embodiment can better maintain the stability of the whole operation of the battery power supply system, and avoid the large fluctuation of the output powers corresponding to the fuel cell and the power cell.
S13: and determining the power battery output power at the next moment according to the fuel battery optimal output power corresponding to the next moment at the current moment in the optimal output powers of the fuel batteries.
As described above, in the process of providing the electric energy for the user by the battery power supply system, the total output power of the fuel cell and the power cell should be the same as the electric power used by the user, and the power cell output power at the next moment can be determined based on the predicted value of the electric power used by the user and the optimal output power of the fuel cell at the next moment when the current moment has been predicted. This will not be described in any great detail in this application.
S14: and controlling the output power of the battery power supply system according to the optimal output power of the fuel battery corresponding to the next moment at the current moment and the output power of the power battery at the next moment.
It can be understood that, although the optimal output power of the fuel cell corresponding to each of a series of time points in the second preset time period after the current time can be directly predicted in the process of performing the optimization operation on the objective function, when the output power of the battery power supply system is actually controlled, only the optimal output power of the fuel cell corresponding to the next time at the current time (i.e., the optimal output power of the first fuel cell in the optimal output powers of the fuel cells) is taken for controlling and outputting. When the next time of the current time is reached, namely after a time interval, the predicted value of the electric power used by the user in a second preset time period is predicted again according to the new current time, on the basis, the optimal output power of the fuel cell corresponding to a series of time points is determined again, and the output electric energy of the battery power supply system is controlled according to the optimal output power of the first fuel cell.
In summary, in the process of powering a user by using a fuel cell and a power cell, an objective function representing operation costs of the fuel cell and the power cell is created, so that optimization iteration is performed by continuously adjusting output power of the fuel cell, and the corresponding output power of the fuel cell when the objective function is minimum is obtained; in the process of iteratively optimizing the operation result of the objective function, according to the predicted value of the predicted electric power of the user, the output power of the fuel cell corresponding to a series of time points which enable the operation result of the objective function to be minimum in a period of time after the current moment can be determined at the same time, so that on one hand, the hysteresis of the regulation of the output power of the whole power supply system of the battery can be avoided, and on the other hand, the stability of the power supply state of the power supply system formed by the fuel cell and the power cell is ensured on the basis of ensuring the low-cost operation of the fuel cell and the power cell.
Based on the above discussion, the creation process of the above objective function will be described in further detail below with specific embodiments.
In an alternative embodiment of the present application, the process of creating the objective function in advance includes:
s21: and determining a fuel cell degradation cost model taking the output power of the fuel cell as a variable according to the operation rule of the fuel cell.
In practical applications, the degradation cost of the fuel cell is different according to the operation state of the fuel cell, and the degradation cost of the fuel cell is a characteristic of the operation loss of the fuel cell to a certain extent.
Alternatively, the fuel cell degradation cost model may include:
C fcs,j ＝C low,j +C high,j +C chg,j ,j＝0,1,2…；
wherein C is fcs,j Fuel cell degradation cost for the j-th time point;
C low,j is the j thThe degradation costs caused by the low load at the time point,γ low for the voltage decay rate per hour at low load of the fuel cell output power lower than 20% of rated power, T low,j For the duration of low load at the jth time point, V fcs,eol Is the voltage of the fuel cell in EOL (End oflife) state; m is M fcs For fuel cell cost, M fcs ＝100β fcs ，β fcs Outputting a price per kilowatt of electricity for the fuel cell;
the EOL (End oflife) state of the fuel cell refers to a state in which the voltage of the fuel cell drops by 10% at the rated current.
C high,j For the degradation cost caused by the high load at the jth time point,γ high a voltage decay rate T per hour at a high load of not less than 80% of the rated power of the fuel cell high,j A high load duration for the j-th time point;
C chg,j for the degradation cost caused by the load change at the jth time point,γ chg the voltage attenuation rate of each kilowatt of the output power of the fuel cell in the transient load change process is set; p (P) fcs (m) is the ignition battery output at the mth moment; n is n fcs Is the number of fuel cells.
It is to be understood that j in the present embodiment represents each time point number from the current time point; when j=0, i.e. the current time, j=1, i.e. the next time of the current time, and so on, the maximum value of j is the time point serial number of the corresponding time point after the second preset time period passes after the current time. The time difference between two adjacent time points can be set based on actual application requirements, and can be 1 minute, 5 minutes, 10 minutes, and so on.
For a fuel cell, when the fuel cell output power is less than 20% of the rated power, the fuel cell is considered to be in a low load state; when the output power of the fuel cell is more than or equal to 80% of rated power, the fuel cell is in a high-load state; and the output power of the fuel cell is more than or equal to 20% of the rated power and less than 80% of the rated power, so that the fuel cell is in a transient load change state.
S22: and determining a battery charge state transfer equation of the power battery according to the operation rule of the power battery.
According to the operation rule of the power battery to output electric energy, the power battery outputs power P b Expressed as: p (P) b ＝U b, oc I b -R b I b 2 ；U b,oc For the open-circuit voltage of the power battery, I b R is the current of the power battery b Is the internal resistance of the power battery. Power battery current I of equivalent circuit b Is a function of power cell output power, power cell internal resistance and power cell open circuit voltage, and can be expressed as:
therefore, the battery charge state of the power battery is calculated by adopting an ampere-hour integration method, and a battery charge state transfer equation of the power battery can be determinedThe battery charge state transfer equation can be used as a battery charge state model.
Wherein Q is m Delta t is the time step of the discrete sampling interval, which is the battery capacity of the power battery; i b For the current of the power battery,U b,oc r is the open-circuit voltage of the power battery b Is the internal resistance of the power battery; p (P) b And outputting power to the power battery.
S23: determining an objective function as based on the fuel cell degradation cost model and the battery state of charge transfer equationWherein C is fcs,j Fuel cell degradation cost at the jth time point and is the amount of change associated with the fuel cell output power; d (D) soc,j Penalty term for power cell at the j-th time point, and +.>D p Is a constant; SOC (0) =soc 0 The method comprises the steps of carrying out a first treatment on the surface of the SOC (m) is the state of charge of the power battery corresponding to the mth time point; and P is fcs (k)+P b (k)+P 0 ＝P de (k)；P de (k) Predicted value of user power for kth time point, P fcs Fuel cell output power for the kth time point; p (P) b (k) Power is output for the power battery at the kth time point; p (P) 0 Output power of power battery supplying power to fuel cell when fuel cell is started, P after fuel cell is started 0 Is 0.
It can be understood that the SOC of the power battery refers to the State of Charge of the battery, and the english word is State of Charge, abbreviated as SOC, and refers to the available State of the remaining Charge in the battery.
Based on the above discussion, the power battery penalty term D in the present embodiment soc,j Based on the battery state of charge transfer equation, the SOC (m) can be expressed as the power battery output power, and based on the correlation between the power battery output power and the fuel battery output power, the power battery penalty term D soc,j And finally, the output power of the fuel cell can be converted into a function taking the output power of the fuel cell as a variable; thereby resulting in the final conversion of the objective function to a function that is a function of the fuel cell output power as a variable.
As described above, in order to ensure the normal operation of the battery power supply system during the optimization operation of the objective function, further constraint conditions need to be set, and the optimization operation of the objective function is performed on the basis of satisfying the constraint conditions.
In another alternative embodiment of the present application, the constraint may include:
SOC state constraints of the power battery: SOC (State of Charge) min ≤SOC(q)≤SOC max The method comprises the steps of carrying out a first treatment on the surface of the Wherein SOC is max And SOC (System on chip) min The maximum value and the minimum value of the charge state of the power battery are respectively;
output power constraint of power battery: p (P) b,min ≤P b (k)≤P b,max ；P b,min And P b,max Respectively the minimum output power and the maximum output power of the power battery;
output power constraints of the fuel cell; p (P) fcs,min ≤P fcs (k)≤P fcs,max ；P fcs,min And P fcs,max Respectively the minimum output power and the maximum output power of the fuel cell;
output power variation constraint of fuel cell: ΔP fcs,min ≤ΔP fcs (k)≤ΔP fcs,max ；ΔP fcs,min And DeltaP fcs,max The minimum output power variation and the maximum output power variation of the fuel cell, respectively.
The following describes an output power control device of a battery power supply system according to an embodiment of the present invention, and the output power control device of the battery power supply system described below and the output power control method of the battery power supply system described above may be referred to correspondingly.
Fig. 2 is a block diagram of an output power control device of a battery power supply system according to an embodiment of the present invention, and referring to fig. 2, the output power control device of the battery power supply system may include:
the power prediction module 100 is configured to collect user power in real time, and predict and obtain a predicted value of the user power in a second preset time period after the current time according to the user power in the first preset time period before the current time;
A first power operation module 200, configured to perform an optimization operation on a pre-created objective function according to the predicted value of the user power consumption and a pre-determined constraint condition, and determine an optimal output power of the fuel cell at each time point in a second preset time period after the current time when an operation result of the objective function is minimum; wherein the objective function is a function representing the operation loss of the fuel cell and the power cell by taking the output power of the fuel cell as a variable;
a second power operation module 300, configured to determine the power output of the power cell at the next time according to the fuel cell optimal output corresponding to the next time at the current time among the fuel cell optimal output;
and the output control module 400 is configured to control the output power of the battery power supply system according to the optimal output power of the fuel cell corresponding to the next time at the current time and the output power of the power cell at the next time.
In an alternative embodiment of the present application, further comprising a function creation module, comprising:
a first creating unit, configured to determine a fuel cell degradation cost model using the output power of the fuel cell as a variable according to an operation rule of the fuel cell;
The second creating unit is used for determining a battery charge state transfer equation of the power battery according to the operation rule of the power battery;
a third creation unit for determining the objective function as based on the fuel cell degradation cost model and the battery state of charge transfer equationWherein C is fcs,j Fuel cell degradation cost at the jth time point and is an amount of change associated with the fuel cell output power; d (D) soc,j A power battery penalty term for the j-th time point, and +.>D p Is a constant; SOC (0) =soc 0 The method comprises the steps of carrying out a first treatment on the surface of the SOC (m) is the corresponding point in time of the mthThe state of charge of the power battery; and P is fcs (k)+P b (k)+P 0 ＝P de (k)；P de (k) For the user power prediction value, P at the kth time point fcs (k) The fuel cell output power for the kth time point; p (P) b (k) The power battery output power for the kth time point; p (P) 0 The output power of the power battery supplying power to the fuel cell when the fuel cell is started, P after the fuel cell is started 0 Is 0.
In an alternative embodiment of the present application, the fuel cell degradation cost model created in advance by the first creation unit includes: c (C) fcs,j ＝C low,j +C high,j +C chg,j J=0, 1,2 …; wherein C is fcs,j Fuel cell degradation cost for the j-th time point; c (C) low,j For the degradation cost caused by the low load at the jth time point,γ low a voltage decay rate T per hour at a low load of 20% lower than a rated power of the fuel cell low,j For the duration of low load at the jth time point, V fcs,eol M is the voltage of the fuel cell in EOL state fcs For fuel cell cost, M fcs ＝100β fcs ，β fcs Outputting a price per kilowatt of electricity for the fuel cell; c (C) high,j Cost of degradation due to high load at the jth time point, +.>γ high A voltage decay rate per hour at a high load of not less than 80% of a rated power for the fuel cell output power; t (T) high,j A high load duration for the j-th time point; c (C) chg,j For the degradation cost caused by the load change at the jth time point,γ chg for the combustion ofThe output power of the material battery is at the voltage attenuation rate of each kilowatt in the transient load change process; p (P) fcs (m) fuel cell output power at the mth time point; n is n fcs Is the number of fuel cells.
In an alternative embodiment of the present application, the process of creating the battery state of charge model in advance by the second creation unit includes: calculating the battery charge state of the power battery by adopting an ampere-hour integration method, and determining a battery charge state transfer equation of the power battery Taking the battery charge state transfer equation as the battery charge state model; wherein Q is m For the battery capacity of the power battery, Δt is the time step of the discrete sampling interval; i b For power battery current, ">U b,oc R is the open-circuit voltage of the power battery b Is the internal resistance of the power battery; p (P) b And outputting power to the power battery.
In an alternative embodiment of the present application, the constraint conditions determined by the function creation module further include: SOC state constraints of the power battery: SOC (State of Charge) min ≤SOC(q)≤SOC max The method comprises the steps of carrying out a first treatment on the surface of the Wherein SOC is max And SOC (System on chip) min The maximum value and the minimum value of the charge state of the power battery are respectively; output power constraint of the power battery: p (P) b,min ≤P b (k)≤P b,max ；P b,min And P b,max Respectively the minimum output power and the maximum output power of the power battery; an output power constraint of the fuel cell; p (P) fcs,min ≤P fcs (k)≤P fcs,max ；P fcs,min And P fcs,max Respectively, the minimum output power and the maximum output power of the fuel cell; the output power variation constraint of the fuel cell: ΔP fcs,min ≤ΔP fcs (k)≤ΔP fcs,max ；ΔP fcs,min And DeltaP fcs,max Respectively isThe fuel cell has a minimum output power variation and a maximum output power variation.
In an optional embodiment of the present application, the power prediction module 100 is configured to input the user power within a first preset time period before the current time into an MLP neural network model obtained by performing neural network training in advance, and predict and obtain the predicted value of the user power within a second preset time period after the current time.
In an optional embodiment of the present application, the first power operation module 200 is configured to perform an optimization operation on a pre-created objective function by using an MPC optimization algorithm according to the predicted value of the electric power for the user and a predetermined constraint condition, and optimally determine an optimal output power of the fuel cell at each time point in a second preset time period after the current time when an operation result of the objective function is minimum.
The output power control device of the battery power supply system of the present embodiment is configured to implement the foregoing output power control method of the battery power supply system, so that the specific implementation of the output power control device of the battery power supply system can be seen from the foregoing example portion of the output power control method of the battery power supply system, which is not described herein again.
The application also provides an output power control device of a battery power supply system, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method for controlling output power of a battery powered system according to any of the above, when executing the computer program.
The memory may include Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The present application also provides a computer-readable storage medium,
the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the output power control method of a battery powered system as described in any of the above.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements is inherent to. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. In addition, the parts of the above technical solutions provided in the embodiments of the present application, which are consistent with the implementation principles of the corresponding technical solutions in the prior art, are not described in detail, so that redundant descriptions are avoided.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to facilitate an understanding of the method of the present invention and its core ideas. It should be noted that it will be apparent to those skilled in the art that various modifications and adaptations of the invention can be made without departing from the principles of the invention and these modifications and adaptations are intended to be within the scope of the invention as defined in the following claims.

Claims (10)

1. An output power control method of a battery power supply system, characterized in that the battery power supply system comprises a power battery and a fuel battery; the output power control method includes:
collecting user power in real time, and predicting and obtaining a predicted value of the user power in a second preset time period after the current moment according to the user power in the first preset time period before the current moment;
performing optimization operation on a pre-established objective function according to the predicted value of the electric power consumption of the user and a pre-determined constraint condition, and determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the operation result of the objective function is minimum; wherein the objective function is a function representing the operation loss of the fuel cell and the power cell by taking the output power of the fuel cell as a variable;
Determining the power battery output power at the next moment according to the fuel battery optimal output power corresponding to the next moment at the current moment in the fuel battery optimal output powers;
and controlling the output power of the battery power supply system according to the optimal output power of the fuel battery corresponding to the next moment at the current moment and the output power of the power battery at the next moment.
2. The output power control method of a battery power supply system according to claim 1, wherein the process of creating the objective function in advance includes:
determining a fuel cell degradation cost model taking the output power of the fuel cell as a variable according to the operation rule of the fuel cell;
determining a battery charge state transfer equation of the power battery according to the operation rule of the power battery;
determining the objective function as based on the fuel cell degradation cost model and the battery state of charge transfer equationWherein C is fcs,j Fuel cell degradation cost at the jth time point and is an amount of change associated with the fuel cell output power; d (D) soc,j A power battery penalty term for the j-th time point, and +.>D p Is a constant; SOC (0) =soc 0 The method comprises the steps of carrying out a first treatment on the surface of the SOC (m) is the state of charge of the power battery corresponding to the mth time point; and P is fcs (k)+P b (k)+P 0 ＝P de (k)；P de (k) For the user power prediction value, P at the kth time point fcs (k) The fuel cell output power for the kth time point; p (P) b (k) The power battery output power for the kth time point; p (P) 0 The output power of the power battery supplying power to the fuel cell when the fuel cell is started, P after the fuel cell is started 0 Is 0.
3. The output power control method of a battery power supply system according to claim 2, wherein the fuel cell degradation cost model created in advance includes:
C fcs,j ＝C low,j +C high,j +C chg,j ,j＝0,1,2…；
wherein C is fcs,j Fuel cell degradation cost for the j-th time point;
C low,j for the degradation cost caused by the low load at the jth time point,γ low a voltage decay rate T per hour at a low load of 20% lower than a rated power of the fuel cell low,j For the duration of low load at the jth time point, V fcs,eol M is the voltage of the fuel cell in EOL state fcs For fuel cell cost, M fcs ＝100β fcs ，β fcs Outputting a price per kilowatt of electricity for the fuel cell;
C high,j for the degradation cost caused by the high load at the jth time point,γ high a voltage decay rate per hour at a high load of not less than 80% of a rated power for the fuel cell output power; t (T) high,j A high load duration for the j-th time point;
C chg,j for the degradation cost caused by the load change at the jth time point,γ chg a voltage decay rate per kilowatt during which the output power of the fuel cell is in a transient load change; p (P) fcs (m) fuel cell output power at the mth time point; n is n fcs Is the number of fuel cells.
4. The method of claim 2, wherein creating the battery state of charge model comprises:
calculating the battery charge state of the power battery by adopting an ampere-hour integration method, and determining a battery charge state transfer equation of the power batteryTaking the battery charge state transfer equation as the battery charge state model;
wherein Q is m For the battery capacity of the power battery, Δt is the time step of the discrete sampling interval; i b For the current of the power battery,U b,oc r is the open-circuit voltage of the power battery b Is the internal resistance of the power battery; p (P) b And outputting power to the power battery.
5. The output power control method of a battery power supply system according to claim 2, wherein the constraint condition includes:
SOC state constraints of the power battery: SOC (State of Charge) min ≤SOC(q)≤SOC max The method comprises the steps of carrying out a first treatment on the surface of the Wherein SOC is max And SOC (System on chip) min The maximum value and the minimum value of the charge state of the power battery are respectively;
output power constraint of the power battery: p (P) b,min ≤P b (k)≤P b,max ；P b,min And P b,max Respectively the minimum output power and the maximum output power of the power battery;
an output power constraint of the fuel cell; p (P) fcs,min ≤P fcs (k)≤P fcs,max ；P fcs,min And P fcs,max Respectively, the minimum output power and the maximum output power of the fuel cell;
the output power variation constraint of the fuel cell: ΔP fcs,min ≤ΔP fcs (k)≤ΔP fcs,max ；ΔP fcs,min And DeltaP fcs,max The minimum output power variation and the maximum output power variation of the fuel cell, respectively.
6. The method of controlling output power of a battery power supply system according to claim 1, wherein predicting the predicted value of the user power consumption in a second preset time period after the current time based on the user power consumption in the first preset time period before the current time includes:
inputting the user power in a first preset time period before the current moment into an MLP neural network model obtained by training a neural network in advance, and predicting to obtain a predicted value of the user power in a second preset time period after the current moment.
7. The output power control method of a battery power supply system according to any one of claims 1 to 6, wherein performing an optimization operation on a pre-created objective function based on the predicted value of the user power and a predetermined constraint condition, determines an optimal output power of the fuel cell at each time point in a second preset time period after the current time when an operation result of the objective function is minimum, comprises:
And carrying out optimization operation on a pre-established objective function by adopting an MPC optimization algorithm according to the predicted value of the electric power of the user and a pre-determined constraint condition, and optimally determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the operation result of the objective function is minimum.
8. An output power control device of a battery power supply system, characterized in that the battery power supply system comprises a power battery and a fuel battery; the output power control device includes:
the power prediction module is used for acquiring the user power in real time, and predicting and obtaining a predicted value of the user power in a second preset time period after the current moment according to the user power in the first preset time period before the current moment;
the first power operation module is used for carrying out optimization operation on a pre-established objective function according to the predicted value of the electric power used by the user and a pre-determined constraint condition, and determining the optimal output power of the fuel cell at each time point in a second preset time period after the current moment when the operation result of the objective function is minimum; wherein the objective function is a function representing the operation loss of the fuel cell and the power cell by taking the output power of the fuel cell as a variable;
The second power operation module is used for determining the power battery output power at the next moment according to the fuel battery optimal output power corresponding to the next moment at the current moment in the fuel battery optimal output powers;
and the output control module is used for controlling the output power of the battery power supply system according to the optimal output power of the fuel battery corresponding to the next moment at the current moment and the output power of the power battery at the next moment.
9. An output power control apparatus of a battery-powered system, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method for controlling the output power of a battery powered system according to any of claims 1 to 7 when executing said computer program.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the output power control method of a battery powered system according to any of claims 1 to 7.
CN202311471229.9A 2023-11-07 2023-11-07 Battery power supply system output power control method, device, equipment and storage medium Pending CN117476983A (en)

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