CN116163816B - Organic Rankine cycle system control method, device, equipment and medium - Google Patents
Organic Rankine cycle system control method, device, equipment and medium Download PDFInfo
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Abstract
The application discloses a control method, a device, equipment and a medium of an organic Rankine cycle system, which relate to the field of energy process control, and the method comprises the following steps: determining a finite step response model of the organic Rankine cycle system by utilizing a real-time optimization layer of the organic Rankine cycle system, and constructing and solving a dynamic real-time optimization function based on a pre-acquired target load value so as to determine an expected reference track of the evaporation pressure of the organic Rankine cycle system; and the model prediction control layer for controlling the organic Rankine cycle system performs tracking control on the organic Rankine cycle system based on the finite step response model and an expected reference track of the evaporation pressure. The invention uses a layered control strategy to realize the control of the ORC system, and the upper RTO layer obtains the optimal target in steady state by calculating an optimization problem and gives the optimal target to the lower MPC layer for tracking control, so that the ORC system obtains higher overall economic performance.
Description
Technical Field
The invention relates to the field of energy process control, in particular to a method, a device, equipment and a medium for controlling an organic Rankine cycle system.
Background
Industrialization and city exacerbate the problems of shortage of energy sources, emission of greenhouse gases and the like in the global scope. Waste heat recovery can effectively alleviate energy and environmental problems by improving energy use efficiency, so that the interest in waste heat recovery in recent years is growing. As an important component of industrial process waste heat, the energy quality of the low-temperature waste heat is low, and the recovery difficulty is high. ORC (i.e. Organic Rankine Cycle, organic rankine cycle) systems are considered as an effective low-temperature waste heat recovery technology, and have been widely used in various fields, in which the system uses energy in the waste heat to push an expander to perform work, thereby realizing power generation, and the control of the evaporation pressure in the evaporator has an important effect on the working power of the expander, so that the smooth control of the working power of the expander is also very important.
The current control method for the ORC system comprises a model prediction control method, a reinforcement learning control method and the like, and has certain defects in the aspect of dynamic performance of the ORC system, so that a certain deviation exists between the actual control effect of the ORC system and the expected control effect, and further the conversion efficiency and the economy of the ORC system are affected.
From the above, how to avoid a certain deviation between the actual control effect of the ORC system and the desired control effect caused by the conventional control method during the control process of the ORC system, and the situation that the conversion efficiency of the ORC system is low is a problem to be solved in the art.
Disclosure of Invention
In view of the above, the present invention aims to provide a method, an apparatus, a device and a medium for controlling an organic rankine cycle system, which can control an ORC system by using a hierarchical control strategy, and improve the economic benefit of the system by improving the net output power in the operation process of the ORC system, and have high practical application value. The specific scheme is as follows:
in a first aspect, the present application discloses an organic rankine cycle system control method, including:
determining a finite step response model of the organic Rankine cycle system by utilizing a real-time optimization layer of the organic Rankine cycle system, and constructing and solving a dynamic real-time optimization function based on a pre-acquired target load value so as to determine an expected reference track of the evaporation pressure of the organic Rankine cycle system;
and controlling the model prediction control layer of the organic Rankine cycle system to carry out tracking control on the organic Rankine cycle system based on the finite step response model and the expected reference track of the evaporation pressure.
Optionally, after determining the finite step response model of the organic rankine cycle system by using the real-time optimization layer of the organic rankine cycle system and constructing and solving a dynamic real-time optimization function based on a target load value obtained in advance to determine an expected reference track of the evaporation pressure of the organic rankine cycle system, the method further includes:
the real-time optimization layer of the organic Rankine cycle system is controlled to transmit the finite step response model and the expected reference track of the evaporation pressure to a data management controller in a model prediction control layer of the organic Rankine cycle system;
correspondingly, the model predictive control layer for controlling the organic Rankine cycle system performs tracking control on the organic Rankine cycle system based on the finite step response model and the expected reference track of the evaporation pressure, and the method comprises the following steps:
and controlling a data management controller in a model predictive control layer of the organic Rankine cycle system to carry out tracking control on the organic Rankine cycle system based on the finite step response model and an expected reference track of the evaporation pressure.
Optionally, the determining the finite step response model of the organic rankine cycle system includes:
determining input variables, output variables and organic working medium types of the organic Rankine cycle system, and adjusting the variation amplitude of the input variables of the organic Rankine cycle system according to a pseudo-random binary sequence method or a step signal;
acquiring test data for identifying the organic Rankine cycle system model, and preprocessing the test data to determine preprocessed data;
and identifying the finite step response model of the organic Rankine cycle system by using a least square method or a prediction error method based on the preprocessed data.
Optionally, the preprocessing the test data to determine preprocessed data includes:
performing corresponding processing on the test data by using a preset coarse value eliminating method to determine processed data;
and correspondingly processing the processed data by using a preset filtering processing method to determine the preprocessed data.
Optionally, the tracking control of the organic rankine cycle system based on the finite step response model and the expected reference trajectory of the evaporation pressure includes:
determining and solving a first controller optimization function for calculating a target sequence of a target state transition matrix based on the finite step response model and an expected reference trajectory of the evaporating pressure;
acquiring target output data of the organic Rankine cycle system according to a preset data acquisition period, constructing a second controller optimization function, solving the second controller optimization function by utilizing the target sequence, and determining a target input variable based on the second controller optimization function;
and inputting the target input variable into the organic Rankine cycle system to perform tracking control on the organic Rankine cycle system.
Optionally, the collecting the target output data of the organic rankine cycle system according to a preset data collection period, constructing a second controller optimization function, solving the second controller optimization function by using the target sequence, and then determining a target input variable based on the second controller optimization function, including:
acquiring target output data of the organic Rankine cycle system according to a preset data acquisition period;
constructing a second controller optimization function, solving a target state transition matrix in the second controller optimization function by utilizing the target sequence, and solving predicted variables of input variables and predicted variables of output variables in the second controller optimization function based on the target state transition matrix and the predicted variables of the input variables and the predicted variables of the output variables in an open loop state in the second controller optimization function;
a target input variable is determined based on predicted variables of the input variables in the second controller optimization function.
Optionally, the collecting the target output data of the organic rankine cycle system according to a preset data collection period includes:
acquiring target output data of the organic Rankine cycle system according to a preset data acquisition period; the target output data comprise waste heat flow and evaporation pressure of the organic Rankine cycle system;
correspondingly, the constructing a second controller optimization function, solving a target state transition matrix in the second controller optimization function by using the target sequence, and solving predicted variables of an input variable and predicted variables of an output variable in the second controller optimization function based on the target state transition matrix and the predicted variables of the input variable and the predicted variables of the output variable in an open loop state in the second controller optimization function, including:
constructing a second controller optimization function, and solving a target state transition matrix in the second controller optimization function by utilizing the target sequence; the second controller optimization function comprises a predicted variable of an input variable and a predicted variable of an output variable in an open loop state, which are determined based on the waste heat flow and the evaporation pressure;
and solving the predicted variables of the input variables and the predicted variables of the output variables in the second controller optimization function based on the target state transition matrix and the predicted variables of the input variables and the predicted variables of the output variables in the open loop state.
In a second aspect, the present application discloses an organic rankine cycle system control device, comprising:
the real-time optimization layer application module is used for determining a finite step response model of the organic Rankine cycle system by using a real-time optimization layer of the organic Rankine cycle system, and constructing and solving a dynamic real-time optimization function based on a target load value obtained in advance so as to determine an expected reference track of the evaporation pressure of the organic Rankine cycle system;
and the model prediction control layer application module is used for performing tracking control on the organic Rankine cycle system based on the finite step response model and the expected reference track of the evaporation pressure by applying the model prediction control layer for controlling the organic Rankine cycle system.
In a third aspect, the present application discloses an electronic device comprising:
a memory for storing a computer program;
and the processor is used for executing the computer program to realize the organic Rankine cycle system control method.
In a fourth aspect, the present application discloses a computer storage medium for storing a computer program; wherein the computer program when executed by a processor implements the steps of the aforementioned disclosed organic rankine cycle system control method.
The method comprises the steps of determining a finite step response model of an organic Rankine cycle system by using a real-time optimization layer of the organic Rankine cycle system, constructing and solving a dynamic real-time optimization function based on a pre-obtained target load value to determine an expected reference track of evaporation pressure of the organic Rankine cycle system, and then controlling a model prediction control layer of the organic Rankine cycle system to carry out tracking control on the organic Rankine cycle system based on the finite step response model and the expected reference track of the evaporation pressure. In this way, the hierarchical control strategy is used to realize the control of the ORC system, the upper RTO layer obtains the optimal target in the steady state by calculating an optimization problem and gives the optimal target to the lower MPC layer for tracking control, and the MPC layer considers the dynamic performance of the ORC system in the running process, so that the ORC system obtains higher overall economic performance. The ORC system dynamic performance improvement strategy based on the dynamic RTO and the pseudo-feedforward DMC algorithm has the characteristics of feasibility, easiness in implementation and the like, and can improve the economic benefit of the system by improving the net output power in the operation process of the ORC system, thereby having high practical application value.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a control method of an organic Rankine cycle system provided by the application;
FIG. 2 is a flow chart of a specific method for controlling an organic Rankine cycle system provided in the present application;
FIG. 3 is a schematic diagram of a control result of steam pressure provided in the present application;
fig. 4 is a schematic structural diagram of an organic rankine cycle system control device provided in the present application;
fig. 5 is a block diagram of an electronic device provided in the present application.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.
In the prior art, the current control method for the ORC system comprises a model prediction control method, a reinforcement learning control method and the like, and certain defects exist in the aspect of the dynamic performance of the ORC system, so that a certain deviation exists between the actual control effect of the ORC system and the expected control effect, and the conversion efficiency and the economy of the ORC system are further affected. In the method, the control of the ORC system can be realized by using a layered control strategy, and the economic benefit of the system is improved by improving the net output power in the operation process of the ORC system, so that the method has high practical application value.
The embodiment of the invention discloses a control method of an organic Rankine cycle system, which is described with reference to FIG. 1 and comprises the following steps:
step S11: and determining a finite step response model of the organic Rankine cycle system by utilizing a real-time optimization layer of the organic Rankine cycle system, and constructing and solving a dynamic real-time optimization function based on a pre-acquired target load value so as to determine an expected reference track of the evaporation pressure of the organic Rankine cycle system.
In this embodiment, the organic rankine cycle system includes an upper RTO (i.e., real-Time Optimization, real-time optimization) layer and a lower MPC (i.e., model Predictive Control, model predictive control) layer. The step of determining the finite step response model of the organic Rankine cycle system, and constructing and solving a dynamic real-time optimization function based on a target load value obtained in advance to determine an expected reference track of the evaporation pressure of the organic Rankine cycle system is realized in an upper RTO layer of the organic Rankine cycle system. The optimal target in the steady state can be obtained by calculating a dynamic real-time optimization function in the upper RTO layer, and can be understood as the optimal target in the steady state can be obtained by calculating an optimization problem.
In this embodiment, the determining the finite step response model of the organic rankine cycle system may include: determining input variables, output variables and organic working medium types of the organic Rankine cycle system, and adjusting the variation amplitude of the input variables of the organic Rankine cycle system according to a pseudo-random binary sequence method or a step signal; acquiring test data for identifying the organic Rankine cycle system model, and preprocessing the test data to determine preprocessed data; and identifying the finite step response model of the organic Rankine cycle system by using a least square method or a prediction error method based on the preprocessed data.
In this embodiment, the preprocessing the test data to determine preprocessed data may include: performing corresponding processing on the test data by using a preset coarse value eliminating method to determine processed data; and correspondingly processing the processed data by using a preset filtering processing method to determine the preprocessed data.
In a specific embodiment, the input variable of the ORC system may be determined as the waste heat flow, the output variable of the ORC system may be determined as the evaporation pressure, and the type of organic working medium used by the ORC system may be determined as R245fa. And adjusting the amplitude of the input variable of the ORC system according to the pseudo-random binary sequence or the step signal to obtain test data for identifying the ORC system model. And preprocessing the test data by using methods such as coarse value elimination, filtering and the like. And identifying a finite step response model of the ORC system by using a least square method, a predictive error method and the like.
Step S12: and controlling the model prediction control layer of the organic Rankine cycle system to carry out tracking control on the organic Rankine cycle system based on the finite step response model and the expected reference track of the evaporation pressure.
In this embodiment, the step of tracking and controlling the organic rankine cycle system based on the finite step response model and the desired reference trajectory of the evaporation pressure is implemented in an MPC layer of a lower layer of the organic rankine cycle system. In other words, in this embodiment, the hierarchical control strategy is used to control the ORC system, and the upper RTO layer obtains an optimal target in a steady state by calculating an optimization problem and gives the optimal target to the lower MPC layer for tracking control, so that the MPC layer considers the dynamic performance of the ORC system in the operation process, and the ORC system obtains higher overall economic performance.
In this embodiment, after determining the finite step response model of the organic rankine cycle system by using the real-time optimization layer of the organic rankine cycle system and constructing and solving a dynamic real-time optimization function based on a target load value obtained in advance to determine an expected reference track of the evaporation pressure of the organic rankine cycle system, the method may further include: the real-time optimization layer of the organic Rankine cycle system is controlled to transmit the finite step response model and the expected reference track of the evaporation pressure to a data management controller in a model prediction control layer of the organic Rankine cycle system; accordingly, the controlling the model predictive control layer of the organic rankine cycle system to track and control the organic rankine cycle system based on the finite step response model and the expected reference trajectory of the evaporation pressure may include: and controlling a data management controller in a model predictive control layer of the organic Rankine cycle system to carry out tracking control on the organic Rankine cycle system based on the finite step response model and an expected reference track of the evaporation pressure. It can be understood that in this embodiment, when the upper RTO layer obtains an optimal target in a steady state by calculating an optimization problem and gives the optimal target to the lower MPC layer for tracking control, the optimal target in the steady state may be given to a data management controller in the lower MPC layer, so that the data management controller performs tracking control on the organic rankine cycle system.
In this embodiment, the real-time optimization layer of the organic rankine cycle system may be used to determine the finite step response model of the organic rankine cycle system, and a dynamic real-time optimization function may be constructed and solved based on a target load value obtained in advance, so as to determine an expected reference track of the evaporation pressure of the organic rankine cycle system, and then the model prediction control layer of the organic rankine cycle system may be controlled to perform tracking control on the organic rankine cycle system based on the finite step response model and the expected reference track of the evaporation pressure. In this way, in this embodiment, the hierarchical control strategy is used to control the ORC system, and the upper RTO layer obtains an optimal target in a steady state by calculating an optimization problem and gives the optimal target to the lower MPC layer for tracking control, so that the MPC layer considers the dynamic performance of the ORC system in the operation process, and the ORC system obtains a higher overall economic performance. The ORC system dynamic performance improvement strategy based on the dynamic RTO and the pseudo-feedforward DMC algorithm has the characteristics of feasibility, easiness in implementation and the like, and can improve the economic benefit of the system by improving the net output power in the operation process of the ORC system, thereby having high practical application value.
Fig. 2 is a flowchart of a specific control method of an organic rankine cycle system according to an embodiment of the present application. Referring to fig. 2, the method includes:
step S21: and determining a finite step response model of the organic Rankine cycle system by utilizing a real-time optimization layer of the organic Rankine cycle system, and constructing and solving a dynamic real-time optimization function based on a pre-acquired target load value so as to determine an expected reference track of the evaporation pressure of the organic Rankine cycle system.
In a specific implementation manner of this embodiment, taking an ORC system-based waste heat recovery process as an example, a dynamic performance improvement strategy of an ORC system is described in detail. In the process of constructing and solving the dynamic real-time optimization function based on the pre-acquired target load value, the dynamic real-time optimization function may be:
wherein u represents an input vector including the temperature T of waste heat a And flow rate qM a . x represents a state vector including the supercooling zone length L e1 Tube wall temperature T in supercooling zone ew1 Tube wall temperature T in two-phase zone ew2 Tube wall temperature T in the superheat zone ew3 . y represents the output vector, including the two-phase region length L e2 Evaporation pressure p of working medium in evaporator e Enthalpy value h of evaporator outlet working medium eo 。t 0 And t f Indicating the integration start time and end time. P represents the net output power of the ORC system, P set For a pre-obtained target load value, the desired ORC system output power is represented. The net output power of the ORC system is related to the output vector by p=w (P e ,h eo U). The differential equation expression f, algebraic equation expressions g, h and the net output power function W may be studied using the existing method "Wu Xialai. Optimization and control of organic Rankine cycle process [ D ]]University of Zhejiang, 2019.DOI:10.27461/d.cnki. Gzjdx.2019.002461 ".
In this embodiment, the dynamic real-time optimization function can be understood as a dynamic optimization problem, and the expected output power P can be preset when determining the parameters of the optimization problem set 3.5KW. In particular implementations, a solution can be applied using a pseudo-sequential algorithm to obtain the evaporation pressure p e Is provided for the reference trajectory.
Step S22: and controlling a model prediction control layer of the organic Rankine cycle system to determine and solve a first controller optimization function of a target sequence for calculating a target state transition matrix based on the finite step response model and an expected reference track of the evaporation pressure, collecting target output data of the organic Rankine cycle system according to a preset data acquisition period, constructing a second controller optimization function, solving the second controller optimization function by utilizing the target sequence, determining a target input variable based on the second controller optimization function, and inputting the target input variable into the organic Rankine cycle system to carry out tracking control on the organic Rankine cycle system.
It may be understood that in this embodiment, a first controller optimization function for calculating a target sequence of the target state transition matrix based on the finite step response model and the desired reference trajectory of the evaporation pressure may be determined and solved by using a DMC (i.e. Data Management Controller, data management controller) controller in the MPC layer, and target output data of the organic rankine cycle system is collected according to a preset data collection period, a second controller optimization function is constructed, then the second controller optimization function is solved by using the target sequence, a target input variable is determined based on the second controller optimization function, and the target input variable is input into the organic rankine cycle system, so as to perform tracking control on the organic rankine cycle system.
In this embodiment, the first controller optimization function may be:
wherein H is p And H m A finite step response model sequence representing the evaporating pressure obtained in step S21 and an expected reference trajectory sequence of evaporating pressure, H l Representing the pseudo-feedforward sequence to be solved. N represents the length of the sequence and α is an adjustable parameter.
And solving the first controller optimization function to obtain a target sequence in the DMC controller, wherein the target sequence can be used for calculating a target state transition matrix. In this embodiment, the DMC controller may be understood as a pseudo-feed-forward DMC controller, and the target sequence may be understood as a pseudo-feed-forward sequence.
In this embodiment, the acquiring the target output data of the organic rankine cycle system according to the preset data acquisition period, and constructing a second controller optimization function, solving the second controller optimization function by using the target sequence, and then determining the target input variable based on the second controller optimization function may include: acquiring target output data of the organic Rankine cycle system according to a preset data acquisition period; constructing a second controller optimization function, solving a target state transition matrix in the second controller optimization function by utilizing the target sequence, and solving predicted variables of input variables and predicted variables of output variables in the second controller optimization function based on the target state transition matrix and the predicted variables of the input variables and the predicted variables of the output variables in an open loop state in the second controller optimization function; a target input variable is determined based on predicted variables of the input variables in the second controller optimization function. The second controller optimization function is based on the predicted variable of the input variable and the predicted variable of the output variable, the predicted variable of the input variable and the predicted variable of the output variable in the open loop state, the target state transition matrix and the vector expression corresponding to the virtual input variable.
In this embodiment, the collecting the target output data of the organic rankine cycle system according to the preset data collection period may include: acquiring target output data of the organic Rankine cycle system according to a preset data acquisition period; the target output data comprise waste heat flow and evaporation pressure of the organic Rankine cycle system; correspondingly, the constructing a second controller optimization function, solving a target state transition matrix in the second controller optimization function by using the target sequence, and solving predicted variables of an input variable and predicted variables of an output variable in the second controller optimization function based on the target state transition matrix and the predicted variables of the input variable and the predicted variables of the output variable in an open loop state in the second controller optimization function, including: constructing a second controller optimization function, and solving a target state transition matrix in the second controller optimization function by utilizing the target sequence; the second controller optimization function comprises a predicted variable of an input variable and a predicted variable of an output variable in an open loop state, which are determined based on the waste heat flow and the evaporation pressure; and solving the predicted variables of the input variables and the predicted variables of the output variables in the second controller optimization function based on the target state transition matrix and the predicted variables of the input variables and the predicted variables of the output variables in the open loop state.
In this embodiment, the MPC layer acquires the residual heat flow qM of the current ORC system at regular intervals a And evaporation pressure p e And solving a second controller optimization function. In a specific embodiment, the second controller optimization function may be:
wherein the method comprises the steps of
Indicating that the predicted output variable at time k is at k+N p And the result of moment, deltav, represents a virtual input variable to be optimized, u represents an input variable, and the predicted results of the input variable and the output variable are required to meet upper and lower limit constraints. Q and R are each an adjustable weight, < ->
Representing the optimal target value of the output variable, N p Representing the prediction step size, N c Representing the control step size. In the last two lines of the above-mentioned optimization problem, U represents the predicted vector of the input variable, Y represents the predicted vector of the output variable, the superscript o represents the corresponding vector in the open loop state, Δv represents the vector of the virtual input variable, D L And D M Representing a state transition matrix, the variables are respectively expressed as:
in this embodiment, after solving the above-mentioned second controller optimization function, the obtained u may be obtained k+1|k Applied to the ORC system. In practice, the control result of the final vapor pressure is shown in fig. 3, in which the abscissa represents time t in seconds(s); the ordinate is steam pressure, the unit is kilopascal (kPa), the expected closed-loop performance is the expected reference track of the steam pressure obtained in the step S21, the closed-loop performance of the method is the control effect obtained after the control in the step S22, and on the premise that the comparison object is DMC, compared with the traditional control method, the method provided in the embodiment can enable the output of the ORC system to more conform to the set track, so that the method conforms to the economical model better, and reduces the energy waste.
In this embodiment, taking the waste heat recovery process based on the ORC system as an example, a dynamic performance improvement strategy of the ORC system is described in detail, and the double-layer control implementation step provided in this embodiment makes the lower-layer control layer more accurate when tracking the reference track given by the upper-layer real-time optimization layer. The output of the ORC system can be more in accordance with the set track, and the energy waste is reduced.
Referring to fig. 4, the embodiment of the application discloses an organic rankine cycle system control device, which specifically may include:
the real-time optimization layer application module 11 is used for determining a finite step response model of the organic Rankine cycle system by using a real-time optimization layer of the organic Rankine cycle system, and constructing and solving a dynamic real-time optimization function based on a pre-acquired target load value so as to determine an expected reference track of the evaporation pressure of the organic Rankine cycle system;
the model predictive control layer application module 12 applies a model predictive control layer for controlling the organic rankine cycle system to track and control the organic rankine cycle system based on the finite step response model and the expected reference trajectory of the evaporation pressure.
The method comprises the steps of determining a finite step response model of an organic Rankine cycle system by utilizing a real-time optimization layer of the organic Rankine cycle system, constructing and solving a dynamic real-time optimization function based on a pre-obtained target load value to determine an expected reference track of evaporation pressure of the organic Rankine cycle system, and then controlling a model prediction control layer of the organic Rankine cycle system to carry out tracking control on the organic Rankine cycle system based on the finite step response model and the expected reference track of the evaporation pressure. In this way, the hierarchical control strategy is used to realize the control of the ORC system, the upper RTO layer obtains the optimal target in the steady state by calculating an optimization problem and gives the optimal target to the lower MPC layer for tracking control, and the MPC layer considers the dynamic performance of the ORC system in the running process, so that the ORC system obtains higher overall economic performance. The ORC system dynamic performance improvement strategy based on the dynamic RTO and the pseudo-feedforward DMC algorithm has the characteristics of feasibility, easiness in implementation and the like, and can improve the economic benefit of the system by improving the net output power in the operation process of the ORC system, thereby having high practical application value.
Further, the embodiment of the present application further discloses an electronic device, and fig. 5 is a block diagram of the electronic device 20 according to an exemplary embodiment, where the content of the figure is not to be considered as any limitation on the scope of use of the present application.
Fig. 5 is a schematic structural diagram of an electronic device 20 according to an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a display screen 24, an input-output interface 25, a communication interface 26, and a communication bus 27. The memory 22 is configured to store a computer program, where the computer program is loaded and executed by the processor 21 to implement relevant steps in the organic rankine cycle system control method disclosed in any of the foregoing embodiments. In addition, the electronic device 20 in the present embodiment may be specifically an electronic computer.
In this embodiment, the power supply 23 is configured to provide an operating voltage for each hardware device on the electronic device 20; the communication interface 26 can create a data transmission channel between the electronic device 20 and an external device, and the communication protocol to be followed is any communication protocol applicable to the technical solution of the present application, which is not specifically limited herein; the input/output interface 25 is used for acquiring external input data or outputting external output data, and the specific interface type thereof may be selected according to the specific application requirement, which is not limited herein.
The memory 22 may be a carrier for storing resources, such as a read-only memory, a random access memory, a magnetic disk, or an optical disk, and the resources stored thereon may include an operating system 221, a computer program 222, virtual machine data 223, and the virtual machine data 223 may include various data. The storage means may be a temporary storage or a permanent storage.
The operating system 221 is used for managing and controlling various hardware devices on the electronic device 20 and computer programs 222, which may be Windows Server, netware, unix, linux, etc. The computer program 222 may further include a computer program that can be used to perform other specific tasks in addition to the computer program that can be used to perform the orc system control method performed by the electronic device 20 as disclosed in any of the previous embodiments.
Further, the present application also discloses a computer readable storage medium, where the computer readable storage medium includes random access Memory (Random Access Memory, RAM), memory, read-Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, magnetic disk, or any other form of storage medium known in the art. Wherein the computer program, when executed by a processor, implements the aforementioned disclosed method of controlling an organic rankine cycle system. For specific steps of the method, reference may be made to the corresponding contents disclosed in the foregoing embodiments, and no further description is given here.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, so that the same or similar parts between the embodiments are referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section. Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in 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.
Finally, it is further 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 does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. 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.
The above describes the control method, device, equipment and storage medium of the organic rankine cycle system provided by the invention in detail, and specific examples are applied to the description of the principle and implementation mode of the invention, and the description of the above examples is only used for helping to understand the method and core idea of the invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (9)
1. An organic rankine cycle system control method, characterized by comprising:
determining a finite step response model of the organic Rankine cycle system by utilizing a real-time optimization layer of the organic Rankine cycle system, and constructing and solving a dynamic real-time optimization function based on a pre-acquired target load value so as to determine an expected reference track of the evaporation pressure of the organic Rankine cycle system;
the model prediction control layer of the organic Rankine cycle system is controlled to carry out tracking control on the organic Rankine cycle system based on the finite step response model and an expected reference track of the evaporation pressure;
the tracking control of the organic Rankine cycle system based on the finite step response model and the desired reference trajectory of the evaporating pressure comprises:
determining and solving a first controller optimization function for calculating a target sequence of a target state transition matrix based on the finite step response model and an expected reference trajectory of the evaporating pressure;
acquiring target output data of the organic Rankine cycle system according to a preset data acquisition period, constructing a second controller optimization function, solving the second controller optimization function by utilizing the target sequence, and determining a target input variable based on the second controller optimization function;
and inputting the target input variable into the organic Rankine cycle system to perform tracking control on the organic Rankine cycle system.
2. The method according to claim 1, wherein after determining the finite step response model of the organic rankine cycle system by using the real-time optimization layer of the organic rankine cycle system and constructing and solving a dynamic real-time optimization function based on a target load value acquired in advance to determine a desired reference trajectory of the evaporation pressure of the organic rankine cycle system, further comprising:
the real-time optimization layer of the organic Rankine cycle system is controlled to transmit the finite step response model and the expected reference track of the evaporation pressure to a data management controller in a model prediction control layer of the organic Rankine cycle system;
correspondingly, the model predictive control layer for controlling the organic Rankine cycle system performs tracking control on the organic Rankine cycle system based on the finite step response model and the expected reference track of the evaporation pressure, and the method comprises the following steps:
and controlling a data management controller in a model predictive control layer of the organic Rankine cycle system to carry out tracking control on the organic Rankine cycle system based on the finite step response model and an expected reference track of the evaporation pressure.
3. The orc system control method of claim 1, wherein the determining the finite step response model of the orc system comprises:
determining input variables, output variables and organic working medium types of the organic Rankine cycle system, and adjusting the variation amplitude of the input variables of the organic Rankine cycle system according to a pseudo-random binary sequence method or a step signal;
acquiring test data for identifying the organic Rankine cycle system model, and preprocessing the test data to determine preprocessed data;
and identifying the finite step response model of the organic Rankine cycle system by using a least square method or a prediction error method based on the preprocessed data.
4. The organic rankine cycle system control method according to claim 3, wherein the preprocessing the test data to determine preprocessed data includes:
performing corresponding processing on the test data by using a preset coarse value eliminating method to determine processed data;
and correspondingly processing the processed data by using a preset filtering processing method to determine the preprocessed data.
5. The method according to claim 1, wherein the acquiring target output data of the organic rankine cycle system according to a preset data acquisition period, and constructing a second controller optimization function, solving the second controller optimization function using the target sequence, and then determining a target input variable based on the second controller optimization function, includes:
acquiring target output data of the organic Rankine cycle system according to a preset data acquisition period;
constructing a second controller optimization function, solving a target state transition matrix in the second controller optimization function by utilizing the target sequence, and solving predicted variables of input variables and predicted variables of output variables in the second controller optimization function based on the target state transition matrix and the predicted variables of the input variables and the predicted variables of the output variables in an open loop state in the second controller optimization function;
a target input variable is determined based on predicted variables of the input variables in the second controller optimization function.
6. The method according to claim 5, wherein the step of collecting target output data of the organic rankine cycle system according to a preset data collection period includes:
acquiring target output data of the organic Rankine cycle system according to a preset data acquisition period; the target output data comprise waste heat flow and evaporation pressure of the organic Rankine cycle system;
correspondingly, the constructing a second controller optimization function, solving a target state transition matrix in the second controller optimization function by using the target sequence, and solving predicted variables of an input variable and predicted variables of an output variable in the second controller optimization function based on the target state transition matrix and the predicted variables of the input variable and the predicted variables of the output variable in an open loop state in the second controller optimization function, including:
constructing a second controller optimization function, and solving a target state transition matrix in the second controller optimization function by utilizing the target sequence; the second controller optimization function comprises a predicted variable of an input variable and a predicted variable of an output variable in an open loop state, which are determined based on the waste heat flow and the evaporation pressure;
and solving the predicted variables of the input variables and the predicted variables of the output variables in the second controller optimization function based on the target state transition matrix and the predicted variables of the input variables and the predicted variables of the output variables in the open loop state.
7. An organic rankine cycle system control device, comprising:
the real-time optimization layer application module is used for determining a finite step response model of the organic Rankine cycle system by using a real-time optimization layer of the organic Rankine cycle system, and constructing and solving a dynamic real-time optimization function based on a target load value obtained in advance so as to determine an expected reference track of the evaporation pressure of the organic Rankine cycle system;
the model prediction control layer application module is used for controlling the model prediction control layer of the organic Rankine cycle system to track and control the organic Rankine cycle system based on the finite step response model and the expected reference track of the evaporation pressure;
the model predictive control layer application module is specifically applied to determining and solving a first controller optimization function for calculating a target sequence of a target state transition matrix based on the finite step response model and an expected reference track of the evaporation pressure; acquiring target output data of the organic Rankine cycle system according to a preset data acquisition period, constructing a second controller optimization function, solving the second controller optimization function by utilizing the target sequence, and determining a target input variable based on the second controller optimization function; and inputting the target input variable into the organic Rankine cycle system to perform tracking control on the organic Rankine cycle system.
8. An electronic device comprising a processor and a memory; wherein the processor, when executing the computer program stored in the memory, implements the organic rankine cycle system control method according to any one of claims 1 to 6.
9. A computer-readable storage medium storing a computer program; wherein the computer program, when executed by a processor, implements the organic rankine cycle system control method according to any one of claims 1 to 6.
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