Cogeneration unit operation control method and device, electronic equipment and storage medium

Abstract

The application provides a combined heat and power unit operation control method and device, electronic equipment and storage medium. The method comprises the following steps: acquiring an actual output value of the combined heat and power unit in a current control mode; calculating output tracking errors of each output of the combined heat and power unit according to an output reference value and the actual output value of the combined heat and power unit in the current control mode; calculating a control gain matrix of the combined heat and power unit according to the output tracking errors in the current control mode; and inputting the control gain matrix to the combined heat and power unit to determine an actual output target value of the combined heat and power unit after adjustment. The application can flexibly adjust the combined heat and power unit and timely meet the control demand.

Description

Technical Field

[0001] This invention relates to the field of power automation technology, and in particular to a method, device, electronic equipment and storage medium for the operation control of a combined heat and power (CHP) unit. Background Technology

[0002] With the accelerating pace of new power system construction and the large-scale grid connection of new energy sources, there will also be a large number of combined heat and power (CHP) units. In northern China, due to the demand for winter heating, CHP units are also widely used. During the heating season, CHP units need to simultaneously handle power supply peak shaving and frequency regulation tasks as well as heating tasks. Therefore, CHP units need to have a fast load response rate to flexibly meet the needs of heating and power supply.

[0003] In recent years, existing technologies have typically used proportional-integral-derivative (PID) controllers to coordinate the control of cogeneration units. However, under different control modes of cogeneration units, PID controllers cannot flexibly adjust the cogeneration units and cannot meet load demands in a timely manner, thus limiting the applicability of PID controllers.

[0004] Therefore, there is an urgent need for a control method that can flexibly adjust cogeneration units and meet different control requirements in a timely manner. Summary of the Invention

[0005] This invention provides a method, device, electronic equipment, and storage medium for operating control of a combined heat and power (CHP) unit, in order to solve the problem in the prior art that the CHP unit cannot be flexibly adjusted under different control modes and cannot meet control requirements in a timely manner.

[0006] In a first aspect, embodiments of the present invention provide a method for controlling the operation of a combined heat and power (CHP) unit. The CHP unit employs multiple control modes, and an output reference value is set for each control mode. The method includes:

[0007] Obtain the actual output value of the cogeneration unit under the current control mode;

[0008] Based on the output reference value and actual output value of the cogeneration unit under the current control mode, calculate the output tracking error of each output of the cogeneration unit;

[0009] Calculate the control gain matrix of the cogeneration unit based on the output tracking error under the current control mode;

[0010] The control gain matrix is ​​input into the cogeneration unit to determine the actual output target value of the cogeneration unit after regulation.

[0011] In one possible implementation, based on the output reference value and actual output value of the cogeneration unit under the current control mode, the output tracking error of each output of the cogeneration unit is calculated, including:

[0012] according to Calculate the output tracking error for each output item;

[0013] Among them, X e (t) represents the output tracking error of the cogeneration unit within time t, Y d Y(τ) is the output reference value of the cogeneration unit under the current control mode at time τ, Y(τ) is the actual output value of the cogeneration unit at time τ, t is the operation control time of the cogeneration unit, and τ is any time within time t.

[0014] In one possible implementation, the control gain matrix of the cogeneration unit is calculated based on the output tracking error under the current control mode, including:

[0015] Under the current control mode, calculate the extended state-space model of the cogeneration unit based on the output tracking error;

[0016] Based on the extended state-space model, the cost function of LQR control is determined;

[0017] Based on the cost function, determine the state weight matrix and input weight matrix of LQR control;

[0018] Calculate the control gain matrix of the cogeneration unit based on the state weight matrix and the input weight matrix.

[0019] In one possible implementation, the state weight matrix and input weight matrix of the LQR control are determined based on the cost function, including:

[0020] Based on the cost function, the particle swarm optimization algorithm is used to determine the state weight matrix and input weight matrix of each output.

[0021] In one possible implementation, the control gain matrix of the cogeneration unit is calculated based on the state weight matrix and the input weight matrix, including:

[0022] Based on the state weight matrix and the input weight matrix, calculate the positive definite matrix solution of the Riccati equation corresponding to the minimum cost function;

[0023] Based on the positive definite matrix solution, calculate the control gain matrix of the cogeneration unit. The control gain matrix includes the state feedback matrix and the error gain matrix.

[0024] In one possible implementation, before inputting the control gain matrix into the cogeneration unit and determining the actual target output value of the cogeneration unit after regulation, the following is also included:

[0025] Obtain the output steam flow rate for heating from the combined heat and power unit;

[0026] Calculate the heating status signal based on the steam extraction flow rate for heating;

[0027] The fuel adjustment signal is determined based on the heating status signal and the preset heating quality signal;

[0028] The control gain matrix is ​​input into the cogeneration unit to determine the actual target output value of the cogeneration unit after regulation, including:

[0029] The fuel regulation signal and control gain matrix are input into the cogeneration unit to determine the actual output target value of the cogeneration unit after regulation.

[0030] In one possible implementation, the heating status signal is calculated based on the heating steam extraction flow rate, including:

[0031] according to Calculate the heating status signal;

[0032] in, Indicates the heating status signal, m H t1 represents the output steam flow rate for heating from the combined heat and power unit, t2 represents the start time for acquiring the steam flow rate for heating, and t2 represents the end time for acquiring the steam flow rate for heating.

[0033] Based on the heating status signal and the preset heating quality signal, determine the fuel adjustment signal, including:

[0034] according to Determine the fuel regulation signal;

[0035] in, P represents the fuel regulation signal. d This represents the output reference value of the combined heat and power (CHP) unit load, where P represents the ratio of the CHP unit output to the heating extraction steam flow rate. This represents the tracking error of the steam extraction flow rate for heating, expressed in meters (m). Hd This indicates the preset heating quality signal. This indicates the heating status signal.

[0036] Secondly, embodiments of the present invention provide a sample data set device for a combined heat and power (CHP) unit. The CHP unit employs multiple control modes, and an output reference value for the CHP unit is set under each control mode. The device includes:

[0037] The acquisition module obtains the actual output value of the cogeneration unit under the current control mode;

[0038] The first calculation module calculates the output tracking error of each output of the cogeneration unit based on the output reference value and actual output value of the cogeneration unit under the current control mode.

[0039] The second calculation module calculates the control gain matrix of the cogeneration unit based on the output tracking error under the current control mode.

[0040] The module determines the actual output target value of the cogeneration unit after adjustment by inputting the control gain matrix into the cogeneration unit.

[0041] Thirdly, embodiments of the present invention provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect or any possible implementation of the first aspect.

[0042] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method as described in the first aspect or any possible implementation of the first aspect.

[0043] This invention provides a method for controlling the operation of a combined heat and power (CHP) unit. By acquiring the actual output value of the CHP unit, the current actual output status can be obtained. Then, based on the output reference value and the actual output value, the output tracking error of each output of the CHP unit is calculated. This tracking output error is the difference between the current output status and the preset status of the CHP unit, and it is also the data that the output of the CHP unit needs to be adjusted. Based on this, a control gain matrix is ​​calculated. The control gain matrix includes a state feedback matrix and an error gain matrix. By controlling the CHP unit through the obtained control gain matrix, the weights of the input variables and state variables of the CHP unit can be comprehensively and flexibly controlled. This allows the actual output value of the CHP unit to be closer to the output reference value, enabling the output of the CHP unit to achieve the expected effect and meet the control requirements for power supply and heating under different control modes. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of the cogeneration unit operation control method provided in an embodiment of the present invention;

[0046] Figure 2 This is a flowchart illustrating the implementation of the cogeneration unit operation control method provided in this embodiment of the invention.

[0047] Figure 3 This is a graph showing the load variation trend of the unit under different control methods provided in the embodiments of the present invention;

[0048] Figure 4 This is a graph showing the variation trend of main steam pressure under different control methods provided in the embodiments of the present invention;

[0049] Figure 5 This is a graph showing the variation trend of heating steam extraction pressure under different control methods provided in the embodiments of the present invention;

[0050] Figure 6 This is a graph showing the changing trend of the heat source quality of a cogeneration unit under the cogeneration unit operation control method provided in this embodiment of the invention.

[0051] Figure 7 This is a schematic diagram of the structure of the cogeneration unit operation control device provided in an embodiment of the present invention;

[0052] Figure 8 This is a schematic diagram of the structure of the quality control evaluation module provided in an embodiment of the present invention;

[0053] Figure 9 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0054] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0055] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0056] Figure 1This is a schematic diagram of the operation control of a combined heat and power (CHP) unit provided in an embodiment of the present invention. The CHP unit adopts multiple control modes, and each control mode sets an output reference value for the CHP unit. The output of the CHP unit includes the main steam pressure, the heating extraction steam pressure, and the unit load. The corresponding output reference values ​​include the main steam pressure output reference value, the heating extraction steam pressure output reference value, and the unit load output reference value. The CHP unit operation control method provided in this embodiment of the present invention controls the actual output values ​​of the main steam pressure, the heating extraction steam pressure, and the unit load by controlling the fuel quantity, the heating extraction steam regulating valve, and the high-pressure regulating valve, respectively.

[0057] Figure 2 The implementation flowchart of the cogeneration unit operation control method provided in the embodiments of the present invention is described in detail below:

[0058] Step S201: Obtain the actual output value of the cogeneration unit under the current control mode.

[0059] In this implementation, obtaining the actual output value of the cogeneration unit allows us to understand the current actual output situation, which facilitates subsequent coordinated control based on the actual output situation.

[0060] Step S202: Calculate the output tracking error of each output of the cogeneration unit based on the output reference value and actual output value of the cogeneration unit under the current control mode.

[0061] In this embodiment, by calculating the output tracking error of each output of the cogeneration unit, the difference between the current output of the cogeneration unit and the preset situation can be determined, so that the second output value can be adjusted in the future to make the output of the cogeneration unit reach the preset effect.

[0062] Step S203: Under the current control mode, calculate the control gain matrix of the cogeneration unit based on the output tracking error.

[0063] In this embodiment, the output tracking error of the cogeneration unit is the data that the output of the cogeneration unit needs to be adjusted. Based on this, the control gain matrix is ​​calculated so that the actual output value of the cogeneration unit can be closer to the output reference value.

[0064] Step S204: Input the control gain matrix into the cogeneration unit to determine the actual output target value of the cogeneration unit after adjustment.

[0065] In this embodiment, the control gain matrix includes a state feedback matrix and an error gain matrix. By controlling the cogeneration unit through the obtained control gain matrix, the weights of the input variables and state variables of the cogeneration unit can be controlled, enabling comprehensive and flexible control. This allows the output of the cogeneration unit to meet the control requirements for power supply and heating under different control modes.

[0066] This invention, through obtaining the actual output value of a combined heat and power (CHP) unit, can determine the current actual output status. Then, based on the output reference value and the actual output value, it calculates the output tracking error of each output of the CHP unit. This tracking error represents the difference between the current output status and the preset status of the CHP unit, and is also the data that needs to be adjusted in the output of the CHP unit. Based on this, a control gain matrix is ​​calculated, which includes a state feedback matrix and an error gain matrix. By controlling the CHP unit using the obtained control gain matrix, the weights of the input variables and state variables of the CHP unit can be comprehensively and flexibly controlled. This allows the actual output value of the CHP unit to be closer to the output reference value, enabling the output of the CHP unit to achieve the expected effect and meet the control requirements for power supply and heating under different control modes.

[0067] In one possible implementation, step S202 calculates the output tracking error of each output of the cogeneration unit based on the output reference value and actual output value of the cogeneration unit under the current control mode. This can be detailed as follows: Based on Calculate the output tracking error for each output; where X e (t) represents the output tracking error of the cogeneration unit within time t, Y d Y(τ) is the output reference value of the cogeneration unit under the current control mode at time τ, Y(τ) is the actual output value of the cogeneration unit at time τ, t is the operation control time of the cogeneration unit, and τ is any time within time t.

[0068] In this embodiment, the output tracking error of each output of the cogeneration unit is calculated by using the actual output value and the output reference value of the cogeneration unit within time t, thereby determining the difference between the current output of the cogeneration unit and the preset condition.

[0069] In one possible implementation, step S203, calculating the control gain matrix of the cogeneration unit based on the output tracking error under the current control mode, can be detailed as follows: Calculating the extended state-space model of the cogeneration unit based on the output tracking error under the current control mode; determining the cost function of LQR control based on the extended state-space model; determining the state weight matrix and input weight matrix of LQR control based on the cost function; and calculating the control gain matrix of the cogeneration unit based on the state weight matrix and input weight matrix.

[0070] In this embodiment, the original state-space model of the cogeneration unit is extended based on the output tracking error to obtain an extended state-space model, thereby accurately describing the existing cogeneration unit. Based on the extended state-space model, the cost function of LQR control is determined, where the cost function is determined based on the principle of minimizing the output tracking error and input consumption, thus enabling the subsequent calculation of a control gain matrix suitable for the cogeneration unit. The determination of the state weight matrix and input weight matrix directly affects the control gain matrix. Determining appropriate state weight matrices and input weight matrices yields an appropriate control gain matrix, enabling the control of the state variables and input variables of the cogeneration unit to achieve the control requirements for power supply and heating under different control modes.

[0071] The original state-space model of a combined heat and power (CHP) unit is extended, and the resulting extended state-space model can be expressed as follows:

[0072]

[0073]

[0074] For ease of representation, let X r (t)=[X(t),X e (t)] T The extended state-space model can then be expressed as:

[0075]

[0076] Y(t) = C r X r (t)

[0077] in, Let represent the first derivative of the input vector of the original state-space model of the cogeneration unit at time t. Let represent the first derivative of the output tracking error of the cogeneration unit at time t, A represent the first system parameter of the extended state-space model, B represent the control parameter of the state-space model, C represent the second system parameter of the extended state-space model, I represent a unit vector, X1(t) represent the input vector of the original state-space model of the cogeneration unit at time t, U1(t) represent the state feedback in LQR control at time t, and Y... d Y(t) represents the output reference value of the cogeneration unit at time t, and Y(t) represents the output vector of the cogeneration unit at time t. X represents the first derivative of the state vector of the extended state-space model of the cogeneration unit at time t. r(t) represents the state vector of the extended state-space model of the cogeneration unit at time t, A r B represents the system matrix of the extended state-space model. r B represents the first control matrix of the extended state-space model. d Let Y(t) represent the second control matrix of the extended state-space model, and let C(t) represent the output vector of the extended state-space model of the cogeneration unit at time t. r Let T represent the output matrix of the extended state-space model, and let T denote the transpose of the matrix.

[0078] To ensure that both output tracking error and input consumption are minimized, the cost function of LQR control is determined based on the output tracking error. This cost can specifically be:

[0079]

[0080] Where J represents the cost function value of LQR control, Q represents the state weight matrix of LQR control, and R represents the input weight matrix of LQR control; in addition, both the state weight matrix and the input weight matrix are adjustable positive definite matrices, and are generally diagonal matrices.

[0081] Furthermore, based on the cost function, the state weight matrix and input weight matrix of LQR control are determined, including: based on the cost function, the state weight matrix and input weight matrix of each output are determined using the particle swarm optimization algorithm.

[0082] In this embodiment, the particle swarm optimization algorithm is used to replace the traditional manual debugging method. With the goal of minimizing the membership function value, the particle swarm optimization algorithm is used to optimize the state weight matrix and input weight matrix. This can quickly and accurately find the appropriate state weight matrix and input weight matrix, avoiding over-reliance on the experience of the debugging personnel and the inability to obtain the optimal result.

[0083] In one possible implementation, the control gain matrix of the cogeneration unit is calculated based on the state weight matrix and the input weight matrix, including: calculating the positive definite matrix solution of the Riccati equation corresponding to the minimum cost function based on the state weight matrix and the input weight matrix; and calculating the control gain matrix of the cogeneration unit based on the positive definite matrix solution, wherein the control gain matrix includes the state feedback matrix and the error gain matrix.

[0084] Specifically, the state feedback in LQR control is U1(t) = -KX r If (t), then the cost function of the extended state-space model can be updated to... Correspondingly, the Riccati equation corresponding to the minimum cost function is A. r T P r +P rA r -P r B r R -1 B r T P r +Q=0,K=R -1 B r T P r Where K represents the control gain matrix of the cogeneration unit, and P r This is the positive definite matrix solution of the Riccati equation; therefore, by calculating the positive definite matrix solution of the above Riccati equation, the control gain matrix can be obtained.

[0085] Furthermore, the control gain matrix, including the state feedback matrix and the error gain matrix, can be expressed as K = [K c ,K i ], K c K represents the state feedback matrix. i This represents the error gain matrix.

[0086] After determining the state weight matrix and the input weight matrix, the Riccati equation described above has a positive definite matrix solution. Based on this positive definite matrix solution, the control gain matrix can then be calculated. The control gain matrix specifically includes a state feedback matrix and an error gain matrix. The state feedback matrix acts on the input variables of the cogeneration unit, i.e., the original input parameters, while the error gain matrix acts on the output error tracking of the state variables of the cogeneration unit. Through the state feedback matrix and the error gain matrix, comprehensive and flexible control of the weights of the input variables and the weights of the state variables of the cogeneration unit can be achieved.

[0087] In one possible implementation, before inputting the control gain matrix into the cogeneration unit in step S204 to determine the actual output target value of the cogeneration unit after adjustment, the method further includes: acquiring the heating extraction steam flow rate output by the cogeneration unit; calculating the heating status signal based on the heating extraction steam flow rate; and determining the fuel adjustment signal based on the heating status signal and the preset heating quality signal. Step S204, inputting the control gain matrix into the cogeneration unit to determine the actual output target value of the cogeneration unit after adjustment, can be detailed as follows: inputting the fuel adjustment signal and the control gain matrix into the cogeneration unit to determine the actual output target value of the cogeneration unit after adjustment.

[0088] In this embodiment, when the cogeneration unit is in power supply priority mode, a portion of the steam originally used as a heat source enters the intermediate-pressure cylinder to continue working in response to the unit's load command during the early stages of load change through active response control of the heat source. Later, when the boiler fuel quantity can follow the load change, the cogeneration unit needs to "return" the portion of the heat source steam "borrowed" during the early stages of load change to the heating network to avoid significant impact on heat users. Therefore, based on the heating extraction steam flow rate, the heating status signal is calculated to determine the current heating situation of the cogeneration unit. Then, based on the heating status signal and the preset heating quality signal, the fuel adjustment signal is determined. This allows for the determination of the deviation between the actual and target values ​​of the heating extraction steam flow rate of the cogeneration unit, enabling subsequent increases in the energy input to the cogeneration unit. Ultimately, this ensures that the actual output value of the cogeneration unit meets the control requirements, thereby achieving precise energy balance.

[0089] In one possible implementation, the heating status signal is calculated based on the heating steam extraction flow rate, including: based on Calculate the heating status signal; where, Indicates the heating status signal, m H This represents the output steam flow rate for heating from the combined heat and power (CHP) unit. t1 represents the start time for acquiring the steam flow rate, and t2 represents the end time for acquiring the steam flow rate.

[0090] Based on the heating status signal and the preset heating quality signal, determine the fuel adjustment signal, including: based on Determine the fuel regulation signal; whereby, P represents the fuel regulation signal. d The output reference value of the combined heat and power (CHP) unit load is represented by P, and the actual output value of the CHP unit load is represented by m. Hd This indicates the preset heating quality signal. This indicates the heating status signal.

[0091] The relationship between the actual output value of the unit load of a combined heat and power (CHP) unit and the extraction steam flow rate at each stage is as follows:

[0092]

[0093]

[0094] Among them, D F Indicates water supply flow rate, h m The value represents the enthalpy of the main steam, σ represents the reheat enthalpy rise, and h c represents the exhaust enthalpy of the steam turbine, and m represents the extraction steam mass flow matrix. Let m represent the auxiliary vector. FPT The steam extraction flow rate of the feedwater pump turbine is expressed in h. i h represents the enthalpy of the i-th stage extraction.H This indicates the enthalpy value of steam extracted for heating.

[0095] In one possible approach, the current operating condition information, actual output value, and control parameters of the cogeneration unit are obtained; in a preset historical case library, a historical case corresponding to the current operating condition information and a first control quality value for that historical case are determined; based on the actual output value of the cogeneration unit, a second control quality value for the cogeneration unit is calculated; the historical case or current control parameter corresponding to the larger control quality value between the first and second control quality values ​​is used as control reference information; based on the control reference information, the output reference values ​​of each output under the corresponding control mode are updated, and the historical case library is updated.

[0096] In this embodiment, by evaluating the current control status of the cogeneration unit, the current state of the cogeneration unit can be determined. Then, by comparing the first control quality value and the second control quality value, it can be determined whether the current state of the cogeneration unit is better than the historical best state under the same operating conditions. If the historical best state in the historical case database is better, it indicates that the control parameters for the cogeneration unit are not optimal at this time and there is room for adjustment. The relevant information corresponding to the first control quality value can be used as a reference to adjust the control parameters of the current cogeneration unit. If the current state of the cogeneration unit is better, it indicates that the control parameters for the cogeneration unit are more suitable at this time. Therefore, the control parameters are updated to the historical database to facilitate the evaluation of the control status of subsequent cogeneration units and the adjustment of control parameters.

[0097] In a specific embodiment, a 300MW cogeneration unit is selected to verify the cogeneration unit operation control method provided in this application. The linear weighted sum of the output tracking error of the cogeneration unit is used as the membership function, which can be specifically expressed as:

[0098]

[0099] Among them, X e,1 (τ) represents the output tracking error of the main steam pressure of the cogeneration unit at time τ, X e,2 (τ) represents the output tracking error of the heating extraction steam pressure of the cogeneration unit at time τ, X e,3 (τ) represents the output tracking error of the cogeneration unit load at time τ, δ1 represents the weight corresponding to the output tracking error of the main steam pressure, δ2 represents the weight corresponding to the output tracking error of the heating extraction steam pressure, and δ3 represents the weight corresponding to the output tracking error of the unit load.

[0100] The combined heat and power (CHP) unit operates in a power supply priority mode, with heat source regulation serving as the primary means of load tracking. Based on this, the weights of main steam pressure, heating extraction steam pressure, and unit load are set to 0.3, 0.1, and 0.6, respectively, when setting the membership function in the particle swarm optimization (PSO) algorithm. In the PSO optimization, the particle swarm size is 100, and the maximum number of iterations is 30. Through optimization, the state weight matrix and control weight matrix are respectively: Q = diag(1, 10...). 5 ,1,10 5 10 5 ,6050,10 5 R = diag(1,1,1)

[0101] State feedback matrix K c Sum and difference gain matrix K i They are respectively:

[0102]

[0103]

[0104] PI controllers are used for all components in the precise energy balance process; the parameters of the energy balance controller are P=1 and I=0.2; the parameters of the heat source quality recovery controller are P=0.5 and I=1.

[0105] The traditional boiler-following-machine CCS strategy was selected for comparison. In this strategy, the turbine PID controls the load through the high-pressure regulating valve with parameters P=0.1 and I=0.02. The boiler PID controls the main steam pressure by adjusting the fuel quantity with parameters P=30, I=0.1 and D=20000. The heating network PID controls the heating extraction steam pressure by adjusting the heating extraction steam regulating valve with parameters P=1 and I=-50.

[0106] In the Matlab / Simulink environment, the cogeneration unit stabilized at a load of 235MW 100 seconds prior, during which time the main steam pressure remained stable at 16.67MPa and the heating extraction steam pressure remained stable at 0.35MPa. At 100 seconds, the AGC load command increased from 235MW to 245MW at a rate of 12MW / min, while the setpoints for the main steam pressure and the heating extraction steam pressure remained unchanged. The final results can be found in [link to relevant documentation]. Figure 3 , Figure 4 and Figure 5 As shown, the optimized control strategy is used to represent the cogeneration unit operation control method provided in this application.

[0107] Figure 3This indicates the tracking status of unit load under optimized control strategy and traditional CCS strategy. The dashed line represents the active response command from the heat source, the straight line represents the result under the optimized control strategy, and the long and short dashed lines represent the result under the traditional CCS strategy. The dashed line and the straight line almost coincide; and from... Figure 3 As can be seen, under the action of the heat source actively responding to the load command, the actual output value of the unit load climbed to the target value of 245MW 151.6s after receiving the command, which is significantly faster than the traditional CCS strategy.

[0108] Figure 4 This indicates the tracking performance of steam pressure under optimized control strategy and traditional CCS strategy, by... Figure 4 It can be seen that under the optimized control strategy, the maximum fluctuation of the main steam pressure is only 0.03 MPa, occurring 48.4 seconds after the AGC issues the load command, which is conducive to the stable operation of the cogeneration unit. In contrast, under the traditional CCS strategy, the main steam pressure fluctuates by more than 0.2 MPa. This is because, under the boiler-following-turbine coordination mode, the unit relies on the turbine regulating valve to adjust the unit load, resulting in significant fluctuations in the main steam pressure. Clearly, the optimized control strategy is superior to the traditional CCS strategy in terms of stable operation.

[0109] Figure 5 This indicates the tracking performance of the extraction steam pressure under both optimized control strategies and traditional CCS strategies, as shown by... Figure 5 It can be seen that when the cogeneration unit adopts the optimized control strategy, the heating extraction steam pressure drops significantly in the initial stage of regulation, and then gradually recovers to the set value when the energy provided by the fuel is sufficient; while when the cogeneration unit adopts the CCS strategy, no heat source is used to regulate the load, so the heating extraction steam pressure only fluctuates slightly.

[0110] By evaluating the extraction steam pressure of the combined heat and power (CHP) unit, i.e., evaluating the heating situation, the heat source quality is obtained. (See [reference]). Figure 6 As shown in the trend of heat source quality changes, due to the effect of precise energy balance, the heat source quality gradually returns to the set value after about 400 seconds of adjustment.

[0111] This invention, through obtaining the actual output value of a combined heat and power (CHP) unit, can determine the current actual output status. Then, based on the output reference value and the actual output value, it calculates the output tracking error of each output of the CHP unit. This tracking output error represents the difference between the current output status and the preset status of the CHP unit, and is also the data that needs to be adjusted in the output of the CHP unit. Based on this, a control gain matrix is ​​calculated, which includes a state feedback matrix and an error gain matrix. The CHP unit is controlled using the obtained control gain matrix. Specifically, the state weight matrix and input weight matrix are determined using a particle swarm optimization algorithm to avoid over-reliance on... Based on human experience, a more suitable weight matrix can be determined, thereby determining a suitable control gain matrix. This enables comprehensive and flexible control of the weights of the input variables and state variables of the cogeneration unit, allowing the actual output value of the cogeneration unit to be closer to the output reference value, achieving the expected effect. In addition, by determining the fuel regulation signal, the deviation between the actual value and the target value of the heating extraction steam flow of the cogeneration unit can be obtained, thereby increasing the energy input of the cogeneration unit, avoiding the degradation of heating quality, and enabling the actual output value of the cogeneration unit to reach the control requirements more quickly, meeting the control requirements of power supply and heating under different control modes.

[0112] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0113] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0114] Figure 7 A schematic diagram of the operation control device for a combined heat and power unit provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below:

[0115] like Figure 7 As shown, the cogeneration unit operation control device 7 includes:

[0116] Module 71 acquires the actual output value of the cogeneration unit under the current control mode;

[0117] The first calculation module 72 calculates the output tracking error of each output of the cogeneration unit based on the output reference value and actual output value of the cogeneration unit under the current control mode.

[0118] The second calculation module 73 calculates the control gain matrix of the cogeneration unit based on the output tracking error under the current control mode.

[0119] Module 74 is used to input the control gain matrix into the cogeneration unit and determine the actual output target value of the cogeneration unit after adjustment.

[0120] In one possible implementation, the first computing module 72 is specifically used for:

[0121] according to Calculate the output tracking error for each output item;

[0122] Among them, X e (t) represents the output tracking error of the cogeneration unit within time t, Y d Y(τ) is the output reference value of the cogeneration unit under the current control mode at time τ, Y(τ) is the actual output value of the cogeneration unit at time τ, t is the operation control time of the cogeneration unit, and τ is any time within time t.

[0123] In one possible implementation, the second computing module 73 is specifically used for:

[0124] Under the current control mode, calculate the extended state-space model of the cogeneration unit based on the output tracking error;

[0125] Based on the extended state-space model, the cost function of LQR control is determined;

[0126] Based on the cost function, determine the state weight matrix and input weight matrix of LQR control;

[0127] Calculate the control gain matrix of the cogeneration unit based on the state weight matrix and the input weight matrix.

[0128] In one possible implementation, the second calculation module 73 determines the state weight matrix and input weight matrix of the LQR control based on the cost function, for:

[0129] Based on the cost function, the particle swarm optimization algorithm is used to determine the state weight matrix and input weight matrix of each output.

[0130] In one possible implementation, the second calculation module 73 calculates the control gain matrix of the cogeneration unit based on the state weight matrix and the input weight matrix, for the purpose of:

[0131] Based on the state weight matrix and the input weight matrix, calculate the positive definite matrix solution of the Riccati equation corresponding to the minimum cost function;

[0132] Based on the positive definite matrix solution, calculate the control gain matrix of the cogeneration unit. The control gain matrix includes the state feedback matrix and the error gain matrix.

[0133] In one possible implementation, the cogeneration unit operation control device 7 further includes a third calculation module 75 and a fourth calculation module 76;

[0134] The acquisition module 71 is also used to acquire the output steam flow rate for heating from the cogeneration unit;

[0135] The third calculation module 75 is used to calculate the heating status signal based on the heating steam extraction flow rate.

[0136] The fourth calculation module 76 is used to determine the fuel adjustment signal based on the heating status signal and the preset heating quality signal;

[0137] The determination module 74 is specifically used to input the fuel regulation signal and control gain matrix into the cogeneration unit to determine the actual output target value of the cogeneration unit after regulation.

[0138] In one possible implementation, the third computing module 75 is specifically used for:

[0139] according to Calculate the heating status signal;

[0140] in, Indicates the heating status signal, m H t1 represents the output steam flow rate for heating from the combined heat and power unit, t2 represents the start time for acquiring the steam flow rate for heating, and t2 represents the end time for acquiring the steam flow rate for heating.

[0141] The fourth calculation module 76 is specifically used for:

[0142] according to Determine the fuel regulation signal;

[0143] in, P represents the fuel regulation signal. d This represents the output reference value of the combined heat and power (CHP) unit load, where P represents the ratio of the CHP unit output to the heating extraction steam flow rate. This represents the tracking error of the steam extraction flow rate for heating, expressed in meters (m). Hd This indicates the preset heating quality signal. This indicates the heating status signal.

[0144] In one possible way, see Figure 8 The diagram shown illustrates the structure of the control quality evaluation module. The control quality evaluation module 8 includes:

[0145] Data storage unit 81 is used to store historical operating information and historical cases of cogeneration units;

[0146] Case reasoning unit 82 is used to determine historical cases corresponding to the current operating condition information of the cogeneration unit;

[0147] Evaluation unit 83 is used to calculate the second control quality value of the cogeneration unit based on the actual output value of the cogeneration unit; and to use the historical cases or current control parameters corresponding to the larger control quality value between the first control quality value and the second control quality value as control reference information.

[0148] The communication unit 84 is used to store control reference information to the data storage unit 81 and to communicate with the external control system.

[0149] In this embodiment of the invention, the actual output value of the cogeneration unit is obtained through an acquisition module, thus revealing the current actual output status. Then, a first calculation module calculates the output tracking error of each output of the cogeneration unit based on the output reference value and the actual output value. This tracking output error represents the difference between the current output status and the preset status of the cogeneration unit, and is also the data that needs to be adjusted in terms of the cogeneration unit's output. Based on this, a second calculation module calculates the control gain matrix, which includes a state feedback matrix and an error gain matrix. The cogeneration unit is controlled using the obtained control gain matrix. Specifically, the state weight matrix and input weight matrix are determined using a particle swarm optimization algorithm. By avoiding over-reliance on human experience, a more suitable weight matrix can be determined, thereby determining an appropriate control gain matrix. This enables comprehensive and flexible control over the weights of the input and state variables of the cogeneration unit, allowing the actual output value of the cogeneration unit to be closer to the output reference value, achieving the expected results. In addition, the fourth calculation module is used to determine the fuel regulation signal and obtain the deviation between the actual and target values ​​of the heating extraction steam flow rate of the cogeneration unit. This increases the energy input of the cogeneration unit, preventing a decline in heating quality and enabling the actual output value of the cogeneration unit to reach the control requirements more quickly, meeting the control requirements for power supply and heating under different control modes.

[0150] Figure 9 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. For example... Figure 9 As shown, the electronic device 9 in this embodiment includes: a processor 90, a memory 91, and a computer program 92 stored in the memory 91 and executable on the processor 90. When the processor 90 executes the computer program 92, it implements the steps in the various embodiments of the cogeneration unit operation control method described above, for example... Figure 2 Steps S201 to S204 are shown. Alternatively, when the processor 90 executes the computer program 92, it implements the functions of each module in the above-described device embodiments, for example... Figure 7 The functions of modules 71 to 74 are shown.

[0151] For example, the computer program 92 can be divided into one or more modules / units, which are stored in the memory 91 and executed by the processor 90 to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 92 in the electronic device 9. For example, the computer program 92 can be divided into... Figure 7 Modules 71 to 74 are shown.

[0152] The electronic device 9 may include, but is not limited to, a processor 90 and a memory 91. Those skilled in the art will understand that... Figure 9 This is merely an example of electronic device 9 and does not constitute a limitation on electronic device 9. It may include more or fewer components than shown, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0153] The processor 90 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0154] The memory 91 can be an internal storage unit of the electronic device 9, such as a hard disk or memory. The memory 91 can also be an external storage device of the electronic device 9, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 91 can include both internal and external storage units of the electronic device 9. The memory 91 is used to store the computer program and other programs and data required by the electronic device. The memory 91 can also be used to temporarily store data that has been output or will be output.

[0155] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0156] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0157] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0158] In the embodiments provided by this invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0159] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0161] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0162] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for operating and controlling a combined heat and power (CHP) unit, characterized in that, The combined heat and power (CHP) unit employs multiple control modes, and each control mode sets a separate output reference value for the CHP unit; the method includes: Obtain the actual output value of the cogeneration unit under the current control mode; Based on the output reference value and the actual output value of the cogeneration unit under the current control mode, calculate the output tracking error of each output of the cogeneration unit; In the current control mode, the control gain matrix of the cogeneration unit is calculated based on the output tracking error; The control gain matrix is ​​input into the cogeneration unit to determine the actual target output value of the cogeneration unit after adjustment; In the current control mode, the control gain matrix of the cogeneration unit is calculated based on the output tracking error, including: In the current control mode, an extended state-space model of the cogeneration unit is calculated based on the output tracking error; the output tracking error is calculated by integrating the difference between the output reference value and the actual output value. Based on the extended state-space model, the cost function of LQR control is determined; Based on the cost function, the state weight matrix and input weight matrix of LQR control are determined using a particle swarm optimization algorithm; the membership function of the particle swarm optimization algorithm is determined based on the output tracking error. The control gain matrix of the cogeneration unit is calculated based on the state weight matrix and the input weight matrix. Based on the state weight matrix and the input weight matrix, the control gain matrix of the combined heat and power unit is calculated, including: Based on the state weight matrix and the input weight matrix, calculate the positive definite matrix solution of the Riccati equation corresponding to the minimum cost function; Based on the positive definite matrix solution, the control gain matrix of the cogeneration unit is calculated, and the control gain matrix includes the state feedback matrix and the error gain matrix.

2. The cogeneration unit operation control method according to claim 1, characterized in that, The step of calculating the output tracking error of each output of the cogeneration unit based on the output reference value and the actual output value of the cogeneration unit under the current control mode includes: according to Calculate the output tracking error for each output; in, for t The output tracking error of the combined heat and power unit within the specified time period for The output reference value of the cogeneration unit under the current control mode at that moment. for The actual output value of the cogeneration unit at the specified time. t For the time of operation control of combined heat and power units, for t Any moment in time.

3. The cogeneration unit operation control method according to claim 1, characterized in that, Before inputting the control gain matrix into the cogeneration unit to determine the actual target output value of the cogeneration unit after adjustment, the method further includes: Obtain the output steam flow rate for heating from the combined heat and power unit; Calculate the heating status signal based on the heating steam extraction flow rate; Based on the heating status signal and the preset heating quality signal, determine the fuel adjustment signal; The step of inputting the control gain matrix into the cogeneration unit to determine the actual target output value of the cogeneration unit after adjustment includes: The fuel regulation signal and the control gain matrix are input into the cogeneration unit to determine the actual output target value of the cogeneration unit after regulation.

4. The cogeneration unit operation control method according to claim 3, characterized in that, Based on the heating steam extraction flow rate, the heating status signal is calculated, including: according to Calculate the heating status signal; in, This indicates the heating status signal. This indicates the output flow rate of the combined heat and power unit for heating steam extraction. This indicates the start time for obtaining the heating steam extraction flow rate. This indicates the end time of obtaining the heating steam extraction flow rate; Based on the heating status signal and the preset heating quality signal, a fuel adjustment signal is determined, including: according to Determine the fuel adjustment signal; in, Indicates a fuel adjustment signal. This represents the output reference value of the unit load of the combined heat and power (CHP) unit. This represents the ratio of the output of the combined heat and power unit to the flow rate of the steam extracted for heating. This indicates the tracking error of the heating steam extraction flow rate. This indicates the preset heating quality signal. This indicates the heating status signal.

5. A combined heat and power (CHP) unit operation control device, characterized in that, The combined heat and power (CHP) unit employs multiple control modes, and each control mode sets a separate output reference value for the CHP unit; the device includes: The acquisition module acquires the actual output value of the cogeneration unit under the current control mode; The first calculation module calculates the output tracking error of each output of the cogeneration unit based on the output reference value and the actual output value of the cogeneration unit under the current control mode. The second calculation module calculates the control gain matrix of the cogeneration unit based on the output tracking error under the current control mode. The module determines the actual output target value of the cogeneration unit after adjustment by inputting the control gain matrix into the cogeneration unit. The second calculation module is specifically used for: In the current control mode, an extended state-space model of the cogeneration unit is calculated based on the output tracking error; the output tracking error is calculated by integrating the difference between the output reference value and the actual output value. Based on the extended state-space model, the cost function of LQR control is determined; Based on the cost function, the state weight matrix and input weight matrix of LQR control are determined using a particle swarm optimization algorithm; the membership function of the particle swarm optimization algorithm is determined based on the output tracking error. The control gain matrix of the cogeneration unit is calculated based on the state weight matrix and the input weight matrix. The second calculation module is specifically used for: Based on the state weight matrix and the input weight matrix, calculate the positive definite matrix solution of the Riccati equation corresponding to the minimum cost function; Based on the positive definite matrix solution, the control gain matrix of the cogeneration unit is calculated, and the control gain matrix includes the state feedback matrix and the error gain matrix.

6. An electronic device comprising a memory and a processor, the memory for storing a computer program, the processor for calling and running the computer program stored in the memory, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 4 above.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 4 above.

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