Multivariable heat supply optimization control system for desuperheater and pressure reducer set based on load prediction technology

Abstract

The application belongs to the technical field of heat supply control application, and particularly discloses a multi-variable heat supply optimization control system for a desuperheater and pressure reducer set based on load prediction technology, which comprises a desuperheating and pressure reducing control module, a desuperheater and a pressure reducer, the desuperheating and pressure reducing control module is connected with the desuperheater and the pressure reducer, the desuperheating and pressure reducing control module is composed of a target load prediction optimization algorithm unit, a data relay unit, an artificial intervention target meeting input unit, a multi-variable fuzzy decoupling controller and a Kalman filter.The application has the beneficial effect that the system can design a multi-variable dynamic decoupling module according to the mutual coupling relationship between temperature and pressure, eliminate the coupling influence between the temperature regulation loop and the pressure regulation loop, and when the system needs to quickly increase the load, give a larger opening degree instruction to the pressure regulating door and the temperature regulating door, so that the system can quickly increase the pressure while maintaining the temperature stable, and when the system flow is close to the flow set value, switch to the steady-state controller for flow control.

Description

Technical Field

[0001] This invention belongs to the field of heating control application technology, specifically relating to a multivariable heating optimization control system based on load prediction technology for desuperheating and pressure reducing device groups. Background Technology

[0002] In the entire heating system, in addition to directly extracting steam from the steam turbine for heating, an important method of steam supply and heating is to directly supply high-temperature, high-pressure steam from the boiler steam header to the outside after passing it through a desuperheater and pressure reducer to achieve the required heating parameters.

[0003] The existing process flow of the heating process using medium and low pressure desuperheaters is as follows: Figure 3 As shown, during the window period of gradually shutting down old units after long-term use and constructing new units, the flexibility of the heating system's operation mode is reduced. Once an emergency occurs, the heating system's desuperheating and pressure reducing unit needs to respond quickly, automatically adjust, and stabilize the heating system load.

[0004] Therefore, based on the above problems, the present invention provides a method for constructing a rapid coordinated intelligent control system for medium and low pressure desuperheaters and pressure reducers based on load prediction. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a multivariable heating optimization control system for desuperheating and pressure reducing units based on load forecasting technology. This system can not only improve the automation level and safety stability of the thermal power plant, but also save energy and reduce consumption. At the same time, during special periods when old units are gradually shut down and operating modes are restricted, it can also quickly respond to and coordinate the control of multiple desuperheating and pressure reducing units in the heating system under emergency conditions of the units, ensuring the stable operation of the heating system.

[0006] Technical Solution: The present invention provides a multivariable heating optimization control system for desuperheating and pressure reducing devices based on load forecasting technology, comprising a desuperheating and pressure reducing control module and a desuperheating and pressure reducing device. The desuperheating and pressure reducing control module is connected to the desuperheating and pressure reducing device. The desuperheating and pressure reducing control module consists of a target load forecasting optimization algorithm unit, a data relay unit, a manual intervention target input unit, a multivariable fuzzy decoupling controller, and a Kalman filter. The target load forecasting optimization algorithm unit, the desuperheating and pressure reducing device, and the multivariable fuzzy decoupling controller are respectively connected to the data relay unit. The multivariable fuzzy decoupling controller is respectively connected to the Kalman filter and the desuperheating and pressure reducing device. The Kalman filter is also connected to the desuperheating and pressure reducing device.

[0007] In this technical solution, the state estimation using state amplification and Kalman filtering effectively eliminates the influence of modeling error-free and unmeasurable disturbances on the control effect of the desuperheater and pressure reducer; the objective function of the heating load prediction control algorithm is shown in the following formula: In the formula, To predict the number of steps, To control the number of steps, For the outlet flow rate, temperature, and pressure of the desuperheater and pressure regulator, The heating load prediction value is obtained based on the state-space model. Provide heat flow for N desuperheaters and pressure reducers. These are the weighting coefficients for the control quantity. A Kalman filter is used to estimate the state, and a state-space model is used to predict future heating loads. Then, rolling optimization of the multivariate control is performed in each control cycle to obtain the control quantity. .

[0008] In this technical solution, the multivariable fast fuzzy decoupling control is proposed to use pressure adjustment gates and temperature adjustment gates to jointly maintain the parameters of the heating steam.

[0009] In this technical solution, when the pressure regulating valve is opened wide, the temperature regulating valve is opened wide in a timely manner through the decoupling controller to ensure that the temperature of the heating steam remains basically constant. Conversely, when the pressure regulating valve is closed narrowly, the opening of the temperature regulating valve should be closed narrowly at the same time. When the temperature regulating valve is opened wide, the pressure regulating valve is closed appropriately through the decoupling link to keep the pressure of the heating steam basically constant. Conversely, when the temperature regulating valve is closed narrowly, the opening of the pressure regulating valve should be opened appropriately at the same time.

[0010] In this technical solution, if it is necessary to eliminate the mutual influence of various disturbances on the outlet temperature and pressure of the desuperheater and pressure reducer in a timely manner, a state-space predictive control algorithm is adopted.

[0011] Compared with existing technologies, the beneficial effects of the multivariable heating optimization control system for desuperheating and pressure reducing valve groups based on load prediction technology of the present invention are as follows: 1. This system designs a multivariable dynamic decoupling module based on the mutual coupling relationship between temperature and pressure to eliminate the coupling influence between the temperature regulation loop and the pressure regulation loop. 2. When the system needs to rapidly increase the load, the multivariable fuzzy decoupling controller will give a large opening command to the pressure valve and temperature valve according to the target load prediction optimization algorithm unit and the manual intervention target conformity input unit, so that the system can quickly increase the pressure while maintaining temperature stability; when the system flow rate approaches the flow rate set value, it will switch to the steady-state controller for flow control. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments 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.

[0013] Figure 1This is a structural block diagram of the multivariable heating optimization control system for desuperheating and pressure reducing device group based on load prediction technology of the present invention and the original DCS control system; Figure 2 This is a flowchart of the multivariable heating optimization control system for desuperheating and pressure reducing unit based on load prediction technology of the present invention. Figure 3 This is a process flow diagram of the existing medium and low pressure desuperheating and pressure reducing device heating process; The numbers in the diagram are as follows: 100-De-temperature and pressure reduction control module, 101-De-temperature and pressure reduction device, 10-Target load prediction optimization algorithm unit, 11-Data relay unit, 12-Manual intervention target input unit, 13-Multivariable fuzzy decoupling controller, 14-Kalman filter. Detailed Implementation

[0014] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0015] In the description of this invention, it should be noted that the terms "top," "bottom," "one side," "the other side," "front," "rear," "middle part," "inner," "top," and "bottom," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. The terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, unless otherwise explicitly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0016] like Figure 1 and Figure 3The multivariable heating optimization control system for desuperheating and pressure reducing devices based on load forecasting technology shown includes a desuperheating and pressure reducing control module 100 and a desuperheating and pressure reducing device 101. The desuperheating and pressure reducing control module 100 is connected to the desuperheating and pressure reducing device 101. The desuperheating and pressure reducing control module 100 consists of a target load forecasting optimization algorithm unit 10, a data relay unit 11, a manual intervention target input unit 12, a multivariable fuzzy decoupling controller 13, and a Kalman filter 14. The target load forecasting optimization algorithm unit 10, the desuperheating and pressure reducing device 101, and the multivariable fuzzy decoupling controller 13 are respectively connected to the data relay unit 11. The multivariable fuzzy decoupling controller 13 is respectively connected to the Kalman filter 14 and the desuperheating and pressure reducing device 101. The Kalman filter 14 is connected to the desuperheating and pressure reducing device 101.

[0017] Furthermore, state estimation is preferably performed by state amplification and using a Kalman filter, which effectively eliminates the influence of modeling error-free and unmeasurable disturbances on the control effect of the desuperheater and pressure reducer; the objective function of the heating load prediction control algorithm is shown in the following equation: In the formula, To predict the number of steps, To control the number of steps, For the outlet flow rate, temperature, and pressure of the desuperheater and pressure regulator, The heating load prediction value is obtained based on the state-space model. Provide heat flow for N desuperheaters and pressure reducers. These are the weighting coefficients for the control quantity. A Kalman filter is used to estimate the state, and a state-space model is used to predict future heating loads. Then, rolling optimization of the multivariate control is performed in each control cycle to obtain the control quantity. .

[0018] In addition, the preferred multivariate fast fuzzy decoupling control proposes to use pressure regulation gates and temperature regulation gates to jointly maintain the parameters of the heating steam.

[0019] In addition, preferably, when the pressure regulating valve is opened wide (when the pressure of the heating steam is too low), the temperature regulating valve is opened wide in a timely manner through the decoupling controller to ensure that the temperature of the heating steam remains basically constant. Conversely, when the pressure regulating valve is closed, the opening of the temperature regulating valve should be closed simultaneously. When the temperature regulating valve is opened wide (when the temperature of the heating steam is too high), the pressure regulating valve is closed appropriately through the decoupling mechanism to keep the pressure of the heating steam basically constant. Conversely, when the temperature regulating valve is closed, the opening of the pressure regulating valve should be opened appropriately.

[0020] In addition, if it is necessary to eliminate the mutual influence of various disturbances on the outlet temperature and pressure of the desuperheater and pressure reducer in a timely manner, a state-space predictive control algorithm is preferably adopted.

[0021] Based on the coupling relationship between temperature and pressure, the system uses a multivariable fuzzy decoupling controller 13 to eliminate the coupling effect between the temperature regulation loop and the pressure regulation loop.

[0022] When the system needs to rapidly increase the load, the multivariate fuzzy decoupling controller 13 will give a large opening command to the pressure valve and temperature valve based on the prediction model (target load prediction optimization algorithm unit 10) and the target load (human intervention target conformity input unit 12), so that the system can rapidly increase the pressure while maintaining the temperature as stable as possible; when the system flow rate is close to the flow rate set value, it will switch to the steady-state controller for flow control.

[0023] Example: During normal operation, this system can coordinate the opening of the pressure regulating valves of each desuperheater and pressure reducer according to the steam supply, unit operating status, unit steam supply, and gate steam pressure, as well as the opening of the regulating valves of each desuperheater and pressure reducer, and ensure the stable operation of the desuperheater and pressure reducer.

[0024] In the event of an accident, this system uses numerous parameters such as power generation load, turbine steam inlet flow, steam supply, turbine status, valve opening, boiler main steam pressure, and flow rate change rate to determine whether the turbine has stopped operating. It then incorporates the requirement for shutting down the specific unit without stopping the boiler, performs a secondary confirmation of the interlocked desuperheater and pressure reducer, and activates the emergency response function.

[0025] In addition, such as Figure 1 The desuperheating and pressure reducing device 101 shown is connected to the original DCS control system and interacts with the original DCS control system for valve commands, authorization confirmation, and system data exchange.

[0026] It should be noted that, in this document, terms such as "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0027] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A multivariable heating optimization control system for desuperheating and pressure reducing generator groups based on load forecasting technology, characterized in that: It includes a de-temperature and pressure reduction control module (100) and a de-temperature and pressure reduction device (101), wherein the de-temperature and pressure reduction control module (100) is connected to the de-temperature and pressure reduction device (101); The temperature and pressure reduction control module (100) consists of a target load prediction optimization algorithm unit (10), a data relay unit (11), a manual intervention target conformity input unit (12), a multivariable fuzzy decoupling controller (13), and a Kalman filter (14); The target load prediction optimization algorithm unit (10), the de-cooling and pressure reducing device (101), and the multivariate fuzzy decoupling controller (13) are respectively connected to the data relay unit (11). The multivariate fuzzy decoupling controller (13) is respectively connected to the Kalman filter (14) and the de-cooling and pressure reducing device (101). The Kalman filter (14) is connected to the de-cooling and pressure reducing device (101).

2. The multivariable heating optimization control system for desuperheating and pressure reducing generator group based on load prediction technology according to claim 1, characterized in that: The state estimation method, which utilizes state amplification and a Kalman filter, effectively eliminates the influence of modeling error-free and unmeasurable disturbances on the control performance of the desuperheater and pressure reducer. The objective function of the heating load prediction control algorithm is shown in the following equation: In the formula, To predict the number of steps, To control the number of steps, For the outlet flow rate, temperature, and pressure of the desuperheater and pressure regulator, The heating load prediction value is obtained based on the state-space model. Provide heat flow for N desuperheaters and pressure reducers. These are the weighting coefficients for the control quantity. A Kalman filter is used to estimate the state, and a state-space model is used to predict future heating loads. Then, rolling optimization of the multivariate control is performed in each control cycle to obtain the control quantity. .

3. The multivariable heating optimization control system for desuperheating and pressure reducing generator group based on load prediction technology according to claim 2, characterized in that: The proposed multivariate fast fuzzy decoupling control uses pressure regulation gates and temperature regulation gates to jointly maintain the parameters of the heating steam.

4. The multivariable heating optimization control system for desuperheating and pressure reducing generator group based on load prediction technology according to claim 2 or 3, characterized in that: When the pressure regulating valve is opened wide, the temperature regulating valve should be opened wide in a timely manner through the decoupling controller to ensure that the temperature of the heating steam remains basically constant. Conversely, when the pressure regulating valve is closed, the opening of the temperature regulating valve should be closed at the same time. When the temperature regulating valve is opened wide, the pressure regulating valve should be closed appropriately through the decoupling mechanism to keep the pressure of the heating steam basically constant. Conversely, when the temperature regulating valve is closed, the pressure regulating valve should be opened appropriately at the same time.

5. The multivariable heating optimization control system for desuperheating and pressure reducing generator group based on load prediction technology according to claim 2, characterized in that: If it is necessary to eliminate the mutual influence of various disturbances on the outlet temperature and pressure of the desuperheater and pressure reducer in a timely manner, a state-space predictive control algorithm is adopted.

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