Variable air volume central air conditioning system distributed event triggering control method and system

Abstract

This invention proposes a distributed event-triggered control method and system for variable air volume (VAV) central air conditioning systems, comprising: decomposing the VAV central air conditioning system into multiple subsystems; establishing mathematical models for each subsystem; discretizing the mathematical models of each subsystem to establish a prediction model; determining the optimal objective function for each subsystem based on the prediction model; obtaining the optimal control variable based on the event triggering mechanism and the optimal objective function; and completing the control of the VAV central air conditioning system based on the control variable.

Description

Technical Field

[0001] This invention belongs to the field of air conditioning system control and optimization technology, and particularly relates to a distributed event-triggered control method and system for variable air volume central air conditioning systems. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Energy conservation has become a new goal for smart buildings, and air conditioning energy consumption accounts for more than 40% of building energy consumption. Therefore, the control and optimization of air conditioning systems are considered the key to energy conservation in smart buildings.

[0004] Considering energy conservation, variable air volume (VAV) central air conditioning systems have become the mainstream for air conditioning systems in various large buildings. VAV central air conditioning systems respond to load changes in multiple areas by using variable air volume at the terminal units, thereby adjusting the system airflow through frequency conversion, saving fan power consumption, and providing more stable and flexible temperature control in each area. VAV central air conditioning systems consist of multiple strongly coupled subsystems, and their control process is a complex multivariable coupled control problem. Model predictive control (MPC) is one of the most effective control methods for handling multivariable coupled systems and has been successfully applied to VAV central air conditioning systems.

[0005] Model predictive control (MPC) is a building automation optimization control technology. Large-scale variable air volume (VAV) central air conditioning systems in buildings are large in scale and have many subsystems. Traditional centralized MPC involves solving high-dimensional rolling time-domain optimization problems, which consumes a significant amount of time, leading to untimely control and poor energy-saving effects. Therefore, centralized MPC is unsuitable for the optimization control of large-scale VAV central air conditioning systems. Distributed MPC divides the complex large-scale system into several distributed subsystems and configures multiple distributed MPC controllers. Each controller acts on a specific subsystem to perform optimal control, reducing the complexity of the system control problem and lowering the computational burden. However, existing distributed predictive control systems for large-scale building air conditioning systems are mostly time-triggered, resulting in too many optimization problem solutions and a still large computational load.

[0006] Specifically, typical MPC controllers employ a time-triggered control mechanism, performing information communication and optimization problem solving in each control cycle, regardless of necessity. However, large building variable air volume (VAV) central air conditioning systems experience slower load changes and have a wider range of indoor comfort levels, eliminating the need for frequent adjustments. Therefore, the time-triggered control mechanism's practice of solving optimization problems when not required increases the computational and communication burden, hindering the application of model predictive control in VAV central air conditioning systems with limited computing power. Summary of the Invention

[0007] To overcome the shortcomings of the existing technologies, this invention provides a distributed event-triggered control method for variable air volume (VAV) central air conditioning systems. It constructs a triggering mechanism for updating the MPC controller of the subsystem, proposes a new triggering condition based on output overshoot, considers the dynamic performance of the system, and improves control stability. This eliminates unnecessary updates in the control optimization problem, significantly reduces computational complexity, effectively reduces the number of optimization problems to solve, and ensures that output performance is almost unaffected.

[0008] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0009] Firstly, a distributed event-triggered control method for variable air volume central air conditioning systems is disclosed, including:

[0010] The variable air volume central air conditioning system is broken down into multiple subsystems;

[0011] Establish mathematical models for each subsystem;

[0012] Discretize the mathematical models of each subsystem and establish a prediction model;

[0013] The optimal objective function for each subsystem is determined based on the prediction model;

[0014] The optimal control variable is obtained by determining the trigger time based on the event triggering mechanism and solving the objective function. Based on the optimal control variable, the control of the variable air volume central air conditioning system is completed, specifically including:

[0015] Adjusting the room's air supply volume to maintain the indoor temperature;

[0016] After interacting with information from various variable air volume systems, relevant prediction calculations are performed to obtain the supply air temperature setpoint and system static pressure. Accordingly, the chilled water flow rate and fan speed are adjusted to control the supply air temperature and total supply air volume.

[0017] By adjusting the opening of the return air valve in the return air duct, the fresh air volume is controlled to maintain indoor air quality.

[0018] As a further technical solution, each subsystem includes a supply air temperature control loop, a total supply air volume control loop, a fresh air volume control loop, and an indoor temperature control loop.

[0019] The input quantities corresponding to each subsystem are: chilled water flow rate, fan speed, fresh air volume, and room air supply volume;

[0020] The outputs of each subsystem are: supply air temperature, static pressure at the static pressure point, carbon dioxide concentration, and room temperature.

[0021] As a further technical solution, the room temperature control loop has the following thermodynamic model:

[0022]

[0023] Among them, M r,p For room air quality p, C r,p Let p be the specific heat capacity of the air in the room, and θ be the specific heat capacity of the air in the room. r,p Let p be the room temperature, and G be the temperature at room temperature. a,p The air supply flow rate for room p, C a For the specific heat capacity of the supply air, θ s For supply air temperature, θ a,f For fresh air temperature, Q room,p R is the heat load generated by room equipment and people. p Let p be the ambient thermal resistance of the room.

[0024] As a further technical solution, the event triggering mechanism is as follows:

[0025] Define the sequence of instants in time corresponding to the controller solving the optimization problem during the i-th system control process, and denote the system output at this moment as the first output;

[0026] The subsequent system output is compared with the first output, and the overshoot is defined as the error between the two.

[0027] Based on the error, the judgment logic is used to evaluate the truth or falsehood of the event and obtain the representation of the next optimization time.

[0028] As a further technical solution, when evaluating the truth or falsehood of an event, the optimal control sequence is calculated at the moment when the event is false, and the first element of the sequence is applied to the system to adjust the control subsystem.

[0029] As a further technical solution, when evaluating the authenticity of an event, the input at the last trigger moment is directly taken when the event is true to adjust the control subsystem.

[0030] As a further technical solution, the optimal control variables are obtained by solving the objective function based on an event-triggered mechanism, specifically:

[0031] At time k, when the room temperature setpoint changes or the room temperature changes due to disturbance, the indoor temperature control loop detects the change in output temperature. When the change meets the event triggering condition, the room temperature control loop performs optimization problem solving, performs rolling optimization to find the optimal control variable, and applies its first element to the room temperature control loop. When the change does not meet the event triggering condition, the room temperature control loop does not perform optimization control, and the controller directly takes the input at the last triggering time.

[0032] As a further technical solution, the optimal control variables are obtained by solving the objective function based on the event-triggered mechanism, which also includes:

[0033] The indoor temperature control loop controls the room temperature by changing the air supply volume of room p. The change in air supply volume will affect the change in static pressure at the static pressure point. At this time, the total air supply volume control system of the central variable frequency air conditioning unit interacts with the variable air volume system at the room terminal to detect the change in static pressure at the static pressure point. If the change in static pressure does not meet the event triggering conditions, the total air supply volume control loop will not perform optimized control, and the controller will directly take the input at the last triggering moment.

[0034] When the air volume of each room changes to a certain extent, the change in static pressure at the static pressure point satisfies the event triggering condition. The total air volume control loop then performs optimization to find the optimal control variable through rolling optimization, and applies its first element to the total air volume control loop.

[0035] As a further technical solution, the optimal control variables are obtained by solving the objective function based on the event-triggered mechanism, which also includes:

[0036] When the temperature setpoints of multiple rooms change, the supply air temperature will no longer meet the control requirements. At this time, the supply air temperature control loop of the central variable frequency air conditioning unit interacts with the variable air volume system at the room terminal to calculate and obtain a new supply air temperature setpoint. The supply air temperature control loop then performs optimization problem solving and rolling optimization to find the optimal control variable, and applies its first element to the supply air temperature control loop.

[0037] As a further technical solution, the optimal control variables are obtained by solving the objective function based on the event-triggered mechanism, which also includes:

[0038] Changes in room supply air volume can lead to changes in room carbon dioxide concentration. In the return air duct, if a change in carbon dioxide concentration is detected that meets the triggering condition, the fresh air volume control loop will perform optimization problem solving, and rolling optimization will be performed to find the optimal control variable. Its first element will be applied to the supply air temperature control loop.

[0039] If the change in carbon dioxide concentration does not meet the event triggering conditions, the fresh air volume control loop will not perform optimized control, and the controller will directly take the input at the last triggering moment.

[0040] Secondly, a distributed event-triggered control system for a variable air volume central air conditioning system is disclosed, including:

[0041] The system includes a supply air temperature control loop, a total supply air volume control loop, an indoor temperature control loop, and a fresh air volume control loop, each with its own controller.

[0042] The controller is configured to: determine the triggering time based on an event-triggered mechanism, solve the optimal objective function to obtain the optimal control variable, and complete the control of the variable air volume central air conditioning system based on the optimal control variable, specifically including:

[0043] Adjusting the room's air supply volume to maintain the indoor temperature;

[0044] After interacting with information from various variable air volume systems, relevant prediction calculations are performed to obtain the supply air temperature setpoint and system static pressure. Accordingly, the chilled water flow rate and fan speed are adjusted to control the supply air temperature and total supply air volume.

[0045] By adjusting the opening of the return air valve in the return air duct, the fresh air volume is controlled to maintain indoor air quality.

[0046] The above one or more technical solutions have the following beneficial effects:

[0047] To address the issue of high online computational load in traditional time-triggered predictive control models, this invention presents a novel distributed event-triggered predictive control method. This method involves determining the communication partners and interactive information within the distributed control system of a variable air volume (VAV) air conditioning system, as well as the input and output of subsystems such as the supply air temperature control loop, total supply air volume control loop, indoor temperature control loop, and fresh air volume control loop. The aim is to formulate the optimal control problem for adjusting the output of the controlled object to the set value and to design the control process using system output overshoot as the event triggering mechanism.

[0048] To control the temperature in each room, the VAV (Variable Air Volume) needs to adjust the opening of the dampers. The damper opening reflects changes in the system static pressure. To maintain static pressure, the AHU (Automatic Heatsink) needs to adjust the fan speed. The temperature requirements of each room also determine the setpoint of the supply air temperature. When the setpoint changes, the AHU's surface cooler needs to adjust. This invention proposes an event-triggered distributed predictive control strategy, dividing the overall control task into multiple subsystems that interact with each other. Each subsystem has its own MPC (Multi-Process Control) controller. After information exchange between different subsystems, each performs optimal control. This achieves the best possible control performance with the simplest possible system communication and the least possible computational burden.

[0049] This invention constructs a triggering mechanism for updating the MPC controller of a subsystem, proposes a new triggering condition based on output overshoot, considers the dynamic performance of the system, and improves the stability of control. It eliminates unnecessary updates for control optimization, significantly reduces computational complexity, effectively reduces the number of optimization problems to solve, and ensures that output performance is almost unaffected.

[0050] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0051] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0052] Figure 1 This is a schematic diagram of the distributed control structure of the system according to an embodiment of the present invention;

[0053] Figure 2 This is a schematic diagram illustrating information interaction between the various subsystems in an embodiment of the present invention;

[0054] Figure 3 This is a flowchart of the event-triggered predictive control of each subsystem based on the output overshoot magnitude in an embodiment of the present invention. Detailed Implementation

[0055] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0056] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0057] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0058] Event-triggered control only solves the optimization problem when system state changes meet triggering conditions; otherwise, the system control output remains constant, significantly reducing computational and communication burdens. This invention addresses event-triggered distributed MPC for room temperature control in large building variable air volume (VAV) central air conditioning systems. It proposes a distributed subsystem decomposition, modeling, and calculation method for large building VAV central air conditioning systems. Based on the control objective, a distributed optimal control problem is defined, and distributed event triggering conditions are designed. By adjusting devices such as chilled water flow valves, fans, room terminal valves, and fresh air valves, the temperature and air quality of each room are controlled.

[0059] Definitions:

[0060] VAV stands for Variable Air Volume system.

[0061] AHU stands for: Central Inverter Air Conditioning Unit.

[0062] Example 1

[0063] This embodiment discloses a distributed event-triggered control method for a variable air volume central air conditioning system, including:

[0064] The variable air volume central air conditioning system is broken down into multiple subsystems;

[0065] Establish mathematical models for each subsystem;

[0066] Discretize the mathematical models of each subsystem and establish a prediction model;

[0067] The optimal objective function for each subsystem is determined based on the prediction model;

[0068] The optimal control variable is obtained by determining the trigger time based on the event triggering mechanism and solving the optimal objective function. The control of the variable air volume central air conditioning system is then completed based on the optimal control variable.

[0069] In this implementation example, the distributed control structure of the variable air volume central air conditioning system is as follows: Figure 1 As shown, to obtain the real-time load status of the air conditioning system, a temperature controller is installed in each room to detect the indoor temperature and compare it with the user-set desired temperature value. The difference between the two is used to calculate the required air volume for that room, controlling the fan speed and damper opening of the VAV terminal to reduce or increase the air volume supplied to the room, thereby regulating the indoor temperature until the indoor temperature returns to the set value. Simultaneously, the air volume output is fed back to the inverter controller of the air conditioning unit via serial communication. The inverter controller receives signals from each temperature controller, calculates the sum of the air volume required by all fans, and derives the control signal required by the inverter through a certain calculation rule. The inverter then controls the total air volume and supply air temperature delivered by the air conditioning unit, ensuring that the total supply air volume meets the actual air volume requirements of each unit.

[0070] This invention decomposes the overall optimization problem of a central air conditioning system control task into optimal control problems for multiple subsystems: supply air temperature control loop, total supply air volume control loop, indoor temperature control loop, and fresh air volume control loop. Each control subsystem solves its own optimization subproblem. The VAVs (Variable Air Volume) in each room maintain indoor temperature by adjusting the room's supply air volume. The AHU (Automatic Air Handling Unit) interacts with each VAV and performs relevant predictive calculations to obtain the supply air temperature setpoint and system static pressure, accordingly adjusting the chilled water flow rate and fan speed to control the supply air temperature and total supply air volume. The fresh air volume controller controls the fresh air volume by adjusting the opening of the return air valve in the return air duct, thus maintaining indoor air quality. The various control subsystems communicate with each other to achieve room temperature and air quality control of the variable air volume air conditioning system.

[0071] In the optimization control of each subsystem, triggering conditions are introduced to perform event-triggered predictive control.

[0072] The variable air volume (VAV) air conditioning control system involved in this invention comprises four main parts:

[0073] The system includes a supply air temperature control loop, a total supply air volume control loop, a fresh air volume control loop, and an indoor temperature control loop. Each terminal room has one indoor temperature control loop, and there are, assuming, n rooms.

[0074] like Figure 2 As shown, the input quantities for each subsystem are: chilled water flow rate u1, fan speed u2, fresh air volume u3; room p supply air volume u p+3 (p = 1, 2, ..., n).

[0075] The output quantities corresponding to each subsystem are as follows: supply air temperature y1, static pressure at static pressure point y2, carbon dioxide concentration y3, room temperature y1, and room temperature y2. p+3 (p = 1, 2, ..., n).

[0076] In variable air volume (VAV) systems, by analyzing the mechanisms of each control loop, the structure of the system model can be determined, and the transfer function model G of each subsystem can be obtained using different methods. ij (S).

[0077] G ij (S) represent the control input u. i (Including chilled water flow rate u1, fan speed u2, fresh air volume u3; room p supply air volume u) p+3 (p = 1, 2, ..., n) and control output y j (Including supply air temperature y1, static pressure at static point y2, carbon dioxide concentration y3, room temperature y) p+3 The transfer function between (p=1,2,…,n)).

[0078] Through mechanistic analysis, the relationships between the system's input and output variables can be obtained. Considering the strength of coupling between system variables, the optimal pairing between control variables and manipulated variables is: u1 controls y1, u2 controls y2, u3 controls y3, u... p+3 Control y p+3 Therefore, the entire system can be divided into n+3 subsystems (where n is the number of rooms involved in the air conditioning system).

[0079] For the room temperature control loop, the thermodynamic model of room p is:

[0080]

[0081] Among them, M r,p For room air quality p, Cr,p Let p be the specific heat capacity of the air in the room, and θ be the specific heat capacity of the air in the room. r,p Let p be the room temperature, and G be the temperature at room temperature. a,p The air supply flow rate for room p, C a For the specific heat capacity of the supply air, θ s For supply air temperature, θ a,f Q represents the temperature of the fresh air (outdoor air). room,p R is the heat load generated by room equipment and people. p Let p be the ambient thermal resistance of the room.

[0082] The result after sorting

[0083]

[0084] The room air volume G can be obtained from the above formula. a,p With indoor temperature θ r,p The transfer function, i.e., u p+3 With y p+3 The transfer function between them.

[0085] For the supply air temperature control loop, the total supply air volume control loop, and the fresh air volume control loop, the mathematical models of the transfer functions between u1 and y1, u2 and y2, and u3 and y3 are obtained using system identification methods. That is, under the condition that other control variables remain constant, the transfer function G of each subsystem is obtained through the step response of the control variables. ij (S).

[0086] Note that due to the coupling between system variables, this model is not an exact model. However, model predictive control can effectively solve the coupling problem between systems. By continuously feeding back and rolling optimization during the control process, each system can make the model gradually approach the real model.

[0087] The continuous transfer function model is converted into a discrete state-space model as shown in equations (3) and (4).

[0088] The discrete state-space model of each subsystem is defined as follows:

[0089] X i (k+1)=A i x i (k)+B i u i (k) (3)

[0090] y i (k)=C i x i (k) (4)

[0091] Where, x i (k) is an n-order matrix representing the system state, ui (k) is n u The y-order matrix represents the input. i (k) is n c The output is represented by an order matrix A. i B i C i Let be the system matrix of the corresponding dimension, and k be the sampling time.

[0092] To eliminate static errors, a state-space model is constructed:

[0093] Δx i (k+1)=A i Δ i x(k)+B i Δ i u(k) (5)

[0094] y i (k)=C i Δx i (k+1)+y i (k-1) (6)

[0095] The cost function is:

[0096]

[0097]

[0098]

[0099]

[0100] Where, N m To determine how many sets of control variables, N, are solved for the time-domain representation of the control. p To predict how many time steps are expected in the future, matrix Q... i and R i Let Q be the weight matrix representing the "penalty" of the controller's control effect. i and R i The larger the value, the slower the output becomes in relation to the reference trajectory and the output error. iref The reference trajectory is represented by the output y. i The control objective of MPC is to drive the output of the closed-loop system to the set desired value. The purpose of equation (7) is to adjust the output of the controlled object to the set value.

[0101] The optimization objective and constraints (i.e., the cost function) are solved in a rolling manner to find the optimal solution ΔU. i * (k).

[0102] The input acting on the controlled system is the first element of the optimal control sequence, which can be written as:

[0103]

[0104] Regarding the event triggering mechanism:

[0105] Define sequence {t i,k |k∈N * Let} be the instantaneous time at which the controller solves the optimization problem during the control process of the i-th system (i=1 is the supply air temperature control system, i=2 is the total supply air volume control system, i=3 is the fresh air volume control system, and i=4 to n+3 are the indoor temperature control systems). The system output at this instant is denoted as}. (i=1 is the supply air temperature, i=2 is the static pressure at the static pressure point, i=3 is the carbon dioxide concentration, and i=4 to n+3 are the indoor temperatures), the subsequent system output y i (k) (i=1 is the supply air temperature, i=2 is the static pressure point, i=3 is the carbon dioxide concentration, i=4 to n+3 are the indoor temperature) and By comparison, the overshoot is defined as the error (e) between the two according to equation (8):

[0106]

[0107]

[0108] The truth or falsehood of an event is evaluated according to the logic described in formula (10).

[0109] Then the next optimization time t i,k+1 This is represented as:

[0110]

[0111] in, This is represented by the moment when the event in formula (10) is false, that is, when the output changes significantly and exceeds the set range, indicating that the control quantity u originally calculated is false. i (i=1 is chilled water flow rate, i=2 is fan speed, i=3 is fresh air volume / return air volume, i=4 to n+3 are room supply air volume) The control requirements are no longer met. At this time, information is exchanged with other systems to perform optimization, and the controller calculates the optimal control sequence ΔU. i * (k), the first element Δu of the sequence i (k) Applied to the system to regulate the control subsystem; t i,k +N pThe moment when the event in formula (8) is true is when the output change is small and within the set range. At this time, the system has become stable and the corresponding control quantity changes little. The controller directly takes the input at the last trigger moment instead of solving the optimization problem again, which reduces the number of times the MPC system optimization problem is solved and reduces the amount of online calculation.

[0112] The control of each subsystem employs asynchronous communication control. During the central air conditioning control process, at time k, when the room temperature setpoint p changes or the room temperature changes due to disturbances, the indoor temperature control system detects the output temperature y. p+3 When the change in (k) satisfies the event triggering condition, the room temperature control system performs optimization problems and performs rolling optimization to find the optimal control variable ΔU. p+3 * (k), its first element Δu p+3 (k) When applied to the room p room temperature control system, if the change does not meet the event triggering conditions, the room p room temperature control system will not perform optimized control, and the controller will directly take the input at the last triggering moment.

[0113] The room temperature control system controls the room temperature by changing the air supply volume of room p. Changes in air supply volume affect the static pressure at the static pressure point. At this time, the AHU's total air supply volume control system interacts with the room terminal VAV to detect changes in the static pressure at the static pressure point y2(k). If the static pressure change does not meet the event triggering condition, the total air supply volume control system does not perform optimization control; the controller directly takes the input from the last triggering moment. When the air supply volume of each room changes to a certain extent, the change in the static pressure at the static pressure point meets the event triggering condition. The total air supply volume control system then solves the optimization problem, performing rolling optimization to find the optimal control variable ΔU2. * (k), and apply its first element Δu2(k) to the total air volume control system.

[0114] When the temperature setpoints of multiple rooms change, the supply air temperature y1(k) will no longer meet the control requirements. At this time, the supply air temperature control system of the AHU interacts with the VAV at the room terminal, calculates a new supply air temperature setpoint, and performs optimization to find the optimal control variable ΔU1. * (k), and apply its first element Δu1(k) to the air supply temperature control system.

[0115] Changes in the room's supply air volume will, to some extent, lead to changes in the room's carbon dioxide concentration y3(k). In the return air duct, if a change in carbon dioxide concentration is detected that meets the trigger condition, the fresh air volume control system will then perform optimization problems, engaging in rolling optimization to find the optimal control variable ΔU3. *(k), its first element Δu3(k) is applied to the air supply temperature control system; if the change in carbon dioxide concentration does not meet the event triggering conditions, the fresh air volume control system does not perform optimized control, and the controller directly takes the input at the last triggering moment.

[0116] The distributed event-triggered control algorithm for variable air volume central air conditioning systems is shown in Table 1 below:

[0117] Table 1

[0118]

[0119]

[0120] Example 2

[0121] The purpose of this embodiment is to provide a distributed event-triggered control system for a variable air volume central air conditioning system, including:

[0122] The system includes a supply air temperature control loop, a total supply air volume control loop, an indoor temperature control loop, and a fresh air volume control loop, each with its own controller.

[0123] The air supply temperature control loop includes an air supply temperature controller, a water valve actuator, a surface cooler, and a temperature sensor.

[0124] The total air volume control loop includes a pressure controller, a variable frequency fan, air ducts, air-conditioned rooms, and a pressure sensor.

[0125] The indoor temperature control loop includes a temperature controller, a damper actuator, air ducts, an air-conditioned room, and a temperature sensor.

[0126] The fresh air volume control loop includes a fresh air volume controller, a return air valve, an air-conditioned room, and a carbon dioxide sensor.

[0127] The controller is configured to: obtain the optimal control variable by solving the objective function based on an event-triggered mechanism, and control the variable air volume central air conditioning system based on the control variable, specifically including:

[0128] Adjusting the room's air supply volume to maintain the indoor temperature;

[0129] After interacting with information from various variable air volume systems, relevant prediction calculations are performed to obtain the supply air temperature setpoint and system static pressure. Accordingly, the chilled water flow rate and fan speed are adjusted to control the supply air temperature and total supply air volume.

[0130] By adjusting the opening of the return air valve in the return air duct, the fresh air volume is controlled to maintain indoor air quality.

[0131] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0132] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A distributed event-triggered control method for a variable air volume central air conditioning system, characterized in that, include: The variable air volume central air conditioning system is decomposed into multiple subsystems; each subsystem includes a supply air temperature control loop, a total supply air volume control loop, a fresh air volume control loop, and an indoor temperature control loop. Establish mathematical models for each subsystem; Discretize the mathematical models of each subsystem and establish a prediction model; The optimal objective function for each subsystem is determined based on the prediction model; The optimal control variable is obtained by determining the trigger time based on the event triggering mechanism and solving the objective function. Based on the optimal control variable, the control of the variable air volume central air conditioning system is completed, specifically including: Adjusting the room's air supply volume to maintain the indoor temperature; After interacting with information from various variable air volume systems, relevant prediction calculations are performed to obtain the supply air temperature setpoint and system static pressure. Accordingly, the chilled water flow rate and fan speed are adjusted to control the supply air temperature and total supply air volume. The amount of fresh air is controlled by adjusting the opening of the fresh air valve in the fresh air duct, so as to maintain indoor air quality. The event triggering mechanism is as follows: Define the sequence of instants in time corresponding to the controller solving the optimization problem during the i-th system control process, and denote the system output at this moment as the first output; The subsequent system output is compared with the first output, and the overshoot is defined as the error between the two. Based on the error, the judgment logic is used to evaluate the truth or falsehood of the event and obtain the representation of the next optimization time. When evaluating the truth or falsehood of an event, the optimal control sequence is calculated at the moment when the event is false, and the first element of the sequence is applied to the system to adjust the control subsystem. When evaluating the truth or falsehood of an event, if the event is true, the input at the last trigger moment is directly used to adjust the control subsystem.

2. The distributed event-triggered control method for a variable air volume central air conditioning system as described in claim 1, characterized in that, The input quantities corresponding to each subsystem are: chilled water flow rate, fan speed, fresh air volume, and room air supply volume; The outputs of each subsystem are: supply air temperature, static pressure at the static pressure point, carbon dioxide concentration, and room temperature.

3. The distributed event-triggered control method for a variable air volume central air conditioning system as described in claim 1, characterized in that, The optimal control variables are obtained by solving the objective function based on an event-triggered mechanism. Specifically: At time k, when the room temperature setpoint changes or the room temperature changes due to disturbance, the indoor temperature control loop detects the change in output temperature. When the change meets the event triggering condition, the room temperature control loop performs optimization problem solving, performs rolling optimization to find the optimal control variable, and applies its first element to the room temperature control loop. When the change does not meet the event triggering condition, the room temperature control loop does not perform optimization control, and the controller directly takes the input at the last triggering time.

4. The distributed event-triggered control method for a variable air volume central air conditioning system as described in claim 1, characterized in that, The optimal control variables are obtained by solving the objective function based on the event-triggered mechanism, and also include: The indoor temperature control loop controls the room temperature by changing the air supply volume of room p. The change in air supply volume will affect the change in static pressure at the static pressure point. At this time, the total air supply volume control system of the central variable frequency air conditioning unit interacts with the variable air volume system at the room terminal to detect the change in static pressure at the static pressure point. If the change in static pressure does not meet the event triggering conditions, the total air supply volume control loop will not perform optimized control, and the controller will directly take the input at the last triggering moment. When the air supply volume of each room changes to a certain extent, the change in static pressure at the static pressure point satisfies the event triggering condition. The total air supply volume control loop then performs optimization to find the optimal control variable through rolling optimization, and applies its first element to the total air supply volume control loop.

5. The method of claim 1, wherein the VAV central air conditioning system distributed event-triggered control method is characterized by, The optimal control variables are obtained by solving the objective function based on the event-triggered mechanism, and also include: When the temperature setpoints of multiple rooms change, the supply air temperature will no longer meet the control requirements. At this time, the supply air temperature control loop of the central variable frequency air conditioning unit interacts with the variable air volume system at the room terminal to calculate and obtain a new supply air temperature setpoint. The supply air temperature control loop then performs optimization problem solving and rolling optimization to find the optimal control variable, and applies its first element to the supply air temperature control loop.

6. The method of claim 1, wherein the VAV central air conditioning system distributed event-triggered control method is characterized by, The optimal control variables are obtained by solving the objective function based on the event-triggered mechanism, and also include: Changes in room supply air volume can lead to changes in room carbon dioxide concentration. In the return air duct, if a change in carbon dioxide concentration is detected that meets the triggering condition, the fresh air volume control loop will perform optimization problem solving, and rolling optimization will be performed to find the optimal control variable. Its first element will be applied to the supply air temperature control loop. If the change in carbon dioxide concentration does not meet the event triggering conditions, the fresh air volume control loop will not perform optimized control, and the controller will directly take the input at the last triggering moment.

7. A distributed event-triggered control system for a variable air volume central air conditioning system, characterized in that, include: The variable air volume central air conditioning system is decomposed into multiple subsystems, including: supply air temperature control loop, total supply air volume control loop, indoor temperature control loop, and fresh air volume control loop, with each control loop having its own controller; Establish mathematical models for each subsystem; Discretize the mathematical models of each subsystem and establish a prediction model; The optimal objective function for each subsystem is determined based on the prediction model; The controller is configured to: determine the triggering time based on an event-triggered mechanism, solve the optimal objective function to obtain the optimal control variable, and complete the control of the variable air volume central air conditioning system based on the optimal control variable, specifically including: Adjusting the room's air supply volume to maintain the indoor temperature; After interacting with information from various variable air volume systems, relevant prediction calculations are performed to obtain the supply air temperature setpoint and system static pressure. Accordingly, the chilled water flow rate and fan speed are adjusted to control the supply air temperature and total supply air volume. The amount of fresh air is controlled by adjusting the opening of the fresh air valve in the fresh air duct, so as to maintain indoor air quality. The event triggering mechanism is as follows: Define the sequence of instants in time corresponding to the controller solving the optimization problem during the i-th system control process, and denote the system output at this moment as the first output; The subsequent system output is compared with the first output, and the overshoot is defined as the error between the two. Based on the error, the judgment logic is used to evaluate the truth or falsehood of the event and obtain the representation of the next optimization time. When evaluating the truth or falsehood of an event, the optimal control sequence is calculated at the moment when the event is false, and the first element of the sequence is applied to the system to adjust the control subsystem. When evaluating the truth or falsehood of an event, if the event is true, the input at the last trigger moment is directly used to adjust the control subsystem.

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