CN114234384B - Air conditioning optimization control method and system for railway passenger station - Google Patents
Air conditioning optimization control method and system for railway passenger station Download PDFInfo
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- CN114234384B CN114234384B CN202111616848.3A CN202111616848A CN114234384B CN 114234384 B CN114234384 B CN 114234384B CN 202111616848 A CN202111616848 A CN 202111616848A CN 114234384 B CN114234384 B CN 114234384B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/54—Control or safety arrangements characterised by user interfaces or communication using one central controller connected to several sub-controllers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/56—Remote control
- F24F11/58—Remote control using Internet communication
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/72—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure
- F24F11/74—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling air flow rate or air velocity
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/72—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure
- F24F11/74—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling air flow rate or air velocity
- F24F11/77—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling air flow rate or air velocity by controlling the speed of ventilators
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/80—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air
- F24F11/83—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air by controlling the supply of heat-exchange fluids to heat-exchangers
- F24F11/84—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air by controlling the supply of heat-exchange fluids to heat-exchangers using valves
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/20—Humidity
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/30—Velocity
- F24F2110/32—Velocity of the outside air
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/50—Air quality properties
- F24F2110/65—Concentration of specific substances or contaminants
- F24F2110/70—Carbon dioxide
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2140/00—Control inputs relating to system states
- F24F2140/20—Heat-exchange fluid temperature
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2140/00—Control inputs relating to system states
- F24F2140/50—Load
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
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Abstract
The application relates to the technical field of air conditioning of railway stations, in particular to an air conditioning optimization control method and system for railway stations, which are implemented by setting characteristic parameters, control targets, optimization targets and constraint conditions of a high-large space air conditioning control system; reading and calculating parameters affecting a control target and control target parameters; estimating future state parameters of the air conditioning system, predicting future output of the system, and carrying out optimization solving calculation on the control quantity according to the control target, the optimization target and the constraint condition; and outputting the obtained optimized control value to an actuator. The scheme provides multi-channel parameter control output, realizes a high-large space air conditioning control algorithm with constraint conditions and optimization strategies, is convenient to access an existing railway passenger station electromechanical equipment monitoring system or an energy management system, realizes coordination and optimization control on a plurality of air treatment units, and achieves better control and energy saving effects.
Description
Technical Field
The application relates to the technical field of air conditioning of railway stations, in particular to an air conditioning optimal control method and system for railway stations.
Background
In the high and large spaces such as a hall, a waiting hall and the like in a railway passenger station, a plurality of air treatment units are arranged for layering and partitioning to air-condition a building space, and because of huge space and complex space constitution, the technical difficulty of controlling the indoor environment is very high due to the large change range of outdoor environment and passenger flow data, and the energy consumption of the air-conditioning systems is huge. Therefore, the problem of optimizing and controlling the air conditioning in a large space in the railway passenger station has huge economic and social benefits, and is a difficulty in the technical research field of the air conditioning control.
The air conditioning control unit is a part or component that is attached to a group of air conditioning spaces, sensors, and air handling units, and that together form an air conditioning control system. The air conditioning control device collects signals of the on-site sensor, takes the signals together with target setting signals as input of the device, and after calculation or judgment of a built-in control strategy, the formed output acts on an adjustable component in an air processing unit or a pipeline, so that compensation quantity can be quickly generated, the influence of state changes such as weather, people flow and equipment on the environment in an air conditioning space is counteracted, the target parameters are ensured to be continuously maintained in a designed or set range, and the requirements of space comfort, manufacturability and energy conservation are met.
The common air conditioning control device mainly comprises a parameter setting unit, an input unit, a control calculation unit and an output unit. When the device is controlled, the control calculation unit controls the compensation amount to be calculated according to the data of the input unit and the parameter setting unit and the control strategy, and the compensation amount acts on the regulating component in the system through the output unit.
The prior high-large space air conditioning system in the railway passenger station generally uses dozens of sets of air treatment units to jointly convey treated air to the space so as to compensate the influence of the state changes of outdoor environment, indoor personnel and equipment on the indoor environment, the prior main stream technology, namely the PLC type and DDC type control strategy, is a PID mode of dozens to hundreds of single-input single-output SISOs, is difficult to cope with the delay and large inertia of a controlled object, is difficult to set PID parameters, cannot consider the influence between closed loops, and causes that an implemented control device and a control system can only operate in a simple control strategy, the control effect is not ideal, and the system energy consumption is high.
Disclosure of Invention
The application provides an air conditioning optimization control method and system for a railway station, which solve the technical problem that the multi-control targets of a multi-processor unit in a high-large-space air conditioning system in the railway station are poor in coordination control effect.
The application provides an air conditioning optimization control method for a railway passenger station, which solves the technical problems and comprises the following steps:
s1, configuring characteristic parameters of a railway station structure and characteristic parameters of a plurality of air handling units, and establishing a state space mathematical model of a controlled object;
s2, detecting and calculating an influence parameter affecting a control target and a control target parameter, and inputting the influence parameter and the control target parameter into the state space mathematical model;
s3, carrying out optimization solution on state estimation of the state space mathematical model, future change trend prediction of the controlled quantity and constraint conditions of the controlled quantity;
and outputting the control quantity obtained by the optimization solution to an actuator of the controlled object so as to compensate the influence of the state changes of the outdoor environment, indoor personnel and indoor equipment on the indoor environment, thereby achieving the purpose of maintaining the target parameters of a plurality of areas within a preset range.
Preferably, the S1 specifically includes: the method comprises the steps of respectively setting geographic position data of a railway station, setting the number of high and large spaces and air conditioning layering and partition areas thereof in the railway station, setting outdoor environment parameters, setting input and output variables of each divided space and a mathematical model parameter of a linearization state space of a rated working point, setting input and output variables of each set of air treatment unit and the mathematical model parameter of the linearization state space of the rated working point, setting input and output connection relation between each divided space and the air treatment unit, and setting control targets and constraint conditions of each divided space.
Preferably, the step S3 specifically includes: and respectively calculating a state observer of each divided space and the corresponding linearization state space model of the air processing unit, outputting prediction calculation and optimizing calculation with constraint conditions.
Preferably, the step S3 specifically includes:
s31, in each control step length time, after the outdoor environment, the adjacent area environment, the local area environment and the local area personnel/lighting/equipment state data are read, performing the state estimation calculation of the step and the output prediction calculation of the future prediction step, and then performing optimization calculation and solving according to the set operation constraint condition and the set cost function to obtain the optimal control output of the control step, and outputting the optimal control output to an on-site executor so as to compensate the change of the indoor environment parameters and achieve the purpose of energy-saving operation;
s32, repeatedly completing the steps in the next control step time, rolling along with time to perform optimal control, and finally realizing the optimal control of the high-large space air conditioning system in the railway passenger station.
Preferably, the step S3 further includes: the geometric and material of the controlled object and the characteristic parameters of the air processing unit are taken as estimation, prediction and optimization calculation models, the multi-channel parameter measurement input is accessed, the multi-channel parameter control output is provided, and the high and large space air conditioning control algorithm with constraint conditions and optimization strategies is realized.
Preferably, the tall space comprises a waiting hall, an inbound hall and a ticketing hall.
Preferably, the S2 specifically includes:
inputting parameters of the air conditioning area and the air treatment unit into the state space mathematical model;
the parameter input of the air conditioning area comprises outdoor environment parameters, air conditioning air supply parameters, indoor environment parameters of adjacent areas and indoor personnel lighting equipment state parameters;
the parameter inputs of the air handling unit comprise fresh air valve opening, return air valve opening, air supply valve opening, return water valve opening, blower frequency converter frequency and cold/hot water supply temperature.
Preferably, the outdoor environment parameters comprise outdoor dry bulb temperature, outdoor relative humidity, outdoor radiation intensity, outdoor wind speed, outdoor carbon dioxide concentration;
the air conditioning air supply parameters comprise air supply dry bulb temperature, air supply relative humidity and air supply quantity;
the indoor environment parameters of the adjacent area comprise indoor dry bulb temperature, indoor relative humidity and indoor carbon dioxide concentration;
the indoor personnel lighting equipment state parameters comprise the number of indoor dynamic personnel, indoor lighting operation power and indoor equipment operation power.
Preferably, the control amount output corresponding to the air conditioning area includes:
zone dry bulb temperature, zone relative humidity, zone carbon dioxide concentration, and zone cooling/heating power;
the control quantity output corresponding to the air treatment unit comprises:
air-dried ball temperature, air supply relative humidity, air supply quantity, fan power, cold/hot water backwater temperature and cold/hot water flow.
The application also provides an air conditioning optimizing control system for the railway passenger station, which comprises the following components:
the model building module is used for configuring characteristic parameters of a railway passenger station structure and characteristic parameters of a plurality of air handling units and building a state space mathematical model of the controlled object;
the parameter input module is used for detecting and calculating an influence parameter influencing a control target and a control target parameter, and inputting the influence parameter and the control target parameter into the state space mathematical model;
the optimization output module is used for carrying out optimization solution on the state estimation of the state space mathematical model, the future change trend prediction of the controlled quantity and the constraint condition of the controlled quantity;
and outputting the control quantity obtained by the optimization solution to an actuator of the controlled object so as to compensate the influence of the state changes of the outdoor environment, indoor personnel and indoor equipment on the indoor environment, thereby achieving the purpose of maintaining the target parameters of a plurality of areas within a preset range.
The beneficial effects are that: the application provides an air conditioning optimization control method and system for railway passenger stations, which are characterized in that characteristic parameters, control targets, optimization targets and constraint conditions of a high-large-space air conditioning control system are set; reading and calculating parameters affecting a control target and control target parameters; estimating future state parameters of the air conditioning system, predicting future output of the system, and carrying out optimization solving calculation on the control quantity according to the control target, the optimization target and the constraint condition; and outputting the obtained optimized control value to an actuator. The scheme provides multi-channel parameter control output, realizes a high-large space air conditioning control algorithm with constraint conditions and optimization strategies, is convenient to access an existing railway passenger station electromechanical equipment monitoring system or an energy management system, realizes coordination and optimization control on a plurality of air treatment units, and achieves better control and energy saving effects.
The foregoing description is only an overview of the present application, and is intended to provide a better understanding of the present application, as it is embodied in the following description, with reference to the preferred embodiments of the present application and the accompanying drawings. Specific embodiments of the present application are given in detail by the following examples and the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a schematic diagram of an air conditioning optimization control method for a railway station provided by the application;
FIG. 2 is a block diagram of a state space mathematical model of the air conditioning optimization control system for a railway station provided by the application;
FIG. 3 is a block diagram of a controller model of the air conditioning optimization control system for a rail passenger station provided by the present application;
FIG. 4 is a block diagram of an air conditioning optimizing control system for a rail passenger station provided by the present application;
fig. 5 is a schematic diagram of the present application for accessing an air conditioning optimizing control system for a railway station to an existing control system.
Detailed Description
The principles and features of the present application are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the application and are not to be construed as limiting the scope of the application. The application is more particularly described by way of example in the following paragraphs with reference to the drawings. Advantages and features of the application will become more apparent from the following description and from the claims. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for convenience and clarity in aiding in the description of embodiments of the application.
It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or intervening elements may also be present. When a component is considered to be "connected" to another component, it can be directly connected to the other component or intervening components may also be present. When an element is referred to as being "disposed on" another element, it can be directly on the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for illustrative purposes only.
Unless defined otherwise, 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 application belongs. The terminology used herein in the description of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
As shown in fig. 1, the present application provides an air conditioning optimizing control method for a railway station, comprising the steps of:
s1, configuring characteristic parameters of a railway station structure and characteristic parameters of a plurality of air handling units, and establishing a state space mathematical model of a controlled object;
s2, detecting and calculating an influence parameter affecting a control target and a control target parameter, and inputting the influence parameter and the control target parameter into the state space mathematical model;
s3, carrying out optimization solution on state estimation of the state space mathematical model, future change trend prediction of the controlled quantity and constraint conditions of the controlled quantity;
and outputting the control quantity obtained by the optimization solution to an actuator of the controlled object so as to compensate the influence of the state changes of the outdoor environment, indoor personnel and indoor equipment on the indoor environment, thereby achieving the purpose of maintaining the target parameters of a plurality of areas within a preset range.
Based on a model predictive control principle, the scheme is characterized in that a state space mathematical model of a controlled object is established, in each control step length time, after the outdoor environment, the adjacent area environment, the local area environment and local area personnel/lighting/equipment state data are read, the state estimation calculation of the step and the output predictive calculation of a future prediction step are carried out, and then the optimal control output of the control step is obtained by carrying out optimization calculation and solving according to a set operation constraint condition and a set cost function and is output to an on-site executor so as to compensate the change of indoor environment parameters, and the aim of energy-saving operation is fulfilled; and repeatedly completing the steps in the next control step time, rolling for optimal control along with time, and finally realizing the optimal control of the high-large space air conditioning system in the railway passenger station.
Specifically, configuring structural feature data of a high space in a railway station and feature data of a plurality of air handling units, namely, a system multiple-input multiple-output MIMO mathematical model obtained by identification, namely, a state space mathematical model; reading indoor and outdoor environment data and air handling unit operation data from a sensor or a transmitter; then, the state estimation of the MIMO mathematical model, the future change trend prediction of the controlled quantity and the optimization solution of the control quantity with constraint conditions are carried out to obtain the optimized and coordinated control quantity so as to compensate the influence of the state change of the outdoor environment, indoor personnel and indoor equipment on the indoor environment; finally, the output module outputs the control quantity of the multiple channels to an actuator on the air processing unit or the pipeline so as to achieve the purpose of maintaining the target parameters of the multiple areas in a designed or reasonable and energy-saving range.
As shown in fig. 4 and fig. 5, in order to make the optimization control method of the embodiment of the present application easy to access to an existing air conditioning control system, the embodiment of the present application further provides an air conditioning optimization control system for a railway passenger station, which implements input and output based on a communication network protocol and implements estimation/prediction/optimization calculation based on an industrial server or workstation, including 3 large modules:
the control object characteristic parameter setting module is a model building module; a parameter input module; and the optimizing output module is used for carrying out state estimation, output prediction, constraint and optimizing control calculation and outputting final control parameters.
The parameter setting module is used for setting characteristic parameters, control targets, optimization targets and constraint conditions of the high and large space air conditioning system; the input parameter detection module is used for detecting and calculating parameters affecting a control target and control target parameters; the calculation module predicts future state parameter estimation of the air conditioning system according to the detection values of the characteristic parameters and the input parameters of the control object, predicts future output of the system, and carries out optimization solving calculation on the control output value according to the control target, the optimization target and the constraint condition; and the optimization output module outputs the obtained optimization control value to the actuator. The application discloses a method and a device for optimizing and controlling high and large space air conditioning in a railway station, which adopt an industrial server as an edge computing carrier, take geometric and material of the high and large space and characteristic parameters of an air processing unit as estimation, prediction and optimizing computing models, connect the device into multi-channel parameter measurement input and provide multi-channel parameter control output, realize a high and large space air conditioning control algorithm with constraint conditions and optimizing strategies, conveniently connect into the existing railway station electromechanical equipment monitoring system or energy management system, implement coordination and optimizing control on a plurality of air processing units, and achieve better control and energy saving effects.
Still further, the parameter setting module includes: the method comprises the steps of setting geographic position data of a railway station, setting the number of high and large spaces and air conditioning layering and partitioning of the railway station, setting outdoor environment parameters, setting input and output variables of each partitioned space and a mathematical model parameter of a linearization state space of a rated working point, setting input and output variables of each set of air treatment unit and the mathematical model parameter of the linearization state space of the rated working point, setting input and output connection relation between each partitioned space and the air treatment unit, and setting control targets and constraint conditions of each partitioned space. In particular, the zoned air conditioning system mathematical model of the present application accounts for the electrical power consumed by the air handling unit blower and the cooling and heating power drawn from the water circuit.
The control optimization calculation module, namely an optimization output module, comprises: a state estimation calculation, output prediction calculation and optimization solution calculation unit; the state estimation calculation unit estimates the state of the air conditioning system of the control step and predicts the state of the air conditioning system of the next control step according to the state estimation in the previous control step and the input and output measurement value of the control step; the output prediction calculation unit predicts the air conditioning system output of a plurality of control steps in the future according to the result of the state estimation calculation unit; and the optimization solving and calculating unit carries out solving and calculating according to the state estimation and the output prediction result and the constraint condition and the optimization target to obtain the decision result of the optimization control.
Still further, the control calculation module, i.e. the optimization control module, includes: and (3) calculating a state observer of each divided space and a corresponding air processing unit linearization state space model, outputting prediction calculation and optimizing calculation with constraint conditions. In particular, the state observer of the air conditioning control system of each subarea space simultaneously accounts for the influence of a plurality of measured parameters, the influence of a plurality of unmeasured parameters is considered as noise, the influence of unmodeled parameters is also considered as noise, meanwhile, the noise of the measured parameters is also considered, and the state estimation of the state observer of the air conditioning control system of the subareas is realized by using a Kalman filtering algorithm. In particular, the energy consumed by regional air conditioning is included in the output prediction calculation, the indoor environment maintenance deviation and the actuator action limit are included in the constraint condition, and the indoor environment maintenance and the energy consumption are included in the optimization calculation cost function.
The input module obtains the states and parameters of outdoor environment, adjacent area environment, indoor environment and indoor personnel/lighting/equipment in the air conditioning system through controlling a communication network system protocol; and the output module sends the air loop valve, the water loop valve and the fan operation parameter command of the air processing unit obtained by the optimization decision to the field executor for execution through a control communication network system protocol.
The parameter setting module is used for setting a linearization state space model, an input channel and an output channel of a control object in the high-large space air conditioning system in the railway passenger station, and constraint conditions and an optimization target cost function in the operation of the air conditioning system.
The input and output modules are connected with parameters of the traditional air conditioning control system and parameters of the energy management system through communication networks by using a plurality of industrial control protocols, advanced protocols such as OPC UA and MQTT industrial Internet of things and the like, so that the control calculation module can realize a complex air conditioning control strategy of a zoned multi-air processing unit for controlling a large space in a railway passenger station based on a model prediction MPC framework.
Furthermore, the air conditioning control method and device of the present application have large calculation capability, and the currently mainstream device forms, i.e. PLC and DDC, cannot meet the requirement of controlling calculation capability, and need to be implemented in a server or workstation form.
The high-large space air conditioning optimization control device in the railway passenger station provided by the embodiment of the application is an industrial server or a workstation entity, and is not limited to a rack type, a guide rail type, a module type, a unit type or other forms.
The setting module is used for configuring a mathematical model, an input and output channel, a control target, a constraint condition and an optimization target of a high-large space air conditioning system in the railway passenger station, the input module is used for reading real-time data of input parameters from the air conditioning control system and the energy management system, the control calculation module is used for realizing state estimation, output prediction and optimization solving calculation with the constraint condition of the air conditioning model prediction control MPC, the output module is used for sending out a control instruction of an optimization solving result, and the control device is used for repeating the steps to realize rolling optimization control of the multi-partition multi-input and output parameter air conditioning control system.
In a specific implementation scenario, as shown in fig. 1, a plurality of sets to dozens of sets of air treatment units are arranged in a high space such as a waiting hall, an entering hall, a ticketing hall and the like in a railway passenger station to perform air conditioning on the space, and the cold and hot water provided by a cold source is used for heating/cooling, dehumidifying and the like on the space return air and fresh air, so that the temperature, the humidity and the carbon dioxide content of the space meet the design requirements; the traditional control method is that a plurality of closed-loop control loops to dozens of closed-loop control loops are arranged, the control quantity is calculated through a deviation PID control strategy, so that the air valve and the water valve generate corresponding actions, the influence caused by the outdoor environment and the indoor personnel/lighting/equipment state is resisted, and the indoor environment parameters are kept to meet the design requirement; because of the complexity of the building space and the nonlinearity of the cold and hot coils of the air treatment unit, the controlled object has large delay and inertia, so that the parameter setting of a plurality of PID control strategies is difficult, the indoor environment control effect is poor, the energy consumption is large, and most of the closed loop control circuits configured on site are in a state of poor running; the application provides an optimal control method and device based on model predictive control aiming at the defects of the existing control method and device, namely a parameter configuration module, an input module, a control calculation module and an output module are arranged in an industrial server or a workstation, the model predictive controllers with the same number as that of air processing units are realized, the model predictive controllers perform state estimation, output prediction and rolling optimal control calculation with constraint target cost function optimization on an air conditioning system of the area according to outdoor environment parameters, indoor environment parameters of adjacent areas, indoor environment parameters of the area and dynamic number of indoor personnel/lighting operation power/equipment operation control of the area, the control output of the current control step is obtained, and finally the actions of an on-site executor are controlled through the output module, so that the optimal control aim of the multi-input multi-output constraint condition of a multi-air conditioning object is realized.
As shown in fig. 2, the objects in the air conditioning control system of the high-rise space in the railway station are air conditioning areas divided by the heating and ventilation profession and configured air treatment units; the model inputs for the individual air conditioning zones are: outdoor weather environmental parameter (t) a,o Outdoor dry bulb temperature, rh o Outdoor relative humidity, i o Intensity of outdoor radiation, ws a,o Outdoor wind speed and c co2,o Outdoor carbon dioxide concentration) and air conditioning air supply parameter (t) a,s,zn Air supply dry bulb temperature, rh s,zn Supply air relative humidity and f a,s,zn Air volume), adjacent area indoor environment parameters (t) a,zi Indoor dry bulb temperature, rh zi Indoor relative humidity and c co2,zi Indoor carbon dioxide concentration) and indoor personal lighting status parameter (c) p,zn Number of indoor dynamic personnel, p l,zn Indoor lighting operating power and p d,zn Indoor equipment operating power), the output is: t is t a,zn Regional dry bulb temperature, rh zn Relative humidity of area c co2,zn Regional carbon dioxide concentration and p c,zn Zone cooling/heating power; the model input of the single air handling unit is as follows: z a,f,zn Fresh air valveDoor opening, z a,r,zn Opening degree, z of return air application a,s,zn Opening degree, z of air supply valve w,r,zn Opening degree, w of backwater valve fan,zn Blower frequency converter frequency t w,s,zn Cold/hot water supply temperature; the output is: t is t a,s,zn Air supply dry bulb temperature, rh s,zn Supply air relative humidity and f a,s,zn Air supply quantity, p f,zn Fan power, t w,r,zn Cold/hot water return temperature f w,zn Cold/hot water flow; the models of the air conditioning area and the air handling unit are obtained by a black box or ash box identification method of theoretical law deduction or simulation or experimental data according to the actual conditions of a high space in a railway passenger station; the models are all linear state space models of the design working conditions.
Fig. 3 is a controller internal structure of a single air conditioning area, and the feedback input amount y includes: t is t a,zn Regional dry bulb temperature, rh zn Relative humidity of region and c co2,zn Regional carbon dioxide concentration; the disturbance variable input v comprises: t is t a,o Outdoor dry bulb temperature, rh o Outdoor relative humidity, i o Intensity of outdoor radiation, ws a,o Outdoor wind speed, c co2,o Outdoor carbon dioxide concentration, t a,zi Indoor dry bulb temperature, rh in adjacent areas zi Indoor relative humidity in adjacent area, c co2,zi Concentration of carbon dioxide, c, in the vicinity of the room p,zn Number of indoor dynamic personnel, p l,zn Indoor lighting operating power, p d,zn Indoor equipment operation power sum t w,s,zn Cold/hot water supply temperature; the noise amount includes: feedback measurement noise n and interference measurement noise w i And model noise w o The method comprises the steps of carrying out a first treatment on the surface of the The optimization control u includes: z a,f,zn Opening degree, z of fresh air valve a,r,zn Opening degree, z of return air application a,s,zn Opening degree, z of air supply valve w,r,zn Backwater valve opening degree and w fan,zn Blower inverter frequency.
The beneficial effects are that:
(1) Coordinated control of the air conditioning system of the high and large space subareas, and mutual influence of all areas is considered;
(2) The air conditioning multi-input multi-output control system of each zone overcomes the defects of difficult adjustment and poor control effect of the single-input single-output control system;
(3) A mathematical model is built, and the defects of difficult regulation and poor control effect of a model-free control system are overcome;
(4) The Kalman filtering algorithm is utilized to consider unmeasured input, unmeasured factors and factors of measured noise, so that the control effect is improved;
(5) The control effect and the energy consumption are improved by using a quadratic programming optimization algorithm with constraint conditions;
(6) And a plurality of industrial server or workstation forms are adopted to support a plurality of communication protocols, so that the existing air conditioning control system and energy management system can be conveniently accessed or inserted.
The above description is only of the preferred embodiments of the present application, and is not intended to limit the present application in any way; those skilled in the art will readily appreciate that the present application may be implemented as shown in the drawings and described above; however, those skilled in the art will appreciate that many modifications, adaptations, and variations of the present application are possible in light of the above teachings without departing from the scope of the application; meanwhile, any equivalent changes, modifications and evolution of the above embodiments according to the essential technology of the present application still fall within the scope of the present application.
Claims (3)
1. An air conditioning optimizing control method for a railway station, characterized by comprising the steps of:
s1, configuring characteristic parameters of a railway station structure and characteristic parameters of a plurality of air handling units, and establishing a state space mathematical model of a controlled object; the method comprises the steps of respectively setting geographic position data of a railway station, setting the number of high and large spaces and air conditioning layering and partition areas thereof in the railway station, setting outdoor environment parameters, setting input and output variables of each divided space and a mathematical model parameter of a linearization state space of a rated working point, setting input and output variables of each set of air treatment unit and the mathematical model parameter of the linearization state space of the rated working point, setting input and output connection relation between each divided space and the air treatment unit, and setting control targets and constraint conditions of each divided space; the high and large space comprises a waiting hall, an inbound hall and a ticket vending hall;
s2, detecting and calculating an influence parameter affecting a control target and a control target parameter, and inputting the influence parameter and the control target parameter into the state space mathematical model;
specifically, parameters of the air conditioning area and the air handling unit are input to the state space mathematical model;
the parameter input of the air conditioning area comprises outdoor environment parameters, air conditioning air supply parameters, indoor environment parameters of adjacent areas and indoor personnel lighting equipment state parameters;
the parameter inputs of the air handling unit comprise fresh air valve opening, return air valve opening, air supply valve opening, return water valve opening, blower frequency converter frequency and cold/hot water supply temperature;
s3, carrying out optimization solution on state estimation of the state space mathematical model, future change trend prediction of the controlled quantity and constraint conditions of the controlled quantity; specifically, S31, after reading the status data of the outdoor environment, the adjacent area environment, the local area environment, and the personnel/lighting/equipment in the local area in each control step time, performing the status estimation calculation in the local step and the output prediction calculation in the future prediction step, and performing optimization calculation and solution according to the set operation constraint condition and the set cost function to obtain the optimal control output of the control step, and outputting the optimal control output to the field executor to compensate the change of the indoor environment parameters, thereby achieving the purpose of energy-saving operation;
s32, repeatedly completing the steps in the next control step time, rolling along with time to perform optimal control, and finally realizing the optimal control of the high-large space air conditioning system in the railway passenger station;
outputting the control quantity obtained by the optimization solution to an actuator of the controlled object so as to compensate the influence of the state changes of the outdoor environment, indoor personnel and indoor equipment on the indoor environment, thereby achieving the purpose of maintaining the target parameters of a plurality of areas within a preset range;
wherein the control amount output corresponding to the air conditioning area includes:
zone dry bulb temperature, zone relative humidity, zone carbon dioxide concentration, and zone cooling/heating power;
the control quantity output corresponding to the air treatment unit comprises:
air-dried ball temperature, air supply relative humidity, air supply quantity, fan power, cold/hot water backwater temperature and cold/hot water flow;
the step S3 further includes: the geometric and material of the controlled object and the characteristic parameters of the air processing unit are taken as estimation, prediction and optimization calculation models, the multi-channel parameter measurement input is accessed, the multi-channel parameter control output is provided, and the high and large space air conditioning control algorithm with constraint conditions and optimization strategies is realized.
2. The optimal control method for air conditioning of a railway station according to claim 1, wherein the outdoor environmental parameters include outdoor dry bulb temperature, outdoor relative humidity, outdoor radiation intensity, outdoor wind speed, outdoor carbon dioxide concentration;
the air conditioning air supply parameters comprise air supply dry bulb temperature, air supply relative humidity and air supply quantity;
the indoor environment parameters of the adjacent area comprise indoor dry bulb temperature, indoor relative humidity and indoor carbon dioxide concentration;
the indoor personnel lighting equipment state parameters comprise the number of indoor dynamic personnel, indoor lighting operation power and indoor equipment operation power.
3. An air conditioning optimizing control system for a railway station, comprising:
the model building module is used for configuring characteristic parameters of a railway passenger station structure and characteristic parameters of a plurality of air handling units and building a state space mathematical model of the controlled object; the method comprises the steps of respectively setting geographic position data of a railway station, setting the number of high and large spaces and air conditioning layering and partition areas thereof in the railway station, setting outdoor environment parameters, setting input and output variables of each divided space and a mathematical model parameter of a linearization state space of a rated working point, setting input and output variables of each set of air treatment unit and the mathematical model parameter of the linearization state space of the rated working point, setting input and output connection relation between each divided space and the air treatment unit, and setting control targets and constraint conditions of each divided space; the high and large space comprises a waiting hall, an inbound hall and a ticket vending hall;
the parameter input module is used for detecting and calculating an influence parameter influencing a control target and a control target parameter, and inputting the influence parameter and the control target parameter into the state space mathematical model;
specifically, parameters of the air conditioning area and the air handling unit are input to the state space mathematical model;
the parameter input of the air conditioning area comprises outdoor environment parameters, air conditioning air supply parameters, indoor environment parameters of adjacent areas and indoor personnel lighting equipment state parameters;
the parameter inputs of the air handling unit comprise fresh air valve opening, return air valve opening, air supply valve opening, return water valve opening, blower frequency converter frequency and cold/hot water supply temperature;
the optimization output module is used for carrying out optimization solution on the state estimation of the state space mathematical model, the future change trend prediction of the controlled quantity and the constraint condition of the controlled quantity; specifically, S31, after reading the status data of the outdoor environment, the adjacent area environment, the local area environment, and the personnel/lighting/equipment in the local area in each control step time, performing the status estimation calculation in the local step and the output prediction calculation in the future prediction step, and performing optimization calculation and solution according to the set operation constraint condition and the set cost function to obtain the optimal control output of the control step, and outputting the optimal control output to the field executor to compensate the change of the indoor environment parameters, thereby achieving the purpose of energy-saving operation;
s32, repeatedly completing the steps in the next control step time, rolling along with time to perform optimal control, and finally realizing the optimal control of the high-large space air conditioning system in the railway passenger station;
outputting the control quantity obtained by the optimization solution to an actuator of the controlled object so as to compensate the influence of the state changes of the outdoor environment, indoor personnel and indoor equipment on the indoor environment, thereby achieving the purpose of maintaining the target parameters of a plurality of areas within a preset range;
wherein the control amount output corresponding to the air conditioning area includes:
zone dry bulb temperature, zone relative humidity, zone carbon dioxide concentration, and zone cooling/heating power;
the control quantity output corresponding to the air treatment unit comprises:
air-dried ball temperature, air supply relative humidity, air supply quantity, fan power, cold/hot water backwater temperature and cold/hot water flow;
further comprises: the geometric and material of the controlled object and the characteristic parameters of the air processing unit are taken as estimation, prediction and optimization calculation models, the multi-channel parameter measurement input is accessed, the multi-channel parameter control output is provided, and the high and large space air conditioning control algorithm with constraint conditions and optimization strategies is realized.
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