CN117010857A - Operation method of heating and ventilation system and related equipment - Google Patents

Abstract

The specification provides a method for operating a heating and ventilation system and related equipment. The method comprises the following steps: acquiring a plurality of system models which are in one-to-one correspondence with a plurality of operation modes of a heating and ventilation system, wherein the system models are used for predicting the operation condition of the heating and ventilation system in the corresponding operation modes; based on a plurality of system models, predicting the operation condition of the heating and ventilation system at a plurality of appointed outdoor wet bulb temperatures, and determining a temperature range for adjusting the operation mode of the heating and ventilation system from the plurality of appointed outdoor wet bulb temperatures based on the operation condition; obtaining the outdoor wet bulb temperature of the heating system, and comparing the outdoor wet bulb temperature with the temperature range; determining a target operation mode for the heating and ventilation system from a plurality of operation modes based on the comparison result, and adjusting the operation mode of the heating and ventilation system to the target operation mode; the target operation mode is one of a plurality of operation modes, which enables the heating and ventilation system to meet the refrigeration requirement at the outdoor wet bulb temperature and has the lowest total energy consumption.

Description

Operation method of heating and ventilation system and related equipment

Technical Field

One or more embodiments of the present disclosure relate to the field of hvac systems, and more particularly, to a method for operating an hvac system and related devices.

Background

With the continuous development of data center related technologies, the problem of energy consumption of the data center is increasingly prominent. Because of the high demands placed on the operating environment of data centers, heating and ventilation systems of data centers often need to be continuously operated to remove heat from equipment in the data centers in order to maintain relatively constant inter-package temperature and humidity requirements. In this way, the heating and ventilation system can generate a great amount of energy consumption, and even occupies about 20% -40% of the total energy consumption of the data center.

Therefore, energy conservation of the heating and ventilation system plays a vital role in the green development of the data center, and parameter control and operation optimization of the heating and ventilation system based on only manual experience has not met the energy conservation requirements.

Disclosure of Invention

In view of this, one or more embodiments of the present disclosure provide a method of operating a hvac system and associated apparatus.

In a first aspect, the present description provides a method of operating a hvac system, the method comprising:

acquiring a plurality of system models corresponding to a plurality of operation modes of the heating and ventilation system one by one, wherein the system models are used for predicting the operation condition of the heating and ventilation system in the corresponding operation modes; the operating conditions comprise at least one operating parameter of the heating ventilation system in the operating process;

Based on the system models, predicting the operation condition of the heating and ventilation system at a plurality of specified outdoor wet bulb temperatures, and determining a temperature range for adjusting the operation mode of the heating and ventilation system from the plurality of specified outdoor wet bulb temperatures based on the operation condition;

acquiring the outdoor wet bulb temperature of the heating and ventilation system, and comparing the outdoor wet bulb temperature with the temperature range;

determining a target operation mode for the heating and ventilation system from the plurality of operation modes based on a comparison result, and adjusting the operation mode of the heating and ventilation system to the target operation mode; the target operation mode is an operation mode with the lowest total energy consumption, wherein the target operation mode is an operation mode which enables the heating and ventilation system to meet the refrigeration requirement at the outdoor wet bulb temperature in the plurality of operation modes.

In a second aspect, the present specification provides an operating device for a hvac system, the device comprising:

the system model acquisition unit is used for acquiring a plurality of system models which are in one-to-one correspondence with a plurality of operation modes of the heating and ventilation system, and the system models are used for predicting the operation condition of the heating and ventilation system in the corresponding operation modes; the operating conditions comprise at least one operating parameter of the heating ventilation system in the operating process;

A temperature range determining unit, configured to predict an operation condition of the heating and ventilation system at a plurality of specified outdoor wet bulb temperatures based on the plurality of system models, and determine a temperature range for performing operation mode adjustment of the heating and ventilation system from the plurality of specified outdoor wet bulb temperatures based on the operation condition;

the comparison unit is used for acquiring the outdoor wet bulb temperature of the heating and ventilation system and comparing the outdoor wet bulb temperature with the temperature range;

an operation mode adjustment unit configured to determine a target operation mode for the heating and ventilation system from the plurality of operation modes based on a comparison result, and adjust the operation mode of the heating and ventilation system to the target operation mode; the target operation mode is an operation mode with the lowest total energy consumption, wherein the target operation mode is an operation mode which enables the heating and ventilation system to meet the refrigeration requirement at the outdoor wet bulb temperature in the plurality of operation modes.

Accordingly, the present specification also provides a computer device comprising a memory and a processor; the memory has stored thereon a computer program executable by the processor; the processor, when executing the computer program, performs the method of operating the hvac system described in the above embodiments.

Accordingly, the present specification also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method of operating a hvac system according to the above embodiments.

In summary, on the premise that the heating and ventilation system includes a plurality of operation modes, the present application may first obtain a plurality of system models for respectively predicting the operation conditions of the heating and ventilation system in the plurality of operation modes. Further, the application can predict the operation condition of the heating and ventilation system at a plurality of specified outdoor wet bulb temperatures based on the plurality of system models, and determine the temperature range which can be used for accurately adjusting the operation mode of the heating and ventilation system from the plurality of outdoor wet bulb temperatures based on the predicted operation condition. Subsequently, the present outdoor wet bulb temperature of the heating and ventilation system can be directly compared with the temperature range, and based on the comparison result, a target operation mode which enables the heating and ventilation system to meet the refrigeration requirement corresponding to the present outdoor wet bulb temperature and has the lowest total energy consumption is determined in a plurality of operation modes, and the operation mode of the heating and ventilation system is timely adjusted to the target operation mode, so that energy conservation of the heating and ventilation system is effectively and rapidly realized, and the environment-friendly development of a data center is facilitated.

Drawings

FIG. 1 is a schematic diagram of a system architecture provided by an exemplary embodiment;

FIG. 2 is a flow chart of a method of operating a heating ventilation system according to an exemplary embodiment;

FIG. 3a is a schematic diagram of a system model corresponding to a free cooling mode according to an exemplary embodiment;

FIG. 3b is a schematic diagram of a system model corresponding to a pre-cooling mode according to an exemplary embodiment;

FIG. 3c is a schematic diagram of a system model corresponding to a mechanical cooling mode according to an exemplary embodiment;

FIG. 4a is a schematic diagram of a keypoint corresponding to a free cooling mode provided by an exemplary embodiment;

FIG. 4b is a schematic diagram of a keypoint corresponding to a pre-cooling mode provided by an exemplary embodiment;

FIG. 4c is a schematic diagram of a key point location corresponding to a mechanical cooling mode according to an exemplary embodiment;

FIG. 5 is a schematic diagram of an operating device of a heating and ventilation system according to an exemplary embodiment;

fig. 6 is a schematic diagram of a server according to an exemplary embodiment.

Detailed Description

Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with one or more embodiments of the present specification. Rather, they are merely examples of apparatus and methods consistent with aspects of one or more embodiments of the present description as detailed in the accompanying claims.

It should be noted that: in other embodiments, the steps of the corresponding method are not necessarily performed in the order shown and described in this specification. In some other embodiments, the method may include more or fewer steps than described in this specification. Furthermore, individual steps described in this specification, in other embodiments, may be described as being split into multiple steps; while various steps described in this specification may be combined into a single step in other embodiments.

The user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or fully authorized by each party, and the collection, use and processing of related data is required to comply with the relevant laws and regulations and standards of the relevant country and region, and is provided with corresponding operation entries for the user to select authorization or rejection.

First, some terms in the present specification are explained for the convenience of understanding by those skilled in the art.

(1) Data centers (Data centers) are globally coordinated equipment-specific networks used to transfer, accelerate, display, calculate, store Data information over the internet (internet) network infrastructure. The main constitution of the data center comprises: machine room, power supply and distribution system, heating and ventilation system, network equipment, server equipment, storage equipment and the like.

(2) The heating and ventilation system is a system for providing a temperature regulation function and comprises a cooling pump, a cooling tower, a chiller, a plate heat exchanger, a primary pump, a secondary pump, a precise air conditioner and other equipment.

(3) And (3) a cooling pump: a water pump for powering the cooling water circulation.

(4) And (3) a cooling tower: and the device is used for realizing heat exchange between cooling water and air through rotation of the fan and discharging heat of a cooling water system into the atmosphere in an evaporative heat-dissipating mode.

(5) A water chiller (abbreviated as chiller): and a device for supplying chilled water satisfying the cooling capacity requirement of the precision air conditioner through a vapor compression refrigeration cycle and transferring heat of the chilled side to the cooling side through a compressed refrigerant. The water chilling unit can be generally divided into an air-cooled water chilling unit and a water-cooled water chilling unit, and the water chilling unit refers to the water-cooled water chilling unit in the application.

(6) Plate heat exchanger (abbreviated plate exchanger): the heat of the chilled water system side is transferred to the physical heat exchange equipment of the cooling water system side through heat exchange, and the device does not consume electric power, namely, is a non-power consumption equipment.

(7) Primary pump: a water pump for powering the chilled water cycle.

(8) And (3) a secondary pump: a relay primary pump, a water pump for providing power for circulation between the chilled water system and the tail end precise air conditioner.

(9) Precision air conditioner: chilled water is used as a heat exchange medium, and heat exchange between the chilled water and air is realized through rotation of an inner fan, so that the temperature of a package is ensured.

(10) Free cooling mode: the cold machine is not used, and the heat exchange operation mode is realized only by the plate heat exchanger.

(11) Precooling mode: and simultaneously, the running mode of heat exchange is realized by using the cooler and the plate heat exchanger.

(12) Mechanical cooling mode: the cold machine is used to realize the operation mode of heat exchange.

As described above, due to the high requirements of the data center on the working environment, the heating and ventilation system of the data center often needs to continuously run to maintain relatively constant temperature and humidity between the packages, so as to avoid the equipment from being failed due to over-high temperature. As such, the hvac system will generate a lot of energy consumption. For the green development of data centers, energy conservation of heating and ventilation systems is particularly important.

In order to reduce the energy consumption of the heating and ventilation system on the premise of ensuring the stable operation of the data center, a manual experience regulation mode is often adopted in the conventional scheme, and a relatively energy-saving operation mode is manually searched through a successive frequency modulation mode or a mode of referencing historical operation points, but the manual regulation mode often has the problems of high time cost and strong expert dependence, and the maximum energy saving cannot be realized.

In an illustrated embodiment, with the improvement of the data acquisition capability, a great amount of acquired data (including, for example, wet bulb temperature, load, and internal setting parameters of the heating ventilation system, including, for example, fan frequency, cooling pump frequency, etc.) related to the heating ventilation system can be taken as input amounts of a neural network model, and packed and input into the neural network model for training, so that the neural network model can finally predict energy consumption or power use efficiency (Power Usage Effectiveness, PUE) of the heating ventilation system, and the heating ventilation system can be parameter-tuned based on the prediction result of the neural network model to reduce energy consumption.

Although the neural network model has higher precision, the neural network model has extremely strong dependence on data and extremely high requirements on data quality, and moreover, due to the deficiency of input data and even the lack of a large amount of data space, the neural network model cannot ensure that stable and reasonable prediction results can be always output, so that tuning advice distortion in partial scenes is extremely easy to cause, and the energy-saving effect of a heating ventilation system is seriously affected. Further, neural network models belong to black box models, which are poorly interpretable, with significant resistance to floor deployment.

Based on the above, the specification provides a technical scheme, based on the outdoor wet bulb temperature of the heating and ventilation system, the operation mode of the heating and ventilation system is adjusted to the most energy-saving operation mode under the current outdoor wet bulb temperature in real time, so that the energy consumption generated by the heating and ventilation system is reduced rapidly, conveniently and furthest.

When the method is realized, a plurality of system models corresponding to a plurality of operation modes of the heating and ventilation system one by one can be acquired first, and each system model can be used for predicting the operation condition of the heating and ventilation system in the corresponding operation mode. Then, based on the plurality of system models, the operation condition of the heating and ventilation system at a plurality of specified outdoor wet bulb temperatures is predicted, and a temperature range for performing operation mode adjustment of the heating and ventilation system is determined from the plurality of specified outdoor wet bulb temperatures based on the operation condition. Further, the application can obtain the outdoor wet bulb temperature of the heating and ventilation system and compare the outdoor wet bulb temperature with the temperature range. Finally, the application can determine a proper target operation mode for the heating ventilation system from a plurality of operation modes based on the comparison result, and adjust the operation mode of the heating ventilation system to the target operation mode. The target operation mode may be one of the above operation modes, in which the heating and ventilation system can meet the refrigeration requirement at the current outdoor wet bulb temperature, and the total energy consumption is the lowest.

In the above technical solution, on the premise that the heating and ventilation system includes a plurality of operation modes, the present application may first obtain a plurality of system models for respectively predicting the operation conditions of the heating and ventilation system in the plurality of operation modes. Further, the application can predict the operation condition of the heating and ventilation system at a plurality of specified outdoor wet bulb temperatures based on the plurality of system models, and determine the temperature range which can be used for accurately adjusting the operation mode of the heating and ventilation system from the plurality of outdoor wet bulb temperatures based on the predicted operation condition. Subsequently, the present outdoor wet bulb temperature of the heating and ventilation system can be directly compared with the temperature range, and based on the comparison result, a target operation mode which enables the heating and ventilation system to meet the refrigeration requirement corresponding to the present outdoor wet bulb temperature and has the lowest total energy consumption is determined in a plurality of operation modes, and the operation mode of the heating and ventilation system is timely adjusted to the target operation mode, so that energy conservation of the heating and ventilation system is effectively and rapidly realized, and the environment-friendly development of a data center is facilitated.

Referring to fig. 1, fig. 1 is a schematic diagram of a system architecture according to an exemplary embodiment. One or more embodiments provided herein may be embodied in the system architecture shown in fig. 1 or a similar system architecture. As shown in fig. 1, the system may include a computer device 100 and a heating ventilation system 200. As shown in fig. 1, a plurality of interconnected heating and ventilation devices such as a cooling pump, a cooling tower, a chiller, a plate heat exchanger, a primary pump, a secondary pump, a precision air conditioner, and the like may be included in the heating and ventilation system 200.

In an illustrated embodiment, computer device 100 may interface with a hvac system 200 for controlling the operation of hvac system 200. For example, the computer device 100 may serve as a control center of the hvac system, and may display the operation parameters of the respective hvac devices in the hvac system 200 to the user, and further, the computer device 100 may be further configured to control the operation parameters of the respective hvac devices in the hvac system 200, such as controlling the fan speed of the cooling tower, the frequency of the cooling pump, the frequencies of the primary pump and the secondary pump, and so on, which are not specifically limited in this specification.

In one illustrated embodiment, the hvac system 200 may include multiple modes of operation. By way of example, the modes of operation of the hvac system 200 may include a free-air cooling mode, a precooling mode, and a mechanical cooling mode.

The free cooling mode refers to an operation mode in which heat exchange (i.e., cooling) is achieved only by means of the plate heat exchanger in the heating and ventilation system 200 without using a chiller. In the free cooling mode, the hvac equipment operating within hvac system 200 may include: cooling pump, cooling tower, plate heat exchanger, primary pump, secondary pump and accurate air conditioner.

The precooling mode refers to an operation mode for realizing heat exchange by using the cooler and the plate heat exchanger at the same time. In the pre-cooling mode, the heating and ventilation devices operating within heating and ventilation system 200 may include: cooling pump, cooling tower, cooler, plate heat exchanger, primary pump, secondary pump and accurate air conditioner.

The mechanical refrigeration mode refers to an operation mode in which heat exchange is realized by using a chiller. In the mechanical cooling mode, the hvac equipment operating within hvac system 200 may include: cooling pump, cooling tower, cooler, primary pump, secondary pump and precision air conditioner.

In an illustrated embodiment, the computer device 100 may adjust the operation mode of the hvac system 200 in real time based on the current outdoor wet bulb temperature, so that the hvac system 200 reduces energy consumption as much as possible while meeting the refrigeration requirement corresponding to the current outdoor wet bulb temperature.

In an illustrated embodiment, computer device 100 may first determine a temperature range for operating mode adjustment of hvac system 200. Then, the computer device 100 may compare the current outdoor wet bulb temperature with the above temperature range, determine a more suitable target operation mode from a plurality of operation modes of the heating ventilation system 200 based on the comparison result, and adjust the operation mode of the heating ventilation system 200 to the target operation mode. It will be appreciated that the target operating mode may be one of a plurality of operating modes that results in the hvac system 200 meeting the refrigeration demand at the current outdoor wet bulb temperature with the lowest overall energy consumption.

It should be noted that, the specific implementation of the computer device 100 for determining the temperature range is not particularly limited in the present application.

In an illustrated embodiment, the computer device 100 may determine the temperature range based on historical operating conditions of the hvac system 200, including, for example, historical energy consumption data and historical cooling effects of the hvac system 200.

In one illustrated embodiment, the computer device 100 may also first obtain a plurality of system models that correspond one-to-one to a plurality of modes of operation of the hvac system 200. The system model may be used to predict an operating condition of the hvac system 200 in a corresponding operating mode, which may include, for example, at least one operating parameter of the hvac system 200 during operation, such as energy consumption due to operation, and a chilled side water supply temperature. For example, the plurality of system models may include a first system model corresponding to a free cooling mode, a second system model corresponding to a pre-cooling mode, and a third system model corresponding to a mechanical cooling mode.

In an embodiment, each of the system models may be a coupling model obtained by performing model coupling processing on device models of a corresponding plurality of heating and ventilation devices. Wherein the device model of the hvac device may be used to predict the operating parameters of the hvac device. By way of example, a cooling pump model may be used to predict cooling pump frequency, power consumption, etc.; the chiller model can be used for predicting chiller refrigeration side backwater temperature, chiller power consumption and the like; the plate heat exchanger model may be used to predict the plate heat exchanger chilled side water supply temperature, etc., which is not particularly limited in this specification.

For example, taking the first system model corresponding to the free cooling mode as an example, since the heating and ventilation device operating in the free cooling mode includes a cooling pump, a cooling tower, a plate heat exchanger, a primary pump, a secondary pump, and a precise air conditioner, the computer device 100 may first obtain a cooling pump model, a cooling tower model, a plate heat exchanger model, a primary pump model, a secondary pump model, and a precise air conditioner model trained in advance, and perform model coupling processing on the plurality of device models based on a connection structure and an operational logic relationship between the plurality of heating and ventilation devices, etc., to obtain the first system model corresponding to the free cooling mode, etc., which will not be described in detail herein, and specific reference may be made to the description of the embodiments below.

Taking a second system model corresponding to the pre-cooling mode as an example, the heating ventilation device working in the pre-cooling mode includes: since the cooling pump, cooling tower, chiller, plate heat exchanger, primary pump, secondary pump, and precise air conditioner are previously obtained, the computer device 100 may obtain a pre-trained cooling pump model, cooling tower model, chiller model, plate heat exchanger model, primary pump model, secondary pump model, and precise air conditioner model, and perform model coupling processing on the plurality of device models based on the connection structure and the operation logic relationship between the plurality of heating and ventilation devices, etc., to obtain a second system model corresponding to the pre-cooling mode, etc., which will not be described in detail herein, and specific reference will be made to the following embodiments.

Taking a third system model corresponding to the mechanical refrigeration mode as an example, the heating ventilation device working in the mechanical refrigeration mode comprises: the cooling pump, cooling tower, chiller, primary pump, secondary pump, and precise air conditioner may be obtained by the computer device 100, and the model coupling process may be performed on the plurality of device models based on the connection structure and the operation logic relationship between the plurality of heating and ventilation devices to obtain a third system model corresponding to the mechanical cooling mode, and so on, which will not be described in detail herein, and specific reference may be made to the description of the following embodiments.

Further, in an illustrated embodiment, the computer device 100 may predict an operation condition (e.g., including a total energy consumption of the heating ventilation system 200, a chilled water supply temperature, etc.) of the heating ventilation system 200 at a plurality of specified outdoor wet bulb temperatures (e.g., 10 ℃, 12 ℃, 13 ℃, 14 ℃, 15 ℃, 20 ℃, 25 ℃, 35 ℃, etc.) based on the first system model, the second system model, and the third system model, and determine a temperature range for performing an operation mode adjustment of the heating ventilation system 200 from the plurality of specified outdoor wet bulb temperatures based on the predicted operation condition.

In an exemplary embodiment, the temperature range may be a temperature range that is formed by a first threshold value and a second threshold value that is greater than the first threshold value.

For example, if the outdoor wet bulb temperature of the heating and ventilation system 200 is less than or equal to the first threshold, the computer device 100 may determine a free cooling mode among the plurality of operation modes as the above-described target operation mode and adjust the operation mode of the heating and ventilation system 200 to the free cooling mode.

For example, if the outdoor wet bulb temperature of the hvac system 200 is greater than the first threshold value and less than or equal to the second threshold value, the computer device 100 may determine a pre-cooling mode of the plurality of operation modes as the target operation mode and adjust the operation mode of the hvac system 200 to the pre-cooling mode.

For example, if the outdoor wet bulb temperature of the hvac system 200 is greater than the second threshold, the computer device 100 may determine a mechanical cooling mode of the plurality of operation modes as the target operation mode and adjust the operation mode of the hvac system 200 to the mechanical cooling mode.

Illustratively, the first threshold is 15 ℃ and the second threshold is 25 ℃. In summer, the outdoor temperature is high, and accordingly, the outdoor wet bulb temperature is generally higher than 25 ℃, and the heating and ventilation system 200 can be operated in the mechanical cooling mode. In autumn, the outdoor temperature gradually decreases, and once the outdoor wet bulb temperature is detected to be lower than 25 ℃, the computer equipment 100 can timely adjust the operation mode of the heating and ventilation system 200 from a mechanical refrigeration mode to a precooling mode, so that the refrigeration requirement at the current temperature is met, and the energy consumption can be reduced. Further, when the outdoor temperature is further reduced from autumn to winter, once the outdoor wet bulb temperature is detected to be lower than 15 ℃, the computer equipment 100 can timely adjust the operation mode of the heating and ventilation system 200 from the precooling mode to the free refrigeration mode, namely, only the plate heat exchanger is used for refrigeration, so that the energy consumption of the heating and ventilation system is greatly reduced. It can be understood that, because the outdoor temperature is extremely low in winter, the outlet water temperature of the cooling tower is also low, and the heat exchange through the plate heat exchanger is enough to meet the refrigeration requirement, so that the energy consumption can be greatly reduced on the premise of meeting the refrigeration requirement.

As described above, the present application obtains a plurality of system models corresponding to a plurality of operation modes by coupling the equipment models of the heating and ventilation equipment operating in the plurality of operation modes, and further determines an accurate and reliable temperature range for adjusting the operation mode of the heating and ventilation system 200 according to the prediction results of the plurality of system models on the operation condition of the heating and ventilation system 200 at a plurality of outdoor wet bulb temperatures, so that the operation mode of the heating and ventilation system 200 can be adjusted to an operation mode with lower total energy consumption under the condition of meeting the refrigeration requirement corresponding to the current wet bulb temperature in time directly according to the comparison between the current outdoor wet bulb temperature and the temperature range, thereby efficiently and rapidly realizing the energy saving of the heating and ventilation system 200 and being beneficial to the green development of a data center.

In an embodiment, the computer device 100 may be a notebook computer, a desktop computer, a server, or the like having the above functions, which is not particularly limited in this specification. Further, in an embodiment, when the computer device 100 is a server, the computer device 100 may be one server, a server cluster formed by a plurality of servers, or the like, which is not specifically limited in this specification.

Referring to fig. 2, fig. 2 is a flow chart illustrating an operation method of a heating ventilation system according to an exemplary embodiment. The method may be applied to the system architecture shown in fig. 1 or a similar system architecture, and in particular, the method may be applied to a computer device 100 in the system architecture shown in fig. 1, which may interface with a hvac system. As shown in fig. 2, the method may specifically include the following steps S101-S104.

Step S101, a plurality of system models corresponding to a plurality of operation modes of the heating and ventilation system one by one are obtained, and the system models are used for predicting the operation condition of the heating and ventilation system in the corresponding operation modes.

In one illustrated embodiment, the present application may be first trained to obtain their respective device models for a plurality of hvac devices contained within an hvac system. Wherein each device model may be used to predict operating parameters of a corresponding hvac device.

In an illustrated embodiment, the present application may first construct a corresponding initial device model for a plurality of hvac devices in an hvac system based on physical characteristics of the plurality of hvac devices. Further, the application can respectively train the plurality of initial equipment models based on the sample data corresponding to the plurality of heating and ventilation equipment so as to obtain a plurality of equipment models corresponding to the plurality of heating and ventilation equipment one by one.

In an illustrated embodiment, the sample data may include historical operating data of the hvac device during operation.

By way of example, taking a chiller as an example, sample data of the chiller may include various data such as power consumption, cooling water flow, chilled water flow, cooling tower water outlet temperature, and chiller side water temperature of the chillers of different brands and various models in the running process, which is not particularly limited in this specification.

By way of example, taking a plate heat exchanger as an example, sample data of the plate heat exchanger can include various data such as cooling water flow, cooling tower water outlet temperature, heat exchange temperature difference of the plate heat exchanger and the like of different brands and various types of plate heat exchangers in the running process, and the specification is not limited in particular.

In an embodiment, the sample data may further include test data of the hvac device, such as operation parameters of the hvac device under different operation conditions tested by different manufacturers in a laboratory environment, and the like, which is not specifically limited in this specification.

By way of example, the process of building a device model for each heating and ventilation device will be described in detail below in connection with the physical characteristics of each heating and ventilation device.

(1) Cold machine model

In one illustrated embodiment, the present application can obtain the cold energy N1 and the saturated evaporating temperature t according to a classical formula of calculation of the refrigeration coefficient (Coefficient Of Performance, COP) ₀ Saturation condensing temperature t _k And the relation of the load factor PLR. Further, the saturated evaporation temperature t0 and the saturated coolingCoagulation temperature t _k The two parameters related to the refrigerant in the cold machine can be converted into directly controllable operation parameters of the cold machine according to thermodynamic theorem, such as cooling water flow, freezing water flow, cooling water temperature, freezing water temperature and the like, so as to obtain a function (1) related to the energy N1 of the cold machine.

N1＝f(Q ₀ ，t _e2 ，M _e ，t _w1 ，M _w ) (1)

Wherein N1 is the energy of the cold machine, Q ₀ Is rated refrigerating capacity of the refrigerator, t _e2 For freezing side backwater temperature M _e For chilled water flow (i.e. primary pump chilled water flow), t _w1 For cooling tower water outlet temperature, M _w Is the cooling water flow. Further, the load factor plr=q/Q ₀ Wherein Q is the refrigerating capacity required currently.

Further, in an illustrated embodiment, the present application may construct an initial equipment model corresponding to the chiller based on the above function (1). Further, the application can train the initial equipment model by taking the historical operation data and the test data of the chillers with different brands and models as sample data to obtain the corresponding chiller model in consideration of different internal processes of the chillers with different brands and models and different heat exchange performances.

It should be understood that the chiller model is a model constructed based on physical characteristics of a chiller, can stably predict various operation parameters of the chiller (e.g., chiller energy consumption, etc.), and has a strong interpretability.

(2) Cooling tower model

The energy consumption N2 of the cooling tower is generally in positive correlation with the power of the cooling tower fan speed f, and a function (2) related to the energy consumption of the cooling tower can be obtained therefrom.

N2＝f(f) (2)

Further, the fan speed f of the cooling tower often determines the outlet water temperature t of the cooling tower _w1 That is to say, the outlet water temperature t of the cooling tower can be obtained by back-pushing according to the rotating speed f of the fan _w1 . Is required toThe outlet water temperature t of the cooling tower _w1 Is a set parameter of the heating and ventilation system, which has an important influence on whether the heat exchange performance of the heating and ventilation system meets the refrigeration requirement, and the lower the outlet water temperature of the cooling tower is, the better the refrigeration performance of the cooling tower is. Therefore, the application further needs to disassemble the cooling tower to influence the outlet water temperature t _w1 Is a parameter of (a). In one illustrated embodiment, the present application may derive the cooling tower outlet water temperature t from an approximation empirical formula _w1 With the water-vapor ratio, the temperature difference of water inlet and outlet of the cooling tower and the outdoor wet bulb temperature, thereby obtaining a function (3) related to the energy efficiency of the cooling tower

t _w1 ＝f(LGR，t _wb ，Δt _w ) (3)

Wherein LGR is the water-vapor ratio of the cooling tower, deltat _w Is the outdoor wet bulb temperature, t _wb Is the temperature difference between the water inlet and the water outlet of the cooling tower. In one illustrated embodiment, the cooling tower has a water to vapor ratioWherein M is _w0 Is rated cooling water flow, f ₀ Is the rated cooling tower fan rotating speed.

Further, in an illustrated embodiment, the present application may construct an initial equipment model corresponding to the cooling tower based on the above-described function (2) and function (3). Further, in consideration of different brands, different types of cooling tower filler performances and different internal processes, the application can train the initial equipment model by taking historical operation data and test data of the cooling towers of different brands and different types as sample data, thereby obtaining a corresponding cooling tower model.

It should be appreciated that the cooling tower model is a model constructed based on the physical characteristics of the cooling tower, which is capable of stably predicting various operating parameters of the cooling tower (such as the cooling tower water outlet temperature and energy consumption, etc.), and has a strong interpretability.

(3) Cooling pump model

The energy consumption N3 of the cooling pump is generally in positive correlation with the power of the cooling pump frequency N, but the setting of the cooling pump frequency N is often also affected by the cooling water demand and the resistance characteristics of the cooling water system pipe network. Different cooling water systems can cause different pipe network impedance S due to the differences of pipe network length, elbow number, water quality change and the like, so that the setting requirements of the cooling pump frequency n can also be different under the same cooling water quantity requirement. Therefore, the application further needs to establish the functional relation between the water pump lift H and the pipe network impedance S and the water demand. When the pipe network is constructed, the pipe side, the pipe health degree and the valve opening degree are unchanged, and the pipe network impedance S is relatively constant, so that a function (4) related to the energy consumption N3 of the cooling pump can be finally obtained.

N3＝f(n，M _w ) (4)

Further, in an illustrated embodiment, the present application may construct an initial equipment model corresponding to the cooling tower based on the above function (4). Further, the application can train the initial equipment model by taking the historical operation data and the test data of the cooling pumps with different brands and different models as sample data to obtain the corresponding cooling pump model in consideration of different processes and different performances of the cooling pumps with different brands and different models.

It should be understood that the cooling pump model is a model constructed based on physical characteristics of the cooling pump, is capable of stably predicting various operation parameters of the cooling pump (for example, energy consumption of the cooling pump, etc.), and has a strong interpretability.

(4) Plate heat exchanger model

It should be noted that the plate heat exchanger is a physical heat exchange device, and no energy consumption is generated. The operation requirement of the plate heat exchanger is that the water outlet temperature t of the freezing side of the plate heat exchanger _e2 ' meet refrigeration requirements, which temperature often determines the heat exchange performance of the plate heat exchanger. The outlet water temperature t at the freezing side of the plate heat exchanger _e2 ' generally depends on the aforementioned cooling tower outlet temperature t _w1 The heat exchange temperature difference delta t of the plate heat exchanger. The heat exchange temperature difference delta t of the plate heat exchanger is further equal to the flow M of the refrigerating water _e And cooling water flow M _w Correlation, therefore, can finallyTo obtain a function (5) related to the performance of the plate heat exchanger.

t _e2 ’＝t _w1 +Δt＝f(t _w1 ，Δt _e-bh ，t _e2 ，M _w ，M _e )(5)

Wherein Δt is _e-bh T is the temperature difference of inlet and outlet of chilled water at the side of the plate heat exchanger _e2 Is the temperature of return water at the freezing side.

Further, in an illustrated embodiment, the present application may construct an initial equipment model corresponding to the plate heat exchanger based on the above function (5). Because the physical properties inside the plate heat exchanger are difficult to accurately solve, and the heat exchange performance of the plate heat exchanger can change along with the time and the difference of maintenance depths, the application can train an initial equipment model by assisting with the historical operation data and the test data of the plate heat exchanger so as to obtain the plate heat exchanger model capable of accurately describing the performance characteristics such as the heat exchange temperature difference of the plate heat exchanger.

(5) Primary pump model

Similar to the cooling pump described above, the primary pump energy consumption N4 is generally directly related to the primary pump frequency N1 to the power of three, but the primary pump frequency N1 is often set to be influenced by the chilled water demand and the chilled water system piping network resistance characteristics, so that a function (6) related to the primary pump energy consumption N4 can be obtained.

N4＝f(n1，M _e ) (6)

Further, in an illustrated embodiment, the present application may construct an initial equipment model corresponding to the primary pump based on the above-described function (6). Further, the application can train the initial equipment model by taking the historical operation data and the test data of the primary pumps with different brands and different models as sample data to obtain the corresponding primary pump model in consideration of different processes and different performances of the primary pumps with different brands and different models.

It should be understood that the primary pump model is a model constructed based on the physical characteristics of the primary pump, can stably predict various operation parameters of the primary pump (for example, the energy consumption of the primary pump, etc.), and has a strong interpretability.

(6) Secondary pump model

Similar to the cooling pump described above, the energy consumption N5 of the secondary pump is generally in positive correlation with the power of the secondary pump frequency N2, but the setting of the secondary pump frequency N2 is also influenced by the secondary side chilled water volume demand and chilled water system piping network resistance characteristics, so that a function (7) related to the secondary pump energy consumption N5 can be obtained.

N5＝f(n2，M _e2 ) (7)

Wherein M is _e2 For the flow of the secondary pump chilled water, the flow M of the chilled water _e Is generally equal to the sum of the flow of the secondary pump chilled water and the flow of the cold storage water.

Further, in an illustrated embodiment, the present application may construct an initial equipment model corresponding to the secondary pump based on the above function (7). Further, the application can train the initial equipment model by taking the historical operation data and the test data of the secondary pumps with different brands and different models as sample data to obtain the corresponding secondary pump model in consideration of different processes and different performances of the secondary pumps with different brands and different models.

It should be understood that the secondary pump model is a model constructed based on the physical characteristics of the secondary pump, and is capable of stably predicting various operation parameters of the secondary pump (for example, energy consumption of the secondary pump, etc.), and has a strong interpretability.

(7) Precision air conditioner model

Note that, the energy consumption N6 of the precision air conditioner often depends on the frequency N' (or the rotational speed) of the precision air conditioner, and the supply air temperature t _s Temperature t of water supply on freezing side _e1 And the water valve opening phi, thereby obtaining a function (8) related to the energy consumption N6 of the precise air conditioner.

N6＝ f(n’，t _s ，t _e1 ，Φ) (8)

Further, in an illustrated embodiment, the present application may construct an initial equipment model corresponding to the precision air conditioner based on the above function (8). Furthermore, the application can train the initial equipment model by taking the historical operation data and the test data of the precise air conditioners with different brands and various models as sample data, thereby obtaining the corresponding precise air conditioner model.

In summary, the building of each equipment model in the application is based on the physical characteristics of the heating ventilation equipment, including analysis of the working principle of each heating ventilation equipment and the influence among various parameters in the operation process, etc., so that the equipment model finally trained by assistance of historical operation data and test data has stronger interpretability and stability, and is beneficial to the subsequent floor deployment of the scheme.

Further, in an illustrated embodiment, after training to obtain device models corresponding to respective hvac devices in the hvac system, the present application may construct a plurality of system models for a plurality of operation modes of the hvac system, respectively.

In an embodiment, the present application may couple the trained device models based on the connection structure and the operation logic relationship between the plurality of heating and ventilation devices, so as to obtain a plurality of system models corresponding to the plurality of operation modes one by one. Wherein each system model may be used to predict an operating condition of the hvac system in a corresponding operating mode, including, for example, predicting a total energy consumption of the hvac system, a cooling effect, etc., wherein the cooling effect may include a chilled side water supply temperature, etc.

The application can carry out model coupling treatment on the plate heat exchanger model in the plurality of equipment models and at least one other equipment model connected with the plate heat exchanger model so as to obtain a first system model corresponding to the free refrigeration mode.

The method and the device can perform model coupling processing on the water chilling unit model and the plate heat exchanger model in the plurality of equipment models and at least one other equipment model connected with the water chilling unit model and the plate heat exchanger model so as to obtain a second system model corresponding to the precooling mode.

The present application may perform model coupling processing on a chiller model of the plurality of device models and at least one other device model connected to the chiller model to obtain a third system model corresponding to the mechanical refrigeration mode.

In an embodiment, the at least one other device model may include a cooling pump model, a cooling tower model, a primary pump model, a secondary pump model, and a precision air conditioning model, or may not include a secondary pump model, and the like, which is not particularly limited in this specification.

Referring to fig. 3a, fig. 3a is a schematic diagram of a system model corresponding to a free cooling mode according to an exemplary embodiment. As shown in fig. 3a, the system model may be a first system model corresponding to a free cooling mode, in which an equipment model corresponding to a plate heat exchanger, a primary pump, a secondary pump, a cooling tower, a precision air conditioner is coupled. In winter, outdoor wet bulb temperature t _wb The temperature of the water discharged from the cooling tower is low, so that the cooling tower can be directly used as a cold source, and the water supply temperature t at the freezing side can be realized only by the heat exchange mode of the plate heat exchanger _e2 ' meet the refrigeration requirements of terminal precision air-conditioning.

Referring to fig. 3b, fig. 3b is a schematic diagram of a system model corresponding to a pre-cooling mode according to an exemplary embodiment. As shown in fig. 3b, the system model may be a second system model corresponding to a precooling mode, in which equipment models corresponding to a chiller, a plate heat exchanger, a primary pump, a secondary pump, a cooling tower, and a precision air conditioner are coupled. During transitional seasons (e.g., spring and autumn), the cooling tower can provide lower outlet water temperature under the same equipment conditions due to lower outdoor wet bulb temperature. As shown in fig. 3b, the outlet water of the cooling tower can exchange heat with the return water temperature at the freezing side through the plate heat exchanger, thereby realizing the cooling of the return water temperature at the freezing side, and then the outlet water is cooled again through the cooler, so as to realize the water supply temperature t at the freezing side _e2 ' meet the refrigeration requirements of terminal precision air-conditioning. As shown in fig. 3b, when the plate heat exchanger and the cooler are used for heat exchange, the plate heat exchanger can reduce the heat exchange burden of the cooler, so that the refrigeration power consumption of the cooler is reduced.

Referring to fig. 3c, fig. 3c is a schematic diagram of a system model corresponding to a mechanical refrigeration mode according to an exemplary embodiment. As shown in fig. 3c, the system model may be a third system model corresponding to a mechanical cooling mode, and equipment models corresponding to a chiller, a primary pump, a secondary pump, a cooling tower, and a precision air conditioner are coupled to the third system model.

As described above, the relationship between the chiller and the chilled water system and the relationship between the chiller and the cooling water system flow rate can be obtained from the function of the chiller energy N1, and the cooling pump model, the primary pump model, and the secondary pump model can be linked. It can be understood that the water supply temperature at the freezing side influences the energy consumption of the cold machine and synchronously influences the opening degree of a water valve of the precise air conditioner, and further, the change of the opening degree of the water valve can cause the change of a characteristic curve of a pipeline network of the frozen water, so that the lift requirements of the primary pump and the secondary pump and the change of the frequency requirement of the water pump are caused. Based on the association analysis, the association closed loop of the refrigeration side multi-equipment model can be realized. On the other hand, the water outlet temperature of the cooling water also influences the energy consumption of the cooling machine, and the water outlet temperature of the cooling water is controlled by the performance of the cooling tower and the cooling water flow, so that the association relation closed loop of the cooling side multi-equipment model can be realized through the association relation.

Referring to FIGS. 3 a-3 c, the outdoor wet bulb temperature t can be known according to the logic diagrams of the system models _wb The external parameters which influence the performance of the heating and ventilation equipment, namely the external parameters which influence the refrigerating effect of the heating and ventilation system, can be used. The control amounts associated with the interior of each heating and ventilation device may include chilled water/cooling water temperature, chilled water/cooling water flow, frequency of each heating and ventilation device, etc. As shown in fig. 3 a-3 c, each system model may calculate the total energy consumption of the hvac system in the corresponding operation mode, and related intermediate variables, which may include, for example, the energy consumption of each hvac device, the chilled water/cooling water temperature, the chilled water/cooling water flow, etc., which are not specifically limited in this specification.

Step S102, based on the system models, predicting the operation condition of the heating and ventilation system at a plurality of designated outdoor wet bulb temperatures, and determining a temperature range for adjusting the operation mode of the heating and ventilation system from the plurality of designated outdoor wet bulb temperatures based on the operation condition.

In an embodiment, after obtaining a plurality of system models corresponding to a plurality of operation modes of the heating and ventilation system one by one, the application can determine the switching point between the operation modes based on the operation conditions of the heating and ventilation system predicted by the plurality of system models under different external parameters, so as to realize timely adjustment of the operation modes of the system when the external parameters are changed, and reduce the energy consumption of the heating and ventilation system as much as possible.

In an illustrated embodiment, the external parameter may be an outdoor wet bulb temperature, and the present application may predict an operating condition (e.g., total energy consumption of the hvac system, chilled side water supply temperature, etc.) of the hvac system at a number of specified outdoor wet bulb temperatures (e.g., 10 ℃, 12 ℃, 13 ℃, 14 ℃, 15 ℃, 20 ℃, 25 ℃, etc.) based on the plurality of system models. Further, the present application may determine a temperature range for operating mode adjustment of the hvac system based on the predicted operating conditions.

In an exemplary embodiment, the temperature range may be a temperature range that is formed by a first threshold value and a second threshold value that is greater than the first threshold value. Illustratively, the temperature may range from 15 ℃ to 25 ℃, or from 12 ℃ to 23 ℃, etc., which is not particularly limited in this specification.

On the one hand, it should be noted that, in the free cooling mode, the heating and ventilation system only exchanges heat through the plate heat exchanger, although the energy consumption is low, the cooling effect is poor, and when the outdoor temperature is raised to a certain extent, the free cooling mode cannot meet the cooling requirement. Based on this, the present application, when determining the above temperature range, needs to determine the highest outdoor wet bulb temperature (i.e., the first threshold) that enables the hvac system to meet the cooling demand in the free cooling mode.

In one embodiment, the application may set the cooling tower frequency to a full frequency such that the cooling tower outputs as low a water outlet temperature as possible, and substitute the full frequency cooling tower frequency into the cooling tower model to find the lowest approximation Tapp. Further, based on the water flow ratio of the two sides of the plate heat exchanger, the heat exchange temperature difference delta t of the plate heat exchanger can be obtained based on a plate heat exchanger model.

In an illustrated embodiment, the present application may set the sum of the approximation Tapp in the first system model and the heat exchanging temperature difference Δt of the plate heat exchanger to a minimum value (i.e., (tapp+Δt) min). Further, under the condition of (tapp+Δt) min, the present application can make the first system model predict the obtained freezing side water supply temperature t _e2 The outdoor wet bulb temperature that' meets the refrigeration demand is determined as the first threshold described above.

Exemplary, under the condition of (tapp+Δt) min, the present application can obtain the predicted refrigeration side water supply temperature t of the heating and ventilation system of the first system model under the above-mentioned several specified outdoor wet bulb temperatures _e2 '. Further, the present application may determine the outdoor wet bulb temperature when the refrigeration side water supply temperature predicted by the first system model is a preset value (for example, 22 ℃ or 23 ℃), as the first threshold.

It can be understood that the first threshold is a switching point for switching the pre-cooling mode to the free cooling mode. When the outdoor wet bulb temperature is less than the first threshold, the free cooling mode is often sufficient to meet the cooling demand.

On the other hand, in the precooling mode, the cooling load is commonly borne by the plate heat exchanger and the chiller, and therefore the energy consumption in the precooling mode is generally lower than that in the mechanical cooling mode. However, in some situations, the energy consumption of the pre-cooling mode may be rather higher than that of the mechanical refrigeration, for example, the energy consumption saved by the chiller is smaller than the energy consumption increased by the cooling tower to increase the cooling tower frequency in order to reach the required approximation, so that the switching point (i.e. the second threshold) between the pre-cooling mode and the mechanical refrigeration mode needs to be obtained.

It can be understood that in the precooling mode, the energy consumption of the cooler is simultaneously subjected to the water outlet temperature t of the refrigerating side of the plate heat exchanger _e2 ' Cooling side Water temperature t of plate Heat exchanger _w2 ' influence. Through plate heat exchanger model and coolingThe tower model can obtain the water temperature of the two sides of the plate heat exchanger under different operation parameters (temperature difference of water supply and return at two sides of the system, water supply temperature at the freezing side, frequency of a cooling tower and the like) under the condition of fixed total load rate, so that the energy consumption of each heating and ventilation device in the heating and ventilation system can be obtained. Further, based on a second system model corresponding to the pre-cooling mode, a total energy consumption of the hvac system at a number of specified outdoor wet bulb temperatures may be obtained.

The solution boundary of the pre-cooling mode needs to make the load ratio borne by the chiller be above the lowest allowable load ratio of the chiller.

Similarly, in the mechanical refrigeration mode, the application can also obtain the total energy consumption of the heating and ventilation system model at a plurality of specified outdoor wet bulb temperatures based on the third system model corresponding to the mechanical refrigeration mode.

Further, the application can compare the total energy consumption of the heating and ventilation system in the mechanical refrigeration mode at a plurality of specified outdoor wet bulb temperatures and the total energy consumption of the heating and ventilation system in the precooling mode at a plurality of specified outdoor wet bulb temperatures on the premise of the same total load rate, and determine the outdoor wet bulb temperature when the total energy consumption in the mechanical refrigeration mode and the total energy consumption in the precooling mode are equal as the second threshold.

It is understood that the second threshold is a switching point between the pre-cooling mode and the mechanical cooling mode. When the outdoor wet bulb temperature is greater than the second threshold, the total energy consumption of the mechanical cooling mode tends to be lower than the total energy consumption of the precooling mode.

In an embodiment, the present application may further calculate a solution with minimum total energy consumption of the hvac system, that is, a minimum value of total energy consumption, based on the second system model and the third system model, respectively, at the above-specified outdoor wet bulb temperatures. Further, the present application may also determine the outdoor wet bulb temperature at which the minimum value of the total energy consumption of the hvac system obtained by the second system model and the third system model is equal as the above-mentioned second threshold value, and the present specification is not limited specifically.

Step S103, obtaining the outdoor wet bulb temperature of the heating and ventilation system, and comparing the outdoor wet bulb temperature with the temperature range.

In one illustrated embodiment, the present application may compare the above temperature ranges of the outdoor wet bulb temperature of the hvac system and subsequently adjust the operating mode of the hvac system based on the comparison.

The method for obtaining the outdoor wet bulb temperature is not particularly limited.

In one illustrated embodiment, the present application may detect the outdoor wet bulb temperature of a hvac system in real time.

In one embodiment, the present application may also periodically detect the outdoor wet bulb temperature of the hvac system at a certain detection frequency and compare the outdoor wet bulb temperature to the above temperature range.

By way of example, the present application may detect the outdoor wet bulb temperature of a once every 3 hours heating ventilation system. By way of example, the present application may also detect the outdoor wet bulb temperature of the heating ventilation system every 1 day, etc., which is not particularly limited in this specification, and the frequency of detecting the outdoor wet bulb temperature may be set by the staff according to actual needs and conditions.

Step S104, determining a target operation mode for the heating and ventilation system from the plurality of operation modes based on the comparison result, and adjusting the operation mode of the heating and ventilation system to the target operation mode.

In one illustrated embodiment, the present application may select an appropriate target operating mode for the hvac system among a plurality of operating modes based on a comparison between the outdoor wet bulb temperature and the above temperature range, and adjust the operating mode thereof to the target operating mode.

It should be noted that if the selected target operation mode is the same as the current operation mode of the hvac system, the current operation mode may be maintained.

In one illustrated embodiment, if the outdoor wet bulb temperature of the hvac system is less than or equal to the first threshold, the free cooling mode of the plurality of operating modes may be determined as the target operating mode and the operating mode of the hvac system may be adjusted to the free cooling mode. Correspondingly, when the outdoor wet bulb temperature is smaller than or equal to the first threshold value, the free refrigeration mode is an operation mode with the lowest total energy consumption, wherein the heating and ventilation system can meet the refrigeration requirement corresponding to the outdoor wet bulb temperature in the operation modes.

In an illustrated embodiment, if the outdoor wet bulb temperature of the hvac system is greater than the first threshold value and less than or equal to the second threshold value, the precooling mode of the plurality of operating modes may be determined as the target operating mode and the operating mode of the hvac system may be adjusted to the precooling mode. Correspondingly, when the outdoor wet bulb temperature is larger than the first threshold value and smaller than or equal to the second threshold value, the precooling mode is an operation mode which is in a plurality of operation modes, enables the heating and ventilation system to meet the refrigeration requirement corresponding to the outdoor wet bulb temperature, and generates the lowest total energy consumption.

In one illustrated embodiment, if the outdoor wet bulb temperature of the hvac system is greater than the second threshold, the mechanical cooling mode of the plurality of operating modes may be determined as the target operating mode and the operating mode of the hvac system may be adjusted to the mechanical cooling mode. Correspondingly, when the outdoor wet bulb temperature is greater than the second threshold value, the mechanical refrigeration mode is one of a plurality of operation modes, so that the heating and ventilation system can meet the refrigeration requirement corresponding to the outdoor wet bulb temperature, and the generated total energy consumption is the lowest.

Therefore, the application can determine the target operation mode which enables the heating and ventilation system to meet the refrigeration requirement corresponding to the current outdoor wet bulb temperature and has the lowest total energy consumption in a plurality of operation modes directly based on the comparison result between the current outdoor wet bulb temperature and the predetermined temperature range, and adjust the operation mode of the heating and ventilation system to the target operation mode in time, thereby realizing energy saving of the heating and ventilation system efficiently and rapidly and being beneficial to green development of a data center.

Further, after determining the target operation mode, the application can also perform global parameter optimizing calculation on the system model corresponding to the target operation mode to obtain more detailed operation suggestions, for example, including determining the target operation parameters of each heating and ventilation device when the total energy consumption of the heating and ventilation system predicted by the system model is the lowest.

In an embodiment, the application can adjust the operation parameters of each heating and ventilation device in the heating and ventilation system to the corresponding target operation parameters, so that the energy consumption of the heating and ventilation device can be reduced to the maximum extent on the premise of meeting the refrigeration requirement.

In an embodiment, the present application may also output and display the target operation parameters of each heating and ventilation device obtained based on global parameter optimization to the user, and the user may manually regulate and control each heating and ventilation device with reference to these target operation parameters, which is not limited in this specification.

Further, in an embodiment, the present application may further divide the operation parameters of each heating and ventilation device into three types of action forms according to the conditions of the upper site and the lower site of the self-control logic of the heating and ventilation system: an operation point A, an observation point W and a monitoring point M.

Wherein operating point a represents that the operating parameter is a directly adjustable parameter; the observation point W represents that the operation parameter is an operation parameter which changes with the change of the operation point a, i.e., a parameter which can be indirectly adjusted; the monitoring point M represents that the operating parameter is an operating parameter that can affect the operating stability of the overall hvac system, i.e., a more critical operating parameter.

In an illustrated embodiment, the application can output and display the division condition of the operation parameters in each operation mode to the staff through a preset interface, and provide a reference basis for the subsequent regulation and control of the staff.

Referring to fig. 4a, fig. 4a is a schematic diagram of a key point location corresponding to a free cooling mode according to an exemplary embodiment.

As shown in fig. 4a, the rotational speed, the number, the air supply temperature, etc. of the precise air conditioner in the heating and ventilation system may be the operation point, and the opening degree of the water valve may be the observation point. Based on the logic diagram shown in fig. 4a, the staff can directly adjust the rotation speed, the number and the air supply temperature of the precise air conditioner by combining the target operation parameters corresponding to the precise air conditioner obtained through the global parameter optimizing calculation, and the opening degree of the water valve also changes along with the change of the rotation speed and the air supply temperature of the precise air conditioner.

As shown in fig. 4a, the end differential pressure may be the operating point and the secondary pump chilled water flow may be the observation point. The staff can directly adjust the end differential pressure based on the logic diagram shown in fig. 4a by combining the target operation parameters corresponding to the secondary pump obtained through the global parameter optimizing calculation, and the flow rate of the secondary pump changes along with the change of the end differential pressure. In addition, as shown in fig. 4a, the end differential pressure and the flow rate of the secondary pump freezing water can also be key monitoring points, and the change of the end differential pressure and the flow rate of the secondary pump freezing water can influence the operation stability of the whole heating ventilation equipment, so that a worker can pay attention to the operation stability of the system in real time in the adjustment process.

As shown in fig. 4a, the outlet water temperature of the freezing side of the plate heat exchanger may be an operation point and a monitoring point, and the staff may directly adjust the outlet water temperature of the freezing side of the plate heat exchanger by combining the target operation parameters corresponding to the plate heat exchanger obtained by the global parameter optimizing calculation based on the logic diagram shown in fig. 4a, and need to pay attention to the stability of the system operation in real time, etc., which will not be described herein.

Referring to fig. 4b, fig. 4b is a schematic diagram of a key point corresponding to a pre-cooling mode according to an exemplary embodiment.

As shown in fig. 4b, the cold side water supply temperature may be an operating point, and the operator may directly adjust the cold side water supply temperature based on the logic diagram shown in fig. 4 b. Meanwhile, as shown in fig. 4b, the water supply temperature at the freezing side of the chiller may also be a monitoring point, and a worker needs to pay attention to the stability of the system operation in real time in the process of adjusting the water supply temperature at the freezing side of the chiller, and the like, and will not be described herein.

Referring to fig. 4c, fig. 4c is a schematic diagram illustrating a key point corresponding to a mechanical refrigeration mode according to an exemplary embodiment. The key points in fig. 4c may refer to the descriptions of the corresponding embodiments in fig. 4a and fig. 4b, and are not described herein.

As described above, the application can disassemble each operation parameter in the heating and ventilation system according to the classification of the key point position action mode, and ensure the operation stability of the whole heating and ventilation system during the optimization and control.

In summary, on the premise that the heating and ventilation system includes a plurality of operation modes, the present application may first obtain a plurality of system models for respectively predicting the operation conditions of the heating and ventilation system in the plurality of operation modes. Further, the application can predict the operation condition of the heating and ventilation system at a plurality of specified outdoor wet bulb temperatures based on the plurality of system models, and determine the temperature range which can be used for accurately adjusting the operation mode of the heating and ventilation system from the plurality of outdoor wet bulb temperatures based on the predicted operation condition. Subsequently, the present outdoor wet bulb temperature of the heating and ventilation system can be directly compared with the temperature range, and based on the comparison result, a target operation mode which enables the heating and ventilation system to meet the refrigeration requirement corresponding to the present outdoor wet bulb temperature and has the lowest total energy consumption is determined in a plurality of operation modes, and the operation mode of the heating and ventilation system is timely adjusted to the target operation mode, so that energy conservation of the heating and ventilation system is effectively and rapidly realized, and the environment-friendly development of a data center is facilitated.

Corresponding to the implementation of the method flow, the embodiment of the specification also provides an operation device of the heating and ventilation system. Referring to fig. 5, fig. 5 is a schematic structural diagram of an operation device of a heating ventilation system according to an exemplary embodiment. The apparatus 30 may be applied to a computer device 100 in the system architecture shown in fig. 1, and may interface with a hvac system. As shown in fig. 5, the apparatus 30 includes:

a system model obtaining unit 301, configured to obtain a plurality of system models corresponding to a plurality of operation modes of the heating and ventilation system one by one, where the system models are used to predict an operation condition of the heating and ventilation system in the corresponding operation modes; the operating conditions comprise at least one operating parameter of the heating ventilation system in the operating process;

a temperature range determining unit 302, configured to predict an operation condition of the hvac system at a plurality of specified outdoor wet bulb temperatures based on the plurality of system models, and determine a temperature range for performing operation mode adjustment of the hvac system from the plurality of specified outdoor wet bulb temperatures based on the operation condition;

a comparison unit 303, configured to obtain an outdoor wet bulb temperature of the heating and ventilation system, and compare the outdoor wet bulb temperature with the temperature range;

An operation mode adjustment unit 304, configured to determine a target operation mode for the hvac system from the plurality of operation modes based on the comparison result, and adjust the operation mode of the hvac system to the target operation mode; the target operation mode is an operation mode with the lowest total energy consumption, wherein the target operation mode is an operation mode which enables the heating and ventilation system to meet the refrigeration requirement at the outdoor wet bulb temperature in the plurality of operation modes.

In an embodiment shown, the heating and ventilation system comprises a plurality of heating and ventilation devices connected to each other, and the apparatus 30 further comprises an operation parameter adjustment unit 305 for:

under the target operation mode, carrying out global parameter optimizing calculation on a system model corresponding to the target operation mode so as to determine target operation parameters of all heating and ventilation devices when the total energy consumption of the heating and ventilation system predicted by the system model is the lowest;

and adjusting the operation parameters of all heating and ventilation equipment in the heating and ventilation system to corresponding target operation parameters.

In an illustrated embodiment, the apparatus 30 further comprises a device model training unit 306 for:

acquiring initial equipment models respectively constructed for a plurality of heating and ventilation equipment based on physical characteristics of the heating and ventilation equipment in the heating and ventilation system;

Training the plurality of initial equipment models based on sample data corresponding to the plurality of heating and ventilation equipment to obtain a plurality of equipment models corresponding to the plurality of heating and ventilation equipment one by one; the equipment model is used for predicting the operation parameters of the corresponding heating and ventilation equipment.

In one illustrated embodiment, the plurality of heating and ventilation devices includes a plate heat exchanger and a chiller; the plurality of operating modes includes: the heat exchanger comprises a free refrigeration mode based on heat exchange of the plate heat exchanger, a precooling mode based on heat exchange of the water chilling unit and the plate heat exchanger and a mechanical refrigeration mode based on heat exchange of the water chilling unit.

In an illustrated embodiment, the system model obtaining unit 301 is specifically configured to:

based on the connection structures of the heating and ventilation devices, performing model coupling processing on a plate heat exchanger model in the device models and at least one other device model connected with the plate heat exchanger model to obtain a first system model corresponding to the free refrigeration mode;

based on the connection structures of the heating and ventilation devices, performing model coupling processing on a water chilling unit model, a plate heat exchanger model and at least one other device model connected with the water chilling unit model and the plate heat exchanger model in the device models to obtain a second system model corresponding to the precooling mode;

And carrying out model coupling processing on a water chilling unit model in the plurality of equipment models and at least one other equipment model connected with the water chilling unit model based on the connection structure of the plurality of heating and ventilation equipment so as to obtain a third system model corresponding to the mechanical refrigeration mode.

In an embodiment shown, the temperature range is a temperature interval consisting of a first threshold value and a second threshold value greater than the first threshold value; the temperature range determining unit 302 is specifically configured to:

setting the sum of approximation degree in the first system model and heat exchange temperature difference of the plate heat exchanger as a minimum value, and acquiring the refrigeration side water supply temperature of the heating and ventilation system, which is predicted by the first system model at the plurality of specified outdoor wet bulb temperatures;

determining the outdoor wet bulb temperature when the refrigeration side water supply temperature predicted by the first system model is a preset value as the first threshold;

acquiring the total energy consumption of the heating and ventilation system, which is obtained by predicting the second system model and the third system model at the plurality of specified outdoor wet bulb temperatures respectively;

and determining the outdoor wet bulb temperature when the total energy consumption of the heating and ventilation system predicted by the second system model and the third system model is equal to the second threshold.

In an illustrated embodiment, the operation mode adjustment unit 304 is specifically configured to:

determining a free cooling mode of the plurality of operating modes as the target operating mode if the outdoor wet bulb temperature is less than or equal to the first threshold;

determining a pre-cooling mode of the plurality of operating modes as the target operating mode if the outdoor wet bulb temperature is greater than the first threshold and less than or equal to the second threshold;

and if the outdoor wet bulb temperature is greater than the second threshold, determining a mechanical cooling mode of the plurality of operating modes as the target operating mode.

The implementation process of the functions and roles of the units in the above device 30 is specifically described in the corresponding embodiments of fig. 1 to fig. 4c, and will not be described in detail herein. It should be understood that the above-mentioned apparatus 30 may be implemented by software, or may be implemented by hardware or a combination of hardware and software. Taking software implementation as an example, the device in a logic sense is formed by reading corresponding computer program instructions into a memory by a processor (CPU) of the device. In addition to the CPU and the memory, the device in which the above apparatus is located generally includes other hardware such as a chip for performing wireless signal transmission and reception, and/or other hardware such as a board for implementing a network communication function.

The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the units or modules may be selected according to actual needs to achieve the purposes of the present description. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

The apparatus, units, modules illustrated in the above embodiments may be implemented in particular by a computer chip or entity or by a product having a certain function. A typical implementation device is a computer, which may be in the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or a combination of any of these devices.

Corresponding to the method embodiments described above, embodiments of the present disclosure also provide a computer device. Referring to fig. 6, fig. 6 is a schematic structural diagram of a computer device according to an exemplary embodiment. The computer device may be, for example, the computer device 100 in the system architecture shown in fig. 1 described above. As shown in fig. 6, the computer device may include a processor 1001 and memory 1002, and further may include an input device 1004 (e.g., keyboard, etc.) and an output device 1005 (e.g., display, etc.). The processor 1001, memory 1002, input devices 1004, and output devices 1005 may be connected by a bus or other means. As shown in fig. 6, the memory 1002 includes a computer-readable storage medium 1003, which computer-readable storage medium 1003 stores a computer program executable by the processor 1001. The processor 1001 may be a general purpose processor, a microprocessor, or an integrated circuit for controlling the execution of the above method embodiments. The processor 1001, when executing the stored computer program, may perform the steps of the method for operating the hvac system in the embodiment of the present specification, including: acquiring a plurality of system models which are in one-to-one correspondence with a plurality of operation modes of a heating and ventilation system, wherein the system models are used for predicting the operation condition of the heating and ventilation system in the corresponding operation modes; the operating conditions comprise at least one operating parameter of the heating ventilation system in the operating process; based on the system models, predicting the operation condition of the heating and ventilation system at a plurality of specified outdoor wet bulb temperatures, and determining a temperature range for adjusting the operation mode of the heating and ventilation system from the plurality of specified outdoor wet bulb temperatures based on the operation condition; acquiring the outdoor wet bulb temperature of the heating and ventilation system, and comparing the outdoor wet bulb temperature with the temperature range; determining a target operation mode for the heating and ventilation system from the plurality of operation modes based on a comparison result, and adjusting the operation mode of the heating and ventilation system to the target operation mode; wherein the target operation mode is an operation mode in which the heating and ventilation system satisfies a refrigeration requirement at the outdoor wet bulb temperature and the total energy consumption is the lowest among the plurality of operation modes, and the like. For a detailed description of each step of the operation method of the above heating and ventilation system, please refer to the previous contents, and a detailed description thereof will not be provided here.

Corresponding to the above-described method embodiments, embodiments of the present description also provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of operating a heating ventilation system in the embodiments of the present description. Please refer to the description of the corresponding embodiments of fig. 1-4 c, and the detailed description is omitted here.

The foregoing description of the preferred embodiments is provided for the purpose of illustration only, and is not intended to limit the scope of the disclosure, since any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the disclosure are intended to be included within the scope of the disclosure.

In a typical configuration, the terminal device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data.

Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computer device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, embodiments of the present specification may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, embodiments of the present description may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

Claims (10)

1. A method of operating a hvac system, the method comprising:

acquiring a plurality of system models corresponding to a plurality of operation modes of the heating and ventilation system one by one, wherein the system models are used for predicting the operation condition of the heating and ventilation system in the corresponding operation modes; the operating conditions comprise at least one operating parameter of the heating ventilation system in the operating process;

based on the system models, predicting the operation condition of the heating and ventilation system at a plurality of specified outdoor wet bulb temperatures, and determining a temperature range for adjusting the operation mode of the heating and ventilation system from the plurality of specified outdoor wet bulb temperatures based on the operation condition;

Acquiring the outdoor wet bulb temperature of the heating and ventilation system, and comparing the outdoor wet bulb temperature with the temperature range;

determining a target operation mode for the heating and ventilation system from the plurality of operation modes based on a comparison result, and adjusting the operation mode of the heating and ventilation system to the target operation mode; the target operation mode is an operation mode with the lowest total energy consumption, wherein the target operation mode is an operation mode which enables the heating and ventilation system to meet the refrigeration requirement at the outdoor wet bulb temperature in the plurality of operation modes.

2. The method of claim 1, the hvac system comprising a plurality of hvac devices interconnected, the method further comprising:

under the target operation mode, carrying out global parameter optimizing calculation on a system model corresponding to the target operation mode so as to determine target operation parameters of all heating and ventilation devices when the total energy consumption of the heating and ventilation system predicted by the system model is the lowest;

and adjusting the operation parameters of all heating and ventilation equipment in the heating and ventilation system to corresponding target operation parameters.

3. The method of claim 2, the method further comprising:

acquiring initial equipment models respectively constructed for a plurality of heating and ventilation equipment based on physical characteristics of the heating and ventilation equipment in the heating and ventilation system;

Training the plurality of initial equipment models based on sample data corresponding to the plurality of heating and ventilation equipment to obtain a plurality of equipment models corresponding to the plurality of heating and ventilation equipment one by one; the equipment model is used for predicting the operation parameters of the corresponding heating and ventilation equipment.

4. The method of claim 3, the plurality of heating and ventilation devices comprising a plate heat exchanger and a chiller; the plurality of operating modes includes: the heat exchanger comprises a free refrigeration mode based on heat exchange of the plate heat exchanger, a precooling mode based on heat exchange of the water chilling unit and the plate heat exchanger and a mechanical refrigeration mode based on heat exchange of the water chilling unit.

5. The method of claim 4, the obtaining a plurality of system models that correspond one-to-one to a plurality of modes of operation of the hvac system, comprising:

based on the connection structures of the heating and ventilation devices, performing model coupling processing on a plate heat exchanger model in the device models and at least one other device model connected with the plate heat exchanger model to obtain a first system model corresponding to the free refrigeration mode;

based on the connection structures of the heating and ventilation devices, performing model coupling processing on a water chilling unit model, a plate heat exchanger model and at least one other device model connected with the water chilling unit model and the plate heat exchanger model in the device models to obtain a second system model corresponding to the precooling mode;

And carrying out model coupling processing on a water chilling unit model in the plurality of equipment models and at least one other equipment model connected with the water chilling unit model based on the connection structure of the plurality of heating and ventilation equipment so as to obtain a third system model corresponding to the mechanical refrigeration mode.

6. The method of claim 5, the temperature range being a temperature interval comprised of a first threshold and a second threshold greater than the first threshold; the determining a temperature range for operating mode adjustment of the hvac system from the number of specified outdoor wet bulb temperatures based on the operating parameters includes:

setting the sum of approximation degree in the first system model and heat exchange temperature difference of the plate heat exchanger as a minimum value, and acquiring the refrigeration side water supply temperature of the heating and ventilation system, which is predicted by the first system model at the plurality of specified outdoor wet bulb temperatures;

determining the outdoor wet bulb temperature when the refrigeration side water supply temperature predicted by the first system model is a preset value as the first threshold;

acquiring the total energy consumption of the heating and ventilation system, which is obtained by predicting the second system model and the third system model at the plurality of specified outdoor wet bulb temperatures respectively;

And determining the outdoor wet bulb temperature when the total energy consumption of the heating and ventilation system predicted by the second system model and the third system model is equal to the second threshold.

7. The method of claim 6, the determining a target operating mode for the hvac system from the plurality of operating modes based on the comparison result, comprising:

determining a free cooling mode of the plurality of operating modes as the target operating mode if the outdoor wet bulb temperature is less than or equal to the first threshold;

determining a pre-cooling mode of the plurality of operating modes as the target operating mode if the outdoor wet bulb temperature is greater than the first threshold and less than or equal to the second threshold;

and if the outdoor wet bulb temperature is greater than the second threshold, determining a mechanical cooling mode of the plurality of operating modes as the target operating mode.

8. An operating device for a hvac system, the device comprising:

the system model acquisition unit is used for acquiring a plurality of system models which are in one-to-one correspondence with a plurality of operation modes of the heating and ventilation system, and the system models are used for predicting the operation condition of the heating and ventilation system in the corresponding operation modes; the operating conditions comprise at least one operating parameter of the heating ventilation system in the operating process;

A temperature range determining unit, configured to predict an operation condition of the heating and ventilation system at a plurality of specified outdoor wet bulb temperatures based on the plurality of system models, and determine a temperature range for performing operation mode adjustment of the heating and ventilation system from the plurality of specified outdoor wet bulb temperatures based on the operation condition;

the comparison unit is used for acquiring the outdoor wet bulb temperature of the heating and ventilation system and comparing the outdoor wet bulb temperature with the temperature range;

an operation mode adjustment unit configured to determine a target operation mode for the heating and ventilation system from the plurality of operation modes based on a comparison result, and adjust the operation mode of the heating and ventilation system to the target operation mode; the target operation mode is an operation mode with the lowest total energy consumption, wherein the target operation mode is an operation mode which enables the heating and ventilation system to meet the refrigeration requirement at the outdoor wet bulb temperature in the plurality of operation modes.

9. A computer device, comprising: a memory and a processor; the memory has stored thereon a computer program executable by the processor; the processor, when running the computer program, performs the method of any one of claims 1 to 7.

10. A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of any of claims 1 to 7.