CN115289602B

CN115289602B - Method, computing device, and medium for determining target operation time of central air conditioning system

Info

Publication number: CN115289602B
Application number: CN202211228850.8A
Authority: CN
Inventors: 林圣剑; 马胜明; 刘星如
Original assignee: Mogulinker Technology Shenzhen Co Ltd
Current assignee: Guangdong Mushroom Iot Technology Co ltd
Priority date: 2022-10-09
Filing date: 2022-10-09
Publication date: 2022-12-16
Anticipated expiration: 2042-10-09
Also published as: CN115289602A

Abstract

The invention provides a method, a computing device and a computer readable storage medium for determining a target operating moment of a central air conditioning system. The method comprises the following steps: determining the system startup completion time of the central air-conditioning system based on the outdoor forecast temperature, the indoor target temperature, the cold load estimation value and the preset user starting working time of a user building served by the central air-conditioning system; determining a plurality of continuous adjusting moments of the central air-conditioning system based on the system startup completion moment; and determining the system shutdown starting time of the central air-conditioning system based on the preset user working finishing time, the cold load estimation value of the user building and the system cold storage amount.

Description

Method, computing device, and medium for determining target operation time of central air conditioning system

Technical Field

The present invention relates generally to the field of industrial control, and more particularly, to a method, computing device, computer-readable storage medium, and computer program product for determining a target operating time for a central air conditioning system.

Background

Currently, a large central air conditioning system has been widely used for heating or cooling in various complex locations, such as an office building or office building group, manufacturing enterprises including various buildings such as workshops and office buildings, schools including various buildings such as teaching buildings, experiment buildings and office buildings. In addition, a building may contain various types of space, such as rooms, offices, etc., that may be needed. Because the cooling/heating load of a large central air-conditioning system is large and the fluctuation is obvious, the traditional unified control method obviously cannot meet the higher and higher energy-saving requirements.

Therefore, a more elaborate control method is required to control the operation of the entire central air conditioning system. For example, when the load at the tail end is too high, so that the cold load rate of the current host running combination is too high, the power adding/power adding adjustment is carried out; or, when the end load is too low, so that the cold load rate of the current host running combination is too low, the engine reduction/power reduction adjustment is carried out. However, these adjustments cannot be performed over time, or else the system adjustments will be made too frequently to compromise host life. Therefore, before performing the adjustment operations, the target operation times for performing the adjustment operations should be first determined to evaluate the operation conditions of the central air conditioning system at the corresponding target operation times to further determine whether the adjustment is required, such as changing the turn-on number, the operation power, and the like of the cooling/heating master machines.

Disclosure of Invention

In view of the above problems, the present invention provides a method capable of dynamically determining in advance various typical target operation timings of a central air conditioning system for heating/cooling a user building according to actual demands of the user building.

According to one aspect of the present invention, a method for determining a target operation time of a central air conditioning system is provided. The method comprises the following steps: determining a system startup completion time of the central air-conditioning system based on an outdoor forecast temperature, an indoor target temperature, a cold load estimation value and a preset user starting working time of a user building served by the central air-conditioning system; determining a plurality of continuous adjusting moments of the central air-conditioning system based on the system startup completion moment; and determining the system shutdown starting time of the central air-conditioning system based on the preset user working finishing time, the cold load estimation value of the user building and the system cold storage amount.

In some embodiments, determining the system completion start-up time of the central air conditioning system comprises: calculating an estimated value of the cooling load of the user building at intervals of a first time from the scheduled working time of the user; determining a first time at which the cold load estimate is greater than zero; determining whether the outdoor forecast temperature is greater than the sum of the indoor target temperature and a temperature margin at a time a predetermined interval before the first time; if the outdoor forecast temperature is larger than the sum of the indoor target temperature and the temperature margin at the moment of a preset interval before the first moment, determining the moment of the preset interval before the first moment as the moment when the system finishes starting; and if the outdoor forecast temperature is not more than the sum of the indoor target temperature and the temperature margin at the time of a preset interval before the first time, determining the first time as the time when the system finishes starting.

In some embodiments, calculating a cold load estimate for the customer premises comprises: determining the cold load estimate based on an outdoor forecasted temperature of the user building, an indoor operating temperature, a number of people within the user building, a solar radiation intensity, and a heat dissipation load of working equipment within the user building.

In some embodiments, determining the cold load estimate comprises: training a neural network-based cold load prediction model based on the outdoor forecasted temperature, the indoor working temperature, the number of people in the user building, the solar radiation intensity, and historical record data of the heat dissipation load of the working equipment in the user building and the historical cold load value of the user building; and determining the cold load estimate using the trained cold load prediction model.

In some embodiments, calculating a cold load estimate for the customer premises comprises: determining the cold load estimate based on a building type of the user building, a load indicator corresponding to the building type, a cold supply area of the user building, the outdoor forecast temperature, and an indoor operating temperature.

In some embodiments, calculating a cold load estimate for the customer premises comprises: determining various space types contained by the user building; determining a cooling area for each space type; and determining the cold load estimation value based on various space types contained in the user building, the cooling area of each space type, the load index and the cooling area corresponding to each space type, the outdoor forecast temperature and the indoor working temperature.

In some embodiments, determining a plurality of consecutive adjustment instants for the central air conditioning system comprises: determining a first adjusting moment for strategy conversion based on the moment when the system finishes starting up and the moment when the user starts working; and taking each integral point time after the first adjusting time as an adjusting time respectively.

In some embodiments, determining a system start-off time of the central air conditioning system comprises: calculating an estimate of the cooling load of the customer premises at second time intervals onwards from the scheduled customer end-of-work time; calculating the system cold accumulation amount of the user building at a second time every second time interval from the scheduled user end working time to the front; determining the earliest moment when the system cold accumulation amount of the user building is larger than the accumulated value of the cold load estimated values of the user building from the second moment; and determining the earliest moment as the moment when the system starts to shut down.

In some embodiments, calculating the system cold storage for the user building comprises: and at each second moment, determining the system cold accumulation of the user building based on the temperature of the chilled water before starting the central air-conditioning system, the outdoor forecast temperature, the chilled water supply temperature at the stable moment after starting the central air-conditioning system, the chilled water return temperature and the indoor target temperature.

In some embodiments, the method further comprises: and determining the number of the running hosts of the system at the starting-up completion time and the multiple continuous adjustment times based on the system cold accumulation of the user building.

In some embodiments, determining the number of active hosts at the time the system completes boot and the plurality of consecutive adjustment times comprises: for a first adjustment time of the plurality of continuous adjustment times, determining the number of operating hosts of the central air conditioning system at the first adjustment time based on the estimated value of the cooling load of the user building; determining the number of the running hosts of the system at the time of finishing starting smoothly based on the number of the running hosts of the central air-conditioning system at the first adjusting time and the system cold accumulation amount at the time of finishing starting; and for other adjusting time in the plurality of continuous adjusting time, smoothly determining the number of the running hosts at the other adjusting time based on the cold load estimated value at the other adjusting time and the number of the running hosts at the previous adjusting time.

According to another aspect of the invention, a computing device is provided. The computing device includes: at least one processor; and at least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor, the instructions when executed by the at least one processor causing the computing device to perform the method as described above.

According to yet another aspect of the present invention, a computer-readable storage medium is provided, having stored thereon computer program code, which, when executed, performs the method as described above.

By utilizing the scheme of the invention, various typical target operation moments are determined for the specific user building according to the self condition of the user building, so that the determination of the target operation moments can be more accurate and dynamic, and the operation of the central air-conditioning system, such as the number of running hosts and the like, can be more timely adjusted.

Drawings

The invention will be better understood and other objects, details, features and advantages thereof will become more apparent from the following description of specific embodiments of the invention given with reference to the accompanying drawings.

Fig. 1 shows a schematic diagram for implementing a central air conditioning system according to an embodiment of the invention.

Fig. 2 illustrates a flow chart of a method for determining a target operating moment of a central air conditioning system according to some embodiments of the present invention.

FIG. 3 illustrates a further detailed flow chart of a process for determining a system complete turn-on time for a central air conditioning system according to some embodiments of the present invention.

FIG. 4 illustrates a further detailed flow chart of a process for determining a time at which a system of a central air conditioning system begins to shutdown, according to some embodiments of the invention.

FIG. 5 illustrates a block diagram of a computing device suitable for implementing embodiments of the present invention.

Detailed Description

Preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

In the following description, for the purposes of illustrating various inventive embodiments, certain specific details are set forth in order to provide a thorough understanding of the various inventive embodiments. One skilled in the relevant art will recognize, however, that the embodiments may be practiced without one or more of the specific details. In other instances, well-known devices, structures and techniques associated with this application may not be shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

Throughout the specification and claims, the word "comprise" and variations thereof, such as "comprises" and "comprising", will be understood to have an open, inclusive meaning, i.e., will be interpreted to mean "including, but not limited to", unless the context requires otherwise.

Reference throughout this specification to "one embodiment" or "some embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least one embodiment. Thus, the appearances of the phrases "in one embodiment" or "in some embodiments" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

Furthermore, the terms first, second and the like used in the description and the claims are used for distinguishing objects for clarity, and do not limit the size, other order and the like of the described objects.

Fig. 1 shows a schematic diagram for implementing a central air conditioning system 1 according to an embodiment of the invention. As shown in fig. 1, the central air conditioning system 1 may include one or more hosts 10 (3 hosts 10-1, 10-2, and 10-3 are exemplarily shown in fig. 1). These main units 10 can supply heat or cold to one or more customer premises 30 (3 customer premises 30-1, 30-2 and 30-3 are exemplarily shown in fig. 1) through ducts 20. The main unit 10 may generate cooling water (or other cooling fluid, collectively referred to herein as cooling water for brevity) that is provided to the user premises 30 via the duct 20 to perform a cooling function. Additionally or alternatively, the main unit 10 may generate hot water or steam to be supplied to the user building 30 via the pipe 20 to perform a heating function. Although not shown in the drawings, it will be understood by those skilled in the art that the pipe 20 may include a water supply pipe for supplying cold/hot water from the main unit 10 to the user building 30 and a water return pipe for returning the used cold/hot water from the user building 30 to the main unit 10. The customer premises 30, which is a service object of the main unit 10, may include a single type or multiple types of spaces, where the type of space refers to spaces having different cooling demands, such as offices, machine rooms, and the like. The central air conditioning system 1 and associated methods are described herein with reference to a cooling application as an example, however, it will be understood by those skilled in the art that the systems and methods may be equally applied to a heating application.

The central air conditioning system 1 may further include a control device 40, and the control device 40 may acquire and control the states of the host computer 10, the duct 20, and the user building 30 via a wired or wireless communication link. The control device 40 may be located locally in the central air conditioning system 1, or may be located at a remote end of the central air conditioning system 1, such as a cloud device.

The control device 40 may include at least one processor 42 and at least one memory 44 coupled to the at least one processor 42, the memory 44 having stored therein instructions 46 executable by the at least one processor 42, the instructions 46 when executed by the at least one processor 42 performing at least a portion of a method as described below. The specific structure of the control device 40 may be described below in conjunction with fig. 5, for example.

The central air conditioning system can be classified into two types according to continuity: the first type is continuous air conditioning; the second type is discontinuous air conditioning. Continuous air conditioning means that an air conditioning system has extremely long on/off periods, generally several months or even one year, and can be considered to be continuously operated after being started, and the air conditioning system cannot be turned off except for maintenance and other special reasons. Discontinuous air conditioning means that the air conditioning system has a short on/off cycle, generally 1 day. For example: the machine is started at 7 am and is turned off at 6 pm every day. For a continuous air conditioner, although the adjustment operation which needs to be executed at each adjustment time needs to be determined, such as addition and subtraction, the meaning of determining the system startup completion time and the system shutdown start time is not great due to long-term operation of the continuous air conditioner, so that the invention mainly aims at the discontinuous air conditioner to determine each target operation time.

As previously mentioned, in a large central air conditioning system, the number and types of user buildings 30 served and the types of spaces contained in the user buildings 30 may vary widely. In the conventional control manner, control is generally unified according to a predetermined user start working time and a predetermined user end working time. For example, assuming that the user start work time in the user building 30 is 9 am and the user end work time is 6 pm, the conventional control manner may fixedly turn on the respective hosts 10 of the central air conditioning system 1 at 8 am (i.e., one hour before the user start work time) and fixedly turn off the respective hosts 10 of the central air conditioning system 1 at 7 pm (i.e., one hour after the user end work time).

However, this fixed control method does not consider the own conditions of the user building 30, such as the indoor target temperature, the cooling load, etc., nor the external conditions, such as the outdoor temperature, etc. Thus, in some cases, the opening operation is performed too early or the closing operation is performed too late with respect to the actual demand of the user building 30, resulting in wasted energy, and in other cases, the opening operation is performed too late or the closing operation is performed too early with respect to the actual demand of the user building 30, resulting in poor user experience in the user building 30.

Therefore, in the solution of the present invention, by comprehensively considering the self-condition and the external condition of the user building 30, each target operation time, such as the system completion startup time, the continuous adjustment time, the system startup start time, and the like of the central air conditioning system 1, is customized for the user building 30, so as to more finely control various operations of the central air conditioning system 1.

Fig. 2 shows a flow chart of a method 200 for determining a target operating moment of the central air conditioning system 1 according to some embodiments of the present invention. The method 200 may be performed by the control device 40 shown in fig. 1. The method 200 is described below in conjunction with fig. 1-5.

As shown in fig. 2, method 200 includes a block 210 in which control device 40 may determine a system complete turn-on time for central air conditioning system 1 based on an outdoor forecasted temperature, an indoor target temperature, a cold load estimate, and a predetermined user start time for a user building 30 serviced by central air conditioning system 1.

Here, the predetermined user start operation time is a start time at which the user building 30 requests the indoor target temperature to be reached. Similarly, the user end work time refers to the end time when the user building 30 requires the maintenance of the indoor target temperature. For example, in the case of an office building, if a predetermined indoor target temperature is required to be maintained between 9 a.m. and 6 a.m. (i.e., a stable work period), then 9 a.m. 00 is the user start work time, and similarly, 6 a.m. 00 is the user end work time.

The indoor target temperature may be a fixed temperature value, for example, 20 ℃, or may be a staged temperature value, that is, the indoor target temperature may be different at different time periods of each day.

The outdoor forecasted temperature can be the forecasted temperature given by the weather station at each moment in the area where the user building 30 is located. With the outdoor forecast temperature, the control device 40 can determine the respective target operation timings of the central air conditioning system 1 in advance (for example, one day in advance).

The estimated cooling load value is the cooling load required by the customer premises 30, i.e. the amount of cooling required to be provided by the central air conditioning system. In this context, the cooling load required by the customer premises 30 as used herein is an estimate, since the control apparatus 40 needs to determine the respective target operating moments in advance.

Fig. 3 illustrates a further detailed flow chart of the process of determining the system complete turn-on time for the central air conditioning system 1 (block 210) according to some embodiments of the present invention.

As shown in fig. 3, at block 211, the control device 40 may calculate an estimate of the cooling load of the customer premises 30 at first time intervals (e.g., 10 minutes) from a predetermined customer start time.

In some embodiments, the control device 40 may train a neural network-based cold load prediction model based on historical data of the user building 30, such as historical indoor target temperatures, historical cold loads, historical outdoor temperatures, and the like, and predict a cold load estimate for the user building 30 using the trained model.

Specifically, the control apparatus 40 may train the neural network-based cold load prediction model based on the outdoor predicted temperature (or outdoor actual temperature) of the user building 30, the indoor operating temperature, the number of persons in the user building 30, the solar radiation intensity, and the historical data of the heat dissipation load of the working apparatuses in the user building 30 and the historical cold load value of the user building 30, and determine the cold load estimation value of the user building 30 using the trained cold load prediction model. For example, for the time period to be predicted, the cold load estimate for the user building 30 at the corresponding time may be determined based on the outdoor forecasted temperature of the user building 30, the indoor operating temperature, the number of people in the user building, the solar radiation intensity, and the heat dissipation load of the working equipment in the user building 30 at each time of the time period.

Here, the neural network-based cold load prediction model may be a linear regression model, and the cold load value/cold load estimation value Q may be expressed as:

wherein,

indicating various factors such as outdoor forecast temperature, indoor working temperature, the number of persons in the user building 30, solar radiation intensity, and heat dissipation load of working equipment in the user building 30,

weights corresponding to the respective influencing factors are indicated, tw indicates an outdoor temperature (outdoor forecast temperature or outdoor history temperature), and Tn indicates an indoor target temperature. Using the historical data of these influencing factors and the historical cooling load values of the user building 30 as training samples, the cooling load prediction model may be trained to determine the corresponding weights

。

Here, it is assumed that the outdoor forecast temperature, the indoor working temperature, the number of people in the user building 30, the solar radiation intensity, and the heat dissipation load of the working equipment in the user building 30 are key factors affecting the cooling load of the user building 30, and of course, in some other embodiments, only some of the factors may be used, or more factors may be used, such as the outdoor forecast humidity outside the user building 30. The historical cooling load values of the user buildings 30 may be calculated from the number of starts and the power of the central air conditioning system 1 at the corresponding historical time.

In other embodiments, the cold load estimate for the customer premises 30 may be determined based solely on the building type of the customer premises 30, the load index corresponding to the building type and the corresponding operating condition temperature differential, the outdoor forecast temperature, and the indoor operating temperature. For example, a common mapping table of building types and load indices may be as shown in table 1 below:

in this case, the cold load value/cold load estimation value Q can be expressed as:

wherein,prepresents a load index (which may be one selected from the load index ranges of table 1 above) corresponding to the building type of the user building 30,sindicates the cooling area of the user building 30, tw indicates the outdoor temperature (outdoor predicted temperature or outdoor historical temperature), tn indicates the indoor target temperature, and Tc indicates the operating condition temperature difference corresponding to the load index (i.e., the indoor and outdoor temperature difference used when the load index is established).

Note that this is a relatively rough estimation, and the cooling load of the user building 30 can be estimated from only the overall type of the user building 30 and the corresponding load index (and the total cooling area).

In some embodiments, the various types of spaces contained by the user building 30 may be determined; determining a cooling area for each space type; and determines an estimated value of the cooling load of the user building 30 based on various space types included in the user building, a cooling area of each space type, a load index corresponding to each space type and a corresponding operating condition temperature difference, an outdoor forecast temperature, and an indoor operating temperature.

For example, a common mapping table of space types and load indexes may be shown in table 2 below:

in this case, the cold load value/cold load estimated value Q may be expressed as

Wherein,

representing a load index corresponding to the type of space of the user building 30,

a cooling area indicating the type of the space, tw an outdoor temperature (outdoor predicted temperature or outdoor historical temperature), tn an indoor target temperature, and Tt _ci And represents the operating temperature difference corresponding to the load index (i.e., the indoor and outdoor temperature differences used in formulating the load index).

This estimation is relatively fine compared to the previous estimation, and can more accurately estimate the cooling load of the customer premises 30.

Further, in the calculation of the cooling load value/cooling load estimation value Q described above, we have calculated the same indoor target temperature, but the present invention is not limited to this, and may also be extended to use a more refined indoor target temperature, for example, different indoor target temperatures at different times and/or in different spaces.

Continuing with fig. 3, at block 212, the control apparatus 40 may determine a first time t _ h at which the estimated cooling load value Q determined at block 211 is greater than zero.

For example, the control apparatus 40 may calculate one cold load estimate Q every 10 minutes from the time when the user starts working, and determine whether the calculated cold load estimate Q is greater than zero, respectively, until finding the first cold load estimate Q greater than zero and a corresponding time, which is referred to herein as a first time t _ h.

In block 213, the control device 40 may determine whether the outdoor forecast temperature Tw is greater than the sum of the indoor target temperature Tn and a temperature margin at a time instant at a predetermined interval at before the first time instant t _ h, i.e., time instant t _ h-at. Here, the temperature margin is a small temperature value, for example 0.5 ℃. That is, it is determined whether Tw is greater than (Tn + 0.5). Here, the predetermined interval Δ t is also referred to as a heat storage amount elimination time, which refers to a time for eliminating the system heat storage amount of the user building, and may be set in advance, for example, to 20 minutes.

If it is determined that the outdoor predicted temperature Tw is greater than the sum of the indoor target temperature Tn and the temperature margin at the time t _ h- Δ t, the control device 40 may determine the time t _ h- Δ t as the system complete power-on time at block 214.

On the other hand, if it is determined that the outdoor predicted temperature Tw is not greater than the sum of the indoor target temperature Tn and the temperature margin at the time t _ h- Δ t, the control device 40 may determine the first time t _ h as the system complete power-on time in block 215.

In this way, the system complete start-up time can be adjusted with respect to the user start-up time in consideration of the cooling load of the user building 30, thereby controlling the central air conditioning system more precisely.

Continuing with fig. 2, at block 220, the control device 40 may determine a plurality of successive adjustment times for the central air conditioning system 1 based on the system complete turn-on time determined at block 210. During the operation of the central air conditioning system 1, it should be adjusted at predetermined time intervals to perform policy conversion, such as adding or subtracting power or the like. Some continuous adjustment time should therefore be determined in addition to the time when the system is finished powering on and the time when the system starts powering off.

In some embodiments, control device 40 may determine a first adjustment time for a policy switch based on the determined system completion turn-on time and the user start work time. For example, if the determined system turn-on completion time is greater than the user start-up time, this indicates that no system heat storage needs to be eliminated at the time the system is turned on. At this time, the first integer time after the system completion power-on time may be determined as the first adjustment time t1. On the other hand, if the determined system startup completion time is less than or equal to the user startup time, this indicates that there is system heat storage to be eliminated at the time the system is completely started. At this time, the first integral time after the system startup completion time and the time required for the system heat storage amount elimination (i.e., the heat storage amount elimination time Δ t) may be determined as the first adjustment time t1. Here, the use of the hour time as the adjustment time is only for the daily routine, and any non-hour time may be used as the adjustment time.

Each of the integer times after the first adjustment time t1 can then be used as an adjustment time. That is, the control device 40 may determine a plurality of consecutive adjustment timings between the time when the system finishes powering on and the time when the system starts powering off, and thus may further determine whether the system needs to be adjusted at each adjustment timing. Here, setting each continuous adjustment time interval to 1 hour can not only achieve the purpose of energy-saving adjustment of system operation, but also reduce the frequent start-stop of the host in the system. It is noted that the invention is not limited to this, and the continuous adjustment moments of the central air conditioning system 1 may have longer or shorter time intervals depending on the actual requirements.

At block 230, the control device 40 may determine a system start shutdown time of the central air conditioning system 1 based on a predetermined user end work time, the estimated cooling load value Q of the user building 30, and the system cold storage amount.

As described above, the control apparatus 40 can determine the cooling load estimation value Q at each time. For the discontinuous air conditioner, the system shutdown starting time can be more accurately determined relative to the scheduled user work finishing time.

Fig. 4 illustrates a further detailed flowchart of the process of determining the time at which the system of the central air conditioning system 1 starts to shut down (block 230) according to some embodiments of the present invention.

As shown in fig. 4, at block 232, the control apparatus 40 may calculate a cold load estimate Q of the customer premises 30 at a second time interval onward, starting from a predetermined customer end working moment. Here, the second time interval may be the same as or different from the first time interval. In this context, for the sake of simplicity, it is assumed that the second time interval is the same as the first time interval, e.g. 10 minutes. The calculation of the estimated cooling load value Q may be performed in any of the ways described above or any other feasible way.

At block 234, the control device 40 may calculate the system cold storage amount of the customer premises 30 at a second time every second time interval, starting from the predetermined customer end work time onwards. Here, the system cold accumulation amount means that the central air conditioning system 1 can more accurately control the system shutdown time under the condition of fully utilizing the cold accumulation amount with respect to the heat difference of the outside under the operation of the central air conditioning system 1 by the user building 30.

In some embodiments, at each second time, the control device 40 may determine the system cold storage amount X of the user building 30 based on the pre-startup chilled water temperature Ts and the outdoor forecast temperature Tw of the central air conditioning system 1, and the chilled water supply temperature Tg, the chilled water return temperature Th, and the indoor target temperature Tn at the post-startup stable time.

For example, the system cold accumulation amount X may be expressed as:

where Tg is the chilled water supply temperature at the stable time after startup, th is the chilled water return temperature at the stable time after startup, ts is the chilled water temperature before startup of the central air conditioning system 1, tw is the outdoor forecast temperature, and Tn is the indoor target temperature. k is a radical of ₁ And k ₂ Is an empirical coefficient, or, k ₁ And k ₂ The method can also be obtained by a linear regression method based on historical data training. Note that, herein, the system cold storage amount may be a positive value or a negative value, and in the case of a negative value, may also be referred to as a system heat storage amount. That is, the terms system cold storage and system heat storage are essentially the same and may be used interchangeably herein.

At block 236, the control apparatus 40 may determine the earliest time at which the system cold accumulation amount X of the user building 30 is greater than the accumulated value of the cold load estimation values Q of the user building 30 from among the plurality of second times.

As previously described, the control apparatus 40 may determine the estimated cooling load values Q at a plurality of times (second times), and may also determine the system cold storage amount X at a plurality of second times at block 234. At block 236, the control apparatus 40 may determine whether the system cold accumulation X is greater than the accumulated value of the cold load estimate Q at each second time.

Assume, for example, that the control device 40 determines that, from the moment when the user ends work onward, at a second moment t _ x at which x second time intervals have elapsed,

(that is, at a second time t _ (x-1) at the elapse of x-1 second time intervals

) Then the earliest time is time t _ x.

In block 238, the control device 40 may determine the earliest time t _ x as the time at which the system starts to shutdown. Thus, the central air conditioning system 1 may start shutdown at this time t _ x.

In this way, the system shutdown start time can be adjusted with respect to the user operation end time in consideration of the cooling load and the cooling storage amount of the user building 30, thereby more accurately controlling the central air conditioning system.

Additionally, in some embodiments, the method 200 may further include a block 240 (shown in fig. 2 as a dashed box), wherein the control device 40 may determine the number of operating hosts at the time the system completes startup and at a plurality of consecutive adjustment times based on the system cold storage amount X of the user building 30.

Different target operating moments may apply different number of operating strategies. In general, the number of combinations of hosts operating at different times may be the same or different, so that different numbers (combinations) of hosts operating at different times may have different power values. In addition, the operation strategy (host operation combination conversion) executed at each target operation time should be as smooth as possible, and on the basis of meeting the power consumption reduction, the load-up and load-down changes of the host are reduced as much as possible, so that the system operates stably. Typically, during initial startup of the system, since there is still heat stored in the user premises 30, it is often necessary to operate a larger capacity host or a larger number of hosts to quickly remove the heat stored in the system; after the heat storage amount is eliminated, the system enters a continuous operation period in which the indoor air temperature is relatively stable. Therefore, the first adjustment time t1 in the multiple continuous adjustment times can be used as the basic reference time for the policy conversion in one day, the number-of-hosts operation policy at the initial startup time of the system is obtained by forward smoothing processing of the policy at the basic reference time, and the number-of-hosts operation policy at the subsequent continuous adjustment time is obtained by backward smoothing processing of the policy at the previous adjustment time.

Specifically, for a first adjustment time t1 (e.g., a first hour after the system completion power-on time) of the plurality of consecutive adjustment times, the control apparatus 40 may determine the number of operating hosts of the central air conditioning system 1 at the first adjustment time t1 based on the estimated value Q of the cooling load of the user building 30. Here, since the system cold storage amount (system heat storage amount) at the time of initial startup of the system has been eliminated at this first adjustment time t1, the central air conditioning system 1 only needs to satisfy the normal cooling power required for the user building 30 to maintain the indoor target temperature.

And then, based on the number of the running hosts of the central air-conditioning system 1 at the first adjusting time t1 and the system cold accumulation X at the system startup completion time, smoothly determining the number of the running hosts at the system startup completion time. From the perspective of operation strategy conversion, the number of the operating hosts at the time when the system finishes startup should be the smallest difference from the number of the operating hosts at the first adjustment time after the system startup, in addition to satisfying the estimated value of the cooling load and the cold storage amount of the system, so that the adjustment operation for the hosts is smooth.

For other adjustment times, of the plurality of successive adjustment times, after the first adjustment time t1, the control device 40 may smoothly determine the number of operating masters for the other adjustment times backward based on the estimated cooling load value Q for the corresponding adjustment time and the number of operating masters for the previous adjustment time. Similarly, the number of hosts operating at other adjustment times after the first adjustment time should be minimally different from the number of hosts operating at the previous adjustment time, in addition to satisfying their estimation of cooling load, so that the adjustment operation for the hosts is smooth.

In this way, the operation strategy (host operation combination conversion) executed at each target operation time can be made as smooth as possible, so as to ensure the stable operation of the system.

FIG. 5 illustrates a block diagram of a computing device 500 suitable for implementing embodiments of the present invention. The computing device 500 may be, for example, the control device 40 in the central air conditioning system 1 as described above.

As shown in fig. 5, computing device 500 may include one or more Central Processing Units (CPUs) 510 (only one shown schematically) that may perform various appropriate actions and processes in accordance with computer program instructions stored in Read Only Memory (ROM) 520 or loaded from storage unit 580 into Random Access Memory (RAM) 530. In the RAM 530, various programs and data required for the operation of the computing device 500 may also be stored. The CPU 510, ROM 520, and RAM 530 are connected to each other by a bus 540. An input/output (I/O) interface 550 is also connected to bus 540.

A number of components in computing device 500 are connected to I/O interface 550, including: an input unit 560 such as a keyboard, a mouse, etc.; an output unit 570 such as various types of displays, speakers, and the like; a storage unit 580 such as a magnetic disk, an optical disk, or the like; and a communication unit 590 such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 590 allows the computing device 500 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

Various methods or blocks described above may be performed, for example, by the CPU 510 of one or more computing devices 500. For example, in some embodiments, the methods or blocks may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 580. In some embodiments, part or all of a computer program may be loaded onto and/or installed onto computing device 500 via ROM 520 and/or communications unit 590. When the computer program is loaded into RAM 530 and executed by CPU 510, one or more operations of the methods described above may be performed. Further, the communication unit 590 may support wired or wireless communication functions.

Those skilled in the art will appreciate that the computing device 500 illustrated in FIG. 5 is merely illustrative. In some embodiments, computing device 500 may contain more or fewer components than shown in FIG. 5.

The method for determining the target operation time of the central air-conditioning system and the computing device which can be used for realizing the method according to the invention are described above with reference to the accompanying drawings. It will be appreciated by those skilled in the art, however, that the performance of the various blocks of the method or portions thereof described above is not limited to the order shown in the figures and described above, but may be performed in any other reasonable order. Further, the computing device 500 also need not include all of the components shown in FIG. 5, it may include only some of the components necessary to perform the functions described in the present disclosure, and the manner in which these components are connected is not limited to the form shown in the figures.

The present invention may be methods, apparatus, systems and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therewith for carrying out aspects of the invention.

In one or more exemplary designs, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. For example, if implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium.

The units of the apparatus disclosed herein may be implemented using discrete hardware components, or may be integrally implemented on a single hardware component, such as a processor. For example, the various illustrative logical blocks, modules, and circuits described in connection with the invention may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein.

Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm blocks described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both.

The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the present invention is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for determining a target operating time for a central air conditioning system, comprising:

determining a system startup completion time of the central air-conditioning system based on an outdoor forecast temperature, an indoor target temperature, a cold load estimation value and a preset user starting working time of a user building served by the central air-conditioning system;

determining a plurality of continuous adjustment moments of the central air-conditioning system based on the system startup completion moment; and

determining the system shutdown starting time of the central air conditioning system based on the preset user finishing working time, the cold load estimation value of the user building and the system cold accumulation amount,

wherein determining a system completion start-up time of the central air conditioning system comprises:

calculating an estimated value of the cooling load of the user building at intervals of a first time from the scheduled working time of the user;

determining a first time at which the cold load estimate is greater than zero;

determining whether the outdoor forecast temperature is greater than the sum of the indoor target temperature and a temperature margin at a time a predetermined interval before the first time;

if the outdoor forecast temperature is greater than the sum of the indoor target temperature and the temperature margin at the moment of a preset interval before the first moment, determining the moment of the preset interval before the first moment as the moment when the system finishes starting; and

and if the outdoor forecast temperature is not greater than the sum of the indoor target temperature and the temperature margin at the moment of a preset interval before the first moment, determining the first moment as the moment when the system finishes starting.

2. The method of claim 1, wherein calculating the cold load estimate for the customer premises comprises:

determining the cold load estimate based on an outdoor forecasted temperature of the user building, an indoor operating temperature, a number of people within the user building, a solar radiation intensity, and a heat dissipation load of working equipment within the user building.

3. The method of claim 2, wherein determining the cold load estimate comprises:

training a neural network-based cold load prediction model based on the outdoor forecasted temperature, the indoor working temperature, the number of people in the user building, the solar radiation intensity, and historical record data of the heat dissipation load of the working equipment in the user building and the historical cold load value of the user building; and

determining the cold load estimate using a trained cold load prediction model.

4. The method of claim 1, wherein calculating the cold load estimate for the customer premises comprises:

determining the cold load estimate based on the building type of the user building, a load indicator corresponding to the building type and a corresponding operating condition temperature differential, a cooling area of the user building, the outdoor forecast temperature, and an indoor operating temperature.

5. The method of claim 1, wherein calculating the cold load estimate for the customer premises comprises:

determining various types of spaces contained by the user building;

determining a cooling area for each space type; and

and determining the cold load estimation value based on various space types contained in the user building, the cold supply area of each space type, the load index corresponding to each space type and the corresponding working condition temperature difference, the outdoor forecast temperature and the indoor working temperature.

6. The method of claim 1, wherein determining a plurality of consecutive adjustment instants for the central air conditioning system comprises:

determining a first adjusting moment for strategy conversion based on the moment when the system finishes starting up and the moment when the user starts working; and

and taking each integral point time after the first adjusting time as an adjusting time respectively.

7. The method of claim 1, wherein determining a system start-off time of the central air conditioning system comprises:

calculating an estimate of the cooling load of the customer premises at second time intervals onwards from the scheduled customer end-of-work time;

calculating the system cold accumulation of the user building at a second time interval from the end working time of the preset user to the front;

determining the earliest moment when the system cold accumulation amount of the user building is larger than the accumulated value of the cold load estimated values of the user building from the second moment; and

and determining the earliest moment as the moment when the system starts to be shut down.

8. The method of claim 7, wherein calculating the system cold storage for the user building comprises:

and at each second moment, determining the system cold accumulation of the user building based on the temperature of the chilled water before starting the central air-conditioning system, the outdoor forecast temperature, the chilled water supply temperature at the stable moment after starting the central air-conditioning system, the chilled water return temperature and the indoor target temperature.

9. The method of claim 1, further comprising:

and determining the number of the running main machines at the moment when the system finishes starting and the plurality of continuous adjusting moments based on the system cold accumulation of the user building.

10. The method of claim 9, wherein determining the number of active hosts at which the system completes boot-up and the plurality of consecutive adjustment times comprises:

for a first adjustment time of the plurality of continuous adjustment times, determining the number of operating hosts of the central air conditioning system at the first adjustment time based on the estimated value of the cooling load of the user building;

determining the number of the running hosts of the system at the time of finishing starting smoothly based on the number of the running hosts of the central air-conditioning system at the first adjusting time and the system cold accumulation amount at the time of finishing starting; and

and for other adjusting moments in the plurality of continuous adjusting moments, smoothly determining the number of the running hosts at the other adjusting moments backward based on the cold load estimated values at the other adjusting moments and the number of the running hosts at the previous adjusting moment.

11. A computing device, comprising:

at least one processor; and

at least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor, the instructions when executed by the at least one processor causing the computing device to perform the method of any of claims 1-10.

12. A computer readable storage medium having stored thereon computer program code which, when executed, performs the method of any of claims 1 to 10.