Method and device for controlling fan coil and storage medium

Abstract

The invention relates to the technical field of heating and ventilation system control, and discloses a method for controlling a fan coil, which comprises the following steps: determining a target function according to a wind system power model; determining a target constraint condition according to the wind system control time sequence dynamical model; solving according to the target function and the target constraint condition to obtain a target control parameter of the fan coil; and controlling the fan coil according to the target control parameter. According to the method, the target function and the target constraint condition can be accurately determined by combining the wind system power model and the wind system control time sequence dynamical model; and solving is carried out according to the target function and the target constraint condition so as to obtain more accurate target control parameters of the fan coil. Therefore, under the condition that the fan coil is controlled according to the target control parameters, the fan coil is controlled more reasonably, and energy consumption is minimized while temperature control of all the areas is met. The invention further discloses a device for controlling the fan coil and a storage medium.

Description

Technical Field

[0001] The present application relates to the technical field of HVAC system control, for example, to a method, device and storage medium for controlling a fan coil unit. Background Art

[0003] At present, in order to meet the different temperature sensitivities of personnel or equipment in different areas, it is necessary to integrate various wind system equipment to control the temperature and humidity of each area differently. However, the traditional method of controlling indoor temperature with fan coil units usually adopts feedback control, which controls the switch state of the fan coil unit two-way valve by comparing the actual indoor temperature and the set temperature at the corresponding position of the fan coil unit, and the air volume position is also adjusted manually or by feedback based on other parameters. However, this adjustment method cannot achieve system energy saving. Therefore, how to control the fan coil unit to reduce system energy consumption while the indoor temperature reaches the set temperature has become a technical problem that needs to be solved urgently.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical components or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0006] The embodiments of the present disclosure provide a method, device and storage medium for controlling a fan coil unit, which can accurately control the fan coil unit to reduce system energy consumption while the indoor temperature reaches a set temperature.

[0007] In some embodiments, the method for controlling a fan coil unit includes: determining an objective function based on a wind system power model; determining target constraints based on a wind system control timing dynamics model; solving the objective function and the target constraints to obtain target control parameters of the fan coil unit; and controlling the fan coil unit according to the target control parameters.

[0008] In some embodiments, the method for controlling fan coil units includes: obtaining the total power of each fan coil unit at a historical moment and the opening state of a two-way valve of each fan coil unit at a historical moment, and the air volume gear; performing data processing on the total power of each fan coil unit at a historical moment and the opening state of a two-way valve of each fan coil unit at a historical moment, and the air volume gear; and constructing a wind system power model based on the processed total power of each fan coil unit at a historical moment and the opening state of a two-way valve of each fan coil unit at a historical moment, and the air volume gear.

[0009] In some embodiments, the method for controlling fan coil units includes: screening out abnormal values ​​of the total power of each fan coil unit at a historical moment and the opening state of the two-way valve of each fan coil unit at a historical moment, and the air volume gear; performing steady-state screening on the total power of each fan coil unit at a historical moment and the opening state of the two-way valve of each fan coil unit at a historical moment after the abnormal value screening; and normalizing the total power of each fan coil unit at a historical moment and the opening state of the two-way valve of each fan coil unit at a historical moment and the air volume gear after the steady-state screening.

[0010] In some embodiments, the method for controlling fan coil units includes: obtaining the two-way valve opening state, air volume level and indoor temperature and indoor humidity of the area corresponding to each fan coil unit at a historical moment; performing data processing on the two-way valve opening state, air volume level and indoor temperature and indoor humidity of the area corresponding to each fan coil unit at a historical moment; and constructing a wind system control timing dynamics model based on the processed two-way valve opening state, air volume level and indoor temperature and indoor humidity of the area corresponding to each fan coil unit at a historical moment.

[0011] In some embodiments, the method for controlling fan coil units includes: screening out abnormal values ​​of the two-way valve opening state, air volume level and indoor temperature and indoor humidity of the area corresponding to each fan coil unit at historical moments; performing steady-state screening on the two-way valve opening state, air volume level and indoor temperature and indoor humidity of the area corresponding to each fan coil unit at historical moments after the abnormal values ​​are screened out; and normalizing the two-way valve opening state, air volume level and indoor temperature and indoor humidity of the area corresponding to each fan coil unit at historical moments after the steady-state screening.

[0012] In some embodiments, the method for controlling a fan coil unit includes: determining a first constraint condition based on a wind system control time-series dynamics model; determining a second constraint condition based on setting temperature and humidity values ​​for each indoor area; and using the first constraint condition and the second constraint condition as target constraints.

[0013] In some embodiments, the device for controlling a fan coil unit includes: a first determination module, configured to determine an objective function based on a wind system power model; a second determination module, configured to determine an objective constraint condition based on a wind system control timing dynamics model; an acquisition module, configured to solve according to the objective function and the objective constraint condition to obtain the target control parameters of the fan coil unit; and a control module, configured to control the fan coil unit according to the target control parameters.

[0014] In some embodiments, the device for controlling a fan coil unit includes: a processor and a memory storing program instructions, and the processor is configured to execute the aforementioned method for controlling a fan coil unit when running the program instructions.

[0015] In some embodiments, the storage medium stores program instructions, and when the program instructions are run, the method for controlling a fan coil unit as described above is executed.

[0016] The method, device and storage medium for controlling fan coil units provided by the embodiments of the present disclosure can achieve the following technical effects: it can be combined with the wind system power model to minimize power as the objective function; and combined with the wind system control time-series dynamics model to accurately determine the target constraints; thereby solving according to the objective function and the target constraints to obtain more accurate target control parameters of the fan coil unit; and then, when the fan coil unit is controlled according to the target control parameters, the fan coil unit is controlled more reasonably to minimize energy consumption while satisfying the temperature control of each area, thereby meeting the user's energy-saving control needs for the fan coil unit.

[0017] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] One or more embodiments are exemplarily described by corresponding drawings, which do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements, and the drawings do not constitute a scale limitation, and wherein:

[0019] Figure 1 is a schematic diagram of a method for controlling a fan coil unit provided by an embodiment of the present disclosure;

[0020] Figure 2 is a schematic diagram of a method for constructing a wind system power model provided by an embodiment of the present disclosure;

[0021] Figure 3-1 is a schematic diagram of a method for constructing a wind system control timing dynamics model provided by an embodiment of the present disclosure;

[0022] Figure 3-2 is another schematic diagram of a method for constructing a wind system control timing dynamics model provided by an embodiment of the present disclosure;

[0023] Figure 4 is a schematic diagram of a method for determining target constraint conditions provided by an embodiment of the present disclosure;

[0024] Figure 5 is a schematic diagram of a device for controlling a fan coil unit provided in an embodiment of the present disclosure;

[0025] Figure 6 is a schematic diagram of another device for controlling a fan coil unit provided by an embodiment of the present disclosure;

[0026] Figure 7 It is a schematic diagram of a fan coil unit provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] In order to be able to understand the features and technical contents of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0028] The terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the embodiments of the present disclosure described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0029] Unless otherwise stated, the term "plurality" means two or more.

[0030] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B indicates: A or B.

[0031] The term "and / or" is a description of the association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.

[0032] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0033] In the embodiments of the present disclosure, smart home appliances refer to home appliances that are formed by introducing microprocessors, sensor technology, and network communication technology into home appliances. They have the characteristics of intelligent control, intelligent perception, and intelligent application. The operation process of smart home appliances often relies on the application and processing of modern technologies such as the Internet of Things, the Internet, and electronic chips. For example, smart home appliances can be connected to electronic devices to enable users to remotely control and manage the smart home appliances.

[0034] In the embodiments of the present disclosure, the terminal device refers to an electronic device with a wireless connection function. The terminal device can communicate with the above-mentioned smart home appliances by connecting to the Internet, or can directly communicate with the above-mentioned smart home appliances through Bluetooth, WiFi, etc. In some embodiments, the terminal device is, for example, a mobile device, a computer, or a vehicle-mounted device built into a hover car, or any combination thereof. Mobile devices may include, for example, mobile phones, smart home devices, wearable devices, smart mobile devices, virtual reality devices, etc., or any combination thereof, wherein wearable devices include, for example: smart watches, smart bracelets, pedometers, etc.

[0035] Figure 7 is a schematic diagram of a fan coil unit provided by an embodiment of the present disclosure; Figure 7 As shown, optionally, points 1, 2, 3, 4, and 5 are all fan coils, and the indoor temperature and humidity of the area enclosed by them can be adjusted by controlling the opening of the two-way valve and the fan gear of each coil.

[0036] Figure 1 is a schematic diagram of a method for controlling a fan coil unit provided by an embodiment of the present disclosure; Figure 1 As shown, the embodiment of the present disclosure provides a method for controlling a fan coil unit, comprising:

[0037] S11, the fan coil unit determines the objective function according to the wind system power model.

[0038] S12, the fan coil unit determines the target constraint conditions according to the wind system control time series dynamics model.

[0039] S13, the fan coil unit is solved according to the objective function and the objective constraint conditions to obtain the target control parameters of the fan coil unit.

[0040] S14, the fan coil unit is controlled according to the target control parameters.

[0041] In this solution, the fan coil unit determines the objective function according to the wind system power model, including: the fan coil unit acquires real-time data; the fan coil unit processes the real-time data; the fan coil unit determines the objective function according to the processed real-time data and the wind system power model. Here, the acquisition parameters of the real-time data are consistent with the parameters collected when training the wind system power model. The fan coil unit processes the real-time data, including the fan coil unit successively screening outliers and normalizing the real-time data. In this way, the objective function can be accurately determined through real-time data and the wind system power model.

[0042] In this solution, the fan coil unit determines the target constraint condition according to the wind system control time series dynamics model, including: the fan coil unit determines the first constraint condition according to the wind system control time series dynamics model. The fan coil unit determines the second constraint condition according to the temperature and humidity values ​​set in each indoor area. The fan coil unit uses the first constraint condition and the second constraint condition as the target constraint condition. Among them, the fan coil unit determines the first constraint condition according to the wind system control time series dynamics model, including: the fan coil unit acquires real-time data; the fan coil unit processes the real-time data; the fan coil unit determines the first constraint condition according to the processed real-time data and the wind system control time series dynamics model. Among them, the acquisition parameters of the real-time data are consistent with the parameters collected when training the wind system control time series dynamics model. The fan coil unit processes the real-time data, including the fan coil unit sequentially performing outlier screening and normalization processing on the real-time data. In this way, the target constraint condition can be accurately determined through the real-time data and the wind system control time series dynamics model.

[0043] Furthermore, the fan coil unit can be solved according to the objective function and the objective constraints to obtain the target control parameters of the fan coil unit. Here, the target control parameters are the two-way valve opening state and air volume gear of each fan coil unit with the minimum power under the temperature and humidity requirements of each area at time t. Specifically, it can be solved by heuristic algorithms such as particle swarm algorithm, simulated annealing algorithm, ant colony optimization algorithm, genetic algorithm and their improved algorithms. As an example, if the particle swarm algorithm is used for solving, the specific solution process includes:

[0044] The first step is initialization: initializing the parameters such as the speed, position and population size of the particles. In this embodiment, the position is the opening state of the two-way valves and the air volume gear of fan coil units No. 1 to No. n.

[0045] The second step is evolution: in each round of evolution, the fitness value function of each particle is calculated. In this embodiment, the fitness value function is the objective function.

[0046] The third step is to update the individual optimal solution and the population optimal solution: if the current fitness value is higher than the individual historical optimal value, the current position is used to update the historical optimal position and update the global optimal value at the same time.

[0047] Step 4: Update speed and position: Using the speed and position update formula, the speed of the particle can be dynamically adjusted according to the historical optimal position of the particle and the historical optimal position of the population.

[0048] Step 5: Determine the termination of the algorithm: If the algorithm reaches the maximum number of iterations or the fitness value reaches the minimum allowable error, the algorithm terminates, otherwise repeat the above steps 2, 3, and 4.

[0049] In this way, the particle swarm algorithm can be used to accurately solve the target control parameters of the fan coil unit, so that the fan coil unit can be controlled according to the target control parameters.

[0050] The method for controlling fan coil units provided by the embodiments of the present disclosure can be combined with a wind system power model to take minimizing power as the objective function; and combined with a wind system control time-series dynamics model to accurately determine the target constraints; thereby solving the target function and the target constraints to obtain more accurate target control parameters of the fan coil units; and then, while controlling the fan coil units according to the target control parameters, the fan coil units can be controlled more reasonably to minimize energy consumption while satisfying the temperature control of each area, thereby meeting the energy-saving control needs of users for the fan coil units.

[0051] Figure 2 is a schematic diagram of a method for constructing a wind system power model provided by an embodiment of the present disclosure; Figure 2 As shown, optionally, the wind system power model is constructed in the following manner, including:

[0052] S21, the fan coil unit obtains the total power of each fan coil unit at a historical moment and the opening state of the two-way valve of each fan coil unit and the air volume gear at a historical moment.

[0053] S22, the fan coil unit performs data processing on the total power of each fan coil unit at a historical moment and the opening state of the two-way valve of each fan coil unit at a historical moment and the air volume gear position.

[0054] S23, the fan coil unit constructs a wind system power model according to the total power of each fan coil unit at the processed historical moment and the opening state of the two-way valve of each fan coil unit at the processed historical moment and the air volume gear.

[0055] In this solution, the fan coil unit can obtain the total power of each fan coil unit at a historical moment, the opening state of the two-way valve of each fan coil unit at a historical moment, and the air volume gear; further, the fan coil unit can process the total power of each fan coil unit at a historical moment, the opening state of the two-way valve of each fan coil unit at a historical moment, and the air volume gear. Among them, the processing process is outlier screening, steady-state screening and normalization processing in turn. In this way, a precise data foundation is provided for the construction of the model.

[0056] Furthermore, the fan coil unit can construct a wind system power model by combining the total power of each fan coil unit at the processed historical moment and the two-way valve opening state and air volume level of each fan coil unit at the processed historical moment. The wind system power model can be expressed as:

[0057] P t =f(A 1t , A 2t , ..., A nt)

[0058] Among them, P t is the total power of the fan coil at time t, (A 1t , A 2t , ..., A nt ) is the two-way valve opening state and air volume gear of fan coil units 1 to n at time t. In the specific implementation process, the fan coil unit can use the two-way valve opening state and air volume gear of each fan at each moment in the processed data as input, and output it through a fully connected deep neural network. and will With P t By making comparisons and constructing the loss function, the network parameters of the fully connected deep neural network are updated by back propagation to obtain the wind system power model. With this solution, the wind system power model can be accurately constructed, providing an accurate data basis for determining the objective function.

[0059] Optionally, S22, the fan coil unit performs data processing on the total power of each fan coil unit at a historical moment and the opening state of the two-way valve of each fan coil unit at a historical moment, and the air volume gear, including:

[0060] The fan coil unit screens out abnormal values ​​of the total power of each fan coil unit at historical moments, the opening status of the two-way valve of each fan coil unit at historical moments, and the air volume gear.

[0061] The fan coil unit will conduct steady-state screening on the total power of each fan coil unit at historical moments after the abnormal values ​​are screened out, as well as the opening state of the two-way valve of each fan coil unit at historical moments and the air volume gear.

[0062] The fan coil unit will normalize the total power of each fan coil unit at the historical moment after steady-state screening, as well as the two-way valve opening state and air volume level of each fan coil unit at the historical moment.

[0063] In this scheme, the fan coil unit can first screen out abnormal values ​​for the total power of each fan coil unit at a historical moment and the opening state of the two-way valve of each fan coil unit at a historical moment, and the air volume level. Here, the abnormal values ​​can be screened out according to the upper and lower limits of each data. Further, the fan coil unit can perform steady-state screening on the total power of each fan coil unit at a historical moment after the abnormal value screening and the opening state of the two-way valve of each fan coil unit at a historical moment, and the air volume level. Here, the amplitude of change of each parameter can be used for steady-state screening. In this way, it is easy to obtain relatively stable data required for model construction. Further, the fan coil unit can normalize the total power of each fan coil unit at a historical moment after the steady-state screening and the opening state of the two-way valve of each fan coil unit at a historical moment, and the air volume level. Here, the normalization process can use the following formula:

[0064]

[0065] Among them, x nom is the normalized data value, x is the original data before normalization, and x max 、x min are the maximum and minimum values ​​in the historical data of the parameter, respectively. With this solution, data can be effectively processed before model training to ensure the accuracy of model training data.

[0066] Figure 3-1 is a schematic diagram of a method for constructing a wind system control timing dynamics model provided by an embodiment of the present disclosure; Figure 3-2 is another schematic diagram of a method for constructing a wind system control timing dynamics model provided by an embodiment of the present disclosure; Figure 3-1 and Figure 3-2 As shown, optionally, a wind system control time series dynamics model is constructed in the following manner, including:

[0067] S31, the fan coil unit obtains the opening state of the two-way valve of each fan coil unit, the air volume level, and the indoor temperature and indoor humidity of the area corresponding to each fan coil unit at the historical moment.

[0068] S32, the fan coil unit performs data processing on the opening state of the two-way valve of each fan coil unit at a historical moment, the air volume level, and the indoor temperature and indoor humidity of the area corresponding to each fan coil unit at a historical moment.

[0069] S33, the fan coil unit constructs a wind system control time series dynamics model according to the processed two-way valve opening state, air volume level and indoor temperature and indoor humidity of the area corresponding to each fan coil unit at the historical moment.

[0070] In this solution, the fan coil unit can obtain the two-way valve opening state, air volume level and indoor temperature and humidity of the corresponding area of ​​each fan coil unit at the historical moment; further, the fan coil unit can process the two-way valve opening state, air volume level and indoor temperature and humidity of the corresponding area of ​​each fan coil unit at the historical moment. The processing process is outlier screening, steady-state screening and normalization processing. In this way, a precise data foundation is provided for the construction of the model.

[0071] Furthermore, the fan coil can be combined with the two-way valve opening state, air volume level and indoor temperature and indoor humidity of the corresponding area of ​​each fan coil at the historical moment after processing to construct a wind system control time series dynamics model. Among them, the wind system control time series dynamics model can be expressed as:

[0072] S t+1 =f[(S t , S t-1 , ..., St-k ), (A t , A t-1 , ..., A t-k )]

[0073] Among them, S t A represents the state tensor of the corresponding area of ​​all fan coil units at time t, and the state parameters include indoor temperature and indoor humidity; t It is understood that the physical meaning of this model is to establish the state parameters of all regions and all fan coil control parameters at the past k moments and the state parameters of all regions at the next moment S t+1 relationship.

[0074] like Figure 3-2 As shown, optionally, the process of constructing the wind system control time series dynamics model includes:

[0075] Step 1: First, construct a graph topology based on the spatial relationship of each fan coil unit. The state parameters of all fan coil units and their corresponding areas at time t can be expressed as a tensor S t , the control parameter can be expressed as a tensor A t ;

[0076] Step 2: Transform the state parameter tensor S at time t t and the control parameter tensor A t Here, the fusion can be a simple tensor stacked left and right; and the graph G is generated based on the fused tensor and the topological structure of the spatial relationship graph. t , and the same method is used to generate the timing diagram G t-1 , G t-2 , ..., G t-k .

[0077] Step 3: Pass the graph at each moment through the graph convolution neural network (GCN) to perform two layers of graph convolution. The forward propagation process of the graph convolution is Among them, H l represents the output value of the lth layer, represents the adjacency matrix of the graph plus a diagonal identity matrix, represents the degree matrix, σ(•) represents the activation function, W l Indicates the parameter value of the lth layer. Optionally, graph neural network methods such as graph attention network and gated graph neural network can also be used to construct the timing graph.

[0078] Step 4: Convolve the graph at each moment to generate H t , H t-1 , ..., H t-kIt is sent to the encoder composed of a long short-term memory neural network for encoding. The calculation process is the forget gate output f t =σ(W f ·[h t-1 , x t ]+b f ), the input gate output is i t =σ(W i •[h t-1 , x t ]+b i ), the current neuron state The output gate output is 0 t =σ(W o ·[h t-1 , x t ]+b o ), where W f , W i , W c , W o is the weight matrix, b f , b i , b c , b o is the bias term, [h t-1 , x t ] means to hide the state h t-1 and input x t The concatenation is performed horizontally, σ represents the activation function, and tanh represents the hyperbolic tangent activation function.

[0079] Step 5: Decode the output of the LSTM neural network through a fully connected deep neural network and output the predicted values ​​of all regional state parameters at the next moment. Finally With actual S t+1 By making comparisons and constructing the loss function, the network parameters in the above process are updated through back propagation to obtain the wind system control timing dynamics model.

[0080] With this scheme, the long short-term memory neural network encoder ~ fully connected deep neural network decoder architecture is used to reconstruct the time series diagram, and the state parameters of all regions and all coil control parameters at the past k moments and the state parameters S of all regions at the next moment are established. t+1 Such a time series dynamics model can comprehensively consider the temperature and humidity states and control parameters at multiple moments in the past, so as to make the control process of the HVAC system with strong time lag more stable and accurate.

[0081] Optionally, constructing an encoder includes but is not limited to long short-term memory neural network (LSTM), recurrent neural network (RNN) and other time series deep learning network methods. Constructing a decoder includes but is not limited to deep learning network methods such as a fully connected deep neural network (DNN). Among them, the allocation of model fixed parameters and update parameters includes not only fixing the parameters of the first few layers of the network and updating the parameters of the last layer of the network, but also various combined updates or fixed parameter forms.

[0082] Optionally, S32, the fan coil unit performs data processing on the opening state of the two-way valve of each fan coil unit at a historical moment, the air volume level, and the indoor temperature and indoor humidity of the area corresponding to each fan coil unit at a historical moment, including:

[0083] The fan coil unit screens out abnormal values ​​of the two-way valve opening status, air volume level, and indoor temperature and indoor humidity of the corresponding area of ​​each fan coil unit at historical moments.

[0084] The fan coil unit will perform steady-state screening on the two-way valve opening status, air volume level and indoor temperature and indoor humidity of the corresponding area of ​​each fan coil unit at historical moments after the abnormal values ​​are screened out.

[0085] The fan coil unit will normalize the two-way valve opening state, air volume level and indoor temperature and indoor humidity of the corresponding area of ​​each fan coil unit at the historical moment after steady-state screening.

[0086] In this solution, the fan coil can filter out abnormal values ​​of the two-way valve opening state, air volume level, and indoor temperature and indoor humidity of the corresponding area of ​​each fan coil at the historical moment. Here, abnormal values ​​can be filtered out according to the upper and lower limits of each data.

[0087] Furthermore, the fan coil can perform steady-state screening on the two-way valve opening state, air volume level, and indoor temperature and humidity of the corresponding area of ​​each fan coil at the historical moment after the abnormal values ​​are screened out. Here, the change range of each parameter can be used for steady-state screening. In this way, it is easy to obtain relatively stable data required for model construction.

[0088] Furthermore, the fan coil unit normalizes the two-way valve opening state, air volume level, and indoor temperature and indoor humidity of the corresponding area of ​​each fan coil unit at the historical moment after the steady-state screening. Here, the normalization process can be performed using the following formula:

[0089]

[0090] Among them, x nom is the normalized data value, x is the original data before normalization, and xmax 、x min are the maximum and minimum values ​​in the historical data of the parameter, respectively. With this solution, data can be effectively processed before model training to ensure the accuracy of model training data.

[0091] Optionally, S11, the fan coil unit determines an objective function according to a wind system power model, including:

[0092] min P t =f(A 1t , A 2t , ..., A nt )

[0093] Among them, P t is the total power of the fan coil at time t, (A 1t , A 2t , ..., A nt ) is the two-way valve opening status and air volume position of fan coil units No. 1 to No. n at time t.

[0094] In this scheme, in order to effectively reduce energy consumption, the constructed wind system power model and the real-time data obtained by the fan coil unit can be combined, and the minimization of power can be used as the objective function, providing an accurate data basis for the solution process of the fan coil unit target control parameters.

[0095] Figure 4 is a schematic diagram of a method for determining target constraint conditions provided by an embodiment of the present disclosure; Figure 4 As shown, optionally, in S12, the fan coil unit determines target constraints according to the wind system control time series dynamics model, including:

[0096] S41, the fan coil unit determines a first constraint condition according to a wind system control time series dynamics model.

[0097] S42, the fan coil unit sets the temperature and humidity values ​​for each indoor area and determines the second constraint condition.

[0098] S43, the fan coil unit uses the first constraint condition and the second constraint condition as target constraint conditions.

[0099] In this solution, the fan coil unit determines the first constraint condition based on the wind system control time series dynamics model, including:

[0100] S t+1 =f[(S t , S t-1 , ..., S t-k ), (A t , A t-1 , ..., A t-k )]

[0101] Among them, S t represents the state tensor representation of all fan coil units corresponding to the area at time t, and the state parameters include indoor temperature and indoor humidity; A t represents the control tensor representation of all fan coil units at time t, and the control parameters include the opening state of the two-way valve and the air volume gear.

[0102] In this solution, the fan coil unit determines the second constraint condition according to the set temperature and humidity values of each area in the room, including:

[0103] s.t. S t+1 = [[T 1 , R 1 , [T 2 , R 2 ,..., [T n , R n

[0104] Among them, T 1 , T 2 ,..., T n and R 1 , R 2 ,..., R n are the set temperature and humidity values of the spaces corresponding to the 1st to nth fan coil units respectively.

[0105] Furthermore, after the fan coil unit determines the first constraint condition and the second constraint condition, the first constraint condition and the second constraint condition are jointly used as the target constraint condition. With this solution, the accurate determination of the target constraint condition can be achieved.

[0106] Figure 5 is a schematic diagram of a device for controlling a fan coil unit provided by an embodiment of the present disclosure; as shown in Figure 5 shown, an embodiment of the present disclosure provides a device for controlling a fan coil unit, including a first determination module 51, a second determination module 52, an acquisition module 53 and a control module 54. The first determination module 51 is configured to determine an objective function according to the wind system power model; the second determination module 52 is configured to determine a target constraint condition according to the wind system control timing dynamics model; the acquisition module 53 is configured to solve according to the objective function and the target constraint condition to obtain the target control parameters of the fan coil unit; the control module 54 is configured to control the fan coil unit according to the target control parameters.

[0107] ​The device for controlling fan coil units provided by the embodiment of the present disclosure can be combined with the wind system power model to take minimizing power as the objective function; and combined with the wind system control time-series dynamics model to accurately determine the target constraints; thereby solving according to the objective function and the target constraints to obtain more accurate target control parameters of the fan coil units; and then, when the fan coil units are controlled according to the target control parameters, the fan coil units can be controlled more reasonably to minimize energy consumption while satisfying the temperature control of each area, thereby meeting the user's energy-saving control needs for the fan coil units.

[0108] Figure 6 is another schematic diagram of a device for controlling a fan coil unit provided by an embodiment of the present disclosure; Figure 6 As shown, the embodiment of the present disclosure provides a device 200 for controlling a fan coil unit, including a processor 201 and a memory 202. Optionally, the device may also include a communication interface 203 and a bus 204. The processor 201, the communication interface 203, and the memory 202 may communicate with each other through the bus 204. The communication interface 203 may be used for information transmission. The processor 201 may call the logic instructions in the memory 202 to execute the method for controlling a fan coil unit of the above embodiment.

[0109] In addition, the logic instructions in the memory 202 described above may be implemented in the form of software functional units and when sold or used as independent products, may be stored in a computer-readable storage medium.

[0110] The memory 202 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The processor 201 executes the function application and data processing by running the program instructions / modules stored in the memory 202, that is, the method for controlling the fan coil unit in the above embodiment is implemented.

[0111] The memory 202 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 202 may include a high-speed random access memory and may also include a non-volatile memory.

[0112] An embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to execute the above-mentioned method for controlling a fan coil unit.

[0113] The computer-readable storage medium mentioned above may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0114] The technical solution of the embodiment of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiment of the present disclosure. The aforementioned storage medium may be a non-transient storage medium, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes, or a transient storage medium.

[0115] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible changes. Unless explicitly required, separate components and functions are optional, and the order of operation may vary. The parts and features of some embodiments may be included in or replace the parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates, the singular forms of "a", "an" and "the" are intended to include plural forms as well. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of listings containing one or more associated ones. In addition, when used in the present application, the term "comprise" and its variants "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the presence of other identical elements in the process, method or device comprising the elements. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments may refer to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can refer to the description of the method part.

[0116] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods for each specific application to implement the described functions, but such implementations should not be considered to exceed the scope of the embodiments of the present disclosure. The technicians may clearly understand that, for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above may refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0117] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units can be only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to implement this embodiment. In addition, each functional unit in the embodiment of the present disclosure may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit.

[0118] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A method for controlling a fan coil unit, It is characterized in that include: Determine the objective function according to the wind system power model; Determine the target constraints based on the wind system control time series dynamics model; Solving according to the objective function and the objective constraint condition to obtain the target control parameters of the fan coil unit; The fan coil unit is controlled according to the target control parameter.

2. The method according to claim 1, It is characterized in that The wind system power model is constructed by: Obtain the total power of each fan coil unit at a historical moment and the two-way valve opening status and air volume level of each fan coil unit at a historical moment; Processing data on the total power of each fan coil unit at the historical moment and the opening state of the two-way valve of each fan coil unit and the air volume level at the historical moment; A wind system power model is constructed according to the processed total power of each fan coil unit at the historical moment and the two-way valve opening state and air volume level of each fan coil unit at the historical moment.

3. The method according to claim 2, It is characterized in that Data processing is performed on the total power of each fan coil unit at the historical moment and the opening state of the two-way valve of each fan coil unit at the historical moment, and the air volume gear, including: Screen out abnormal values ​​of the total power of each fan coil unit at the historical moment and the opening state of the two-way valve and the air volume level of each fan coil unit at the historical moment; The total power of each fan coil unit at the historical moment after the abnormal values ​​are screened out, and the two-way valve opening state and air volume level of each fan coil unit at the historical moment are screened in a steady state; The total power of each fan coil unit at the historical moment after steady-state screening, the two-way valve opening state and air volume level of each fan coil unit at the historical moment are normalized.

4. The method according to claim 1, It is characterized in that The wind system control time series dynamics model is constructed by: Obtain the two-way valve opening status, air volume level, and indoor temperature and humidity of the corresponding area of ​​each fan coil unit at the historical moment; Processing data on the opening state of the two-way valve of each fan coil unit at the historical moment, the air volume level, and the indoor temperature and indoor humidity of the area corresponding to each fan coil unit at the historical moment; According to the processed two-way valve opening state of each fan coil unit at the historical moment, the air volume gear and the indoor temperature and indoor humidity of the area corresponding to each fan coil unit at the historical moment, a wind system control time series dynamics model is constructed.

5. The method according to claim 4, It is characterized in that Data processing is performed on the opening state of the two-way valve of each fan coil unit at the historical moment, the air volume level, and the indoor temperature and indoor humidity of the area corresponding to each fan coil unit at the historical moment, including: Screen out abnormal values ​​of the two-way valve opening state, air volume level, and indoor temperature and indoor humidity of the area corresponding to each fan coil unit at the historical moment; The two-way valve opening state, air volume level and indoor temperature and indoor humidity of the corresponding area of ​​each fan coil unit at the historical moment after the abnormal values ​​are screened out are screened in a steady state; The two-way valve opening state, air volume level of each fan coil unit at the historical moment after steady-state screening, and the indoor temperature and indoor humidity of the corresponding area of ​​each fan coil unit at the historical moment are normalized.

6. The method according to claim 1, It is characterized in that According to the wind system power model, determine the objective function, including: minP t =f(A 1t ,A 2t ,…,A nt ) Among them, P t is the total power of the fan coil at time t, (A 1t ,A 2t ,…,A nt ) is the two-way valve opening status and air volume position of fan coil units No. 1 to No. n at time t.

7. The method according to claim 1, It is characterized in that According to the wind system control time series dynamics model, the target constraints are determined, including: Determine the first constraint condition according to the wind system control time series dynamics model; According to the temperature and humidity values ​​set in each indoor area, the second constraint condition is determined; The first constraint condition and the second constraint condition are used as target constraint conditions.

8. A device for controlling a fan coil unit, It is characterized in that include: A first determination module is configured to determine an objective function according to a wind system power model; A second determination module is configured to determine a target constraint condition according to a wind system control time series dynamics model; An acquisition module is configured to solve according to the objective function and the objective constraint condition to obtain the target control parameter of the fan coil unit; The control module is configured to control the fan coil unit according to the target control parameter.

9. A device for controlling a fan coil unit, comprising a processor and a memory storing program instructions, It is characterized in that The processor is configured to execute the method for controlling a fan coil unit according to any one of claims 1 to 7 when running the program instructions.

10. A storage medium storing program instructions, It is characterized in that When the program instructions are executed, the method for controlling a fan coil unit according to any one of claims 1 to 7 is executed.

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