Energy efficiency control method and system based on energy-saving air conditioner

Abstract

The application relates to the technical field of air conditioner energy efficiency control, and discloses an energy efficiency control method and system based on an energy-saving air conditioner, an energy efficiency control method based on an energy-saving air conditioner, which comprises the following steps: step S101, when being set as an intelligent energy efficiency management mode, entering step S102, and when being set as a forced energy efficiency management mode, entering step S105; step S102, generating an environment sequence through pretreatment; step S103, obtaining a target temperature through a target temperature prediction model; step S104, calculating an energy efficiency ratio, and combining the target temperature to realize the intelligent energy efficiency management mode; and step S105, calculating the energy efficiency ratio, combining an indoor temperature and a target temperature of an air conditioner system set by a user to realize the forced energy efficiency management; the application provides the intelligent energy efficiency management mode and the forced energy efficiency management mode, which can automatically adjust the compressor operation frequency and the fan operation rotating speed according to the energy efficiency ratio of the air conditioner system in real time, so that the energy efficiency ratio of the air conditioner system is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air conditioner energy efficiency control, more particularly, it relates to an energy efficiency control method and system based on energy-saving air conditioner. BACKGROUND

[0002] With the development of global economy and the acceleration of urbanization process, air conditioning system has become an indispensable part of modern building environment, however, the high energy consumption problem of air conditioning system is increasingly prominent, according to relevant statistical data, the energy consumption of air conditioning system accounts for 30% to 60% of the total building energy consumption, especially in summer and winter, due to the large temperature change and the increase of air conditioning frequency, the energy consumption of air conditioning system will also fluctuate greatly.

[0003] The existing air conditioning control method mainly depends on the set running mode, lacks real-time monitoring and self-adaptive adjustment function, and it is difficult to achieve the best energy efficiency ratio (COP) under the changing environmental conditions, and the existing air conditioning energy-saving control method mainly depends on the set energy-saving mode, which limits the speed of the compressor in the energy-saving mode, but in the case of heavy load or frequent load change, the lower speed of the compressor may not meet the comfort requirements of the user, resulting in the decline of user experience.

[0004] Therefore, an air conditioning energy-saving control method based on real-time monitoring is needed to improve the operation efficiency of air conditioning system. SUMMARY

[0005] The present application provides an energy efficiency control method and system based on energy-saving air conditioner, which solves the technical problems in the background art.

[0006] The present application provides an energy efficiency control method based on energy-saving air conditioner, comprising the following steps:

[0007] Step S101, when the user opens the energy efficiency management mode, and the energy efficiency management mode is set to intelligent energy efficiency management mode, then enter step S102, when the energy efficiency management mode is set to forced energy efficiency management mode, then enter step S105;

[0008] Step S102, in the first time period T1, the environmental parameters of the place where the air conditioning system is located are collected according to the first preset time interval t1, and the pre-processing is performed to generate the environment sequence;

[0009] The environmental parameters include indoor temperature and humidity, indoor air quality, outdoor temperature and humidity, outdoor air quality, outdoor rainfall and outdoor light intensity;

[0010] The environment sequence includes N sequence units, the nth sequence unit represents the environmental parameters of the nth time point after preprocessing, wherein 1≤n≤N, N=T1 / t;

[0011] Step S103, input the environment sequence into the target temperature prediction model, and output a value representing the target temperature of the air conditioning system in the second time period T2;

[0012] Step S104, collect the operating parameters of the air conditioning system to calculate the energy efficiency ratio of the air conditioning system, and adjust the compressor operating frequency and fan operating speed of the air conditioning system in combination with the target temperature of the air conditioning system in the second time period T2;

[0013] The operating parameters include: inlet water temperature, outlet water temperature, refrigerant flow and electric power;

[0014] The greater the value of the energy efficiency ratio, the higher the energy conversion efficiency and the less the power consumption;

[0015] Step S105, collect the operating parameters of the air conditioning system to calculate the energy efficiency ratio of the air conditioning system, and adjust the compressor operating frequency and fan operating speed of the air conditioning system in combination with the indoor temperature and the target temperature of the air conditioning system set by the user.

[0016] Further, the first time period T1, the preset time interval t1 and the second time period T2 are all self-defined parameters.

[0017] Further, the environment sequence is generated by preprocessing the environment parameters, including the following steps:

[0018] Step S201, for the missing values in the environment parameters, the missing values are filled by interpolation by taking the average of the environment parameters of the adjacent two time points;

[0019] Step S202, calculate the change rate of the environment parameters at each time point respectively, and splice the change rate with the environment parameters at each time point to obtain a combined vector;

[0020] The change rate of the environment parameters at the first time point is assigned as 1;

[0021] Step S203, normalize each combined vector at each time point by the standard score method to obtain the environment sequence.

[0022] Further, the target temperature prediction model includes N hidden layers, and each hidden layer includes: a first unit and a second unit;

[0023] The first unit of the nth hidden layer inputs the nth sequence unit of the environment sequence, and outputs an update matrix;

[0024] The second unit of the nth hidden layer inputs the update matrix output by the first unit of the nth hidden layer, and outputs an update vector;

[0025] The update vector output by the second unit of the nth hidden layer is input to the first classifier, and the classification space of the first classifier represents the target temperature of the air conditioning system in the second time period T2.

[0026] Further, the calculation formula of the target temperature prediction model comprises:

[0027] The calculation formula of the first unit of the nth hidden layer is as follows:

[0028] ;

[0029] Wherein represents the update matrix output by the first unit of the nth hidden layer, represents the nth sequence unit of the environment sequence input by the first unit of the nth hidden layer, and respectively represent the weight parameter and the bias parameter of the first unit of the nth hidden layer, represents the convolution operation with a convolution kernel of 3x3 size and a step of 1, represents the maximum pooling operation with a pooling window of 3x3 size and a step of 1, and sigmoid represents the sigmoid activation function.

[0030] The calculation formula of the second unit of the nth hidden layer comprises:

[0031] ;

[0032] ;

[0033] ;

[0034] Wherein represents the update vector output by the second unit of the nth hidden layer, represents the intermediate vector of the second unit of the nth hidden layer, and respectively represent the update matrix input by the second unit of the nth and (n-1)th hidden layers, represented by a matrix with the same size as the update matrix and element values of 0, represents and the correlation coefficient between and, K represents the number of elements of the update matrix, spread represents the expansion of the matrix into a vector representation and the sorting according to the element values from small to large, and Rank represents the rank value calculation. and respectively represent the first weight parameter and the second weight parameter of the second unit of the nth hidden layer, and respectively represent the first bias parameter and the second bias parameter of the second unit of the nth hidden layer, and Swish represents a Swish activation function.

[0035] Further, a plurality of independent experimental rooms are built to simulate the same environmental parameters, and sample data of the training samples for training the target temperature prediction model are obtained according to steps S101 to S102, and then the target temperature of each independent experimental room is set artificially, the difference between the target temperatures of each independent experimental room cannot exceed 5℃, and after the second time period T2, the target temperature with the maximum average value of the comfort of the multiple persons in the experimental room is taken as the sample label of the training sample for training the target temperature prediction model.

[0036] Further, the calculation formula of the energy efficiency ratio COP of the air conditioning system is as follows:

[0037] ;

[0038] wherein Cp represents the specific heat capacity at constant pressure, and is assigned a value of 4.1868 KJ / kg·℃, R represents the specific gravity of the refrigerant, and is assigned a value of 1000 Kg / m³, represents the refrigerant flow rate, in units of m³ / h, Ts represents the outlet water temperature, in units of ℃, Tw represents the inlet water temperature, in units of ℃, and P represents the electric power, in units of kW.

[0039] Further, the intelligent energy efficiency management mode adjusts the compressor operating frequency and the fan operating speed of the air conditioning system, including the following steps:

[0040] Step S301, the absolute value of the difference between the outlet water temperature and the target temperature of the air conditioning system within the second time period T2 is calculated as a temperature difference value, and it is judged whether the temperature difference value is less than or equal to 1℃, and if so, step S302 is entered;

[0041] Step S302, within the third time period T3, the energy efficiency ratio is calculated according to the second preset time interval t2, and the average value of the energy efficiency ratios of all time points is calculated as an energy efficiency ratio reference value;

[0042] wherein the third time period T3 and the second preset time interval t2 are both self-defined parameters;

[0043] Step S303, it is judged whether the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 1℃, then the compressor operating frequency is reduced by 1 Hz and runs for 30 seconds, and step S304 is entered;

[0044] Step S304, it is judged whether the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 1℃, then the fan operating speed is reduced by 1% and runs for 30 seconds, and step S305 is entered;

[0045] Step S305, the energy efficiency ratio of the current time point is less than the energy efficiency ratio reference value or the temperature difference value is greater than 1℃, then stop adjusting, return to step S301.

[0046] Further, the forced energy efficiency management mode adjusts the compressor operating frequency and the fan operating speed of the air conditioning system, comprising the following steps:

[0047] Step S401, judge whether the indoor temperature is in the preset indoor temperature range and the outlet water temperature is in the preset outlet water temperature range, then determine the energy efficiency ratio reference value according to the mapping relationship between the indoor temperature, the outlet water temperature and the preset energy efficiency ratio;

[0048] Wherein, the preset indoor temperature range, the preset outlet water temperature range and the mapping relationship between the indoor temperature, the outlet water temperature and the preset energy efficiency ratio are all self-defined settings;

[0049] Step S402, calculate the absolute value of the difference between the outlet water temperature and the target temperature of the air conditioning system set by the user as the temperature difference value, and judge whether the temperature difference value is less than or equal to 2℃, then enter step S403;

[0050] Step S403, judge whether the energy efficiency ratio of the current time point is greater than or equal to the energy efficiency ratio reference value and the temperature difference value is less than or equal to 2℃, then reduce the compressor operating frequency by 1 Hz and run for 30 seconds, enter step S404;

[0051] Step S404, judge whether the energy efficiency ratio of the current time point is greater than or equal to the energy efficiency ratio reference value and the temperature difference value is less than or equal to 2℃, then reduce the fan operating speed by 1% and run for 30 seconds, enter step S405;

[0052] Step S405, the energy efficiency ratio of the current time point is less than the energy efficiency ratio reference value or the temperature difference value is greater than 2℃, then stop adjusting, return to step S401.

[0053] The present application provides an energy efficiency control system based on energy-saving air conditioner, comprising:

[0054] An environment sequence generation module is used to collect the environmental parameters of the location of the air conditioning system in a first time period T1 according to a first preset time interval t1, and generate an environment sequence after preprocessing.

[0055] A target temperature prediction module is used to input the environment sequence into a target temperature prediction model, and the output value represents the target temperature of the air conditioning system in a second time period T2.

[0056] An intelligent energy efficiency management module is used to collect the operating parameters of the air conditioning system, to calculate the energy efficiency ratio of the air conditioning system, and to adjust the compressor operating frequency and the fan operating speed of the air conditioning system in combination with the target temperature of the air conditioning system in the second time period T2.

[0057] The forced energy efficiency management module is used for collecting the operation parameters of the air conditioning system, so as to calculate the energy efficiency ratio of the air conditioning system, and adjust the compressor operation frequency and the fan operation rotating speed of the air conditioning system in combination with the indoor temperature and the target temperature of the air conditioning system set by the user.

[0058] The present application has the beneficial effect that the present application provides the intelligent energy efficiency management mode and the forced energy efficiency management mode to automatically adjust the compressor operation frequency and the fan operation rotating speed according to the calculated energy efficiency ratio of the air conditioning system in real time, so as to improve the energy efficiency ratio of the air conditioning system, and the intelligent energy efficiency management mode predicts the target temperature of the air conditioning system through the target temperature prediction model, so as to ensure the comfort of the user. BRIEF DESCRIPTION OF DRAWINGS

[0059] Figure 1 is a flow chart of an energy efficiency control method based on an energy-saving air conditioner of the present application;

[0060] Figure 2 is a flow chart of the pre-processing generation environment sequence of the present application;

[0061] Figure 3 is a flow chart of the intelligent energy efficiency management mode of the present application;

[0062] Figure 4 is a flow chart of the forced energy efficiency management mode of the present application;

[0063] Figure 5 is a schematic diagram of an energy efficiency control system based on an energy-saving air conditioner of the present application;

[0064] Figure 6 is a schematic diagram of the mapping relationship between the indoor temperature and the outlet water temperature and the preset energy efficiency ratio of the present application.

[0065] In the figure: the environment sequence generation module 501, the target temperature prediction module 502, the intelligent energy efficiency management module 503, and the forced energy efficiency management module 504. DETAILED DESCRIPTION

[0066] The subject matter described herein will now be discussed with reference to example implementations. It should be understood that discussions of these implementations are merely provided to enable those skilled in the art to better understand subject matter in order to better utilize from the subject matter described herein, and variations of elements can be made dependant on design within the scope of the present specification. Each example can omit, substitute, or add various procedures or components as desired. In addition, features described in relation to some examples can also be combined in other examples.

[0067] It should be noted that the technical terms or scientific terms used in one or more embodiments of the present application should be understood as the general meaning understood by those skilled in the art of the field to which the present application belongs, unless otherwise defined. The terms "first", "second", and similar terms used in one or more embodiments of the present application do not represent any order, number, or importance, but are only used to distinguish different components. The terms "include" or "contain" and similar terms mean that the elements or objects appearing before the terms encompass the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connected" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "up", "down", "left", "right", and the like are only used to represent relative positional relationships, and when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0068] As shown in Figures 1-6 An energy efficiency control method based on an energy-saving air conditioner, comprising the following steps:

[0069] Step S101, when the user starts the energy efficiency management mode, and the energy efficiency management mode is set to the intelligent energy efficiency management mode, step S102 is entered, and when the energy efficiency management mode is set to the forced energy efficiency management mode, step S105 is entered;

[0070] Step S102, in the first time period T1, the environmental parameters of the air conditioning system are collected according to the first preset time interval t1, and preprocessed to generate an environmental sequence;

[0071] The environmental parameters include indoor temperature and humidity, indoor air quality, outdoor temperature and humidity, outdoor air quality, outdoor rainfall, and outdoor light intensity;

[0072] The environmental sequence includes N sequence units, and the nth sequence unit represents the environmental parameters at the nth time point after preprocessing, wherein 1≤n≤N, and N=T1 / t;

[0073] Step S103, inputting the environmental sequence into a target temperature prediction model, and outputting a value representing the target temperature of the air conditioning system in the second time period T2;

[0074] Step S104, collecting the operating parameters of the air conditioning system to calculate the energy efficiency ratio of the air conditioning system, and adjusting the compressor operating frequency and the fan operating speed of the air conditioning system in combination with the target temperature of the air conditioning system in the second time period T2;

[0075] The operating parameters include water inlet temperature, water outlet temperature, refrigerant flow, and electric power;

[0076] The greater the value of the energy efficiency ratio is, the higher the energy conversion efficiency is, and the less the power consumption is.

[0077] In step S105, the operation parameters of the air conditioning system are collected to calculate the energy efficiency ratio of the air conditioning system, and the compressor operation frequency and the fan operation speed of the air conditioning system are adjusted in combination with the indoor temperature and the target temperature of the air conditioning system set by the user.

[0078] It should be noted that the opening and closing of the energy efficiency management mode are controlled by the user, and the opening and closing of the intelligent energy efficiency management mode and the forced energy efficiency management mode are also controlled by the user, wherein the intelligent energy efficiency management mode is to predict the target temperature of the air conditioning system that needs to be adjusted in a future time period according to the environmental parameters by a target temperature prediction model, and then automatically adjust the compressor operation frequency and the fan operation speed of the air conditioning system according to the energy efficiency ratio of the air conditioning system calculated in real time, mainly for the purpose of meeting the comfort of the user; and the forced energy efficiency management mode is to adjust the compressor operation frequency and the fan operation speed of the air conditioning system according to the indoor temperature and the target temperature of the air conditioning system set by the user, mainly for the purpose of energy saving and optimizing the energy efficiency ratio.

[0079] In an embodiment of the present application, the air quality is represented by inhalable particulate matter (PM2.5), which is collected by a PM2.5 detector, and the air quality can also be represented by carbon dioxide concentration, which is collected by a carbon dioxide concentration detector, the temperature and humidity, rainfall and light intensity are collected by a temperature and humidity sensor, a rain gauge and a light intensity sensor respectively, the refrigerant flow is collected by a liquid flow sensor, and the electric power is collected by an electric energy meter.

[0080] In an embodiment of the present application, the first time period T1, the preset time interval t1 and the second time period T2 are all self-defined parameters, preferably, the first time period T1 is set to 5 minutes, the preset time interval t1 is set to 15 seconds, then N=T1 / t1=20, and the second time period T2 is set to 30 minutes.

[0081] In an embodiment of the present application, as shown in Figure 2 The environmental parameters are preprocessed to generate an environmental sequence, including the following steps:

[0082] In step S201, for the missing values in the environmental parameters, the missing values are filled by interpolation by taking the average of the environmental parameters of the adjacent two time points;

[0083] In step S202, the change rate of the environmental parameters at each time point is calculated respectively, and is spliced with the environmental parameters at each time point to obtain a combined vector;

[0084] The change rate of the environmental parameters at the first time point is assigned as 1.

[0085] Step S203, normalize the combined vector of each time point by the standard score (Z-score) method to obtain an environment sequence.

[0086] It should be noted that the normalized combined vector corresponds to a sequence unit of the environment sequence, and the size of the normalized combined vector is 1x16, that is, the dimension number is 16, which is respectively 8 values of the environment parameters and 8 change rate values of the environment parameters, in addition, the average value, maximum value, minimum value, skewness and kurtosis of the environment parameters can be extracted, which will not be repeated here.

[0087] In an embodiment of the present application, the target temperature prediction model includes N hidden layers, each of which includes a first unit and a second unit.

[0088] The first unit of the nth hidden layer inputs the nth sequence unit of the environment sequence and outputs an update matrix.

[0089] The second unit of the nth hidden layer inputs the update matrix output by the first unit of the nth hidden layer and outputs an update vector.

[0090] The update vector output by the second unit of the Nth hidden layer is input to a first classifier, and the classification space of the first classifier represents the target temperature of the air conditioning system in the second time period T2.

[0091] In an embodiment of the present application, the calculation formula of the target temperature prediction model includes:

[0092] The calculation formula of the first unit of the nth hidden layer is as follows:

[0093] ;

[0094] wherein represents the update matrix output by the first unit of the nth hidden layer, represents the nth sequence unit of the environment sequence input by the first unit of the nth hidden layer, and respectively represent the weight parameter and the bias parameter of the first unit of the nth hidden layer, represents a convolution operation with a convolution kernel of 3x3 size and a step of 1, represents a maximum pooling operation with a pooling window of 3x3 size and a step of 1, and sigmoid represents a sigmoid activation function.

[0095] The calculation formula of the second unit of the nth hidden layer includes:

[0096] ;

[0097] ;

[0098] ;

[0099] wherein denotes the update vector of the second unit output of the nth hidden layer, denotes the intermediate vector of the second unit of the nth hidden layer, and denote the update matrix of the second unit input of the nth and the (n-1)th hidden layer respectively, denoted by a matrix with the same size as the update matrix and with all elements being 0, denotes and the correlation coefficient between and, K denotes the number of elements of the update matrix, spread denotes the expansion of the matrix into a vector and the sorting according to the element values from small to large, and Rank denotes the rank value calculation, and denote the first weight parameter and the second weight parameter of the second unit of the nth hidden layer respectively, and denote the first bias parameter and the second bias parameter of the second unit of the nth hidden layer respectively, and Swish denotes the Swish activation function.

[0100] It should be noted that the calculation of the update vector does not need to rely on the output of the previous hidden layer when calculating the output of the current hidden layer, like RNN (recurrent neural network model) or LSTM (long short-term memory neural network model). The second unit provided in the present application calculates the correlation between the output of the current hidden layer and the output of the previous hidden layer through the Spearman rank correlation coefficient, realizes the "gate" function through the Spearman rank correlation coefficient, and can be calculated and trained in parallel, thereby greatly improving the calculation speed of the target temperature prediction model.

[0101] It should be noted that the weight parameters and bias parameters in the target temperature prediction model are all learnable hyperparameters, for example the size of is 1x16, can be designed as a 16x1 size vector, and the multiplication of the two obtains a 16x16 size matrix, which is subjected to a convolution operation with a 3x3 size convolution kernel and a step size of 1 to obtain a 14x14 size matrix, and then subjected to a maximum pooling operation with a 3x3 size pooling window and a step size of 1 to obtain a 12x12 size matrix, so the size of the update matrix is 12x12, and K is equal to 12x12, which is equal to 144, and can be designed as a 1x12 size vector, and the size of the intermediate vector is 1x12, The matrix can be designed to be 12*8 in size, and the size of the updated vector obtained by multiplying the two is 1*8.

[0102] In one embodiment of the present application, a plurality of independent experimental rooms are built to simulate the same environmental parameters, and sample data of the training samples for training the target temperature prediction model are obtained according to steps S101 to S102, then the target temperature of each independent experimental room is set artificially, the difference between the target temperatures of each independent experimental room cannot exceed 5℃, and after the second time period T2, the target temperature with the maximum average comfort level of the personnel in the experimental room is taken as the sample label of the training sample for training the target temperature prediction model.

[0103] In one embodiment of the present application, one training sample includes one sample data and one sample label, and the signs of the personnel in each experimental room are as close as possible to ensure the accuracy of the target temperature prediction model prediction. In addition, in order to speed up the training speed of the target temperature prediction model, pre-training can be added, and the updated vector output by the second unit of the Nth hidden layer is input into the second classifier, and the classification space of the second classifier represents the indoor temperature in the second time period T2.

[0104] It should be noted that the mean square error between the prediction value of the target temperature prediction model and the sample label of the training sample is specified as the loss function, and the weight parameters and bias parameters of the target temperature prediction model are updated through the chain rule and the gradient descent algorithm, so that the loss value obtained by the loss function calculation is minimized.

[0105] In one embodiment of the present application, the calculation formula of the energy efficiency ratio COP of the air conditioning system is as follows:

[0106] ;

[0107] Wherein Cp represents the specific heat capacity at constant pressure, and is assigned a value of 4.1868 KJ / kg·℃, R represents the specific gravity of the refrigerant, and is assigned a value of 1000 Kg / m³, Q represents the refrigerant flow rate, with a unit of m³ / h, Ts represents the outlet water temperature, with a unit of ℃, Tw represents the inlet water temperature, with a unit of ℃, and P represents the electric power, with a unit of kW.

[0108] In one embodiment of the present application, as shown in Figure 3 The intelligent energy efficiency management mode adjusts the operating frequency of the compressor and the operating speed of the fan of the air conditioning system, including the following steps:

[0109] Step S301, calculate the absolute value of the difference between the outlet water temperature and the target temperature of the air conditioning system in the second time period T2 as a temperature difference value, and determine whether the temperature difference value is less than or equal to 1℃, then enter step S302;

[0110] Step S302, in the third time period T3, the energy efficiency ratio is calculated according to the second preset time interval t2, and the average value of the energy efficiency ratio at all time points is calculated as the energy efficiency ratio reference value;

[0111] Wherein the third time period T3 and the second preset time interval t2 are both self-defined parameters, preferably, the third time period T3 is set to 3 minutes, and the second preset time interval t2 is set to 10 seconds;

[0112] Step S303, if the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 1℃, the compressor operating frequency is reduced by 1 Hz and runs for 30 seconds, and step S304 is entered;

[0113] Step S304, if the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 1℃, the fan operating speed is reduced by 1% and runs for 30 seconds, and step S305 is entered;

[0114] Step S305, if the energy efficiency ratio at the current time point is less than the energy efficiency ratio reference value or the temperature difference value is greater than 1℃, the adjustment is stopped, and step S301 is returned.

[0115] In an embodiment of the present application, as shown in Figure 4 The forced energy efficiency management mode adjusts the compressor operating frequency and the fan operating speed of the air conditioning system, including the following steps:

[0116] Step S401, if the indoor temperature is in the preset indoor temperature range, and the outlet water temperature is in the preset outlet water temperature range, the energy efficiency ratio reference value is determined according to the mapping relationship between the indoor temperature, the outlet water temperature and the preset energy efficiency ratio;

[0117] Wherein the preset indoor temperature range, the preset outlet water temperature range and the mapping relationship between the indoor temperature, the outlet water temperature and the preset energy efficiency ratio are all self-defined settings;

[0118] Step S402, the absolute value of the difference between the outlet water temperature and the target temperature of the air conditioning system set by the user is calculated as the temperature difference value, and if the temperature difference value is less than or equal to 2℃, step S403 is entered;

[0119] Step S403, if the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 2℃, the compressor operating frequency is reduced by 1 Hz and runs for 30 seconds, and step S404 is entered;

[0120] Step S404, if the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 2℃, the fan operating speed is reduced by 1% and runs for 30 seconds, and step S405 is entered;

[0121] Step S405, if the energy efficiency ratio at the current time point is less than the energy efficiency ratio reference value or the temperature difference value is greater than 2℃, stop adjusting and return to step S401.

[0122] In one embodiment of the present application, as shown in Figure 5 An energy efficiency control system based on an energy-saving air conditioner, comprising:

[0123] An environment sequence generation module 501 is configured to collect environment parameters of a location of the air conditioner system at a first preset time interval t1 within a first time period T1, and generate an environment sequence after preprocessing.

[0124] A target temperature prediction module 502 is configured to input the environment sequence into a target temperature prediction model, and output a value representing a target temperature of the air conditioner system within a second time period T2.

[0125] An intelligent energy efficiency management module 503 is configured to collect operation parameters of the air conditioner system, calculate an energy efficiency ratio of the air conditioner system, and adjust a compressor operating frequency and a fan operating speed of the air conditioner system in combination with the target temperature of the air conditioner system within the second time period T2.

[0126] A forced energy efficiency management module 504 is configured to collect operation parameters of the air conditioner system, calculate an energy efficiency ratio of the air conditioner system, and adjust a compressor operating frequency and a fan operating speed of the air conditioner system in combination with an indoor temperature and a target temperature of the air conditioner system set by a user.

[0127] The above describes the embodiments of the present application, but the present application is not limited to the above specific embodiments, and the above specific embodiments are only illustrative but not restrictive. Those skilled in the art can make many forms under the inspiration of the present application, which are all within the protection scope of the present application.

Claims

1. An energy efficiency control method based on an energy-saving air conditioner, characterized by, The method comprises the following steps: Step S101, when the user starts the energy efficiency management mode, and the energy efficiency management mode is set to the intelligent energy efficiency management mode, step S102 is entered, and when the energy efficiency management mode is set to the forced energy efficiency management mode, step S105 is entered; Step S102, in a first time period T1, environment parameters of a place where the air conditioning system is located are collected according to a first preset time interval t1, and pre-processing is performed to generate an environment sequence; The environment parameters include indoor temperature and humidity, indoor air quality, outdoor temperature and humidity, outdoor air quality, outdoor rainfall and outdoor light intensity; The environment sequence includes N sequence units, and the nth sequence unit represents the environment parameters at the nth time point after pre-processing, wherein 1≤n≤N, and N=T1 / t1; Step S103, the environment sequence is input into a target temperature prediction model, and a value output by the target temperature prediction model represents a target temperature of the air conditioning system in a second time period T2; Step S104, operation parameters of the air conditioning system are collected, the energy efficiency ratio of the air conditioning system is calculated, and the compressor operation frequency and the fan operation speed of the air conditioning system are adjusted in combination with the target temperature of the air conditioning system in the second time period T2; The operation parameters include water inlet temperature, water outlet temperature, refrigerant flow and electric power; The greater the value of the energy efficiency ratio is, the higher the energy conversion efficiency is, and the less the power consumption is; Step S105, operation parameters of the air conditioning system are collected, the energy efficiency ratio of the air conditioning system is calculated, and the compressor operation frequency and the fan operation speed of the air conditioning system are adjusted in combination with the indoor temperature and the target temperature of the air conditioning system set by the user.

2. The energy efficiency control method based on an energy-saving air conditioner according to claim 1, characterized by, The first time period T1, the preset time interval t1 and the second time period T2 are all self-defined parameters.

3. The energy efficiency control method based on an energy-saving air conditioner according to claim 1, characterized by, The pre-processing of the environment parameters to generate the environment sequence comprises the following steps: Step S201, for missing values in the environment parameters, the missing values are filled by interpolation by taking the average of the environment parameters at the adjacent two time points of the missing values; Step S202, the change rate of the environment parameters at each time point is calculated respectively, and the change rate is spliced with the environment parameters at each time point to obtain a combination vector; The change rate of the environment parameters at the first time point is assigned as 1; Step S203, the combination vector at each time point is normalized by a standard score method to obtain the environment sequence.

4. The energy efficiency control method based on an energy-saving air conditioner according to claim 1, characterized by, The target temperature prediction model comprises N hidden layers, and each hidden layer comprises a first unit and a second unit; The first unit of the nth hidden layer inputs the nth sequence unit of the environment sequence, and outputs an update matrix; The second unit of the nth hidden layer inputs the update matrix output by the first unit of the nth hidden layer, and outputs an update vector; The update vector output by the second unit of the Nth hidden layer is input into a first classifier, and the classification space of the first classifier represents the target temperature of the air conditioning system in the second time period T2.

5. The energy efficiency control method based on an energy-saving air conditioner according to claim 4, characterized by, The calculation formula of the target temperature prediction model comprises: The calculation formula of the first unit of the nth hidden layer is as follows: ； wherein represents an update matrix of the first unit output of the nth hidden layer, represents the nth sequence unit of the environment sequence input of the first unit of the nth hidden layer, and respectively represent a weight parameter and a bias parameter of the first unit of the nth hidden layer, represents a convolution operation with a convolution kernel of 3x3 size and a step of 1, represents a max-pooling operation with a pooling window of 3x3 size and a step of 1, and sigmoid represents a sigmoid activation function. The calculation formula of the second unit of the nth hidden layer comprises: ； ； ； wherein denotes an update vector of the second unit output of the n-th hidden layer, denotes an intermediate vector of the second unit of the n-th hidden layer, and denote an update matrix of the second unit input of the n-th and n-1-th hidden layer, respectively, denoted by a matrix of the same size as the update matrix with element values of 0, denotes and a correlation coefficient between and, K denotes the number of elements of the update matrix, spread denotes a spread of the matrix into a vector and sorting according to the element values from small to large, and Rank denotes a rank value calculation, and denote a first weight parameter and a second weight parameter of the second unit of the n-th hidden layer, respectively, and denote a first bias parameter and a second bias parameter of the second unit of the n-th hidden layer, respectively, and Swish denotes a Swish activation function.

6. The energy efficiency control method based on an energy-saving air conditioner according to claim 1, characterized by, A plurality of independent experimental rooms are built to simulate the same environmental parameters, and sample data of the training samples for training the target temperature prediction model are obtained according to steps S101 to S102, then the target temperature of each independent experimental room is set manually, the difference between the target temperatures of each independent experimental room cannot exceed 5℃, and after the second time period T2, the target temperature with the maximum average value of the comfort levels of the multiple persons in the experimental room is taken as the sample label of the training sample for training the target temperature prediction model.

7. The energy efficiency control method based on an energy-saving air conditioner according to claim 1, characterized by, The calculation formula of the energy efficiency ratio COP of the air conditioning system is as follows: ； wherein Cp represents the specific heat capacity at constant pressure, assigned the value 4.1868 KJ / kg-°C, R represents the refrigerant specific weight, assigned the value 1000 Kg / m3, represents the refrigerant flow rate, in m3 / h, Ts represents the outlet water temperature, in °C, Tw represents the inlet water temperature, in °C, and P represents the electric power, in kW.

8. The energy efficiency control method based on an energy-saving air conditioner according to claim 1, characterized by, The intelligent energy efficiency management mode adjusts the compressor operating frequency and the fan operating speed of the air conditioning system, including the following steps: Step S301, the absolute value of the difference between the water temperature and the target temperature of the air conditioning system in the second time period T2 is calculated as the temperature difference value, and it is judged whether the temperature difference value is less than or equal to 1℃, and if so, step S302 is entered; Step S302, in the third time period T3, the energy efficiency ratio is calculated according to the second preset time interval t2, and the average value of the energy efficiency ratios at all time points is calculated as the energy efficiency ratio reference value; Wherein the third time period T3 and the second preset time interval t2 are both self-defined parameters; Step S303, it is judged whether the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 1℃, then the compressor operating frequency is reduced by 1 Hz and runs for 30 seconds, and step S304 is entered; Step S304, it is judged whether the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 1℃, then the fan operating speed is reduced by 1% and runs for 30 seconds, and step S305 is entered; Step S305, the energy efficiency ratio at the current time point is less than the energy efficiency ratio reference value or the temperature difference value is greater than 1℃, then the adjustment is stopped, and step S301 is returned.

9. The energy efficiency control method based on an energy-saving air conditioner according to claim 1, characterized by, The forced energy efficiency management mode adjusts the compressor operating frequency and the fan operating speed of the air conditioning system, including the following steps: Step S401, it is judged whether the indoor temperature is in the preset indoor temperature range and the outlet water temperature is in the preset outlet water temperature range, then the energy efficiency ratio reference value is determined according to the mapping relationship between the indoor temperature, the outlet water temperature and the preset energy efficiency ratio; Wherein the preset indoor temperature range, the preset outlet water temperature range and the mapping relationship between the indoor temperature, the outlet water temperature and the preset energy efficiency ratio are all self-defined settings; Step S402, the absolute value of the difference between the outlet water temperature and the target temperature of the air conditioning system set by the user is calculated as the temperature difference value, and it is judged whether the temperature difference value is less than or equal to 2℃, and if so, step S403 is entered; Step S403, it is judged whether the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 2℃, then the compressor operating frequency is reduced by 1 Hz and runs for 30 seconds, and step S404 is entered; Step S404, it is judged whether the energy efficiency ratio at the current time point is greater than or equal to the energy efficiency ratio reference value, and the temperature difference value is less than or equal to 2℃, then the fan operating speed is reduced by 1% and runs for 30 seconds, and step S405 is entered; Step S405, the energy efficiency ratio at the current time point is less than the energy efficiency ratio reference value or the temperature difference value is greater than 2℃, then the adjustment is stopped, and step S401 is returned.

10. An energy efficiency control system based on an energy saving air conditioner, characterized by, The energy efficiency control method based on the energy-saving air conditioner according to any one of claims 1 to 9 is executed, comprising: an environment sequence generation module for collecting environment parameters of a place where the air conditioning system is located at a first preset time interval t1 in a first time period T1, and generating an environment sequence after preprocessing; a target temperature prediction module for inputting the environment sequence into a target temperature prediction model, and outputting a value representing a target temperature of the air conditioning system in a second time period T2; an intelligent energy efficiency management module for collecting operation parameters of the air conditioning system, calculating an energy efficiency ratio of the air conditioning system, and adjusting a compressor operation frequency and a fan operation speed of the air conditioning system in combination with the target temperature of the air conditioning system in the second time period T2; a forced energy efficiency management module for collecting operation parameters of the air conditioning system, calculating an energy efficiency ratio of the air conditioning system, and adjusting a compressor operation frequency and a fan operation speed of the air conditioning system in combination with an indoor temperature and a target temperature of the air conditioning system set by a user.

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