Energy-saving control system and method for cooling tower

Abstract

The invention discloses an energy-saving control system and method for a cooling tower, and the system comprises an obtaining module which is used for obtaining historical control data of different devices in the cooling tower under different historical working condition demands; the screening module is used for screening out energy consumption associated control data of each device under different historical working condition requirements and generating a historical energy-saving evaluation value; the construction module is used for constructing an optimal data set according to the energy consumption associated control data and the historical energy-saving evaluation value, and constructing an energy-saving control model of the corresponding equipment; and the control module is used for obtaining real-time optimal control data of each device under the real-time working condition demand based on the energy-saving control model, generating a control strategy according to the real-time optimal control data, reducing the energy consumption in the use process of the cooling tower, improving the cooling efficiency of the cooling tower and realizing energy-saving optimal control of the cooling tower.

Description

Technical Field

[0001] The present application relates to the technical field of cooling tower energy-saving control, and in particular to an energy-saving control system and method for a cooling tower. Background Art

[0002] A cooling tower is an auxiliary device that uses water as a circulating coolant to absorb heat from a system and discharge it into the atmosphere to avoid excessive temperature in the system and ensure the normal operation of the system. It has been widely used in many fields such as steel mills, thermal power plants, and petrochemicals. However, in the use of cooling towers, a large amount of energy and water resources are often wasted, which seriously affects production efficiency and economic benefits. Therefore, there is an urgent need for an energy-saving control system and method for cooling towers to achieve energy-saving control and optimization of cooling towers. Summary of the invention

[0003] To solve the above technical problems, the present application provides an energy-saving control system and method for a cooling tower. By screening the energy consumption management control data of different equipment in the cooling tower under different historical operating conditions and calculating the corresponding historical energy-saving evaluation values, an optimal data set and an energy-saving control model of the corresponding equipment are constructed, thereby obtaining the optimal control data for each equipment under real-time operating conditions, reducing the energy consumption during the use of the cooling tower and improving the cooling efficiency of the cooling tower, thereby realizing energy-saving optimization control of the cooling tower.

[0004] In some embodiments of the present application, a cooling tower energy-saving control system is provided, comprising:

[0005] An acquisition module is used to acquire historical control data of different equipment in the cooling tower under different historical working conditions;

[0006] A screening module is used to perform energy consumption correlation analysis on the historical control data, screen out energy consumption correlation control data of each device under different historical working conditions, and generate a historical energy-saving evaluation value of the energy consumption correlation control data;

[0007] A construction module is used to construct a preferred data set according to the energy consumption associated control data and the corresponding historical energy-saving evaluation value, and to construct an energy-saving control model for the corresponding equipment based on the preferred data set;

[0008] The control module is used to obtain the real-time optimal control data of each device under the real-time working condition requirements based on the energy-saving control model, and generate a control strategy according to the real-time optimal control data.

[0009] In some embodiments of the present application, energy consumption correlation analysis is performed on the historical control data to filter out energy consumption correlation control data of each device, including:

[0010] Dividing the historical control data of different equipment in the cooling tower under different historical working condition requirements into a plurality of historical control data groups, each of which includes a plurality of historical control data of the same equipment in the cooling tower under the same historical working condition requirements;

[0011] Establishing a time reference line for the preset control time of each historical control data group, and plotting each historical control data and the corresponding equipment energy consumption value in the historical control data group on the corresponding time reference line;

[0012] Performing a change degree analysis on the historical control data on the same time reference line, marking a change time node whose first change degree is greater than a preset first change degree threshold, and marking the corresponding historical control data at the same time;

[0013] Obtaining a second change degree of the energy consumption value in a time period after the marked change time node, and determining the energy consumption correlation degree of the marked historical control data under the corresponding historical operating condition demand according to the number of second change degrees greater than a preset second change degree threshold and the second change degree difference amount of the second change degree greater than the preset second change degree threshold;

[0014] Pre-set energy consumption correlation degree threshold;

[0015] If the energy consumption correlation degree of the historical control data under the corresponding historical operating condition demand is greater than the energy consumption correlation degree threshold, the historical control data is set as the energy consumption correlation control data under the corresponding historical operating condition demand.

[0016] In some embodiments of the present application, determining the energy consumption correlation degree of the marked historical control data under the corresponding historical operating condition requirements includes:

[0017] The calculation formula of the energy consumption correlation degree is:

[0018] ;

[0019] Among them, H is the energy consumption correlation degree of historical control data under the corresponding historical operating conditions, n0 is the number of energy consumption values ​​in the time period after the marked change time node whose second change degree is greater than the preset second change degree threshold, N is the total number of energy consumption values ​​in the time period after the marked change time node whose second change degree is greater than the preset second change degree threshold, △di is the i-th second change degree difference whose second change degree is greater than the preset second change degree threshold, i=1, 2,…n0.

[0020] In some embodiments of the present application, generating a historical energy-saving evaluation value of energy consumption associated control data includes:

[0021] Analyze the energy consumption-related control data of each device under different historical working conditions, determine the historical regulation time of the energy consumption-related control data under the corresponding historical working conditions, and the historical energy consumption within the historical regulation time;

[0022] Obtain the historical cooling efficiency of the corresponding energy consumption related control data after the adjustment time;

[0023] Generate historical energy-saving evaluation values ​​for corresponding energy consumption-related control data based on historical control duration, historical energy consumption, and historical cooling efficiency;

[0024] Q = a × e tj ×(G0j-gj)×(kj-K0j);

[0025] Among them, Q is the historical energy-saving evaluation value, a is the energy-saving evaluation conversion coefficient, tj is the j-th historical regulation duration of the energy consumption associated control data under the corresponding historical operating conditions, G0j is the maximum allowable energy consumption of the energy consumption associated control data within the j-th historical regulation duration under the corresponding historical operating conditions, gj is the historical energy consumption of the energy consumption associated control data within the j-th historical regulation duration under the corresponding historical operating conditions, K0j is the minimum allowable cooling efficiency of the energy consumption associated control data after the j-th historical regulation duration under the corresponding historical operating conditions, and kj is the historical cooling efficiency of the energy consumption associated control data after the j-th historical regulation duration under the corresponding historical operating conditions.

[0026] In some embodiments of the present application, a preferred data set is constructed according to the energy consumption associated control data and the historical energy saving evaluation value of the corresponding device, including:

[0027] Selecting S1 objects as the first center from the energy consumption associated control data under the same historical working condition demand of each device, and selecting S2 objects as the second center from the historical energy-saving evaluation values ​​corresponding to the energy consumption associated control data under the same historical working condition demand of each device;

[0028] Calculate the control time of each first center and the remaining energy consumption associated control data under the same historical working condition demand of the same equipment, and set the remaining energy consumption associated control data with a control time longer than the preset control time as the first subset, and determine whether the first center needs to be replaced according to the first subset;

[0029] If necessary, replace the energy consumption related control data in the first subset that satisfies the shortest regulation time with the first center;

[0030] Compare each second center with the remaining historical energy-saving evaluation value under the same historical working condition requirement of the same equipment, and set the remaining historical energy-saving evaluation value whose historical energy-saving evaluation value is greater than the preset energy-saving evaluation value threshold as the second subset, and determine whether the second center needs to be replaced according to the second subset;

[0031] If necessary, replace the maximum historical energy saving evaluation value in the second subset with the second center;

[0032] Based on the plurality of first centers and the plurality of second centers, preferred control data are determined, and a preferred data set is constructed based on the plurality of preferred control data.

[0033] In some embodiments of the present application, determining preferred control data according to a plurality of first centers and a plurality of second centers includes:

[0034] One-to-one mapping is performed according to multiple first centers and multiple second centers under the same historical working condition requirements of each device, and the energy consumption associated control data involved in the successfully mapped first center is set as the preferred control data of the corresponding category of the successfully mapped first center;

[0035] Comprehensively analyzing the first subset and the second subset of the first center and the second center that are not successfully mapped, and setting the energy consumption associated control data that is ranked first in the comprehensive arrangement order in the first subset and the second subset as the preferred control data of the corresponding category of the first center that is not successfully mapped;

[0036] The preferred data set is constructed based on multiple categories of preferred control data under different historical operating conditions of each device.

[0037] In some embodiments of the present application, based on the preferred data set, an energy-saving control model of the corresponding device is constructed, including:

[0038] Divide the preferred data set of each device into a training data set and a test data set;

[0039] According to the historical working condition requirements in the training data set as input items, the optimal control data of multiple categories corresponding to the historical working condition requirements in the training data set are used as output items, and the neural network training is performed to obtain the initial energy-saving control model;

[0040] Credibility of the initial energy-saving control model generated based on the test data set;

[0041] Pre-set credibility threshold;

[0042] If the credibility is greater than the credibility threshold, the initial energy-saving control model is set as the energy-saving control model of the corresponding device;

[0043] If the credibility is less than the credibility threshold, the training data set is iterated and the initial energy-saving control model is reconstructed until the credibility is greater than the credibility threshold, and the reconstructed initial energy-saving control model is set as the energy-saving control model of the corresponding device.

[0044] In some embodiments of the present application, based on the energy-saving control model, real-time optimal control data of each device under real-time working condition requirements is obtained, including:

[0045] Obtain real-time working condition requirements, input the real-time working condition requirements into the energy-saving control model of the corresponding equipment, and obtain real-time optimal control data corresponding to the real-time working condition requirements;

[0046] A plurality of control processes are generated according to a preset control sequence of real-time optimal control data, and a control strategy is generated according to the plurality of control processes.

[0047] In some embodiments of the present application, a cooling tower energy-saving control method is also included:

[0048] Obtain historical control data of different equipment in the cooling tower under different historical working conditions;

[0049] Performing energy consumption correlation analysis on the historical control data, screening out energy consumption correlation control data of each device under different historical working conditions, and generating historical energy-saving evaluation values ​​of the energy consumption correlation control data;

[0050] According to the energy consumption related control data and the corresponding historical energy saving evaluation values, a preferred data set is constructed, and based on the preferred data set, an energy saving control model for the corresponding equipment is constructed;

[0051] Based on the energy-saving control model, the real-time optimal control data of each device under the real-time working condition requirements is obtained, and the control strategy is generated according to the real-time optimal control data.

[0052] Compared with the prior art, the energy-saving control system and method of a cooling tower in the embodiment of the present application have the following beneficial effects:

[0053] By screening the energy consumption management control data of different equipment in the cooling tower under different historical operating conditions and calculating the corresponding historical energy-saving evaluation values, an optimal data set and an energy-saving control model for the corresponding equipment are constructed, thereby obtaining the optimal control data for each equipment under real-time operating conditions, reducing the energy consumption during the use of the cooling tower and improving the cooling efficiency of the cooling tower, thereby achieving energy-saving optimization control of the cooling tower. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic diagram of an energy-saving control system of a cooling tower in a preferred embodiment of the present application;

[0055] Figure 2It is a flow chart of an energy-saving control method for a cooling tower in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0056] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0057] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0058] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0059] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0060] like Figure 1 As shown, an energy-saving control system for a cooling tower according to a preferred embodiment of the present application includes:

[0061] An acquisition module is used to acquire historical control data of different equipment in the cooling tower under different historical working conditions;

[0062] A screening module is used to perform energy consumption correlation analysis on the historical control data, screen out energy consumption correlation control data of each device under different historical working conditions, and generate a historical energy-saving evaluation value of the energy consumption correlation control data;

[0063] A construction module is used to construct a preferred data set according to the energy consumption associated control data and the corresponding historical energy-saving evaluation value, and to construct an energy-saving control model for the corresponding equipment based on the preferred data set;

[0064] The control module is used to obtain the real-time optimal control data of each device under the real-time working condition requirements based on the energy-saving control model, and generate a control strategy according to the real-time optimal control data.

[0065] In this embodiment, the historical operating condition demand refers to the amount of heat that needs to be absorbed by the cooling tower from the system. Based on the historical control data under different historical operating condition demands, the historical energy-saving evaluation value of each energy consumption-related control data under the corresponding historical operating condition demand is calculated, laying a data foundation for the subsequent construction of the preferred data set and the construction of the energy-saving control model.

[0066] In this embodiment, by screening the energy consumption management control data of different equipment in the cooling tower under different historical operating conditions and calculating the corresponding historical energy-saving evaluation values, a preferred data set and an energy-saving control model of the corresponding equipment are constructed, thereby obtaining the preferred control data of each equipment under real-time operating conditions, reducing the energy consumption during the use of the cooling tower and improving the cooling efficiency of the cooling tower, thereby realizing energy-saving optimization control of the cooling tower.

[0067] In some embodiments of the present application, energy consumption correlation analysis is performed on the historical control data to filter out energy consumption correlation control data of each device, including:

[0068] Dividing the historical control data of different equipment in the cooling tower under different historical working condition requirements into a plurality of historical control data groups, each of which includes a plurality of historical control data of the same equipment in the cooling tower under the same historical working condition requirements;

[0069] Establishing a time reference line for the preset control time of each historical control data group, and plotting each historical control data and the corresponding equipment energy consumption value in the historical control data group on the corresponding time reference line;

[0070] Performing a change degree analysis on the historical control data on the same time reference line, marking a change time node whose first change degree is greater than a preset first change degree threshold, and marking the corresponding historical control data at the same time;

[0071] Obtaining a second change degree of the energy consumption value in a time period after the marked change time node, and determining the energy consumption correlation degree of the marked historical control data under the corresponding historical operating condition demand according to the number of second change degrees greater than a preset second change degree threshold and the second change degree difference amount of the second change degree greater than the preset second change degree threshold;

[0072] Pre-set energy consumption correlation degree threshold;

[0073] If the energy consumption correlation degree of the historical control data under the corresponding historical operating condition demand is greater than the energy consumption correlation degree threshold, the historical control data is set as the energy consumption correlation control data under the corresponding historical operating condition demand.

[0074] In this embodiment, the preset control duration of each historical control data group refers to the control time length that meets the corresponding historical operating conditions. The change degree analysis of the historical control data on the same time reference line refers to the analysis of the degree of change of the change value of the historical control data within the corresponding preset control duration. The equipment energy consumption value refers to the change value of the equipment energy consumption within the corresponding preset control duration. The time period after the marked change time node refers to the 10 minutes after the marked change time node.

[0075] In this embodiment, the energy consumption-related control data of each device under different historical operating conditions are accurately screened out, laying the foundation for the subsequent formulation of an energy-saving control model for each device, thereby improving the energy-saving efficiency of the cooling tower.

[0076] In some embodiments of the present application, determining the energy consumption correlation degree of the marked historical control data under the corresponding historical operating condition requirements includes:

[0077] The calculation formula of the energy consumption correlation degree is:

[0078]

[0079] Among them, H is the energy consumption correlation degree of historical control data under the corresponding historical operating conditions, n0 is the number of energy consumption values ​​in the time period after the marked change time node whose second change degree is greater than the preset second change degree threshold, N is the total number of energy consumption values ​​in the time period after the marked change time node whose second change degree is greater than the preset second change degree threshold, △di is the i-th second change degree difference whose second change degree is greater than the preset second change degree threshold, i=1, 2,…n0.

[0080] In some embodiments of the present application, generating a historical energy-saving evaluation value of energy consumption associated control data includes:

[0081] Analyze the energy consumption-related control data of each device under different historical working conditions, determine the historical regulation time of the energy consumption-related control data under the corresponding historical working conditions, and the historical energy consumption within the historical regulation time;

[0082] Obtain the historical cooling efficiency of the corresponding energy consumption related control data after the adjustment time;

[0083] Generate historical energy-saving evaluation values ​​for corresponding energy consumption-related control data based on historical control duration, historical energy consumption, and historical cooling efficiency;

[0084] Q = a × etj ×(G0j-gj)×(kj-K0j);

[0085] Among them, Q is the historical energy-saving evaluation value, a is the energy-saving evaluation conversion coefficient, tj is the j-th historical regulation duration of the energy consumption associated control data under the corresponding historical operating conditions, G0j is the maximum allowable energy consumption of the energy consumption associated control data within the j-th historical regulation duration under the corresponding historical operating conditions, gj is the historical energy consumption of the energy consumption associated control data within the j-th historical regulation duration under the corresponding historical operating conditions, K0j is the minimum allowable cooling efficiency of the energy consumption associated control data after the j-th historical regulation duration under the corresponding historical operating conditions, and kj is the historical cooling efficiency of the energy consumption associated control data after the j-th historical regulation duration under the corresponding historical operating conditions.

[0086] In this embodiment, the historical energy-saving evaluation value of the corresponding energy consumption associated control data is determined according to the regulation time of each energy consumption associated control data under the corresponding historical operating condition demand, the historical energy consumption within the regulation time, and the historical cooling efficiency after the regulation time. According to the historical energy-saving evaluation value of the energy consumption associated control data under different historical operating conditions, the preferred control data is screened out to lay a data foundation for the subsequent construction of the energy-saving control model, ensure the accuracy of the energy-saving control model, provide preferred control data for real-time operating conditions, improve the cooling efficiency of the cooling tower, reduce the energy consumption of the cooling tower, and realize energy-saving optimization control of the cooling tower.

[0087] In some embodiments of the present application, a preferred data set is constructed according to the energy consumption associated control data and the historical energy saving evaluation value of the corresponding device, including:

[0088] Selecting S1 objects as the first center from the energy consumption associated control data under the same historical working condition demand of each device, and selecting S2 objects as the second center from the historical energy-saving evaluation values ​​corresponding to the energy consumption associated control data under the same historical working condition demand of each device;

[0089] Calculate the control time of each first center and the remaining energy consumption associated control data under the same historical working condition demand of the same equipment, and set the remaining energy consumption associated control data with a control time longer than the preset control time as the first subset, and determine whether the first center needs to be replaced according to the first subset;

[0090] If necessary, replace the energy consumption related control data in the first subset that satisfies the shortest regulation time with the first center;

[0091] Compare each second center with the remaining historical energy-saving evaluation value under the same historical working condition requirement of the same equipment, and set the remaining historical energy-saving evaluation value whose historical energy-saving evaluation value is greater than the preset energy-saving evaluation value threshold as the second subset, and determine whether the second center needs to be replaced according to the second subset;

[0092] If necessary, replace the maximum historical energy saving evaluation value in the second subset with the second center;

[0093] Based on the plurality of first centers and the plurality of second centers, preferred control data are determined, and a preferred data set is constructed based on the plurality of preferred control data.

[0094] In this embodiment, S1 refers to the number of categories of energy consumption-related control data under the same historical operating condition requirements of each device. For example, the energy consumption-related control data under the same historical operating condition requirements of each device include the first energy consumption-related control data, the second energy consumption-related control data, ... the mth energy consumption-related control data, that is, the number of categories is m, and there are 10 categories of energy consumption-related control data under historical operating condition requirements, that is, S1 is 10, and the energy consumption-related control data with the shortest regulation time in each category is selected as the first center. The regulation time refers to the time required for each energy consumption-related control data to be adjusted to meet the corresponding historical operating condition requirements. The number of S2 corresponds to the number of S1, and the maximum historical energy-saving evaluation value in each category is selected as the second center.

[0095] In this embodiment, when the mapping is unsuccessful, it means that the historical energy-saving evaluation value of the corresponding first center is small and does not meet the energy-saving constraint conditions. The first subset of the corresponding first center and the second subset of the second center of the corresponding category are analyzed, and the energy consumption associated control data with the first place in the comprehensive arrangement order is set as the preferred control data of the corresponding category. The comprehensive arrangement order = 0.5 * the arrangement order of the first subset + the sorting order of the second subset * 0.5.

[0096] In some embodiments of the present application, determining preferred control data according to a plurality of first centers and a plurality of second centers includes:

[0097] One-to-one mapping is performed according to multiple first centers and multiple second centers under the same historical working condition requirements of each device, and the energy consumption associated control data involved in the successfully mapped first center is set as the preferred control data of the corresponding category of the successfully mapped first center;

[0098] Comprehensively analyzing the first subset and the second subset of the first center and the second center that are not successfully mapped, and setting the energy consumption associated control data that is ranked first in the comprehensive arrangement order in the first subset and the second subset as the preferred control data of the corresponding category of the first center that is not successfully mapped;

[0099] The preferred data set is constructed based on multiple categories of preferred control data under different historical operating conditions of each device.

[0100] In this embodiment, the first center and the second center are mapped, and multiple categories of preferred control data under the same historical operating condition requirements are screened out according to the mapping results. According to the preferred control data under multiple historical operating conditions of each device, a preferred data set of the corresponding device is constructed, which provides a basis for the subsequent construction of an energy-saving control model for each device, and quickly obtains the preferred control data of each device in the cooling tower, thereby improving the energy-saving efficiency of each device in the cooling tower under different operating conditions.

[0101] In some embodiments of the present application, based on the preferred data set, an energy-saving control model of the corresponding device is constructed, including:

[0102] Divide the preferred data set of each device into a training data set and a test data set;

[0103] According to the historical working condition requirements in the training data set as input items, the optimal control data of multiple categories corresponding to the historical working condition requirements in the training data set are used as output items, and the neural network training is performed to obtain the initial energy-saving control model;

[0104] Credibility of the initial energy-saving control model generated based on the test data set;

[0105] Pre-set credibility threshold;

[0106] If the credibility is greater than the credibility threshold, the initial energy-saving control model is set as the energy-saving control model of the corresponding device;

[0107] If the credibility is less than the credibility threshold, the training data set is iterated and the initial energy-saving control model is reconstructed until the credibility is greater than the credibility threshold, and the reconstructed initial energy-saving control model is set as the energy-saving control model of the corresponding device.

[0108] In this embodiment, the predicted preferred control data output by the initial energy-saving control model is compared with the corresponding preferred control data in the test data set, and the difference in the predicted preferred control data and the difference in the number of predicted categories are obtained based on the comparison results. The smaller the difference in the predicted preferred control data and the smaller the difference in the number of predicted categories, the greater the credibility of the initial energy-saving control model.

[0109] In some embodiments of the present application, based on the energy-saving control model, real-time optimal control data of each device under real-time working condition requirements is obtained, including:

[0110] Obtain real-time working condition requirements, input the real-time working condition requirements into the energy-saving control model of the corresponding equipment, and obtain real-time optimal control data corresponding to the real-time working condition requirements;

[0111] A plurality of control processes are generated according to a preset control sequence of real-time optimal control data, and a control strategy is generated according to the plurality of control processes.

[0112] In some embodiments of the present application, Figure 2 As shown, it also includes an energy-saving control method for a cooling tower:

[0113] Step S201: Acquire historical control data of different equipment in the cooling tower under different historical operating conditions;

[0114] Step S202: performing energy consumption correlation analysis on the historical control data, screening out energy consumption correlation control data of each device under different historical working conditions, and generating a historical energy-saving evaluation value of the energy consumption correlation control data;

[0115] Step S203: constructing a preferred data set according to the energy consumption associated control data and the corresponding historical energy-saving evaluation values, and constructing an energy-saving control model for the corresponding equipment based on the preferred data set;

[0116] Step S204: Based on the energy-saving control model, obtain the real-time optimal control data of each device under the real-time working condition requirements, and generate a control strategy according to the real-time optimal control data.

[0117] In this embodiment, by screening the energy consumption management control data of different equipment in the cooling tower under different historical operating conditions and calculating the corresponding historical energy-saving evaluation values, a preferred data set and an energy-saving control model of the corresponding equipment are constructed, thereby obtaining the preferred control data of each equipment under real-time operating conditions, reducing the energy consumption during the use of the cooling tower and improving the cooling efficiency of the cooling tower, thereby realizing energy-saving optimization control of the cooling tower.

[0118] In summary, the present invention discloses an energy-saving control system and method for a cooling tower, which system includes: an acquisition module, which is used to acquire historical control data of different devices in the cooling tower under different historical working conditions; a screening module, which is used to perform energy consumption correlation analysis on the historical control data, screen out the energy consumption-related control data of each device under different historical working conditions, and generate historical energy-saving evaluation values ​​of the energy consumption-related control data; a construction module, which is used to construct a preferred data set according to the energy consumption-related control data and the corresponding historical energy-saving evaluation values, and to construct an energy-saving control model for the corresponding device based on the preferred data set; a control module, which is used to obtain the real-time preferred control data of each device under the real-time working condition requirements based on the energy-saving control model, and to generate a control strategy according to the real-time preferred control data; by screening the energy consumption management control data of different devices in the cooling tower under different historical working conditions and calculating the corresponding historical energy-saving evaluation values, a preferred data set and an energy-saving control model for the corresponding device are constructed, thereby obtaining the preferred control data of each device under the real-time working condition requirements, reducing the energy consumption during the use of the cooling tower and improving the cooling efficiency of the cooling tower, and realizing energy-saving optimization control of the cooling tower.

[0119] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present application. These improvements and substitutions should also be regarded as the scope of protection of the present application.

Claims

1. An energy-saving control system for a cooling tower, characterized in that: include: An acquisition module is used to acquire historical control data of different equipment in the cooling tower under different historical working conditions; A screening module is used to perform energy consumption correlation analysis on the historical control data, screen out energy consumption correlation control data of each device under different historical working conditions, and generate a historical energy-saving evaluation value of the energy consumption correlation control data; A construction module is used to construct a preferred data set according to the energy consumption associated control data and the corresponding historical energy-saving evaluation value, and to construct an energy-saving control model for the corresponding equipment based on the preferred data set; The control module is used to obtain the real-time optimal control data of each device under the real-time working condition requirements based on the energy-saving control model, and generate a control strategy according to the real-time optimal control data.

2. The energy-saving control system of a cooling tower according to claim 1, characterized in that: Perform energy consumption correlation analysis on the historical control data to filter out energy consumption correlation control data of each device, including: Dividing the historical control data of different equipment in the cooling tower under different historical working condition requirements into a plurality of historical control data groups, each of which includes a plurality of historical control data of the same equipment in the cooling tower under the same historical working condition requirements; Establishing a time reference line for the preset control time of each historical control data group, and plotting each historical control data and the corresponding equipment energy consumption value in the historical control data group on the corresponding time reference line; Performing a change degree analysis on the historical control data on the same time reference line, marking a change time node whose first change degree is greater than a preset first change degree threshold, and marking the corresponding historical control data at the same time; Obtaining a second change degree of the energy consumption value in a time period after the marked change time node, and determining the energy consumption correlation degree of the marked historical control data under the corresponding historical operating condition demand according to the number of second change degrees greater than a preset second change degree threshold and the second change degree difference amount of the second change degree greater than the preset second change degree threshold; Pre-set energy consumption correlation degree threshold; If the energy consumption correlation degree of the historical control data under the corresponding historical operating condition demand is greater than the energy consumption correlation degree threshold, the historical control data is set as the energy consumption correlation control data under the corresponding historical operating condition demand.

3. The energy-saving control system of a cooling tower according to claim 2, characterized in that: Determine the energy consumption correlation degree of the marked historical control data under the corresponding historical working condition requirements, including: The calculation formula of the energy consumption correlation degree is: Among them, H is the energy consumption correlation degree of historical control data under the corresponding historical operating conditions, n0 is the number of energy consumption values ​​in the time period after the marked change time node whose second change degree is greater than the preset second change degree threshold, N is the total number of energy consumption values ​​in the time period after the marked change time node whose second change degree is greater than the preset second change degree threshold, △di is the i-th second change degree difference whose second change degree is greater than the preset second change degree threshold, i=1, 2,…n0.

4. The energy-saving control system for a cooling tower according to claim 2, characterized in that: Generate historical energy-saving evaluation values ​​of energy consumption-related control data, including: Analyze the energy consumption-related control data of each device under different historical working conditions, determine the historical regulation time of the energy consumption-related control data under the corresponding historical working conditions, and the historical energy consumption within the historical regulation time; Obtain the historical cooling efficiency of the corresponding energy consumption related control data after the adjustment time; Generate historical energy-saving evaluation values ​​for corresponding energy consumption-related control data based on historical control duration, historical energy consumption, and historical cooling efficiency; Q=a×e tj ×(G0j-gj)×(kj-K0j); Among them, Q is the historical energy-saving evaluation value, a is the energy-saving evaluation conversion coefficient, tj is the j-th historical regulation duration of the energy consumption associated control data under the corresponding historical operating conditions, G0j is the maximum allowable energy consumption of the energy consumption associated control data within the j-th historical regulation duration under the corresponding historical operating conditions, gj is the historical energy consumption of the energy consumption associated control data within the j-th historical regulation duration under the corresponding historical operating conditions, K0j is the minimum allowable cooling efficiency of the energy consumption associated control data after the j-th historical regulation duration under the corresponding historical operating conditions, and kj is the historical cooling efficiency of the energy consumption associated control data after the j-th historical regulation duration under the corresponding historical operating conditions.

5. The energy-saving control system for a cooling tower according to claim 3, characterized in that: According to the energy consumption related control data and the historical energy saving evaluation value of the corresponding equipment, the optimal data set is constructed, including: Selecting S1 objects as the first center from the energy consumption associated control data under the same historical working condition demand of each device, and selecting S2 objects as the second center from the historical energy-saving evaluation values ​​corresponding to the energy consumption associated control data under the same historical working condition demand of each device; Calculate the control time of each first center and the remaining energy consumption associated control data under the same historical working condition demand of the same equipment, and set the remaining energy consumption associated control data with a control time longer than the preset control time as the first subset, and determine whether the first center needs to be replaced according to the first subset; If necessary, replace the energy consumption related control data in the first subset that satisfies the shortest regulation time with the first center; Compare each second center with the remaining historical energy-saving evaluation value under the same historical working condition requirement of the same equipment, and set the remaining historical energy-saving evaluation value whose historical energy-saving evaluation value is greater than the preset energy-saving evaluation value threshold as the second subset, and determine whether the second center needs to be replaced according to the second subset; If necessary, replace the maximum historical energy saving evaluation value in the second subset with the second center; Based on the plurality of first centers and the plurality of second centers, preferred control data are determined, and a preferred data set is constructed based on the plurality of preferred control data.

6. The energy-saving control system for a cooling tower according to claim 5, characterized in that: Determining preferred control data according to the plurality of first centers and the plurality of second centers includes: One-to-one mapping is performed according to multiple first centers and multiple second centers under the same historical working condition requirements of each device, and the energy consumption associated control data involved in the successfully mapped first center is set as the preferred control data of the corresponding category of the successfully mapped first center; Comprehensively analyzing the first subset and the second subset of the first center and the second center that are not successfully mapped, and setting the energy consumption associated control data that is ranked first in the comprehensive arrangement order in the first subset and the second subset as the preferred control data of the corresponding category of the first center that is not successfully mapped; The preferred data set is constructed based on multiple categories of preferred control data under different historical operating conditions of each device.

7. The energy-saving control system for a cooling tower according to claim 6, characterized in that: Based on the optimal data set, an energy-saving control model for the corresponding equipment is constructed, including: Divide the preferred data set of each device into a training data set and a test data set; According to the historical working condition requirements in the training data set as input items, the optimal control data of multiple categories corresponding to the historical working condition requirements in the training data set are used as output items, and the neural network training is performed to obtain the initial energy-saving control model; Credibility of the initial energy-saving control model generated based on the test data set; Pre-set credibility threshold; If the credibility is greater than the credibility threshold, the initial energy-saving control model is set as the energy-saving control model of the corresponding device; If the credibility is less than the credibility threshold, the training data set is iterated and the initial energy-saving control model is reconstructed until the credibility is greater than the credibility threshold, and the reconstructed initial energy-saving control model is set as the energy-saving control model of the corresponding device.

8. The energy-saving control system for a cooling tower according to claim 7, characterized in that: Based on the energy-saving control model, the real-time optimal control data of each device under the real-time working condition requirements is obtained, including: Obtain real-time working condition requirements, input the real-time working condition requirements into the energy-saving control model of the corresponding equipment, and obtain real-time optimal control data corresponding to the real-time working condition requirements; A plurality of control processes are generated according to a preset control sequence of real-time optimal control data, and a control strategy is generated according to the plurality of control processes.

9. A cooling tower energy-saving control method, characterized in that: include: Obtain historical control data of different equipment in the cooling tower under different historical working conditions; Performing energy consumption correlation analysis on the historical control data, screening out energy consumption correlation control data of each device under different historical working conditions, and generating historical energy-saving evaluation values ​​of the energy consumption correlation control data; According to the energy consumption related control data and the corresponding historical energy saving evaluation values, a preferred data set is constructed, and based on the preferred data set, an energy saving control model for the corresponding equipment is constructed; Based on the energy-saving control model, the real-time optimal control data of each device under the real-time working condition requirements is obtained, and the control strategy is generated according to the real-time optimal control data.

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