A Modeling Method for Multi-Head Magnetic Levitation Chiller Units

Abstract

This invention discloses a modeling method for a multi-head magnetic levitation chiller unit, comprising: collecting operating data of the chiller unit, including the evaporation temperature Te of each individual head module within the chiller unit. i Condensation temperature Tc i and actual operating load L i According to the Te of each single-head module i 、Tc i L i Rated cooling capacity Q des,i and energy efficiency ratio (COP) i The invention determines the performance model of each individual unit module; based on the performance models of each individual unit module, it establishes the performance model of the chiller unit. This invention enables the establishment of a highly accurate performance model for multi-unit magnetic levitation chillers, effectively achieving energy-saving optimization control.

Description

Technical Field

[0001] This invention relates to the field of energy-saving control technology for refrigeration systems, and in particular to a modeling method for multi-head magnetic levitation chillers. Background Technology

[0002] Magnetic levitation refrigeration refers to the use of magnetic levitation technology in centrifugal chiller units, which reduces mechanical losses and makes refrigeration operation more efficient and energy-saving. Compared with ordinary variable frequency centrifugal chillers, the key difference and crucial component of magnetic levitation variable frequency centrifugal chillers lies in the magnetic levitation centrifugal compressor.

[0003] To achieve energy efficiency control of magnetic levitation chiller units, it is necessary to establish a performance model of the chiller unit. Establishing a performance model of the chiller unit is an important step in energy-saving regulation, and the accuracy of the performance model directly affects the energy-saving control effect.

[0004] Currently, there are modeling methods for chiller units with only one compressor, including traditional data modeling based on equipment mechanism and black-box modeling based on operating data. However, there is no good modeling method for large magnetic levitation water chiller units with multiple compressors. Most modeling methods simply treat the unit with multiple compressors as a whole and model it by collecting data from the entire system as if it were a chiller unit with a single compressor.

[0005] This modeling method fails to consider the characteristics of multi-compressor chiller systems, such as independent refrigerant systems and shared water systems, resulting in poor model accuracy. Consequently, when using this model for energy-saving control, it cannot achieve good energy-saving effects. Furthermore, it requires extensive operational testing and data collection for each large chiller unit, which significantly impacts product delivery time and wastes a large amount of experimental resources. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a modeling method for multi-head magnetic levitation chillers. Based on the performance model of a single-head module, a performance model for the multi-head magnetic levitation chiller is established, resulting in a highly accurate model that effectively achieves energy-saving optimization control.

[0007] This application provides a modeling method for multi-head magnetic levitation chiller units, including:

[0008] Collect operating data of the chiller unit, including the evaporation temperature Te of each individual unit module within the chiller unit. i Condensation temperature Tc i and actual operating load L i ;

[0009] According to the Te of each single-head module i 、Tc i Li Rated cooling capacity Q des,i and energy efficiency ratio (COP) i Determine the performance model of each single-unit head module;

[0010] Based on the performance models of each individual unit module, a performance model for the chiller unit is established.

[0011] The performance model of the chiller unit mentioned above involves: based on the determined performance model of each individual unit module, Te i and Tc i Determine the predicted energy efficiency ratio of each individual unit module;

[0012] The electrical power of the chiller unit is determined based on the predicted energy efficiency ratio and cooling capacity of each individual unit module.

[0013] The predicted energy efficiency ratio of the chiller unit is determined based on the electrical power and the cooling capacity of the chiller unit.

[0014] The modeling method for multi-head magnetic levitation chiller units provided in this application has the following advantages and beneficial effects:

[0015] (1) Based on the operating data of the chiller unit, the performance model of each single unit module can be established first, and then the performance model of the multi-unit magnetic levitation chiller unit can be established through the performance models of multiple single unit modules. The performance model takes into account the characteristics of each single unit model, so that the performance model of the whole chiller unit has high accuracy.

[0016] (2) This modeling method is convenient and quick in actual use, and does not require a lot of experiments for each model, saving product development cycle and experimental resources;

[0017] (3) In system-level energy-saving control, combined optimization control can be performed on models of different single-head modules.

[0018] In some embodiments of this application, based on the Te of each single-head module i 、Tc i L i Rated cooling capacity Q des,i and energy efficiency ratio (COP) i Determine the performance model of each individual head unit module, including:

[0019] According to the Te of each single-head module i 、Tc i and energy efficiency ratio (COP) i Determine the performance coefficients (DCOP) of each individual head unit module. i ;

[0020] Based on the condensation temperature Tc of each individual unit module i and evaporation temperature Tei The weights dT related to the temperature difference between them i and cooling load rate PLR i Both establish the relationship between the performance coefficients of each individual head unit module;

[0021] According to the determined DCOP i Identify the coefficients of the relational formula to determine the performance model of each single-unit head module;

[0022] The cooling load rate PLR ​​mentioned above i Compared with the actual operating load L i and rated cooling capacity Q des,i related.

[0023] By using the operating data of the chiller unit obtained under actual operating conditions, the actual coefficient of performance (DCOP) of each individual unit module is determined. i Furthermore, by identifying the coefficients of the performance coefficients of each fitted single-head module, the performance model of the single-head module can be identified.

[0024] In some embodiments of this application, wherein

[0025] Performance coefficient , where i≥1.

[0026] In some embodiments of this application, the relational expression is as follows:

[0027] DCOP i =A i *PLR i 2 + B i *PLR i *dT i + C i *dT i 2 + D i *PLR i + E i *dT i + F i ,

[0028] Where A i B i C i D i E i and F i represents the fitting coefficient.

[0029] In some embodiments of this application, the cooling load rate PLR ​​is... i The calculation is as follows:

[0030] , ,

[0031] Among them, Q des,i Q represents the rated cooling capacity of the i-th single-unit module. i L represents the cooling capacity of the i-th single-unit module. i Q represents the actual operating load of the i-th single-head module. chw This indicates the current cooling capacity of the chiller unit, and n indicates the number of single-head modules in the multi-head magnetic levitation chiller unit.

[0032] In some embodiments of this application, ,

[0033] Among them, dT i ΔT represents the weighting factor related to the temperature difference between the condensation temperature and the evaporation temperature of the i-th single-unit head module. max ΔT represents the maximum temperature difference between the condensation temperature and the evaporation temperature of the i-th single-unit module. min This represents the minimum temperature difference between the condensation temperature and the evaporation temperature of the i-th single-unit head module.

[0034] In some embodiments of this application, based on the determined performance model, Tc i and Te i Determine the predicted energy efficiency ratio (COP) of each individual unit module. pre,i Specifically:

[0035] COP pre,i =Performance Model * Te i / (Tc i -Te i ).

[0036] In some embodiments of this application, the electrical power P of the chiller unit is determined based on the predicted energy efficiency ratio and cooling capacity of each individual unit module. w Specifically:

[0037] ,

[0038] Among them, Q i COP represents the cooling capacity of the i-th single-unit module. pre,i The predicted energy efficiency ratio of each single-unit module is given by n, where n represents the number of single-unit modules in a multi-unit magnetic levitation chiller unit.

[0039] To improve the accuracy of the performance model, outliers are removed from the operating data of the chiller unit to ensure that the acquired data is accurate. In some embodiments of this application, the step of removing outliers from the collected operating data is described.

[0040] In some embodiments of this application, the collected operational data also includes the chilled water supply temperature T. e-out Chilled water return temperature T e-in chilled water flow rate Q e Cooling water inlet temperature T c-in Cooling water outlet temperature T c-out Cooling water flow rate Q c The operating power P of each single unit module within the chiller unit i ;

[0041] Outliers are removed from the collected operational data, specifically including:

[0042] Calculate the cooling capacity of the chiller unit ;

[0043] Calculate the heat output of the chiller unit ;

[0044] Calculate the energy balance coefficient ;

[0045] When the energy balance coefficient is greater than the first preset value, the collected operating data is determined to be an anomaly.

[0046] Remove the outliers;

[0047] Where n represents the number of single-unit modules in a multi-unit magnetic levitation chiller unit, and c represents the specific heat capacity of water. Attached Figure Description

[0048] Figure 1 A schematic diagram of the structural composition of a multi-head magnetic levitation chiller unit is shown.

[0049] Figure 2 A flowchart is shown showing a modeling method for a multi-head magnetic levitation chiller unit according to some embodiments;

[0050] Figure 3 The data collected by the 500RT chiller unit under different operating conditions are shown;

[0051] Figure 4 The data collected by a 200RT module unit inside a 500RT chiller unit under different operating conditions is shown.

[0052] Figure 5 The data collected by a 150RT module unit inside a 500RT chiller unit under different operating conditions is shown.

[0053] Figure 6 The data collected by another 150RT module unit in the 500RT chiller unit under different operating conditions is shown;

[0054] Figure 7The data on predicted COP, actual COP, and relative error of COP obtained by the 500RT chiller unit under different operating conditions are shown.

[0055] Figure 8 A comparison chart of the predicted COP and the actual COP of the 500RT chiller unit under different operating conditions is shown.

[0056] Figure 9 The graph shows the relative error of COP for a 500RT chiller unit under different operating conditions;

[0057] Figure 10 The data collected by the 800RT chiller unit under different operating conditions are shown;

[0058] Figure 11 The data collected by a 200RT module unit inside an 800RT chiller unit under different operating conditions is shown.

[0059] Figure 12 The data collected by another 200RT module unit in the 800RT chiller unit under different operating conditions is shown;

[0060] Figure 13 The data collected by another 200RT module unit in the 800RT chiller unit under different operating conditions is shown.

[0061] Figure 14 The data collected by a 200RT module unit inside an 800RT chiller unit under different operating conditions is shown.

[0062] Figure 15 The data on predicted COP, actual COP, and relative error of COP obtained by the 800RT chiller unit under different operating conditions are shown.

[0063] Figure 16 A comparison chart of the predicted COP and the actual COP of the 800RT chiller unit under different operating conditions is shown.

[0064] Figure 17 The graph shows the relative error of COP for the 800RT chiller unit under different operating conditions. Detailed Implementation

[0065] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0066] In the description of this invention, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0067] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0068] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0069] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0070] The following disclosure provides many different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the invention. Furthermore, reference numerals and / or letters may be repeated in different examples; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. In addition, examples of various specific processes and materials are provided in this invention, but those skilled in the art will recognize the application of other processes and / or the use of other materials.

[0071] A multi-head magnetic levitation chiller (i.e., a multi-compressor magnetic levitation chiller) is composed of multiple single-head modules, each of which has one compressor. Thus, a multi-head magnetic levitation chiller has multiple compressors.

[0072] For example, a 400RT (Ton of Refrigeration) multi-head magnetic levitation chiller unit can be composed of two 200RT single-head modules, a 500RT chiller unit can be composed of one 200RT single-head module and two 150RT single-head modules connected in series, and an 800RT chiller unit can be composed of four 200RT single-head modules connected in series.

[0073] In this multi-head magnetic levitation chiller unit, each individual head module shares a water circuit, while the refrigerant circuits are independent of each other.

[0074] Currently, the mainstream single-head modules come in four capacities: 125RT, 150RT, 180RT, and 200RT.

[0075] See Figure 1 It shows a schematic diagram of the composition of a multi-head magnetic levitation chiller unit, which is mainly composed of four single-head modules connected in series.

[0076] Therefore, the performance models of multi-head magnetic levitation chillers under various combinations can be established using the performance models of four single-head modules.

[0077] See Figure 2 It illustrates the modeling process of a multi-head magnetic levitation chiller unit.

[0078] The following will be for reference Figure 2 This document describes in detail the modeling process of a multi-head magnetic levitation chiller unit (hereinafter referred to as the chiller unit).

[0079] S1: Collect operating data of the chiller unit.

[0080] Real-time on-site collection of actual operating data for the chiller unit includes: the evaporation temperature Te of all individual unit modules within the multi-unit magnetic levitation chiller unit. i Condensation temperature Tc i and actual operating load L i .

[0081] Where i represents the i-th single-head module.

[0082] If a multi-head magnetic levitation chiller unit includes n (n>1 and are natural numbers) single-head modules, then 1≤i≤n and i is a natural number.

[0083] The evaporation temperature Te collected above i Condensation temperature Tc i and actual operating load L i Used to build a performance model for a single-header module.

[0084] In addition, to ensure the reliability of the collected data, outlier removal is performed. See [link to relevant documentation]. Figure 2 Dashed box.

[0085] When removing outliers, it is necessary to collect data from the chiller unit for reference.

[0086] Therefore, it is also necessary to collect real-time operating data of the chiller unit on-site, including: chilled water supply temperature T. e-out Chilled water return temperature T e-in chilled water flow rate Q e Cooling water inlet temperature T c-in Cooling water outlet temperature T c-out Cooling water flow rate Q c The operating power P of each single unit module within the chiller unit i .

[0087] Outliers are identified using the following method.

[0088] (a) Calculate the cooling capacity Q of the chiller unit according to the following formula (1). chw :

[0089] (1)

[0090] Where c represents the specific heat capacity of water.

[0091] (b) Calculate the heat dissipation Q of the chiller unit according to the following formula (2). cw :

[0092] (2).

[0093] (c) Calculate the energy balance coefficient γ according to the following formula (3):

[0094] (3)

[0095] Where n represents the number of single-unit modules in the chiller unit. This represents the sum of the operating power of multiple single-unit modules in a chiller unit.

[0096] (d) When the energy balance coefficient γ is greater than the first preset value, the collected operating data is determined to be an abnormal value.

[0097] Here, "energy balance coefficient γ is greater than the first preset value" is the judgment condition for data to be an outlier as specified in this application, where the first preset value can be preset or changed according to needs.

[0098] For example, the first preset value can be selected as 10%.

[0099] When the capacity balance coefficient γ is greater than 10%, the operating data corresponding to that γ is considered an outlier.

[0100] That is, these operational data: chilled water supply temperature T e-out Chilled water return temperature T e-in chilled water flow rate Q e Cooling water inlet temperature T c-in Cooling water outlet temperature T c-out Cooling water flow rate Q c The operating power P of each single unit module within the chiller unit i The evaporation temperature Te of all single-unit modules inside the multi-unit magnetic levitation chiller unit i Condensation temperature Tc i and actual operating load L i .

[0101] Removing these outliers helps to accurately establish the performance model of the single-head module.

[0102] Of course, other methods can also be used to remove outliers from the collected data.

[0103] S2: Establish a performance model for the single-header module.

[0104] According to the Te of each single-head module i 、Tc i L i Rated cooling capacity Q of each single unit module des,i and energy efficiency ratio (COP) i Determine the performance model of each individual head module.

[0105] A performance coefficient DCOP is introduced to characterize the performance model of a single-head module.

[0106] In some embodiments of this application, establishing a performance model for a single-head module includes two processes:

[0107] (A) For the i-th single-head module, based on the actual operating data Te i 、Tc i and energy efficiency ratio (COP) i Calculate the actual coefficient of performance (DCOP) i .

[0108] (B) Fit the relationship between the performance coefficient DCOP of each single unit module and the weight dT related to the temperature difference between the cooling load rate PLR, the condensing temperature Tc, and the evaporating temperature Te.

[0109] For (A), calculate DCOP i as follows.

[0110] Based on the actual obtained operating data Te i 、Tc i and energy efficiency ratio (COP) i DCOP is characterized using the following formula (4). i .

[0111] (4)

[0112] Thus, the actual performance coefficient (DCOP) of the i-th single-head module can be calculated. i .

[0113] To obtain a large amount of data, performance coefficients can be obtained for single-head modules under different operating conditions.

[0114] For (B), based on the experiment, the relationship between the performance coefficient DCOP and the weight dT related to the temperature difference between the cooling load rate PLR ​​and the condensing temperature Tc and the evaporating temperature Te is fitted.

[0115] Based on the operating load L of the i-th single-head module i Rated cooling capacity Q des,i And the current cooling capacity Q of the chiller unit chw The actual cooling load rate PLR ​​of the i-th single-unit module is calculated using the following formulas (5) and (6). i .

[0116] (5)

[0117] (6)

[0118] in, This represents the sum of the operating loads of all single-head modules.

[0119] Q chw Formula (1) and the collected operating data (chilled water supply temperature T) can be used. e-out Chilled water return temperature T e-in chilled water flow rate Q e (This information was obtained.)

[0120] In some embodiments of this application, other methods may also be used to calculate the cooling capacity Q. chw .

[0121] The actual weight dT of the i-th single-head module can be calculated using formula (7). i .

[0122] (7)

[0123] Among them, dT i ΔT represents the weighting factor related to the temperature difference between the condensation temperature and the evaporation temperature of the i-th single-unit head module. max ΔT represents the maximum temperature difference between the condensation temperature and the evaporation temperature of the i-th single-unit module. min This represents the minimum temperature difference between the condensation temperature and the evaporation temperature of the i-th single-unit head module.

[0124] For ease of calculation, △T can be... max Set to 45℃, and set △T min Set to 15℃.

[0125] In some embodiments of this application, other values ​​of △T may also be set. max and △T min Alternatively, other coefficients related to the temperature difference between the condensation temperature and the evaporation temperature of the i-th single-head module can be set, which are not restricted here.

[0126] For the i-th single-unit module, the fitted DCOP and the relationship between the cooling load rate PLR ​​and dT are given by formula (8).

[0127] DCOP=A i *PLR 2 + B i *PLR*dT + C i *dT 2 + D i *PLR+ E i *dT+ F i (8)

[0128] Where A i B i C i D i E i and F i represents the fitting coefficient.

[0129] Using formulas (4), (5) and (7), the fitting coefficients as described above are identified.

[0130] Thus, by substituting the fitting coefficients as described above into formula (8), the performance module of the i-th single-head module is obtained.

[0131] The fitting coefficients identified vary depending on the capacity of the single-head module.

[0132] Taking a 500RT chiller unit as an example, the performance model of each single unit module is illustrated.

[0133] The 500RT chiller unit can be composed of one 200RT single-head module and two 150RT single-head modules connected in series.

[0134] For example, the fitting coefficients of a single unit module with a cooling load of 200RT are A1, B1, C1, D1, E1 and F1, respectively, and the cooling load rate PLR ​​is PLR1, and the weight dT is dT1.

[0135] Therefore, the performance model of the 200RT single-head module is as follows:

[0136] DCOP=A1*PLR 2 + B1*PLR*dT + C1*dT 2 + D1*PLR+ E1*dT+ F1.

[0137] The fitting coefficients for the 150RT single-unit module are A2, B2, C2, D2, E2 and F2, respectively, and the cooling load rate PLR ​​is PLR2, and the weight dT is dT2.

[0138] Therefore, the performance model of the 150RT single-head module is as follows:

[0139] DCOP = A2 * PLR 2 + B2*PLR*dT+ C2*dT 2 + D2*PLR+ E2*dT+ F2.

[0140] S3: Based on the performance models of each individual unit module, establish the performance model of the chiller unit.

[0141] Based on the performance models of each individual unit module, the performance model of the chiller unit mainly involves the following three aspects.

[0142] (a) Based on the determined performance model of the i-th single-head module, Te i and Tc i Determine the predicted energy efficiency ratio (COP) of the i-th single-unit head module. pre,i .

[0143] Using the identified fitting coefficients (8) and the evaporation temperature Te of the i-th single-head module i and condensation temperature Tc i The predicted energy efficiency ratio (COP) of the i-th single-head module is obtained using the following formula (9). pre,i.

[0144] (9)

[0145] (b) Based on the predicted COP of each individual unit module pre,i and the cooling capacity Q of each single unit module i Determine the electrical power P of the chiller unit. w .

[0146] In some embodiments of this application, the electrical power P of the chiller unit is determined using formula (10). w :

[0147] (10)

[0148] Where i represents the i-th single-head module (i.e., Q) i (where represents the cooling capacity of the i-th single-unit module), and n represents the number of single-unit modules in a multi-unit magnetic levitation chiller unit.

[0149] (c) Based on the electric power P w The cooling capacity Q of the chiller unit chw Determine the predicted energy efficiency ratio (COP) of the chiller unit. pre .

[0150] In some embodiments of this application, the predicted energy efficiency ratio (COP) of the chiller unit is determined using formula (11). pre .

[0151] COP pre =Q chw / P w (11)

[0152] Thus, based on the performance models of multiple single-unit modules, the performance model of the chiller unit (see formulas (9) to (11)) and the predicted energy efficiency ratio (COP) are obtained. pre .

[0153] This modeling method can quickly establish performance models of large-scale chiller units with different combinations, and optimize them by combining actual operating data, thus achieving good model accuracy. Moreover, this modeling method takes into account the characteristics of multiple single-unit modules, and can comprehensively reflect the operating status of the chiller unit. Therefore, when using this model for energy-saving control, it can achieve good energy-saving effects.

[0154] For reference: Figures 3 to 17 The performance model was established using operating data from two different chiller units, and the performance model was then validated.

[0155] See Figures 3 to 9It shows a 500RT chiller unit, which is composed of a 200RT single-head module and two 150RT single-head modules connected in series.

[0156] Figure 3 The operating data of the 500RT chiller unit is shown. Figure 4 The operating data of a 200RT single-unit module in a 500RT chiller unit is shown. Figure 5 The data shown is the operating data of a 150RT single-unit module in a 500RT chiller unit. Figure 6 The operating data of another 150RT single-head module in the 500RT chiller unit is shown.

[0157] Based on the modeling method described above, 20 sample points were selected to calculate the predicted COP of a 500RT chiller unit. pre ,refer to Figure 7 .

[0158] exist Figure 7 The paper also provides the actual energy efficiency ratio and COP relative error of the 500RT chiller unit.

[0159] Furthermore, the actual energy efficiency ratio and predicted energy efficiency ratio (COP) of the 500RT chiller unit were compared. pre The contrast in Figure 8 As shown in the image.

[0160] Furthermore, the relative error of the COP of the 500RT chiller unit is within... Figure 9 As shown in the image.

[0161] pass Figure 8 and Figure 9 It can be seen intuitively that the predicted COP of the chiller unit pre It is basically equal to the actual energy efficiency ratio (COP).

[0162] See Figures 10 to 17 It shows an 800RT chiller unit, which is composed of four 200RT single-unit modules connected in series.

[0163] Figure 10 The operating data of the 800RT chiller unit is shown. Figure 11 The data shown is the operating data of a 200RT single-head unit in an 800RT chiller unit. Figure 12 The data shown is the operating data of another 200RT single-unit module in the 800RT chiller unit. Figure 13 The data shown is the operating data of another 200RT single-unit module in the 800RT chiller unit. Figure 14 The data shown is the operating data of a 200RT single-unit module in an 800RT chiller unit.

[0164] Based on the modeling method described above, 12 sample points were selected to calculate the predicted COP of an 800RT chiller unit. pre ,refer to Figure 15 .

[0165] exist Figure 15 The paper also provides the actual energy efficiency ratio and COP relative error of the 800RT chiller unit.

[0166] Furthermore, the actual energy efficiency ratio and predicted energy efficiency ratio (COP) of the 800RT chiller unit were compared. pre The contrast in Figure 16 As shown in the image.

[0167] Furthermore, the relative error of the COP of the 800RT chiller unit is within... Figure 17 As shown in the image.

[0168] pass Figure 16 and Figure 17 It can be seen intuitively that the predicted COP of the chiller unit pre It is basically equal to the actual energy efficiency ratio (COP).

[0169] The high accuracy of the performance model was verified through the above verification of two different types of chillers. At the same time, the modeling method can be applied to practical applications, and it is highly operable and convenient to use the performance module for energy-saving optimization control.

[0170] It can model chiller units with different combinations of single-unit modules, offering high flexibility and wide applicability, and enabling better selection of optimized energy-saving solutions based on load.

[0171] Taking a 500RT chiller unit as an example, when the partial load rate of the chiller unit is 40%, it is possible to operate one 200RT single-unit module and one 150RT single-unit module, or two 150RT single-unit modules. The overall performance of the chiller unit will differ depending on the operation mode. This modeling method is not only convenient for modeling, but also provides a good model foundation for precise control.

[0172] In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0173] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A modeling method for a multi-head magnetic levitation chiller unit, characterized in that, include: Collect operating data of the chiller unit, including the evaporation temperature Te of the i-th single-head module within the chiller unit. i Condensation temperature Tc i and actual operating load L i ; According to the Te of the i-th single-head module i 、Tc i L i Rated cooling capacity Q des,i and energy efficiency ratio (COP) i Determine the performance model of the i-th single-head module; Based on the performance models of each individual unit module, a performance model for the chiller unit is established. The performance model of the chiller unit involves: based on the determined performance model of the i-th single-unit module, Te i and Tc i Determine the predicted energy efficiency ratio of the i-th single-unit head module; The electrical power of the chiller unit is determined based on the predicted energy efficiency ratio and cooling capacity of each individual unit module. The predicted energy efficiency ratio of the chiller unit is determined based on the electrical power and the cooling capacity of the chiller unit.

2. The modeling method for multi-head magnetic levitation chiller units according to claim 1, characterized in that, According to the Te of the i-th single-head module i 、Tc i L i Rated cooling capacity Q des,i and energy efficiency ratio (COP) i The performance model of the i-th single-head module is determined as follows: According to the Te of the i-th single-head module i 、Tc i and energy efficiency ratio (COP) i Determine the actual performance coefficient (DCOP) of the i-th single-head module. i ; Fit the relationship between the coefficient of performance DCOP of the i-th single-unit head module and the weight dT and the cooling load rate PLR, wherein the weight dT is related to the temperature difference between the condensing temperature Tc and the evaporating temperature Te of the single-unit head module; Based on the actual DCOP of the determined i-th single-head module i dT i and PLR i Identify the coefficients of the relation to determine the performance model of the i-th single-head module; Wherein, the cooling load rate PLR i Compared with the actual operating load L i and rated cooling capacity Q des,i related.

3. The modeling method for multi-head magnetic levitation chiller units according to claim 2, characterized in that, The actual performance coefficient (DCOP) of the i-th single-head module i for: 。 4. The modeling method for multi-head magnetic levitation chiller units according to claim 2, characterized in that, The relationship fitted by the i-th single-head module is as follows: DCOP=A i *PLR 2 + B i *PLR*dT+ C i *dT 2 + D i *PLR+ E i *dT+ F i , Where A i B i C i D i E i and F i represents the fitting coefficient.

5. The modeling method for multi-head magnetic levitation chiller units according to claim 4, characterized in that, The actual cooling load rate (PLR) of the i-th single-unit module i The calculation is as follows: ， ， Among them, Q des,i Q represents the rated cooling capacity of the i-th single-unit module. i L represents the cooling capacity of the i-th single-unit module. i Q represents the actual operating load of the i-th single-head module. chw This indicates the current cooling capacity of the chiller unit, and n indicates the number of single-head modules in the multi-head magnetic levitation chiller unit.

6. The modeling method for multi-head magnetic levitation chiller units according to claim 4 or 5, characterized in that, The actual weight dT of the i-th single-head module i for: ， Among them, dT i ΔT represents the weighting factor related to the temperature difference between the condensation temperature and the evaporation temperature of the i-th single-unit head module. max ΔT represents the maximum temperature difference between the condensation temperature and the evaporation temperature of the i-th single-unit module. min This represents the minimum temperature difference between the condensation temperature and the evaporation temperature of the i-th single-unit head module.

7. The modeling method for multi-head magnetic levitation chiller units according to claim 1, characterized in that, Based on the performance model of the i-th single-head module and Tc i and Te i Determine the predicted energy efficiency ratio (COP) of the i-th single-unit head module. pre,i Specifically: COP pre,i =Performance Model * Te i / (Tc i -Te i ).

8. The modeling method for multi-head magnetic levitation chiller units according to claim 1, characterized in that, Based on the predicted energy efficiency ratio and cooling capacity of each individual unit module, the electrical power P of the chiller unit is determined. w Specifically: ， Among them, Q i COP represents the cooling capacity of the i-th single-unit module. pre,i Let be the predicted energy efficiency ratio of the i-th single-unit module, and n represent the number of single-unit modules in a multi-unit magnetic levitation chiller unit.

9. The modeling method for multi-head magnetic levitation chiller units according to claim 1, characterized in that, The steps for removing outliers from the collected operational data.

10. The modeling method for a multi-head magnetic levitation chiller unit according to claim 9, characterized in that, The collected operational data also includes the chilled water supply temperature T. e-out Chilled water return temperature T e-in chilled water flow rate Q e Cooling water inlet temperature T c-in Cooling water outlet temperature T c-out Cooling water flow rate Q c The operating power P of each single unit module within the chiller unit i ; Outliers are removed from the collected operational data, specifically including: Calculate the cooling capacity of the chiller unit ; Calculate the heat output of the chiller unit ; Calculate the energy balance coefficient ; When the energy balance coefficient is greater than the first preset value, the collected operating data is determined to be an anomaly. Remove the outliers; Where n represents the number of single-head modules in a multi-head magnetic levitation chiller unit, and c represents the specific heat capacity of water.

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