Cooling water temperature difference adjustment method and system for a refrigeration system based on energy consumption analysis

Abstract

The present invention relates to the field of regulating the temperature difference of cooling water, and discloses a method and system for regulating the temperature difference of cooling water in a refrigeration system based on energy consumption analysis, including the following steps: constructing a target refrigeration simulation system capable of simulating the operation of the target refrigeration system, calculating different cooling parameter combinations of the cooling water pump simulation model in the target refrigeration simulation system, and calculating the optimal cooling water supply and return temperature difference of the target refrigeration system according to different cooling parameter combinations. Finally, the operation stability of the optimized target refrigeration system is evaluated and optimized. The present invention can construct a simulation model for the refrigeration system, perform energy consumption analysis in the simulation model, obtain the optimal cooling water supply and return temperature difference of the refrigeration system, and realize the intelligent regulation of the energy consumption of the refrigeration system. It reduces the energy consumption during the operation of the refrigeration system, meets the economic benefits during refrigeration, and reduces the adverse impact on the environment during the refrigeration process.

Description

Technical Field

[0001] The present invention relates to the field of cooling water temperature difference regulation, in particular to a method and system for regulating the cooling water temperature difference of a refrigeration system based on energy consumption analysis. Background Art

[0002] In a traditional refrigeration system, the temperature difference between the inlet and outlet of the cooling water of the refrigeration unit is 5°C. According to the sensible heat formula Q = CMΔT (Q is the heat exchange amount, C is the specific heat capacity of water, M is the water flow rate, and ΔT is the temperature difference between the inlet and outlet), it can be known that when Q is constant, under a constant temperature difference, the water flow rate M is also a constant value. When the size of the water flow rate is changed, the temperature difference between the inlet and outlet will also change accordingly. When the water flow rate increases, the supply-return water temperature difference will decrease; when the water flow rate decreases, the supply-return water temperature difference will increase. The two are in an inverse proportion relationship.

[0003] In a traditional refrigeration system, the flow rate selection basis of the cooling water pump is the water flow rate required to maintain a 5°C temperature difference between the inlet and outlet of the cooling water when the main engine is under full load. This means that when the load rate of the main engine becomes smaller, due to the fixed water flow rate, the temperature difference between the inlet and outlet will become smaller. For the refrigeration main engine in this case, a large flow rate and a small temperature difference, a larger flow rate is beneficial to the heat exchange effect of the main engine condenser and improves the energy efficiency of the main engine. However, at the same time, a larger flow rate also brings greater energy consumption to the cooling water pump. In traditional practices, either the water flow rate of the refrigeration unit is maintained unchanged, with a large power input to the pump, and when the load of the main engine changes, the temperature difference changes to ensure a small power input to the main engine; or the temperature difference of the cooling water is maintained at 5°C, thereby reducing the input power of the pump, and at this time, the input power of the main engine will increase slightly. Neither of the two practices can efficiently and scientifically achieve the lowest input of the input power of the cooling water pump and the refrigeration main engine, that is, it is impossible to achieve the overall lowest energy consumption of the cooling water pump and the refrigeration unit. Therefore, a method for calculating and analyzing the lowest energy consumption point of the cooling water pump and the refrigeration unit in real time is invented. Summary of the Invention

[0004] The present invention overcomes the deficiencies of the prior art and provides a method and system for regulating the cooling water temperature difference of a refrigeration system based on energy consumption analysis.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] The first aspect of the present invention provides a method for regulating the cooling water temperature difference of a refrigeration system based on energy consumption analysis, including the following steps:

[0007] Obtain the operation parameter thresholds of the target refrigeration system, and construct a target refrigeration simulation system based on the operation parameter thresholds of the target refrigeration system;

[0008] Determine the cooling water heat transfer amount of the condenser simulation model in the refrigeration unit simulation model, and calculate different cooling parameter combinations of the cooling water pump simulation model in combination with the sensible heat formula;

[0009] In the cooling water pump simulation model where the operating frequency is equal to the target operating frequency, based on different cooling parameter combinations, calculate the optimal cooling water supply and return water temperature difference, and obtain the optimized target refrigeration system based on the optimal cooling water supply and return water temperature difference;

[0010] Operate the optimized target refrigeration system, and conduct operating stability evaluation and optimization of the optimized target refrigeration system during the operation of the optimized target refrigeration system.

[0011] Further, in a preferred embodiment of the present invention, the method for obtaining the operating parameter threshold of the target refrigeration system and constructing the target refrigeration simulation system based on the operating parameter threshold of the target refrigeration system is as follows:

[0012] Obtain the refrigeration system that needs to adjust the cooling water temperature difference, label it as the target refrigeration system, and label the sub-devices in the target refrigeration system as target sub-devices;

[0013] Obtain the user manual of the target refrigeration system, and based on the user manual of the target refrigeration system, obtain the operating parameter thresholds of all target sub-devices;

[0014] Obtain system modeling and simulation software, and build a basic model of the refrigeration simulation system in the system modeling and simulation software;

[0015] Import the operating parameter thresholds of all the target sub-devices into the system modeling and simulation software for data training and analysis to obtain the operating parameter threshold boundary conditions and the initial conditions of the operating parameter thresholds of the target sub-devices;

[0016] Apply the operating parameter threshold boundary conditions and the initial conditions of the operating parameter thresholds of the target sub-devices in the basic model of the refrigeration simulation system to obtain the target refrigeration simulation system;

[0017] Among them, the target refrigeration simulation system includes a cooling water pump simulation model and a refrigeration unit simulation model, and the refrigeration unit simulation model includes a condenser simulation model.

[0018] Further, in a preferred embodiment of the present invention, the method for determining the cooling water heat transfer amount of the condenser simulation model in the refrigeration unit simulation model and calculating different cooling parameter combinations of the cooling water pump simulation model in combination with the sensible heat formula is as follows:

[0019] Obtain a big data network, and retrieve the sensible heat formula in the big data network;

[0020] Determine the temperature that the target refrigeration simulation system needs to output, and calibrate it as the target temperature;

[0021] Input the target temperature into the refrigeration unit simulation model, control the refrigeration unit simulation model to analyze the target temperature, and obtain the heat exchange amount of the cooling water that the condenser simulation model in the refrigeration unit simulation model needs to output when the target refrigeration simulation system maintains the temperature equal to the target temperature, and calibrate it as the target cooling water heat exchange amount;

[0022] Based on the operation manual of the target refrigeration system, determine all the cooling water supply and return temperature differences supported by the target refrigeration system, and calibrate them as the selectable cooling water supply and return temperature differences;

[0023] Based on the sensible heat formula, combined with the target cooling water heat exchange amount, calculate the required water flow of the cooling water pump simulation model corresponding to different selectable cooling water supply and return temperature differences, and combine the selectable cooling water supply and return temperature differences and the corresponding required water flow of the cooling water pump simulation model, and calibrate them as the cooling parameter combinations.

[0024] Further, in a preferred embodiment of the present invention, in the cooling water pump simulation model with the operating frequency equal to the target operating frequency, based on different cooling parameter combinations, calculate the optimal cooling water supply and return temperature difference, and obtain the optimized target refrigeration system based on the optimal cooling water supply and return temperature difference, specifically:

[0025] Obtain the pump flow - head curve of the cooling water pump simulation model at different operating frequencies, and obtain the pump flow - shaft power curve of the cooling water pump simulation model at different operating frequencies;

[0026] Control the operation of the cooling water pump simulation model. During the operation of the cooling water pump simulation model, preset the target operating frequency of the cooling water pump simulation model, and adjust the operating frequency of the cooling water pump simulation model to be equal to the target operating frequency to obtain a type of cooling water pump simulation model;

[0027] When the cooling water pump model is equal to a type of cooling water pump model, based on the pump flow - head curve of the cooling water pump simulation model at different operating frequencies, obtain the pump flow - head curve of the type of cooling water pump model, and based on the pump flow - shaft power curve of the cooling water pump simulation model at different operating frequencies, obtain the pump flow - shaft power curve of the type of cooling water pump model;

[0028] Apply different combinations of cooling parameters to the simulation model of the first type of cooling water pump, and combine the pump flow-head curve of the first type of cooling water pump model and the pump flow-shaft power curve of the first type of cooling water pump model to obtain the head and shaft power of the first type of cooling water pump model at different cooling water flows, and calculate the input power of the first type of cooling water pump model under different combinations of cooling parameters based on the head and shaft power of the first type of cooling water pump model at different cooling water flows;

[0029] Based on the input power of the first type of cooling water pump model under different combinations of cooling parameters, perform an energy consumption analysis on the target refrigeration simulation system, and determine the optimal cooling water supply and return water temperature difference of the target refrigeration simulation system based on the energy consumption analysis results.

[0030] Further, in a preferred embodiment of the present invention, the input power analysis of the target refrigeration simulation system and the determination of the optimal cooling water supply and return water temperature difference of the target refrigeration simulation system based on the input power analysis results are specifically as follows:

[0031] Calculate the input power when the condenser simulation model in the refrigeration unit simulation model outputs the target cooling water heat transfer amount, and calibrate it as the refrigeration input power of the refrigeration unit simulation model;

[0032] Add the input power of the first type of cooling water pump model under different combinations of cooling parameters to the refrigeration input power of the refrigeration unit simulation model to obtain the total input power corresponding to the target refrigeration simulation system when applying different combinations of cooling parameters;

[0033] Analyze the total input power corresponding to the target refrigeration simulation system when applying different combinations of cooling parameters, select the combination of cooling parameters corresponding to the minimum total input power of the target refrigeration simulation system, and calibrate it as the target cooling parameter combination;

[0034] Based on the target cooling parameter combination, obtain the cooling water supply and return water temperature difference of the target cooling parameter combination, and calibrate it as the optimal cooling water supply and return water temperature difference;

[0035] Apply the optimal cooling water supply and return water temperature difference in the target refrigeration system to obtain an optimized target refrigeration system.

[0036] Further, in a preferred embodiment of the present invention, the operation of the optimized target refrigeration system and the evaluation and optimization of the operation stability of the optimized target refrigeration system during the operation of the optimized target refrigeration system are specifically as follows:

[0037] Operate the optimized target refrigeration system, and during the operation of the optimized target refrigeration system, determine whether the cooling water supply and return water temperature difference of the optimized target refrigeration system is constantly equal to the optimal cooling water supply and return water temperature difference;

[0038] If so, evaluate the optimized target refrigeration system as a refrigeration system with qualified stability;

[0039] If not, evaluate the optimized target refrigeration system as a refrigeration system with unqualified stability, and calibrate the operating parameters of each sub-device when the temperature difference between the supply and return water of the cooling water is not equal to the optimal temperature difference between the supply and return water of the cooling water in the refrigeration system with unqualified stability as abnormal operating parameters of the sub-device;

[0040] Introduce the decision tree algorithm, construct the basic fault tree model based on the decision tree algorithm, and convert the abnormal operating parameters of the sub-device into a training set, where the training set contains the characteristic data of the abnormal operating parameters of the sub-device;

[0041] Introduce the singular value decomposition algorithm to transform the characteristic data of the abnormal operating parameters of the sub-device in the training set into a characteristic vector matrix, obtain the characteristic vector matrix, introduce the genetic algorithm, and import the characteristic vector matrix into the basic fault tree model. The basic fault tree model iteratively trains the characteristic vector matrix based on the genetic algorithm;

[0042] Preset the maximum number of iterative training times. When the number of times the basic fault tree model iteratively trains the characteristic vector matrix based on the genetic algorithm is equal to the maximum number of iterative training times, stop the iterative training to obtain the fault tree training model;

[0043] Run the fault tree training model, obtain all abnormal positions of the sub-devices in the refrigeration system with unqualified stability, calibrate them as refrigeration abnormal positions, and retrieve and output the maintenance methods for the refrigeration abnormal positions in the big data network, so that the temperature difference between the supply and return water of the cooling water in the refrigeration system with unqualified stability is constantly equal to the optimal temperature difference between the supply and return water of the cooling water, and obtain a refrigeration system with qualified stability.

[0044] The second aspect of the present invention also provides a cooling water temperature difference adjustment system for a refrigeration system based on energy consumption analysis. The cooling water temperature difference adjustment system includes a memory and a processor. The memory stores a cooling water temperature difference adjustment method. When the cooling water temperature difference adjustment method is executed by the processor, the following steps are implemented:

[0045] Obtain the operating parameter threshold of the target refrigeration system, and construct a target refrigeration simulation system based on the operating parameter threshold of the target refrigeration system;

[0046] Determine the heat exchange amount of the cooling water in the condenser simulation model in the refrigeration unit simulation model, and calculate different cooling parameter combinations of the cooling water pump simulation model in combination with the sensible heat formula;

[0047] In the cooling water pump simulation model with the operating frequency equal to the target operating frequency, calculate the optimal temperature difference between the supply and return water of the cooling water based on different cooling parameter combinations, and obtain the optimized target refrigeration system based on the optimal temperature difference between the supply and return water of the cooling water;

[0048] Operate the optimized target refrigeration system, and conduct operation stability evaluation and optimization on the optimized target refrigeration system during its operation.

[0049] To solve the technical defects existing in the background art, the present invention has the following beneficial effects: construct a target refrigeration simulation system that can simulate the operation of the target refrigeration system, calculate different cooling parameter combinations of the cooling water pump simulation model in the target refrigeration simulation system, and calculate the optimal cooling water supply and return temperature difference of the target refrigeration system according to different cooling parameter combinations. Finally, conduct operation stability evaluation and optimization on the optimized target refrigeration system. The present invention can construct a simulation model for the refrigeration system, conduct energy consumption analysis in the simulation model, obtain the optimal cooling water supply and return temperature difference of the refrigeration system, and realize intelligent adjustment of the energy consumption of the refrigeration system. It reduces the energy consumption during the operation of the refrigeration system, conforms to the economic benefits during refrigeration, and reduces the adverse impact on the environment during the refrigeration process. Brief Description of the Drawings

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0051] Figure 1 Shows the flowchart of the method for adjusting the cooling water temperature difference of the refrigeration system based on energy consumption analysis;

[0052] Figure 2 Shows the flowchart of the method for calculating the optimal cooling water supply and return temperature difference;

[0053] Figure 3 Shows the program view of the system for adjusting the cooling water temperature difference of the refrigeration system based on energy consumption analysis;

[0054] Figure 4 Shows the curves of the refrigeration unit simulation model under different cooling water supply and return temperature differences. Detailed Description of the Embodiments

[0055] In order to more clearly understand the above objects, features, and advantages of the present invention, the following will further describe the present invention in detail with reference to the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0056] In the following description, many specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention may be practiced in other ways than those specifically described herein, and thus, the scope of protection of the present invention is not limited by the specific embodiments disclosed below.

[0057] Figure 1 The flowchart of the cooling water temperature difference adjustment method for a refrigeration system based on energy consumption analysis is shown, including the following steps:

[0058] S102: Obtain the operating parameter thresholds of the target refrigeration system, and based on the operating parameter thresholds of the target refrigeration system, construct a target refrigeration simulation system;

[0059] S104: Determine the cooling water heat transfer amount of the condenser simulation model in the refrigeration unit simulation model, and combine with the sensible heat formula to calculate different cooling parameter combinations of the cooling water pump simulation model;

[0060] S106: In the cooling water pump simulation model with the operating frequency equal to the target operating frequency, based on different cooling parameter combinations, calculate the optimal cooling water supply and return temperature difference, and obtain the optimized target refrigeration system based on the optimal cooling water supply and return temperature difference;

[0061] S108: Operate the optimized target refrigeration system, and conduct operating stability evaluation and optimization during the operation of the optimized target refrigeration system.

[0062] Further, in a preferred embodiment of the present invention, the obtaining of the operating parameter thresholds of the target refrigeration system and constructing a target refrigeration simulation system based on the operating parameter thresholds of the target refrigeration system are specifically as follows:

[0063] Obtain the refrigeration system that needs to adjust the cooling water temperature difference, label it as the target refrigeration system, and label the sub-devices in the target refrigeration system as target sub-devices;

[0064] Obtain the user manual of the target refrigeration system, and based on the user manual of the target refrigeration system, obtain the operating parameter thresholds of all target sub-devices;

[0065] Obtain system modeling and simulation software, and construct a basic model of the refrigeration simulation system in the system modeling and simulation software;

[0066] Import the operating parameter thresholds of all target sub-devices into the system modeling and simulation software for data training and analysis to obtain the operating parameter threshold boundary conditions and the initial conditions of the operating parameter thresholds of the target sub-devices;

[0067] Apply the operating parameter threshold boundary conditions and the initial conditions of the operating parameters of the target sub-device to the basic model of the refrigeration simulation system to obtain the target refrigeration simulation system;

[0068] Among them, the target refrigeration simulation system includes a cooling water pump simulation model and a refrigeration unit simulation model, and the refrigeration unit simulation model includes a condenser simulation model.

[0069] It should be noted that the sub-devices of the target refrigeration system include a cooling water pump and a refrigeration unit. Among them, the main component of the refrigeration unit is the condenser, whose function is to condense the high-pressure gaseous refrigerant into a high-pressure liquid refrigerant to achieve the refrigeration purpose. It also includes an expansion valve and an evaporator to assist in providing the refrigeration purpose. The cooling water pump is used to circulate the cooling water, transporting the cooling water from the cooling tower or heat dissipation device to the condenser, and then sending the cooling water after absorbing heat back to the cooling tower or heat dissipation device for cooling. It is a device to maintain the efficient operation of the refrigeration system. The purpose of obtaining the operating parameter thresholds of the sub-devices is to provide data conditions for constructing the simulation model. After the system modeling and simulation software analyzes the operating parameters of the sub-devices, the operating parameter threshold boundary conditions and the initial conditions of the operating parameters can be obtained. Based on the operating parameter threshold boundary conditions and the initial conditions of the operating parameters, the target refrigeration simulation system can be constructed. The purpose of constructing the target refrigeration simulation system is to intuitively understand the parameter changes within the system and facilitate the adjustment of the temperature difference between the supply and return water of the cooling water.

[0070] Further, in a preferred embodiment of the present invention, determine the cooling water heat exchange amount of the condenser simulation model in the refrigeration unit simulation model, and combine it with the sensible heat formula to calculate different cooling parameter combinations of the cooling water pump simulation model, specifically:

[0071] Obtain a big data network and retrieve the sensible heat formula in the big data network;

[0072] Determine the temperature that the target refrigeration simulation system needs to output, and label it as the target temperature;

[0073] Input the target temperature into the refrigeration unit simulation model, control the refrigeration unit simulation model to analyze the target temperature, and obtain the cooling water heat exchange amount that the condenser simulation model in the refrigeration unit simulation model needs to output when the target refrigeration simulation system maintains the temperature equal to the target temperature, and label it as the target cooling water heat exchange amount;

[0074] Based on the user manual of the target refrigeration system, determine all the temperature differences between the supply and return water of the cooling water supported by the target refrigeration system, and label it as the selectable temperature difference between the supply and return water of the cooling water;

[0075] Based on the sensible heat formula and combined with the target cooling water heat transfer amount, calculate the required water flow of the cooling water pump simulation model corresponding to different selectable cooling water supply and return water temperature differences, and combine the selectable cooling water supply and return water temperature differences and the corresponding required water flow of the cooling water pump simulation model, and calibrate them as cooling parameter combinations.

[0076] It should be noted that the big data network is a database storing various solutions and formulas, and the sensible heat formula can be retrieved in the big data network. The sensible heat formula is: Where Q is the heat transfer amount, C is the specific heat capacity of the cooling water, M is the water flow of the cooling water, is the cooling water supply and return water temperature difference. Among them, C is a known number. To determine Q, the target temperature needs to be determined first. The heat output required for the target refrigeration simulation system to maintain different output temperatures is different. Therefore, according to the target temperature, determine the heat transfer amount of the target cooling water, and based on the heat transfer amount of the target cooling water, confirm M and . When Q is constant, M increases, and the corresponding should decrease. On the contrary, when Q is constant and M decreases, the corresponding should increase. Therefore, when Q is constant, the relationship between M and is uniquely determined, so different cooling parameter combinations are obtained. Among them, due to the limitation of the specification parameters of the target refrigeration system, the cooling water supply and return water temperature difference is limited. Therefore, it is necessary to calculate the required water flow of the cooling water pump simulation model corresponding to different selectable cooling water supply and return water temperature differences under the condition of the selectable cooling water supply and return water temperature difference, so as to obtain the cooling parameter combination.

[0077] Further, in a preferred embodiment of the present invention, operate and optimize the target refrigeration system, and perform operation stability evaluation and operation stability optimization on the optimized target refrigeration system during the operation of the optimized target refrigeration system, specifically:

[0078] Operate and optimize the target refrigeration system, and during the operation of the optimized target refrigeration system, judge whether the cooling water supply and return water temperature difference of the optimized target refrigeration system is constantly equal to the optimal cooling water supply and return water temperature difference;

[0079] If so, evaluate the optimized target refrigeration system as a refrigeration system with qualified stability;

[0080] If not, evaluate the optimized target refrigeration system as a refrigeration system with unqualified stability, and calibrate the operation parameters of each sub-device when the cooling water supply and return water temperature difference is not equal to the optimal cooling water supply and return water temperature difference in the unqualified stability refrigeration system as sub-device abnormal operation parameters;

[0081] Introduce the decision tree algorithm, construct a basic fault tree model based on the decision tree algorithm, convert the abnormal operation parameters of the sub-devices into a training set, and the training set contains the characteristic data of the abnormal operation parameters of the sub-devices;

[0082] Introduce the singular value decomposition algorithm to transform the characteristic data of the abnormal operation parameters of the sub-devices in the training set into a feature vector matrix, obtain the feature vector matrix, introduce the genetic algorithm, and import the feature vector matrix into the basic fault tree model. The basic fault tree model iteratively trains the feature vector matrix based on the genetic algorithm;

[0083] Preset the maximum number of iterative training times. When the number of times the basic fault tree model iteratively trains the feature vector matrix based on the genetic algorithm is equal to the maximum number of iterative training times, stop the iterative training to obtain a trained fault tree model;

[0084] Run the trained fault tree model, obtain all the abnormal positions of the sub-devices in the refrigeration system with unqualified stability, mark them as refrigeration abnormal positions, and retrieve and output the maintenance methods for the refrigeration abnormal positions in the big data network, so that the temperature difference between the supply and return water of the cooling water in the refrigeration system with unqualified stability is constantly equal to the optimal temperature difference between the supply and return water of the cooling water, and obtain a refrigeration system with qualified stability.

[0085] It should be noted that after applying the optimal temperature difference between the supply and return water of the cooling water in the target refrigeration system, if the temperature difference between the supply and return water of the cooling water in the target refrigeration system is constantly equal to the optimal temperature difference between the supply and return water of the cooling water, it proves that there is no abnormality in the target refrigeration system and it is a refrigeration system with qualified stability. Otherwise, it is a refrigeration system with unqualified stability. It is necessary to perform abnormal traceability positioning on the refrigeration system with unqualified stability and perform maintenance on the abnormal positions. Abnormal traceability positioning can be achieved by constructing a trained fault tree model. Based on the trained fault tree model, the abnormal positions of the refrigeration system with unqualified stability can be predicted. Obtain the abnormal operation parameters of the sub-devices and convert them into a training set. In the basic fault tree model, iterate and train the data in the training set, and the singular value decomposition algorithm and the genetic algorithm should be combined during the analysis. The singular value decomposition algorithm can convert the data into feature vector data, which plays a role in reducing the computational complexity. The genetic algorithm plays a role in finding the optimal solution during the training process, and stops training when the maximum number of iterative training times is reached. The output trained fault tree model can predict the abnormal positions of the refrigeration system with unqualified stability. After obtaining the abnormal positions of the refrigeration system with unqualified stability, through the big data network, the corresponding maintenance plans for the abnormal positions of the refrigeration system with unqualified stability can be retrieved. After outputting the maintenance plan, a refrigeration system with qualified stability can be obtained. Among them, the abnormal positions may usually be problems such as the cooling water pump may not circulate water, or there may be machine failures during refrigeration, etc.

[0086] Figure 2The flowchart of the method for calculating the optimal temperature difference between the supply and return water of the cooling water is shown, including the following steps:

[0087] S202: Adjust the operating frequency of the cooling water pump simulation model to be equal to the target operating frequency, and construct a type of cooling water pump simulation model;

[0088] S204: In the type of cooling water pump simulation model, based on different combinations of cooling parameters, calculate the input power of the type of cooling water pump simulation model under different combinations of cooling parameters;

[0089] S206: Conduct an input power analysis on the target refrigeration simulation system, and determine the optimal temperature difference between the supply and return water of the cooling water of the target refrigeration simulation system based on the input power analysis results.

[0090] Further, in a preferred embodiment of the present invention, the step of calculating the input power of the type of cooling water pump simulation model under different combinations of cooling parameters in the type of cooling water pump simulation model is specifically as follows:

[0091] Obtain the pump flow - head curve of the cooling water pump simulation model at different operating frequencies, and obtain the pump flow - shaft power curve of the cooling water pump simulation model at different operating frequencies;

[0092] When the cooling water pump model is equal to the type of cooling water pump model, based on the pump flow - head curve of the cooling water pump simulation model at different operating frequencies, obtain the pump flow - head curve of the type of cooling water pump model, and based on the pump flow - shaft power curve of the cooling water pump simulation model at different operating frequencies, obtain the pump flow - shaft power curve of the type of cooling water pump model;

[0093] Apply different combinations of cooling parameters in the type of cooling water pump simulation model, and combine the pump flow - head curve and the pump flow - shaft power curve of the type of cooling water pump model to obtain the head and shaft power of the type of cooling water pump model at different cooling water flows, and calculate the input power of the type of cooling water pump model under different combinations of cooling parameters based on the head and shaft power of the type of cooling water pump model at different cooling water flows.

[0094] It should be noted that the head is an important performance parameter of the cooling water pump, which refers to the maximum height that the cooling water pump can lift the liquid after overcoming the liquid flow resistance, usually expressed in meters. The shaft power refers to the actual power transmitted by the cooling water pump to the liquid, usually expressed in kilowatts. The shaft power reflects the energy transfer ability of the cooling water pump under specific working conditions. Among them, the mathematical formula of the pump flow - head curve is: Among them, H(Q) refers to the head, with the unit of meter, as a function of the flow rate Q, is the maximum head of the cooling water pump at zero flow rate. Q represents the flow rate of the cooling water, with the unit of cubic meters per second. a and b are constants fitted based on the performance data of the actual cooling water pump. The mathematical formula for the pump flow rate - shaft power curve is: Among them, represents the shaft power of the cooling water pump, represents the density of the cooling water, g represents the acceleration due to gravity, Q represents the flow rate of the cooling water, and H represents the head of the cooling water, represents the efficiency of the cooling water pump. Through the pump flow rate - head curve and the pump flow rate - shaft power curve, the head and shaft power of a type of cooling water pump model at different cooling water flow rates can be calculated. Since the head and shaft power of a type of cooling water pump model vary at different cooling water flow rates, they need to be calculated separately. When calculating the input power of a type of cooling water pump model under different cooling parameter combinations, the shaft power needs to be considered, and its calculation formula is: Among them, represents the input power of a type of cooling water pump, represents the shaft power of the cooling water pump, represents the efficiency of the drive in the cooling water pump. The efficiency of the drive in the cooling water pump can be monitored and obtained through sensors.

[0095] Furthermore, in a preferred embodiment of the present invention, when performing input power analysis on the target refrigeration simulation system and determining the optimal cooling water supply - return water temperature difference of the target refrigeration simulation system based on the input power analysis result, specifically:

[0096] Calculate the input power when the condenser simulation model in the refrigeration unit simulation model outputs the target cooling water heat transfer amount, and calibrate it as the refrigeration input power of the refrigeration unit simulation model;

[0097] Add the input power of the type of cooling water pump model under different cooling parameter combinations to the refrigeration input power of the refrigeration unit simulation model to obtain the corresponding total input power of the target refrigeration simulation system when applying different cooling parameter combinations;

[0098] Analyze the corresponding total input power of the target refrigeration simulation system when applying different cooling parameter combinations, select the cooling parameter combination corresponding to the minimum total input power of the target refrigeration simulation system, and calibrate it as the target cooling parameter combination;

[0099] Based on the target cooling parameter combination, obtain the cooling water supply - return water temperature difference of the target cooling parameter combination, and calibrate it as the optimal cooling water supply - return water temperature difference;

[0100] Apply the optimal cooling water supply - return water temperature difference in the target refrigeration system to obtain an optimized target refrigeration system.

[0101] It should be noted that after obtaining the input power of a type of cooling water pump model under different combinations of cooling parameters, it is necessary to combine it with the input power when the condenser simulation model in the refrigeration unit simulation model outputs the target cooling water heat exchange amount to obtain the total input power. Based on the curve of the refrigeration unit simulation model under different cooling water supply and return temperature differences, it can be known that the input power when the condenser simulation model in the refrigeration unit simulation model outputs the target cooling water heat exchange amount increases with the increase of the load of the refrigeration unit and tends to be stable after reaching the highest point. Since the heat exchange amount of the target cooling water in the refrigeration unit is determined, the input power when the condenser simulation model in the refrigeration unit simulation model outputs the target cooling water heat exchange amount is known. The total input power is different under different combinations of cooling parameters, and there is one combination of cooling parameters that will minimize the total input power of the target refrigeration simulation system. At this time, this combination of cooling parameters is the target cooling parameter combination. Based on the target cooling parameter combination, the optimal cooling water supply and return temperature difference can be obtained. When the target cooling system is under the optimal cooling water supply and return temperature difference, the energy consumption generated during its operation is the lowest, and it is more environmentally friendly and energy-saving.

[0102] In addition, the method for adjusting the cooling water temperature difference of the refrigeration system based on energy consumption analysis further includes the following steps:

[0103] If the cooling water supply and return temperature difference of the refrigeration system with unqualified stability still does not remain constant and equal to the optimal cooling water supply and return temperature difference after the maintenance method for the refrigeration abnormal position is output, then the refrigeration system with unqualified stability is calibrated as an abnormally maintained refrigeration system;

[0104] Obtain a PID controller, connect the PID controller to the abnormally maintained refrigeration system, and retrieve the PID parameters corresponding to the PID controller when the cooling water supply and return temperature difference of the abnormally maintained refrigeration system remains constant and equal to the optimal cooling water supply and return temperature difference in the big data network, and calibrate them as the target PID parameters;

[0105] Configure the target PID parameters in the PID controller to obtain a parameter-configured PID controller, perform PID control on the abnormally maintained refrigeration system through the parameter-configured PID controller, and preset a control standard period;

[0106] Within the control standard period, determine whether the cooling water supply and return temperature difference of the abnormally maintained refrigeration system remains constant and equal to the optimal cooling water supply and return temperature difference;

[0107] If so, obtain a refrigeration system with qualified stability, and calibrate the parameter-configured PID controller as a parameter-configured stable PID controller;

[0108] If not, repeatedly adjust the integral time and derivative time in the parameter configuration PID controller to obtain the integral time and derivative time that can make the temperature difference between the supply and return water of the cooling water in the abnormal maintenance refrigeration system constantly equal to the optimal temperature difference between the supply and return water of the cooling water. Calibrate them as the optimal integral time and the optimal derivative time, and adjust the integral time and derivative time to the optimal integral time and the optimal derivative time in the parameter configuration PID controller.

[0109] It should be noted that the PID controller is a control method for controlling a refrigeration system. By adjusting variables of the refrigeration system, such as the water flow rate in the cooling water pump, the rotation speed of the compressor, the opening and closing degree of the regulating valve, etc., the refrigeration system is maintained within the set parameter thresholds. The PID controller realizes the control of the refrigeration system through proportional control (P), integral control (I), and derivative control (D). After obtaining the target PID parameters, apply them to the PID controller to realize the control of the temperature difference between the supply and return water of the cooling water in the refrigeration system. If the temperature difference between the supply and return water of the cooling water in the refrigeration system is still not constantly equal to the optimal temperature difference between the supply and return water of the cooling water, it proves that the parameters in the PID controller still need to be adjusted at this time. The adjustment method is to adjust the integral time and derivative time in the PID controller. For example, if there is an error in the refrigeration system, the integral time can be appropriately reduced. However, reducing the integral time may cause the refrigeration system to be unstable and oscillate. At this time, the derivative time needs to be appropriately increased to ensure that the oscillation amplitude of the system is reduced and the temperature difference between the supply and return water of the cooling water in the refrigeration system is constantly equal to the optimal temperature difference between the supply and return water of the cooling water.

[0110] As Figure 3 shown, the second aspect of the present invention also provides a cooling water temperature difference adjustment system for a refrigeration system based on energy consumption analysis. The cooling water temperature difference adjustment system includes a memory 31 and a processor 32. The memory 31 stores a cooling water temperature difference adjustment method. When the cooling water temperature difference adjustment method is executed by the processor 32, the following steps are realized:

[0111] Obtain the operation parameter thresholds of the target refrigeration system, and based on the operation parameter thresholds of the target refrigeration system, construct a target refrigeration simulation system;

[0112] Determine the heat exchange amount of the cooling water in the condenser simulation model in the refrigeration unit simulation model, and combine with the sensible heat formula to calculate different cooling parameter combinations of the cooling water pump simulation model;

[0113] In the cooling water pump simulation model with the operating frequency equal to the target operating frequency, based on different cooling parameter combinations, calculate the optimal temperature difference between the supply and return water of the cooling water, and obtain an optimized target refrigeration system based on the optimal temperature difference between the supply and return water of the cooling water;

[0114] Operate the optimized target refrigeration system, and conduct operation stability evaluation and operation stability optimization on the optimized target refrigeration system during the operation of the optimized target refrigeration system.

[0115] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for adjusting the temperature difference of cooling water in a refrigeration system based on energy consumption analysis, characterized in that: The following steps are involved: Acquire an operating parameter threshold of a target refrigeration system, and construct a target refrigeration simulation system based on the operating parameter threshold of the target refrigeration system; Determine the cooling water heat exchange capacity of the condenser simulation model in the refrigeration unit simulation model, and calculate different cooling parameter combinations of the cooling water pump simulation model in combination with the sensible heat formula; In a cooling water pump simulation model whose operating frequency is equal to the target operating frequency, the optimal cooling water supply and return water temperature difference is calculated based on different cooling parameter combinations, and the optimized target refrigeration system is obtained based on the optimal cooling water supply and return water temperature difference; operating the optimized target refrigeration system, and performing operation stability evaluation and operation stability optimization on the optimized target refrigeration system during the operation of the optimized target refrigeration system; The operation of the optimized target refrigeration system and the evaluation and optimization of the operation stability of the optimized target refrigeration system during the operation of the optimized target refrigeration system are specifically as follows: Running the optimized target refrigeration system, and during the operation of the optimized target refrigeration system, determining whether the cooling water supply and return water temperature difference of the optimized target refrigeration system is constant and equal to the optimal cooling water supply and return water temperature difference; If yes, the optimized target refrigeration system is evaluated as a refrigeration system with qualified stability; If not, the optimization target refrigeration system is evaluated as a refrigeration system with unqualified stability, and in the refrigeration system with unqualified stability, the operating parameters of each sub-equipment when the cooling water supply and return water temperature difference is not equal to the optimal cooling water supply and return water temperature difference is calibrated as abnormal operating parameters of the sub-equipment; A decision tree algorithm is introduced, a fault tree basic model is constructed based on the decision tree algorithm, and abnormal operation parameters of sub-equipment are converted into a training set, wherein the training set contains characteristic data of abnormal operation parameters of sub-equipment; A singular value decomposition algorithm is introduced to transform the characteristic data of abnormal operation parameters of sub-equipment in the training set into a characteristic vector matrix to obtain a characteristic vector matrix, a genetic algorithm is introduced to import the characteristic vector matrix into a fault tree basic model, and the fault tree basic model iteratively trains the characteristic vector matrix based on the genetic algorithm; A maximum number of iterative training times is preset, and when the number of iterative training times of the fault tree basic model on the characteristic vector matrix based on the genetic algorithm is equal to the maximum number of iterative training times, the iterative training is stopped to obtain a fault tree training model; Run the fault tree training model to obtain all abnormal positions of sub-equipment in the refrigeration system with unqualified stability, mark them as refrigeration abnormal positions, and retrieve and output the maintenance methods of the refrigeration abnormal positions in the big data network, so that the cooling water supply and return water temperature difference of the refrigeration system with unqualified stability is constant and equal to the optimal cooling water supply and return water temperature difference, and obtain a refrigeration system with qualified stability; Wherein, the cooling water temperature difference adjustment method of the refrigeration system based on energy consumption analysis further includes the following steps: If, after the inspection method of the abnormal refrigeration position is output, the cooling water supply and return water temperature difference of the unqualified stability refrigeration system is still not constant and equal to the optimal cooling water supply and return water temperature difference, the unqualified stability refrigeration system is calibrated as an abnormal inspection refrigeration system; Obtain a PID controller, connect the PID controller to the abnormal maintenance refrigeration system, and retrieve PID parameters corresponding to the PID controller when the cooling water supply and return water temperature difference of the abnormal maintenance refrigeration system is constant and equal to the optimal cooling water supply and return water temperature difference in the big data network, and calibrate them as target PID parameters; Configuring target PID parameters in the PID controller to obtain a parameter-configured PID controller, performing PID control on the abnormal maintenance refrigeration system through the parameter-configured PID controller, and presetting a control standard cycle; During the control standard cycle, determining whether the cooling water supply and return water temperature difference of the abnormal maintenance refrigeration system is constant and equal to the optimal cooling water supply and return water temperature difference; If so, a refrigeration system with qualified stability is obtained, and the parameter configuration PID controller is calibrated as a parameter configuration stable PID controller; If not, the integral time and differential time in the parameter-configured PID controller are repeatedly adjusted to obtain the integral time and differential time that can make the cooling water supply and return water temperature difference of the abnormal maintenance refrigeration system constant equal to the optimal cooling water supply and return water temperature difference, calibrate them as the optimal integral time and optimal differential time, and adjust the integral time and differential time to the optimal integral time and optimal differential time in the parameter-configured PID controller.

2. The method for adjusting the temperature difference of cooling water in a refrigeration system based on energy consumption analysis according to claim 1, characterized in that: The step of obtaining the operating parameter threshold of the target refrigeration system and constructing the target refrigeration simulation system based on the operating parameter threshold of the target refrigeration system is specifically as follows: Acquire a refrigeration system that needs to adjust the cooling water temperature difference, mark it as a target refrigeration system, and mark a sub-device as a target sub-device in the target refrigeration system; Obtaining an instruction manual of a target refrigeration system, and obtaining operating parameter thresholds of all target sub-devices based on the instruction manual of the target refrigeration system; Obtaining system modeling and simulation software, and constructing a basic model of a refrigeration simulation system in the system modeling and simulation software; Importing the operating parameter thresholds of all target sub-devices into the system modeling simulation software for data training and analysis to obtain the operating parameter threshold boundary conditions of the target sub-devices and the operating parameter threshold initial conditions of the target sub-devices; Applying the target sub-device operation parameter threshold boundary conditions and the target sub-device operation parameter threshold initial conditions in the refrigeration simulation system basic model to obtain a target refrigeration simulation system; The target refrigeration simulation system includes a cooling water pump simulation model and a refrigeration unit simulation model, and the refrigeration unit simulation model includes a condenser simulation model.

3. The method for adjusting the temperature difference of cooling water in a refrigeration system based on energy consumption analysis according to claim 1, characterized in that: The cooling water heat exchange capacity of the condenser simulation model in the refrigeration unit simulation model is determined, and different cooling parameter combinations of the cooling water pump simulation model are calculated in combination with the sensible heat formula, specifically: Obtaining a big data network, and retrieving a sensible heat formula in the big data network; Determine the temperature that the target refrigeration simulation system needs to output and calibrate it as the target temperature; Input the target temperature into the refrigeration unit simulation model, control the refrigeration unit simulation model to analyze the target temperature, and obtain the cooling water heat exchange amount that the condenser simulation model in the refrigeration unit simulation model needs to output when the target refrigeration simulation system maintains the temperature equal to the target temperature, which is calibrated as the target cooling water heat exchange amount; Based on the instruction manual of the target refrigeration system, all cooling water supply and return water temperature differences supported by the target refrigeration system are determined and calibrated as selectable cooling water supply and return water temperature differences; Based on the sensible heat formula and in combination with the target cooling water heat exchange rate, the required water flow of the cooling water pump simulation model corresponding to different selectable cooling water supply and return water temperature differences is calculated, and the selectable cooling water supply and return water temperature differences and the corresponding required water flow of the cooling water pump simulation model are combined and calibrated as a cooling parameter combination.

4. The method for adjusting the temperature difference of cooling water in a refrigeration system based on energy consumption analysis according to claim 1, characterized in that: In the cooling water pump simulation model whose operating frequency is equal to the target operating frequency, the optimal cooling water supply and return water temperature difference is calculated based on different cooling parameter combinations, and the optimized target refrigeration system is obtained based on the optimal cooling water supply and return water temperature difference, specifically: Obtaining the water pump flow-head curve of the cooling water pump simulation model at different operating frequencies, and obtaining the water pump flow-shaft power curve of the cooling water pump simulation model at different operating frequencies; Controlling the operation of the cooling water pump simulation model, during the operation of the cooling water pump simulation model, presetting a target operating frequency of the cooling water pump simulation model, and adjusting the operating frequency of the cooling water pump simulation model to be equal to the target operating frequency, thereby obtaining a class of cooling water pump simulation models; When the cooling water pump model is equal to a type of cooling water pump model, a water pump flow-head curve of a type of cooling water pump model is obtained based on a water pump flow-head curve of the cooling water pump simulation model at different operating frequencies, and a water pump flow-shaft power curve of a type of cooling water pump model is obtained based on a water pump flow-shaft power curve of the cooling water pump simulation model at different operating frequencies; Applying different cooling parameter combinations to the cooling water pump simulation model, and combining the pump flow-head curve of the cooling water pump model and the pump flow-shaft power curve of the cooling water pump model, obtaining the head and shaft power of the cooling water pump model at different cooling water flow rates, and calculating the input power of the cooling water pump model under different cooling parameter combinations based on the head and shaft power of the cooling water pump model at different cooling water flow rates; Based on the input power of the cooling water pump model under different cooling parameter combinations, an energy consumption analysis is performed on the target refrigeration simulation system, and the optimal cooling water supply and return water temperature difference of the target refrigeration simulation system is determined based on the energy consumption analysis result.

5. The method for adjusting the cooling water temperature difference of a refrigeration system based on energy consumption analysis according to claim 4, characterized in that: The target refrigeration simulation system is subjected to input power analysis, and the optimal cooling water supply and return water temperature difference of the target refrigeration simulation system is determined based on the input power analysis result, specifically: Calculate the input power when the condenser simulation model in the refrigeration unit simulation model outputs the target cooling water heat exchange amount, and calibrate it as the refrigeration input power of the refrigeration unit simulation model; The input power of a cooling water pump model under different cooling parameter combinations is added to the cooling input power of the refrigeration unit simulation model to obtain the total input power corresponding to the target refrigeration simulation system when different cooling parameter combinations are applied; The total input power corresponding to the target refrigeration simulation system when different cooling parameter combinations are applied is analyzed, and the cooling parameter combination corresponding to the minimum total input power of the target refrigeration simulation system is selected and calibrated as the target cooling parameter combination; Based on the target cooling parameter combination, a cooling water supply and return water temperature difference of the target cooling parameter combination is obtained, and calibrated as an optimal cooling water supply and return water temperature difference; The optimal cooling water supply and return water temperature difference is applied in the target refrigeration system to obtain an optimized target refrigeration system.

6. A cooling water temperature difference adjustment system for a refrigeration system based on energy consumption analysis, characterized in that: The cooling water temperature difference adjustment system includes a memory and a processor, wherein a cooling water temperature difference adjustment method program is stored in the memory, and when the cooling water temperature difference adjustment method program is executed by the processor, the cooling water temperature difference adjustment method steps as described in any one of claims 1 to 5 are implemented.

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