Air conditioner cold source system operation control method based on load prediction

Abstract

The air conditioner cold source system operation control method based on load prediction comprises the steps that dynamic monitoring data fusing water chilling unit equipment body characteristics, operation working conditions and surrounding environment comprehensive influences are obtained; a water chilling unit system load prediction model and a water chilling unit variable working condition performance prediction model are constructed based on the dynamic monitoring data, and the dynamic monitoring data comprise current operation parameters of the water chilling unit and multi-element environment and building operation comprehensive monitoring data; and calculating the load of the next hour based on the water chilling unit system load prediction model, calculating the performance of the cold machine after machine adding or machine reducing in the next hour by using the water chilling unit variable working condition performance prediction model, and adjusting the starting-up combination of the water chilling unit according to the load change and the unit performance change. By implementing the method, accurate active control and efficient adjustment of the air conditioner cold source system can be achieved.

Description

Technical Field

[0001] This application relates to the field of automatic control technology for air conditioning systems, and more specifically, to a method for operating control of an air conditioning cold source system based on load forecasting. Background Technology

[0002] According to statistics, the average power consumption of airport terminals in my country is approximately The energy consumption of airport buildings is almost twice that of existing energy-saving standards for commercial office buildings. Among these, the energy consumption of heating and air conditioning systems accounts for 40% to 70% of the overall energy consumption of airport buildings. Therefore, it is crucial to achieve energy-saving design and efficient operation of air conditioning systems to reduce the overall energy consumption of the terminal building while meeting indoor environmental requirements.

[0003] The key to energy-saving design and efficient operation of air conditioning cooling systems lies in the precise control and efficient matching of cooling demand. In recent years, scholars both domestically and internationally have conducted a series of studies on air conditioning load forecasting, aiming to achieve proactive control and efficient regulation of air conditioning cooling systems through accurate prediction of heating and cooling loads. However, existing load forecasting models generally suffer from the following problems in practical engineering applications: on the one hand, too many precise physical parameters are required, while actual engineering applications often lack accurate design and construction parameters, making it difficult to build forecasting models. On the other hand, due to oversimplification of the models, the accuracy of the forecast results is low, making it difficult to guide practical engineering applications.

[0004] Therefore, in order to effectively solve the problems of difficulty in obtaining parameters and insufficient prediction accuracy of existing air conditioning load prediction models in practical engineering applications, and to effectively reduce the operating energy consumption of the air conditioning cooling source system of airport terminals and improve the overall energy utilization efficiency of the terminal, it is necessary to carry out research on new air conditioning load prediction models for the characteristics of airport terminals, and to build a more scientific and reasonable prediction system that is adapted to actual engineering conditions, so as to achieve precise and active control and efficient regulation of the air conditioning cooling source system. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an operation control method for an air conditioning cold source system based on load forecasting, which addresses the shortcomings of the prior art.

[0006] The technical solution of this invention to solve the above-mentioned technical problems is as follows: A method for operating control of an air conditioning cold source system based on load forecasting, comprising the following steps:

[0007] S1. Acquire dynamic monitoring data that integrates the characteristics of the chiller unit itself, its operating conditions, and the comprehensive influence of the surrounding environment. Based on the dynamic monitoring data, construct a system load prediction model for the chiller unit and a variable operating condition performance prediction model for the chiller unit. The dynamic monitoring data includes the current operating parameters of the chiller unit and comprehensive monitoring data of multiple environments and building operations.

[0008] S2. Calculate the load for the next hour based on the chiller system load prediction model, and calculate the chiller performance for the next hour after adding or removing chillers using the chiller variable operating condition performance prediction model. Adjust the chiller start-up combination according to load changes and unit performance changes.

[0009] Furthermore, in step S1, the calculation formula for the chiller system load prediction model includes:

[0010] ;

[0011] in, express Real-time forecasting of building cooling load, Indicates that it is determined based on outdoor meteorological data. outdoor dry-bulb temperature at all times Indicates that it is determined based on outdoor meteorological data. outdoor solar radiation intensity at any time Indicates that it is determined based on building operation data. Constant ventilation and electricity consumption Indicates that it is determined based on outdoor meteorological data. outdoor air enthalpy value at any time Indicates that it is determined based on outdoor meteorological data. outdoor wind speed at all times Indicates that it is determined based on building operation data. Total electricity consumption at all times This represents the sensible heat output per person per unit, determined based on personnel pyrography data. This represents the latent heat output per employee per unit, determined based on employee pyrography data. This represents the coefficients obtained through regression fitting.

[0012] Furthermore, in step S1, based on the chiller unit variable operating condition performance prediction model, the chiller unit cooling efficiency is predicted through the following steps:

[0013] (1) Obtain real-time monitoring data of the chiller unit and input the real-time monitoring data of the chiller unit into the system load prediction model of the chiller unit for calculation to obtain the building cooling load;

[0014] (2) Based on the building cooling load, chilled water flow rate and cooling water flow rate, the evaporation temperature and condensation temperature are determined by series analysis of multi-stage thermodynamic models and parameter iteration solution;

[0015] (3) Determine the condensation-evaporation temperature difference based on the ratio between the condensation temperature and the evaporation temperature;

[0016] (4) Determine the rated cooling capacity based on the chiller start-up combination, and determine the load rate of each chiller based on the ratio between the building cooling load and the rated cooling capacity;

[0017] (5) Based on the condensation-evaporation temperature difference and the load rate of each chiller, the refrigeration efficiency of the chiller unit is calculated by a comprehensive calculation method that combines regression fitting and thermodynamic theory.

[0018] (6) When the difference between the chiller unit’s cooling efficiency and the ideal chiller unit’s operating efficiency is less than a preset threshold, output the current chiller unit’s cooling efficiency; otherwise, adjust the current chiller unit’s operating efficiency and perform iterative calculations of the chiller unit’s cooling efficiency based on the adjusted parameter values.

[0019] Furthermore, the chilled water flow rate is determined through the following steps:

[0020] (1) Substitute the obtained outdoor wet-bulb temperature into the formula of the first correlation model constructed by a quadratic polynomial and determined by regression fitting of actual operation data to calculate the temperature difference between chilled water supply and return water.

[0021] (2) Based on the building cooling load and the temperature difference between the chilled water supply and return water, the chilled water flow rate is calculated by converting the heat exchange equal relationship between the chilled water and the building cooling load in the circulation system according to the energy conservation rule.

[0022] Furthermore, the cooling water flow rate is determined through the following steps:

[0023] (1) The heat dissipation of the condenser is obtained by combining the operating efficiency of the chiller unit and the cooling load of the building;

[0024] (2) Substitute the obtained outdoor wet-bulb temperature into the formula of the second correlation model constructed by a quadratic polynomial and determined by regression fitting of actual operating data to calculate and determine the cooling water supply and return water temperature difference;

[0025] (3) Based on the heat dissipation of the condenser and the temperature difference between the supply and return water of the cooling water, the flow rate of the cooling water is calculated according to the role of the cooling water in the circulation system and the law of energy conservation, based on the heat balance.

[0026] Furthermore, the evaporation temperature is determined through the following steps:

[0027] (1) The determined chilled water flow rate and building cooling load are input into the following evaporator heat transfer model, and the evaporator heat transfer area is obtained through regression analysis:

[0028] ;

[0029] in, Indicates the building's cooling load. Indicates chilled water flow rate, This represents the regression fit coefficient determined based on actual operating data.

[0030] (2) Based on the chilled water flow rate, building cooling load and determined chilled water supply temperature, the chilled water return temperature is obtained by inverse calculation and parameter decoupling based on the law of conservation of energy;

[0031] (3) Based on the heat transfer area of ​​the evaporator and the building cooling load, the logarithmic mean temperature difference of the evaporator is obtained by reverse derivation of the basic heat transfer equation.

[0032] (4) Based on the logarithmic mean temperature difference of the evaporator, the chilled water supply temperature and the chilled water return temperature, the evaporation temperature is obtained by reverse derivation of the formula for calculating the logarithmic mean temperature difference of the evaporator and the solution of temperature parameters.

[0033] Furthermore, the condensation temperature is determined through the following steps:

[0034] (1) The determined cooling water flow rate and condenser heat dissipation are substituted into the following condenser heat transfer model, and the condenser heat transfer area is obtained through regression analysis:

[0035] ;

[0036] in, Indicates the heat dissipation of the condenser. Indicates the cooling water flow rate. This represents the regression fit coefficient determined based on actual operating data.

[0037] (2) Based on the cooling water flow rate, condenser heat dissipation and the determined cooling water supply temperature, the cooling water return temperature is obtained by inverse calculation and parameter decoupling based on the law of conservation of energy.

[0038] (3) Based on the heat transfer area and heat dissipation of the condenser, the logarithmic mean temperature difference of the condenser is obtained by reverse derivation of the heat transfer equation of the condenser.

[0039] (4) Based on the logarithmic mean temperature difference of the condenser, the supply temperature of the cooling water and the return temperature of the cooling water, the condensing temperature is obtained by reverse derivation of the formula for calculating the logarithmic mean temperature difference of the condenser and the solution of the temperature parameters.

[0040] Furthermore, based on the condensation-evaporation temperature difference and the load rate of each chiller, the chiller unit's refrigeration efficiency is calculated using a comprehensive calculation method that integrates regression fitting and thermodynamic theory, including:

[0041] (1) Based on the condensation-evaporation temperature difference and the load rate of each chiller, regression fitting analysis was performed to obtain the thermodynamic perfection of the chiller unit;

[0042] (2) The coefficient of performance of the ideal refrigeration cycle is obtained by performing thermodynamic analysis based on the condensation temperature and evaporation temperature;

[0043] (3) The cooling efficiency of the chiller is obtained by multiplying the coefficient of performance of the ideal refrigeration cycle with the thermal perfection of the chiller.

[0044] Furthermore, in step S2, the calculation of the load for the next hour based on the chiller system load prediction model, and the calculation of the chiller performance after adding more chillers for the next hour using the chiller variable operating condition performance prediction model, and the adjustment of the chiller unit start-up combination according to load changes and unit performance changes, include:

[0045] (1) When the chilled water supply temperature is determined to be greater than the preset value, if the current chiller operating load rate is greater than the preset maximum allowable load rate, the load for the next hour is calculated using the chiller system load prediction model.

[0046] (2) If the load value is less than or equal to the preset threshold and the operating load rate in the next hour is greater than the preset maximum allowable load rate, it is determined that applying the current start-up combination in the next hour will reduce the operating efficiency of the chiller unit. At this time, it is determined to execute the add-unit strategy. Otherwise, the current start-up combination is maintained and the set value of the chilled water supply and return water temperature difference is reduced.

[0047] (3) If the load value is greater than the preset threshold, the chiller performance after adding more chiller in the next hour is calculated using the chiller variable operating condition performance prediction model.

[0048] (4) If the performance value is greater than the preset threshold, it is determined that the performance of the chiller will be improved by implementing the additional chiller strategy in the next hour. At this time, it is determined to implement the additional chiller strategy. Otherwise, the current start-up combination is maintained and the set value of the chilled water supply and return water temperature difference is reduced.

[0049] Furthermore, in step S2, the calculation of the load for the next hour based on the chiller system load prediction model, and the calculation of the chiller performance after reducing capacity for the next hour using the chiller variable operating condition performance prediction model, and the adjustment of the chiller unit start-up combination according to load changes and unit performance changes, include:

[0050] (1) When the chilled water supply temperature is determined to be less than or equal to the preset value, if the current chiller operating load rate is less than the preset minimum allowable load rate, the load for the next hour is calculated using the chiller system load prediction model.

[0051] (2) If the load value is greater than or equal to the preset threshold and the operating load rate in the next hour is less than the preset minimum allowable load rate, it is determined that the application of the current start-up combination in the next hour will cause the chiller to operate in an inefficient state. At this time, it is determined to execute the reduction strategy. Otherwise, the current start-up combination is maintained and the set value of the chilled water supply and return water temperature difference is increased.

[0052] (3) If the load value is less than the preset threshold, the chiller performance after the unit is reduced in the next hour is predicted using the chiller variable operating condition performance prediction model.

[0053] (4) If the performance value is greater than or equal to the preset threshold, it is determined that the chiller performance will be improved by implementing the reduction strategy in the next hour. At this time, the reduction strategy is determined to be implemented. Otherwise, the current operating combination is maintained and the temperature difference setting of chilled water supply and return is increased.

[0054] The beneficial effects of this invention are: by acquiring dynamic monitoring data that integrates multiple factors and constructing a load and performance prediction model, the operating pattern of the chiller unit can be accurately grasped; based on the model, the future load and chiller performance after adding or removing units can be calculated, and the start-up combination can be reasonably adjusted, which can effectively improve the operating efficiency of the chiller unit, reduce energy consumption, and achieve stable and efficient system operation. Attached Figure Description

[0055] Figure 1 This is a flowchart illustrating an air conditioning cold source system operation control method based on load forecasting disclosed in this invention. Detailed Implementation

[0056] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0057] like Figure 1 As shown, this application discloses an operation control method for an air conditioning cold source system based on load forecasting, which includes the following steps:

[0058] Step S1: Obtain dynamic monitoring data that integrates the characteristics of the chiller unit itself, its operating conditions, and the comprehensive influence of the surrounding environment. Based on the dynamic monitoring data, construct a system load prediction model and a variable operating condition performance prediction model for the chiller unit. The dynamic monitoring data includes the current operating parameters of the chiller unit and comprehensive monitoring data of multiple environments and building operations.

[0059] Specifically, the current operating parameters of the chiller unit include the current operating configuration of the chiller unit, the operating efficiency of the chiller unit, and the operating load rate, etc., and the multi-environment and building operation integrated monitoring data include outdoor meteorological data, building operation data, and personnel fever data, etc.

[0060] Step S2: Calculate the load for the next hour based on the chiller system load prediction model, and calculate the chiller performance for the next hour after adding or removing chillers using the chiller variable operating condition performance prediction model. Adjust the chiller start-up combination according to the load change and unit performance change.

[0061] Specifically, this application calculates the system load forecast for the next hour based on the aforementioned chiller system load prediction model. Then, it determines the load change trend based on this forecast: if the predicted load for the next hour is greater than 90% of the current load, the load is considered not to have decreased significantly; if it is less than or equal to 90% of the current load, the load is considered to have decreased. Next, for different load change scenarios, this application also uses the aforementioned chiller variable operating condition performance prediction model for calculation. When it is determined that the load has not decreased significantly, the chiller performance after adding more chiller units in the next hour is calculated; when it is determined that the load may decrease, the chiller performance after reducing the number of units in the next hour is calculated. Finally, the calculated chiller performance is compared and analyzed with the current chiller performance. If the chiller performance value after adding or removing chillers is greater than or equal to the preset performance improvement threshold (e.g., 160% of the current chiller performance), it is determined that implementing the corresponding addition or removal strategy will improve the chiller performance, and the chiller unit start-up combination will be adjusted accordingly. If the performance improvement does not reach the threshold, the current start-up combination will be maintained, and the chilled water supply and return water temperature difference setting value will be appropriately reduced according to the actual situation to optimize system operation.

[0062] As can be seen from the above, the air conditioning cold source system operation control method disclosed in this application, by acquiring dynamic monitoring data that integrates multiple influences and constructing a load and performance prediction model, can accurately grasp the operating law of the chiller unit; based on the model, it calculates the future load and the chiller performance after adding or removing units, and then reasonably adjusts the start-up combination, which can effectively improve the operating efficiency of the chiller unit, reduce energy consumption, and achieve stable and efficient system operation.

[0063] In one embodiment, in step S1, the calculation formula for the chiller system load prediction model includes:

[0064] ;

[0065] in, express Real-time forecasting of building cooling load, Indicates that it is determined based on outdoor meteorological data. outdoor dry-bulb temperature at all times Indicates that it is determined based on outdoor meteorological data. outdoor solar radiation intensity at any time Indicates that it is determined based on building operation data. Constant ventilation and electricity consumption Indicates that it is determined based on outdoor meteorological data. outdoor air enthalpy value at any time Indicates that it is determined based on outdoor meteorological data. outdoor wind speed at all times Indicates that it is determined based on building operation data. Total electricity consumption at all times This represents the sensible heat output per person per unit, determined based on personnel pyrography data. This represents the latent heat output per employee per unit, determined based on employee pyrography data. This represents the coefficients obtained through regression fitting.

[0066] It should be noted that, based on the functional characteristics and building envelope of the airport terminal, the building cooling load mainly consists of heat gain from the building envelope, solar radiation heat gain, fresh air load, heat dissipation from personnel, and heat gain from equipment. This application, based on the principle of HVAC load calculation, adopts a regression analysis method, using data from continuous testing and measurement of actual cooling capacity as the training set to regress unknown parameters or parameters that are difficult to obtain in the model, and substitutes them into the data in the test set to test the model. The model that passes the test will be used as the load prediction model required for future operation and adjustment decision-making.

[0067] In one embodiment, in step S1, the chiller unit's cooling efficiency is predicted based on the chiller unit's variable operating condition performance prediction model through the following steps:

[0068] (1) Obtain real-time monitoring data of the chiller unit and input the real-time monitoring data of the chiller unit into the system load prediction model of the chiller unit for calculation to obtain the building cooling load.

[0069] (2) Based on the building's cooling load, chilled water flow rate and cooling water flow rate, the evaporation temperature and condensation temperature are determined by series analysis of multi-stage thermodynamic models and parameter iteration.

[0070] (3) Determine the condensation-evaporation temperature difference based on the ratio between the condensation temperature and the evaporation temperature.

[0071] (4) Determine the rated cooling capacity based on the chiller start-up combination, and determine the load rate of each chiller based on the ratio between the building cooling load and the rated cooling capacity.

[0072] (5) Based on the condensation-evaporation temperature difference and the load rate of each chiller, the refrigeration efficiency of the chiller unit is calculated by integrating regression fitting and thermodynamic theory.

[0073] (6) When the difference between the chiller unit’s cooling efficiency and the ideal chiller unit’s operating efficiency is less than a preset threshold, output the current chiller unit’s cooling efficiency; otherwise, adjust the current chiller unit’s operating efficiency and perform iterative calculations of the chiller unit’s cooling efficiency based on the adjusted parameter values.

[0074] Specifically, if the difference between the chiller unit's cooling efficiency and the ideal chiller unit operating efficiency is less than 0.1%, then the chiller unit's cooling efficiency is considered to be in a relatively stable and close state to the ideal value, and the current chiller unit cooling efficiency will be output. Conversely, if the difference is greater than 0.1%, then the efficiency will be calculated using the formula... (in, This indicates the cooling efficiency of the chiller unit. (This represents the ideal operating efficiency of the chiller unit) Adjust the current operating efficiency of the chiller unit.

[0075] In one embodiment, the chilled water flow rate is determined by the following steps:

[0076] (1) Substitute the obtained outdoor wet-bulb temperature into the formula of the first correlation model constructed by a quadratic polynomial and determined by regression fitting of actual operation data to calculate the temperature difference between chilled water supply and return water.

[0077] Specifically, the first correlation model formula includes a model formula reflecting the correlation between outdoor wet-bulb temperature and the temperature difference between chilled water supply and return water, which can be found in the following content:

[0078] ;

[0079] in, Indicates the temperature difference between chilled water supply and return water. express outdoor wet-bulb temperature at all times This represents the regression fit coefficient obtained by fitting actual operating data.

[0080] (2) Based on the building cooling load and the temperature difference between the chilled water supply and return water, the chilled water flow rate is calculated by converting the heat exchange equal relationship between the chilled water and the building cooling load in the circulation system according to the energy conservation rule.

[0081] Specifically, building cooling load This represents the amount of heat that the building needs to remove at a specific moment, while the heat absorbed by the chilled water is determined by the chilled water flow rate. water density Specific heat at constant pressure of water and the temperature difference between supply and return water Joint decision, that is .because By transforming the formula, the formula representing the heat absorbed by chilled water is converted into an expression for solving the chilled water flow rate, i.e.: .

[0082] In one embodiment, the cooling water flow rate is determined by the following steps:

[0083] (1) The heat dissipation of the condenser is obtained by combining the operating efficiency of the chiller unit and the building cooling load.

[0084] (2) Substitute the obtained outdoor wet-bulb temperature into the second correlation model formula constructed by a quadratic polynomial and determined by regression fitting of actual operating data to calculate the cooling water supply and return water temperature difference.

[0085] Specifically, the second correlation model formula includes a model formula reflecting the correlation between outdoor wet-bulb temperature and the temperature difference between cooling water supply and return water. For details, please refer to: ,in, express outdoor wet-bulb temperature at all times This represents the regression fit coefficient obtained by fitting actual operating data.

[0086] (3) Based on the heat dissipation of the condenser and the temperature difference between the supply and return water of the cooling water, the flow rate of the cooling water is calculated according to the role of the cooling water in the circulation system and the law of energy conservation, based on the heat balance.

[0087] Specifically, based on the heat exchange equality relationship, this application calculates the cooling water flow rate using the following formula. : ,in, Indicates the heat dissipation of the condenser. Indicates the temperature difference between the cooling water supply and return water. This indicates the density of water. This represents the specific heat at constant pressure of water.

[0088] In one embodiment, the evaporation temperature is determined by the following steps:

[0089] (1) The determined chilled water flow rate and building cooling load are input into the following evaporator heat transfer model, and the evaporator heat transfer area is obtained through regression analysis:

[0090] ;

[0091] in, Indicates the building's cooling load. Indicates chilled water flow rate, This represents the regression fit coefficient determined based on actual operating data.

[0092] (2) Based on the chilled water flow rate, building cooling load and determined chilled water supply temperature, the chilled water return temperature is obtained by inverse calculation and parameter decoupling based on the law of conservation of energy.

[0093] Specifically, this application will first, based on the law of conservation of energy, clarify the quantitative relationship between building cooling load and changes in chilled water heat. Specifically, building cooling load... Numerically, this equals the heat absorbed by the chilled water as it transitions from a supply state to a return state. The amount of heat absorbed by the chilled water can be determined based on the chilled water flow rate. The density of water Specific heat capacity at constant pressure and the temperature difference between chilled water supply and return water To calculate, that is ,in, Indicates the chilled water supply temperature. This represents the regression fitting coefficient obtained by fitting actual operating data. Then, this formula is transformed to solve for the chilled water return temperature. As the target, the corresponding computational expression includes Finally, the known chilled water flow rate... Building cooling load and the determined chilled water supply temperature Substituting this into the expression, the chilled water return temperature can be calculated.

[0094] (3) Based on the heat transfer area of ​​the evaporator and the building cooling load, the logarithmic mean temperature difference of the evaporator is obtained by reverse derivation of the basic heat transfer equation.

[0095] Specifically, in the heat transfer process, the fundamental heat transfer equation describes the relationship between heat transfer and the heat transfer coefficient, heat transfer area, and temperature difference. (Formula) This refers to the expression of the fundamental heat transfer equation in the specific scenario of a chiller evaporator. This represents the logarithmic mean temperature difference of the evaporator, which is the driving force behind heat transfer. When the heat transfer area of ​​the evaporator is known... and building cooling load At this time, the logarithmic mean temperature difference of the evaporator needs to be calculated from the fundamental heat transfer equation. This requires reverse derivation to transform the formula into... .

[0096] (4) Based on the logarithmic mean temperature difference of the evaporator, the chilled water supply temperature and the chilled water return temperature, the evaporation temperature is obtained by reverse derivation of the formula for calculating the logarithmic mean temperature difference of the evaporator and the solution of temperature parameters.

[0097] Specifically, the formula for calculating the logarithmic mean temperature difference of the evaporator is as follows: ,in, Indicates the chilled water return temperature. Indicates the chilled water supply temperature. Indicates the evaporation temperature. This represents the logarithmic mean temperature difference of the evaporator. This formula is the core formula for calculating the logarithmic mean temperature difference based on temperature parameters during the heat exchange process of the evaporator. It reflects the thermodynamic difference between the chilled water side and the evaporation temperature side and is a key basis for deriving the evaporation temperature.

[0098] In one embodiment, the condensation temperature is determined by the following steps:

[0099] (1) The determined cooling water flow rate and condenser heat dissipation are substituted into the following condenser heat transfer model, and the condenser heat transfer area is obtained through regression analysis:

[0100] ;

[0101] in, Indicates the heat dissipation of the condenser. Indicates the cooling water flow rate. This represents the regression fit coefficient determined based on actual operating data.

[0102] (2) Based on the cooling water flow rate, condenser heat dissipation and the determined cooling water supply temperature, the cooling water return temperature is obtained by inverse calculation and parameter decoupling based on the law of conservation of energy.

[0103] Specifically, according to the law of conservation of energy, the heat dissipation of the condenser... This equals the heat absorbed by the cooling water. Given the cooling water flow rate... condenser heat dissipation and cooling water supply temperature In the case of formula By performing deformation calculations, the cooling water return temperature can be obtained. The calculation formula is .

[0104] (3) Based on the heat transfer area and heat dissipation of the condenser, the logarithmic mean temperature difference of the condenser is obtained by reverse derivation of the heat transfer equation of the condenser.

[0105] Specifically, the formula It is the fundamental formula in heat transfer theory that describes heat transfer, given the heat transfer area of ​​the condenser. and condenser heat dissipation In this case, the logarithmic mean temperature difference of the condenser can be obtained by inverse derivation of this heat transfer equation. .

[0106] (4) Based on the logarithmic mean temperature difference of the condenser, the supply temperature of the cooling water and the return temperature of the cooling water, the condensing temperature is obtained by reverse derivation of the formula for calculating the logarithmic mean temperature difference of the condenser and the solution of the temperature parameters.

[0107] Specifically, the formula for calculating the logarithmic mean temperature difference of the condenser includes: ,in, Indicates the cooling water return temperature. Indicates the cooling water supply temperature. This represents the condensation temperature. This formula is derived from the heat transfer relationship between the hot and cold fluids in the condenser. It is based on the definition of the logarithmic mean temperature difference in heat transfer and the characteristics of the heat transfer process in the condenser. It is used to solve for the remaining temperature parameters when two temperature parameters, namely the cooling water supply and return temperatures and the condensation temperature, as well as the logarithmic mean temperature difference of the condenser, are known.

[0108] In one embodiment, the chiller unit's cooling efficiency is calculated based on the condensation-evaporation temperature difference and the load rate of each chiller, using a comprehensive calculation method that integrates regression fitting and thermodynamic theory. This includes:

[0109] (1) Based on the condensation-evaporation temperature difference and the load rate of each chiller, regression fitting analysis was performed to obtain the thermal perfection of the chiller unit.

[0110] Specifically, this application will calculate the thermal perfection of the chiller unit based on the following formula:

[0111] ;

[0112] in, This indicates the thermal efficiency of the chiller unit; DT represents the condensing-evaporating temperature difference; and PLR represents the load rate of each chiller unit. , This represents the regression fit coefficient determined based on actual operating data.

[0113] (2) The coefficient of performance of the ideal refrigeration cycle is obtained by performing thermodynamic analysis based on the condensation temperature and evaporation temperature.

[0114] Specifically, based on the first and second laws of thermodynamics and combined with the Carnot refrigeration cycle principle, this application calculates the coefficient of performance (COP) of an ideal refrigeration cycle using the following formula:

[0115] ;

[0116] in, The coefficient of performance (COP) represents the performance of an ideal refrigeration cycle. Indicates the evaporation temperature. Indicates the condensation temperature.

[0117] (3) The cooling efficiency of the chiller is obtained by multiplying the coefficient of performance of the ideal refrigeration cycle with the thermal perfection of the chiller.

[0118] In one embodiment, step S2, which involves calculating the load for the next hour based on the chiller system load prediction model and calculating the chiller performance after adding more chillers for the next hour using the chiller variable operating condition performance prediction model, and adjusting the chiller start-up combination according to load changes and unit performance changes, includes:

[0119] (1) When the chilled water supply temperature is determined to be greater than the preset value, if the current chiller operating load rate is greater than the preset maximum allowable load rate, the load for the next hour is calculated using the chiller system load prediction model.

[0120] It should be noted that the maximum allowable load rate is the maximum load rate of the chiller unit currently in operation, which is generally around 95%.

[0121] (2) If the load value is less than or equal to the preset threshold, and the operating load rate in the next hour (determined based on the chiller system load prediction model) is greater than the preset maximum allowable load rate, it is determined that applying the current start-up combination in the next hour will reduce the operating efficiency of the chiller. At this time, it is determined to execute the add-unit strategy. Otherwise, the current start-up combination is maintained and the set value of the chilled water supply and return water temperature difference is reduced.

[0122] Specifically, if the load value is less than or equal to 90% of the current load, it is determined that the load will decrease significantly in the next hour. In order to ensure the stability of the chiller unit during low-load operation in the future and prevent failures caused by poor operating conditions, this application will further determine whether the application of the current start-up combination in the next hour will reduce the operating efficiency of the chiller unit. If so, the strategy of adding more units will be implemented; otherwise, the current start-up combination will be maintained and the set value of the chilled water supply and return water temperature difference will be reduced to maintain the stable and reliable operation of the system and reduce the risk of failure.

[0123] (3) If the load value is greater than the preset threshold, the chiller performance after adding the chiller in the next hour is calculated using the chiller variable operating condition performance prediction model.

[0124] (4) If the performance value is greater than the preset threshold, it is determined that the performance of the chiller will be improved by implementing the additional chiller strategy in the next hour. At this time, it is determined to implement the additional chiller strategy. Otherwise, the current start-up combination is maintained and the set value of the chilled water supply and return water temperature difference is reduced.

[0125] Specifically, if the load value is greater than 90% of the current load, it is determined that the load will not decrease significantly in the next hour. In order to accurately assess the actual impact of adding units on the performance of the chiller unit and avoid blindly adding units leading to resource waste or abnormal operation, this application will use the chiller unit variable operating condition performance prediction model to calculate the chiller performance after adding units in the next hour. If the performance value is greater than or equal to 160% of the current chiller performance, it is determined that implementing the adding unit strategy in the next hour will improve the chiller performance. In this case, it is determined to implement the adding unit strategy. Otherwise, the current operating combination will be maintained and the set value of the chilled water supply and return water temperature difference will be reduced.

[0126] In one embodiment, step S2, which involves calculating the load for the next hour based on the chiller system load prediction model and calculating the chiller performance after reducing capacity for the next hour using the chiller variable operating condition performance prediction model, and adjusting the chiller operating combination according to load changes and unit performance changes, includes:

[0127] (1) When the chilled water supply temperature is less than or equal to the preset value, if the current chiller operating load rate is less than the preset minimum allowable load rate, the load for the next hour is calculated using the chiller system load prediction model.

[0128] It should be noted that the minimum allowable load rate is the minimum partial load rate of the chiller unit in the current operating combination. It is generally the rated cooling capacity of the smaller combination divided by the rated cooling capacity of the current combination (it can be appropriately reduced by about 5% to avoid frequent start-ups and shutdowns of the unit).

[0129] (2) If the load value is greater than or equal to the preset threshold and the operating load rate in the next hour is less than the preset minimum allowable load rate, it is determined that the application of the current start-up combination in the next hour will cause the chiller to be in an inefficient operating state. At this time, it is determined to execute the reduction strategy. Otherwise, the current start-up combination is maintained and the set value of the chilled water supply and return water temperature difference is increased.

[0130] Specifically, if the load value is greater than or equal to 110% of the current load, it is determined that the load will increase significantly in the next hour. In this case, it will further determine whether the operating load rate in the next hour is less than the preset minimum allowable load rate. If so, it is determined that applying the current operating combination will cause the chiller to operate inefficiently in the next hour, and a reduction strategy will be implemented to reduce the additional energy consumption caused by the inefficient operation of the chiller. Otherwise, the current operating combination will be maintained, and the chilled water supply and return temperature difference setpoint will be increased to achieve energy saving and consumption reduction by optimizing system operating parameters.

[0131] (3) If the load value is less than the preset threshold, the chiller performance after the unit is reduced in the next hour is predicted using the variable operating condition performance prediction model of the chiller unit.

[0132] Specifically, if the load value is less than 110% of the current load, it is determined that the load will not increase significantly in the next hour. At this time, in order to optimize the operation mode of the chiller unit to achieve energy saving and consumption reduction while meeting the cooling demand, and to avoid energy waste and reduced operating efficiency due to an excessive number of units, this application will use the chiller unit variable operating condition performance prediction model to predict the chiller performance after reducing the number of units in the next hour.

[0133] (4) If the performance value is greater than or equal to the preset threshold, it is determined that the chiller performance will be improved by implementing the reduction strategy in the next hour. At this time, the reduction strategy is determined to be implemented. Otherwise, the current operating combination is maintained and the temperature difference setting of chilled water supply and return is increased.

[0134] Specifically, if the performance value is greater than or equal to 150% of the current chiller capacity, it is determined that implementing a reduction strategy in the next hour will improve chiller performance. In this case, the reduction strategy will be implemented to allow the remaining chillers to operate at higher efficiency while meeting the current and next hour's load requirements, thereby improving cooling performance and ensuring a stable and comfortable indoor temperature. Otherwise, the operating configuration will be maintained and the chilled water supply and return temperature difference setpoint will be increased.

[0135] It should be noted that for the chiller addition / reduction strategy, this application determines the specific operating combination based on the building's cooling load forecast. During the reduction strategy, at least one chiller is maintained in operation. This avoids frequent unit start-ups and shutdowns through feedforward prediction, and the decision to add / reduce chillers is based primarily on whether unit performance can be improved. If the load trend is stable and there is no room for performance improvement, the pump flow rate is adjusted through the "chilled water supply and return water temperature difference setpoint adjustment," achieving system energy savings while ensuring cooling supply. This solves the problem of existing technologies being unable to perform real-time control of chilled water supply temperature, supply and return water temperature difference, and operating combination based on changing cooling demand.

[0136] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for operating and controlling an air conditioning cooling source system based on load forecasting, characterized in that, Includes the following steps: S1. Acquire dynamic monitoring data that integrates the characteristics of the chiller unit itself, its operating conditions, and the comprehensive influence of the surrounding environment. Based on the dynamic monitoring data, construct a system load prediction model for the chiller unit and a variable operating condition performance prediction model for the chiller unit. The dynamic monitoring data includes the current operating parameters of the chiller unit and comprehensive monitoring data of multiple environments and building operations. S2. Calculate the load for the next hour based on the chiller system load prediction model, and calculate the chiller performance for the next hour after adding or removing chillers using the chiller variable operating condition performance prediction model. Adjust the chiller start-up combination according to load changes and unit performance changes.

2. The method according to claim 1, characterized in that, In step S1, the calculation formula for the chiller system load prediction model includes: ； in, express Real-time forecasting of building cooling load, Indicates that it is determined based on outdoor meteorological data. outdoor dry-bulb temperature at all times Indicates that it is determined based on outdoor meteorological data. outdoor solar radiation intensity at any time Indicates that it is determined based on building operation data. Constant ventilation and electricity consumption Indicates that it is determined based on outdoor meteorological data. outdoor air enthalpy value at any time Indicates that it is determined based on outdoor meteorological data. outdoor wind speed at all times Indicates that it is determined based on building operation data. Total electricity consumption at all times This represents the sensible heat output per person per unit, determined based on personnel pyrography data. This represents the latent heat output per employee per unit, determined based on employee pyrography data. This represents the coefficients obtained through regression fitting.

3. The method according to claim 1, characterized in that, In step S1, the chiller unit's cooling efficiency is predicted based on the chiller unit's variable operating condition performance prediction model through the following steps: (1) Obtain real-time monitoring data of the chiller unit and input the real-time monitoring data of the chiller unit into the system load prediction model of the chiller unit for calculation to obtain the building cooling load; (2) Based on the building cooling load, chilled water flow rate and cooling water flow rate, the evaporation temperature and condensation temperature are determined by series analysis of multi-stage thermodynamic models and parameter iteration solution; (3) Determine the condensation-evaporation temperature difference based on the ratio between the condensation temperature and the evaporation temperature; (4) Determine the rated cooling capacity based on the chiller start-up combination, and determine the load rate of each chiller based on the ratio between the building cooling load and the rated cooling capacity; (5) Based on the condensation-evaporation temperature difference and the load rate of each chiller, the refrigeration efficiency of the chiller unit is calculated by a comprehensive calculation method that combines regression fitting and thermodynamic theory. (6) When the difference between the chiller unit’s cooling efficiency and the ideal chiller unit’s operating efficiency is less than a preset threshold, output the current chiller unit’s cooling efficiency; otherwise, adjust the current chiller unit’s operating efficiency and perform iterative calculations of the chiller unit’s cooling efficiency based on the adjusted parameter values.

4. The method according to claim 3, characterized in that, The chilled water flow rate is determined through the following steps: (1) Substitute the obtained outdoor wet-bulb temperature into the formula of the first correlation model constructed by a quadratic polynomial and determined by regression fitting of actual operation data to calculate the temperature difference between chilled water supply and return water. (2) Based on the building cooling load and the temperature difference between the chilled water supply and return water, the chilled water flow rate is calculated by converting the heat exchange equal relationship between the chilled water and the building cooling load in the circulation system according to the energy conservation rule.

5. The method according to claim 3, characterized in that, The cooling water flow rate is determined through the following steps: (1) The heat dissipation of the condenser is obtained by combining the operating efficiency of the chiller unit and the cooling load of the building; (2) Substitute the obtained outdoor wet-bulb temperature into the formula of the second correlation model constructed by a quadratic polynomial and determined by regression fitting of actual operating data to calculate and determine the cooling water supply and return water temperature difference; (3) Based on the heat dissipation of the condenser and the temperature difference between the supply and return water of the cooling water, the flow rate of the cooling water is calculated according to the role of the cooling water in the circulation system and the law of energy conservation, based on the heat balance.

6. The method according to claim 3, characterized in that, The evaporation temperature is determined through the following steps: (1) The determined chilled water flow rate and building cooling load are input into the following evaporator heat transfer model, and the evaporator heat transfer area is obtained through regression analysis: ； in, Indicates the building's cooling load. Indicates chilled water flow rate, This represents the regression fit coefficient determined based on actual operating data. (2) Based on the chilled water flow rate, building cooling load and determined chilled water supply temperature, the chilled water return temperature is obtained by inverse calculation and parameter decoupling based on the law of conservation of energy; (3) Based on the heat transfer area of ​​the evaporator and the building cooling load, the logarithmic mean temperature difference of the evaporator is obtained by reverse derivation of the basic heat transfer equation. (4) Based on the logarithmic mean temperature difference of the evaporator, the chilled water supply temperature and the chilled water return temperature, the evaporation temperature is obtained by reverse derivation of the formula for calculating the logarithmic mean temperature difference of the evaporator and the solution of temperature parameters.

7. The method according to claim 3, characterized in that, The condensation temperature is determined through the following steps: (1) The determined cooling water flow rate and condenser heat dissipation are substituted into the following condenser heat transfer model, and the condenser heat transfer area is obtained through regression analysis: ； in, Indicates the heat dissipation of the condenser. Indicates the cooling water flow rate. This represents the regression fit coefficient determined based on actual operating data. (2) Based on the cooling water flow rate, condenser heat dissipation and the determined cooling water supply temperature, the cooling water return temperature is obtained by inverse calculation and parameter decoupling based on the law of conservation of energy. (3) Based on the heat transfer area and heat dissipation of the condenser, the logarithmic mean temperature difference of the condenser is obtained by reverse derivation of the heat transfer equation of the condenser. (4) Based on the logarithmic mean temperature difference of the condenser, the supply temperature of the cooling water and the return temperature of the cooling water, the condensing temperature is obtained by reverse derivation of the formula for calculating the logarithmic mean temperature difference of the condenser and the solution of the temperature parameters.

8. The method according to claim 3, characterized in that, The chiller unit's refrigeration efficiency is calculated using a comprehensive calculation method that integrates regression fitting and thermodynamic theory, based on the condensation-evaporation temperature difference and the load rate of each chiller. This includes: (1) Based on the condensation-evaporation temperature difference and the load rate of each chiller, regression fitting analysis was performed to obtain the thermodynamic perfection of the chiller unit; (2) The coefficient of performance of the ideal refrigeration cycle is obtained by performing thermodynamic analysis based on the condensation temperature and evaporation temperature; (3) The cooling efficiency of the chiller is obtained by multiplying the coefficient of performance of the ideal refrigeration cycle with the thermal perfection of the chiller.

9. The method according to claim 1, characterized in that, In step S2, the calculation of the load for the next hour based on the chiller system load prediction model, and the calculation of the chiller performance after adding more chillers for the next hour using the chiller variable operating condition performance prediction model, and the adjustment of the chiller unit start-up combination according to load changes and unit performance changes, include: (1) When the chilled water supply temperature is determined to be greater than the preset value, if the current chiller operating load rate is greater than the preset maximum allowable load rate, the load for the next hour is calculated using the chiller system load prediction model. (2) If the load value is less than or equal to the preset threshold and the operating load rate in the next hour is greater than the preset maximum allowable load rate, it is determined that applying the current start-up combination in the next hour will reduce the operating efficiency of the chiller unit. At this time, it is determined to execute the add-unit strategy. Otherwise, the current start-up combination is maintained and the set value of the chilled water supply and return water temperature difference is reduced. (3) If the load value is greater than the preset threshold, the chiller performance after adding more chiller in the next hour is calculated using the chiller variable operating condition performance prediction model. (4) If the performance value is greater than the preset threshold, it is determined that the performance of the chiller will be improved by implementing the additional chiller strategy in the next hour. At this time, it is determined to implement the additional chiller strategy. Otherwise, the current start-up combination is maintained and the set value of the chilled water supply and return water temperature difference is reduced.

10. The method according to claim 1, characterized in that, In step S2, the calculation of the load for the next hour based on the chiller system load prediction model, and the calculation of the chiller performance after reducing capacity for the next hour using the chiller variable operating condition performance prediction model, and the adjustment of the chiller operating combination according to load changes and unit performance changes, include: (1) When the chilled water supply temperature is determined to be less than or equal to the preset value, if the current chiller operating load rate is less than the preset minimum allowable load rate, the load for the next hour is calculated using the chiller system load prediction model. (2) If the load value is greater than or equal to the preset threshold and the operating load rate in the next hour is less than the preset minimum allowable load rate, it is determined that the application of the current start-up combination in the next hour will cause the chiller to operate in an inefficient state. At this time, it is determined to execute the reduction strategy. Otherwise, the current start-up combination is maintained and the set value of the chilled water supply and return water temperature difference is increased. (3) If the load value is less than the preset threshold, the chiller performance after the unit is reduced in the next hour is predicted using the chiller variable operating condition performance prediction model. (4) If the performance value is greater than or equal to the preset threshold, it is determined that the chiller performance will be improved by implementing the reduction strategy in the next hour. At this time, the reduction strategy is determined to be implemented. Otherwise, the current operating combination is maintained and the temperature difference setting of chilled water supply and return is increased.

Images