Wind speed gear control system and method for fan coil

Abstract

The invention belongs to the technical field of industrial equipment control, and provides a fan coil air speed gear control system and method.The fan coil air speed gear control method includes the steps that the change relation between air conditioner refrigerant flow and indoor loads is evaluated through a correlation analysis method, whether correlation exists between the air conditioner refrigerant flow and the indoor loads or not is judged, and if the flow and the loads have the correlation, the fan coil air speed gear control method is started; if yes, the indoor load demand quantity in the future time period is predicted, matching analysis is carried out on the predicted refrigerant demand flow and the current air speed gear of the fan coil, whether the current air speed can meet the future load demand or not is judged, correlation analysis is carried out on the air speed of the fan coil and the refrigerant demand flow, and the indoor load demand quantity in the future time period is judged. And whether a collaborative change relation exists between the two is verified, if the relevance exists, the optimal wind speed gear in the future time period is determined according to the refrigerant prediction demand flow, dynamic optimization of the wind speed gear is achieved, and the system energy efficiency and the indoor environment comfort degree are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial equipment control, and in particular relates to a wind speed gear control system and method for a fan coil unit. Background Art

[0002] In the operation and management of air-conditioning systems, the dynamic matching of refrigerant flow and indoor load is a key factor affecting system energy efficiency and indoor environmental comfort. Traditional air-conditioning systems typically employ fixed control strategies or simple threshold-based adjustment methods, making it difficult to respond to complex changes in indoor load in real time. This results in insufficient coordination between refrigerant flow and fan coil unit speed. For example, existing fan coil unit speed settings are often based on fixed logic or manual experience, lacking dynamic correlation analysis with indoor load. This can cause the fan to continuously run at high speed under low-load conditions, resulting in incomplete refrigerant evaporation or excess cooling, leading to energy waste. Under high-load conditions, the fan speed may not meet the refrigerant flow demand, causing indoor temperature fluctuations, reduced comfort, and even frequent system starts and stops, further increasing energy consumption. Furthermore, traditional systems have limited ability to predict indoor loads, often relying on real-time feedback adjustments. This results in a response lag, making it difficult to adjust refrigerant flow and speed in advance of load changes. This leads to significant fluctuations in indoor environmental parameters (such as temperature and humidity), impacting user comfort. At the same time, due to the lack of in-depth analysis of the coordinated relationship between refrigerant flow and wind speed, existing technologies are unable to dynamically optimize wind speed levels according to refrigerant demand, resulting in the system operating in non-optimal conditions for a long time, which not only increases operating costs but also reduces equipment life.

[0003] To this end, the present invention provides a wind speed gear control system and method for a fan coil unit. Summary of the Invention

[0004] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0005] The technical solution adopted by the present invention to solve the technical problem is: a method for controlling the wind speed level of a fan coil unit, comprising: Through correlation analysis, determine whether there is a correlation change relationship between the air conditioning refrigerant flow and the indoor load; If there is a correlation between the air conditioning refrigerant flow rate and the indoor load, the indoor load demand in the preset future period is predicted, and the predicted demand flow of the air conditioning refrigerant in the preset future period is determined based on the correlation between the air conditioning refrigerant flow rate and the indoor load; Based on the predicted demand for air conditioning refrigerant, the system analyzes and determines whether the current fan coil unit's wind speed level meets the preset future time period. If not, a wind speed level adjustment signal is generated. Based on the wind speed level adjustment signal, a correlation analysis is performed on the wind speed of the fan coil unit and the air conditioning refrigerant demand flow to determine whether there is a correlation change relationship between the wind speed of the fan coil unit and the air conditioning refrigerant demand flow. If so, the optimal wind speed level of the fan coil unit in the preset future time period is determined based on the air conditioning refrigerant predicted demand flow in the preset future time period.

[0006] Furthermore, the process of determining whether there is a correlation change relationship between the air conditioning refrigerant flow rate and the indoor load includes: According to the data integration of different indoor loads and air conditioning refrigerant flow, indoor load groups and air conditioning refrigerant flow groups are obtained; The indoor load group and the air conditioning refrigerant flow group are processed using the Pearson correlation coefficient method to obtain the load flow correlation value. If the load flow correlation value is within the preset correlation range, it means that there is an associated change relationship, otherwise, it does not exist.

[0007] Furthermore, the indoor load demand in a preset future period is predicted as follows: The predicted values of indoor load at different times in the preset future period are obtained by time series analysis, and the indoor load demand in the preset future period is obtained by averaging.

[0008] Furthermore, the process of determining the predicted demand flow of air-conditioning refrigerant in a preset future period is as follows: The flow-load variation curve drawn based on the indoor load group and the air conditioning refrigerant flow group is fitted using the least squares method to determine the flow-load correlation model; The indoor load demand in the preset future period is used as the input of the flow-load correlation model, and the predicted demand flow of air-conditioning refrigerant in the preset future period is output.

[0009] Furthermore, the wind speed gear adjustment signal is generated as follows: The deviation of the air conditioning refrigerant flow rate corresponding to the fan coil unit at the current wind speed level and the air conditioning refrigerant demand flow rate predicted in the preset future period is analyzed to obtain the air conditioning refrigerant deviation degree value; Analyze the persistence of the deviation of the air conditioning refrigerant flow at different times in the preset future period to obtain the air conditioning refrigerant deviation persistence value; The sum of the air-conditioning refrigerant deviation degree value and the air-conditioning refrigerant deviation duration value is calculated to obtain the air-conditioning refrigerant satisfaction value. If the air-conditioning refrigerant satisfaction value is greater than or equal to the air-conditioning refrigerant satisfaction threshold, a wind speed gear adjustment signal is generated.

[0010] Furthermore, the specific method of obtaining the air conditioning refrigerant deviation value is as follows: Calculate the deviation between the air conditioning refrigerant flow rate corresponding to the fan coil unit at the current wind speed level and the air conditioning refrigerant predicted demand flow rate in a preset future time period to obtain the air conditioning refrigerant deviation amount; If the air-conditioning refrigerant deviation is not within the air-conditioning refrigerant normal flow error range, the air-conditioning refrigerant deviation is subjected to absolute deviation ratio processing with the nearest air-conditioning refrigerant normal flow error range endpoint value to obtain the air-conditioning refrigerant deviation degree value.

[0011] Furthermore, the specific method for obtaining the air-conditioning refrigerant deviation persistence value is as follows: Input the predicted values of indoor load at different times in the preset future period into the flow-load correlation model to obtain the air conditioning refrigerant flow at different times in the preset future period and draw a time-flow change curve; By constructing a first air-conditioning refrigerant satisfaction line and a second air-conditioning refrigerant satisfaction line, the two-dimensional coordinate system where the time-flow change curve is located is marked as an air-conditioning refrigerant satisfaction area; The time-flow variation curve outside the air-conditioning refrigerant satisfaction zone is marked as the refrigerant non-satisfaction curve; The duration of the refrigerant non-satisfaction curve on the X-axis is measured, and the ratio between the duration and the preset future time period is used to obtain the air conditioning refrigerant deviation duration value.

[0012] Furthermore, the label of the air-conditioning refrigerant satisfaction zone is obtained in the following manner: The first air conditioner refrigerant flow rate and the second air conditioner refrigerant flow rate are calculated based on the corresponding air conditioner refrigerant flow rate at the current wind speed level as the reference value and the endpoint value of the normal air conditioner refrigerant flow rate error range. The first air-conditioning refrigerant satisfaction flow rate and the second air-conditioning refrigerant satisfaction flow rate are used to construct the first air-conditioning refrigerant satisfaction line and the second air-conditioning refrigerant satisfaction line respectively. In the two-dimensional coordinate system where the time-flow change curve is located, the area between the first air-conditioning refrigerant satisfaction line and the second air-conditioning refrigerant satisfaction line is marked as the air-conditioning refrigerant satisfaction area.

[0013] Furthermore, the optimal wind speed level of the fan coil unit is obtained as follows: Obtain the air conditioning refrigerant demand flow corresponding to the fan coil unit at different wind speeds, and integrate the data of different wind speeds and different air conditioning refrigerant demand flow rates to obtain wind speed groups and air conditioning refrigerant demand flow rate groups; Calculate the Pearson correlation coefficient between the wind speed group and the air conditioning refrigerant demand flow group to obtain the wind speed and flow correlation value; If the wind speed and flow correlation value is within the preset correlation range, it means that there is a correlation between the wind speed of the fan coil unit and the air conditioning refrigerant demand flow rate. The wind speed-flow change curve drawn according to the wind speed group and the air conditioning refrigerant demand flow rate group is fitted using the least squares method to determine the wind speed-flow correlation model; The indoor load demand in the preset future period is input into the wind speed-flow correlation model, and the optimal wind speed of the fan coil unit in the preset future period is output, thereby determining the optimal wind speed gear of the fan coil unit.

[0014] A wind speed level control system for a fan coil unit, comprising: Flow-load correlation analysis module: Through correlation analysis, it determines whether there is a correlation change relationship between the air conditioning refrigerant flow and the indoor load; Refrigerant flow demand analysis module: If there is a correlation between the air conditioning refrigerant flow and the indoor load, the indoor load demand in the preset future period is predicted, and the predicted air conditioning refrigerant demand flow in the preset future period is determined based on the correlation between the air conditioning refrigerant flow and the indoor load. Wind speed level matching analysis module: Based on the predicted demand for air conditioning refrigerant, it analyzes and determines whether the current fan coil unit wind speed level meets the preset future time period. If not, it generates a wind speed level adjustment signal; Wind speed level adjustment module: Based on the wind speed level adjustment signal, the correlation analysis is performed on the wind speed of the fan coil unit and the air conditioning refrigerant demand flow to determine whether there is a correlation change relationship between the wind speed of the fan coil unit and the air conditioning refrigerant demand flow. If so, the optimal wind speed level of the fan coil unit in the preset future time period is determined based on the predicted demand flow of the air conditioning refrigerant in the preset future time period.

[0015] The beneficial effects of the present invention are as follows: through the correlation analysis method, the changing relationship between the air-conditioning refrigerant flow and the indoor load is evaluated to determine whether there is a correlation between the two, providing data support for the subsequent refrigerant flow demand forecast and wind speed gear adjustment. If there is a correlation between the flow and the load, the indoor load demand in the future time period is predicted to achieve dynamic prediction of the refrigerant flow, and provide target parameters for the wind speed gear matching of the fan coil. The refrigerant predicted demand flow is matched with the current wind speed gear of the fan coil to determine whether the current wind speed can meet the future load demand, ensuring that the wind speed of the fan coil is matched with the refrigerant flow demand in real time, avoiding energy waste or reduced comfort caused by insufficient or excessive wind speed, and performing a correlation analysis on the wind speed of the fan coil and the refrigerant demand flow to verify whether there is a coordinated change relationship between the two. If there is a correlation, the optimal wind speed gear in the future time period is determined based on the refrigerant predicted demand flow, achieving dynamic optimization of the wind speed gear, and improving system energy efficiency and indoor environmental comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below with reference to the accompanying drawings.

[0017] Figure 1 This is a flowchart of the steps of a method for controlling wind speed levels of a fan coil unit according to an embodiment of the present invention; Figure 2 This is a flowchart of a wind speed control system for a fan coil unit according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific implementation methods.

[0019] Example 1 See also Figure 1 As shown, a method for controlling the wind speed level of a fan coil unit according to an embodiment of the present invention includes the following steps: Step 1: Use correlation analysis to determine whether there is a correlation between the air conditioning refrigerant flow rate and the indoor load; In step 1, the air conditioning refrigerant flow rate represents the average flow rate of chilled water or hot water under different indoor load environments. The indoor load includes heating load and cooling load. The air conditioning refrigerant flow rate and indoor load are obtained by the control center of the air conditioning system. The air conditioning refrigerant flow rate is obtained by a flow meter installed in the air conditioning system and transmitted to the control center. The indoor load is monitored by a temperature and humidity sensor and transmitted to the control center. In step 1, the process of determining whether there is a correlation change relationship between the air conditioning refrigerant flow rate and the indoor load through correlation analysis includes: Obtain the air conditioning refrigerant flow under different indoor load environments, obtain indoor load groups based on the data integration of different indoor loads, and obtain air conditioning refrigerant flow groups based on the data integration of air conditioning refrigerant flow under different indoor load environments; The Pearson correlation coefficient is used to process the air conditioning refrigerant flow group and the indoor load group, and the Pearson correlation coefficient between the air conditioning refrigerant flow group and the indoor load group is calculated to obtain the load flow correlation value; For example, assume that the air conditioning refrigerant flow rate group is (Lm1, Lm2, Lm3...Lmn), with the unit of kg / s, where Lmn represents the nth air conditioning refrigerant flow rate, and the indoor load group is (fh1, fh1, fh1...fhn), with the unit of kW, where fhn represents the nth indoor load. The Pearson correlation coefficient R between the air conditioning refrigerant flow group and the indoor load group is calculated as follows: Among them, Lmi represents the i-th air conditioner refrigerant flow in the air conditioner refrigerant flow group, and fhi represents the i-th indoor load in the indoor load group; If the load flow correlation value is within the preset correlation range, it means that there is a correlation change relationship between the air conditioning refrigerant flow and the indoor load; If the load flow related value is not within the preset related range, it means that there is no correlation change relationship between the air conditioning refrigerant flow and the indoor load; It should be noted that the correlation between the air conditioning refrigerant flow rate and the indoor load indicated in step 1 specifically means that the relative changes in the air conditioning refrigerant flow rate and the indoor load show a linear correlation, for example, the relative changes between the air conditioning refrigerant flow rate and the indoor load change in a certain proportion; Step 2: If there is a correlation between the air conditioning refrigerant flow rate and the indoor load, then the indoor load demand in the preset future time period is predicted. Based on the predicted indoor load demand and the correlation between the air conditioning refrigerant flow rate and the indoor load, the predicted air conditioning refrigerant demand flow in the preset future time period is determined; It should be noted that in step 2, the preset future time period is based on indoor air conditioning usage demand or is preset in advance by those skilled in the art, so as to facilitate indoor load prediction and thus effectively control the wind speed level of the fan coil unit; In step 2, the process of predicting the indoor load demand in a preset future period includes: A10 collects actual data on indoor heating or cooling loads during a historical period, and also records relevant factors such as the corresponding time, outdoor temperature, and number of people indoors. A20, draw the ACF and PACF graphs of the load data and determine the order of the ARIMA model based on the graphical characteristics; For example, if the ACF graph decays rapidly after lag 1 and the PACF graph is truncated after lag 1, then the AR (1) model is suitable; if the ACF graph tails and the PACF graph is truncated after lag 2, then the AR (2) model is suitable; A30, using the ARIMA model to determine parameters based on the actual data of indoor heating load or cooling load during the historical period, as well as relevant factors such as time, outdoor temperature, and number of indoor occupants, to determine the coefficients of the AR term, MA term, and constant term of the ARIMA model; A40 inputs the time series corresponding to the preset future period and related factor data (such as the outdoor temperature obtained from the weather forecast report and the number of indoor occupants estimated based on usage demand) into the ARIMA model to obtain the predicted values of the indoor load at different times in the preset future period; In step 2, based on the indoor load demand forecast results and the correlation between the air conditioning refrigerant flow rate and the indoor load, the process of determining the predicted demand flow rate of the air conditioning refrigerant in the preset future period is as follows: The predicted values of indoor load at different times in the preset future period are averaged to obtain the indoor load demand in the preset future period; Based on the indoor load group and the air conditioning refrigerant flow group, a two-dimensional coordinate system is constructed with the indoor load as the X-axis and the air conditioning refrigerant flow as the Y-axis. A curve showing the change of air conditioning refrigerant flow with indoor load is plotted to obtain a flow-load change curve. The flow-load variation curve is fitted using the least squares method to determine the flow-load correlation model, where the flow-load correlation model is Y=kX+b, where Y represents the air conditioning refrigerant flow, X represents the indoor load, k represents the slope, and b represents the intercept; Input the indoor load demand in the preset future period into the flow-load correlation model, and output the predicted demand flow of air-conditioning refrigerant in the preset future period; Step 3: Based on the predicted demand for air conditioning refrigerant, analyze and determine whether the current fan coil unit wind speed level meets the preset future time period. If not, generate a wind speed level adjustment signal; In step 3, the process of analyzing and judging whether the current fan coil unit's wind speed level meets the preset future time period based on the predicted demand for air conditioning refrigerant is as follows: According to the design specifications of the fan coil unit and air conditioning system, the corresponding air conditioning refrigerant flow rate of the fan coil unit at the current wind speed level is obtained, and the difference between the air conditioning refrigerant demand flow rate and the predicted demand flow rate in the preset future time period is processed to obtain the air conditioning refrigerant deviation; Compare the air conditioning refrigerant deviation with the normal flow error range of the air conditioning refrigerant; If the air conditioning refrigerant deviation is not within the air conditioning refrigerant normal flow error range, the air conditioning refrigerant deviation is processed with the air conditioning refrigerant normal flow error range endpoint value by absolute deviation ratio to obtain the air conditioning refrigerant deviation degree value; For example, if the normal flow error range of the air-conditioning refrigerant is [wc1, wc2], the air-conditioning refrigerant deviation is wc3, and wc3>wc2, then the air-conditioning refrigerant deviation degree value kpc is calculated as: If the air conditioning refrigerant deviation is within the normal flow error range of the air conditioning refrigerant, the air conditioning refrigerant deviation value is 0; It should be noted that the air conditioning refrigerant deviation value reflects the average deviation between the air conditioning refrigerant flow rate in the preset future period and the air conditioning refrigerant flow rate corresponding to the current wind speed level, which exceeds the normal air conditioning refrigerant flow error range. The greater the average deviation, the less satisfactory the current fan coil unit's wind speed level is for the preset future period. Using the air conditioner refrigerant flow rate corresponding to the current wind speed level as the reference value and combining it with the endpoint values of the normal air conditioner refrigerant flow rate error range, calculate the first air conditioner refrigerant flow rate and the second air conditioner refrigerant flow rate. The first air conditioner refrigerant flow rate is greater than the second air conditioner refrigerant flow rate. Specifically, the method for obtaining the first air-conditioning refrigerant flow rate and the second air-conditioning refrigerant flow rate is described as follows: For example, if the corresponding air conditioner refrigerant flow rate under the current wind speed gear is dL, then the first air conditioner refrigerant satisfies the flow rate of dL+wc2, and the second air conditioner refrigerant satisfies the flow rate of dL+wc1. It should be noted that in the normal flow error range of the air conditioner refrigerant [wc1, wc2], wc1 < 0, wc2 > 0, so the second air conditioner refrigerant satisfies the flow rate of dL+wc1; It can be understood that the purpose of obtaining the first air-conditioning refrigerant satisfying flow rate and the second air-conditioning refrigerant satisfying flow rate is that: the first air-conditioning refrigerant satisfying flow rate and the second air-conditioning refrigerant satisfying flow rate are obtained in combination with the air-conditioning refrigerant flow rate corresponding to the current wind speed gear and the endpoint value of the air-conditioning refrigerant normal flow rate error range. If the air-conditioning refrigerant predicted demand in the preset future time period is between the first air-conditioning refrigerant satisfying flow rate and the second air-conditioning refrigerant satisfying flow rate, it means that the air-conditioning refrigerant predicted demand in the preset future time period matches the current wind speed gear. Therefore, by obtaining the first air-conditioning refrigerant satisfying flow rate and the second air-conditioning refrigerant satisfying flow rate, it is determined whether the current wind speed gear meets the preset future time period. Since the constructed flow-load correlation model reflects the correlation and change relationship between the air conditioning refrigerant flow and the indoor load, the predicted value of the indoor load at different times in the preset future period is input into the flow-load correlation model to obtain the air conditioning refrigerant flow at different times in the preset future period; According to the air conditioning refrigerant flow at different times in the preset future period, a two-dimensional coordinate system is constructed with time as the X-axis and the air conditioning refrigerant flow as the Y-axis, and a curve of the air conditioning refrigerant flow changing with time is plotted to obtain a time-flow change curve; In the two-dimensional coordinate system where the time-flow rate variation curve is located, a first air-conditioning refrigerant satisfaction line and a second air-conditioning refrigerant satisfaction line are constructed respectively based on the first air-conditioning refrigerant satisfaction flow rate and the second air-conditioning refrigerant satisfaction flow rate; In the two-dimensional coordinate system where the time-flow rate variation curve is located, the area between the first air-conditioning refrigerant satisfaction line and the second air-conditioning refrigerant satisfaction line is marked as the air-conditioning refrigerant satisfaction area; The time-flow variation curve outside the air-conditioning refrigerant satisfaction zone is marked as the refrigerant non-satisfaction curve; Measure the time length corresponding to the refrigerant non-satisfaction curve on the X-axis to obtain the refrigerant non-satisfaction duration. The refrigerant non-satisfaction duration reflects the abnormal duration during which the air conditioner refrigerant flow is not within the air conditioner refrigerant satisfaction zone within the preset future period. Calculate the ratio between the refrigerant non-satisfaction duration and the corresponding duration of the preset future period to obtain the air conditioning refrigerant deviation duration value; It should be noted that the air conditioning refrigerant deviation duration value reflects the duration of the mismatch between the air conditioning refrigerant flow at different times in the preset future period and the air conditioning refrigerant flow corresponding to the current wind speed level. The larger the air conditioning refrigerant deviation duration value, the less likely the current fan coil unit's wind speed level is to meet the preset future period. The air conditioning refrigerant deviation duration value and the air conditioning refrigerant deviation degree value are summed to obtain the air conditioning refrigerant satisfaction value; Comparing the air conditioning refrigerant satisfaction value with the air conditioning refrigerant satisfaction threshold; If the air conditioning refrigerant satisfaction value is greater than or equal to the air conditioning refrigerant satisfaction threshold, it means that the current fan coil wind speed level cannot meet the preset future time period, and a wind speed level adjustment signal is generated; If the air conditioning refrigerant satisfaction value is less than the air conditioning refrigerant satisfaction threshold, it means that the current fan coil wind speed level meets the preset future time period; Step 4: Based on the wind speed level adjustment signal, a correlation analysis is performed on the wind speed of the fan coil unit and the air conditioning refrigerant demand flow rate to determine whether there is a correlation change relationship between the wind speed of the fan coil unit and the air conditioning refrigerant demand flow rate. If so, the optimal wind speed level of the fan coil unit in the preset future time period is determined based on the predicted air conditioning refrigerant demand flow rate in the preset future time period; According to the design specifications of the fan coil unit and air conditioning system, obtain the air conditioning refrigerant demand flow corresponding to the fan coil unit at different wind speeds. According to the integration of data of different wind speeds, a wind speed group is obtained, and according to the integration of data of different air-conditioning refrigerant demand flow rates, an air-conditioning refrigerant demand flow rate group is obtained; The Pearson correlation coefficient method is used to calculate the Pearson correlation coefficient between the wind speed group and the air conditioning refrigerant demand flow group to obtain the wind speed and flow correlation value; It should be noted that the Pearson correlation coefficient method has been publicly explained in the above step 1 and will not be repeated here; If the wind speed and flow rate correlation values are within the preset correlation range, it means that there is a correlation between the wind speed of the fan coil unit and the required flow rate of the air conditioner refrigerant; If the wind speed and flow rate correlation values are not within the preset correlation range, it means that there is no correlation between the wind speed of the fan coil unit and the air conditioning refrigerant demand flow rate; In step 4, the process of determining the optimal wind speed level of the fan coil unit in the preset future period based on the predicted demand flow of the air-conditioning refrigerant in the preset future period is as follows: Based on the wind speed group and the air conditioning refrigerant demand flow group, a two-dimensional coordinate system is constructed with the air conditioning refrigerant demand flow as the X-axis and the wind speed as the Y-axis. A curve showing the change of wind speed with the air conditioning refrigerant demand flow is plotted to obtain a wind speed-flow change curve. The wind speed-flow variation curve is fitted using the least squares method to determine the wind speed-flow correlation model; Input the indoor load demand in a preset future period into the wind speed-flow correlation model, and output the optimal wind speed of the fan coil unit in the preset future period. According to the optimal wind speed of the fan coil unit, query the design specifications of the fan coil unit and the air conditioning system to determine the optimal wind speed level of the fan coil unit; The technical solution of the embodiment of the present invention is: through the correlation analysis method, the changing relationship between the air conditioning refrigerant flow and the indoor load is evaluated to determine whether there is a correlation between the two, providing data support for the subsequent refrigerant flow demand forecast and wind speed gear adjustment. If there is a correlation between the flow and the load, the indoor load demand in the future period is predicted to achieve dynamic prediction of the refrigerant flow, and provide target parameters for the wind speed gear matching of the fan coil. The refrigerant predicted demand flow is matched with the current fan coil wind speed gear to determine whether the current wind speed can meet the future load demand, ensure that the fan coil wind speed matches the refrigerant flow demand in real time, avoid energy waste or reduced comfort caused by insufficient or excessive wind speed, perform correlation analysis on the fan coil wind speed and refrigerant demand flow, and verify whether there is a coordinated change relationship between the two. If there is a correlation, the optimal wind speed gear in the future period is determined based on the refrigerant predicted demand flow, achieve dynamic optimization of the wind speed gear, and improve system energy efficiency and indoor environmental comfort.

[0020] Example 2 See also Figure 2 As shown, a wind speed level control system for a fan coil unit according to an embodiment of the present invention includes the following modules: Flow-load correlation analysis module: Through correlation analysis, it determines whether there is a correlation change relationship between the air conditioning refrigerant flow and the indoor load; The process of determining whether there is a correlation change relationship between the air conditioning refrigerant flow rate and the indoor load through correlation analysis includes: Obtain the air conditioning refrigerant flow under different indoor load environments, obtain indoor load groups based on the data integration of different indoor loads, and obtain air conditioning refrigerant flow groups based on the data integration of air conditioning refrigerant flow under different indoor load environments; The Pearson correlation coefficient is used to process the air conditioning refrigerant flow group and the indoor load group, and the Pearson correlation coefficient between the air conditioning refrigerant flow group and the indoor load group is calculated to obtain the load flow correlation value; If the load flow correlation value is within the preset correlation range, it means that there is a correlation change relationship between the air conditioning refrigerant flow and the indoor load; If the load flow related value is not within the preset related range, it means that there is no correlation change relationship between the air conditioning refrigerant flow and the indoor load; Refrigerant flow demand analysis module: If there is a correlation between the air conditioning refrigerant flow and the indoor load, the indoor load demand in the preset future period is predicted. Based on the predicted indoor load demand and the correlation between the air conditioning refrigerant flow and the indoor load, the predicted air conditioning refrigerant demand flow in the preset future period is determined; The process of predicting the indoor load demand in a preset future period includes: A10 collects actual data on indoor heating or cooling loads during a historical period, and also records relevant factors such as the corresponding time, outdoor temperature, and number of people indoors. A20, draw the ACF and PACF graphs of the load data and determine the order of the ARIMA model based on the graphical characteristics; For example, if the ACF graph decays rapidly after lag 1 and the PACF graph is truncated after lag 1, then the AR (1) model is suitable; if the ACF graph tails and the PACF graph is truncated after lag 2, then the AR (2) model is suitable; A30, using the ARIMA model to determine parameters based on the actual data of indoor heating load or cooling load during the historical period, as well as relevant factors such as time, outdoor temperature, and number of indoor occupants, to determine the coefficients of the AR term, MA term, and constant term of the ARIMA model; A40 inputs the time series corresponding to the preset future period and related factor data (such as the outdoor temperature obtained from the weather forecast report and the number of indoor occupants estimated based on usage demand) into the ARIMA model to obtain the predicted values of the indoor load at different times in the preset future period; Based on the indoor load demand forecast results and the correlation between the air conditioning refrigerant flow rate and the indoor load, the process of determining the air conditioning refrigerant forecast demand flow rate in the preset future period is as follows: The predicted values of indoor load at different times in the preset future period are averaged to obtain the indoor load demand in the preset future period; Based on the indoor load group and the air conditioning refrigerant flow group, a two-dimensional coordinate system is constructed with the indoor load as the X-axis and the air conditioning refrigerant flow as the Y-axis. A curve showing the change of air conditioning refrigerant flow with indoor load is plotted to obtain a flow-load change curve. The flow-load variation curve is fitted using the least squares method to determine the flow-load correlation model, where the flow-load correlation model is Y=kX+b, where Y represents the air conditioning refrigerant flow, X represents the indoor load, k represents the slope, and b represents the intercept; Input the indoor load demand in the preset future period into the flow-load correlation model, and output the predicted demand flow of air-conditioning refrigerant in the preset future period; Wind speed level matching analysis module: Based on the predicted demand for air conditioning refrigerant, it analyzes and determines whether the current fan coil unit wind speed level meets the preset future time period. If not, it generates a wind speed level adjustment signal; Combined with the predicted demand for air conditioning refrigerant, the process of analyzing and judging whether the current fan coil unit wind speed level meets the preset future time period is as follows: According to the design specifications of the fan coil unit and air conditioning system, the corresponding air conditioning refrigerant flow rate of the fan coil unit at the current wind speed level is obtained, and the difference between the air conditioning refrigerant demand flow rate and the predicted demand flow rate in the preset future time period is processed to obtain the air conditioning refrigerant deviation; Compare the air conditioning refrigerant deviation with the normal flow error range of the air conditioning refrigerant; If the air conditioning refrigerant deviation is not within the air conditioning refrigerant normal flow error range, the air conditioning refrigerant deviation is processed with the air conditioning refrigerant normal flow error range endpoint value by absolute deviation ratio to obtain the air conditioning refrigerant deviation degree value; If the air conditioning refrigerant deviation is within the normal flow error range of the air conditioning refrigerant, the air conditioning refrigerant deviation value is 0; Using the air conditioner refrigerant flow rate corresponding to the current wind speed level as the reference value and combining it with the endpoint values of the normal air conditioner refrigerant flow rate error range, calculate the first air conditioner refrigerant flow rate and the second air conditioner refrigerant flow rate. The first air conditioner refrigerant flow rate is greater than the second air conditioner refrigerant flow rate. Since the constructed flow-load correlation model reflects the correlation and change relationship between the air conditioning refrigerant flow and the indoor load, the predicted value of the indoor load at different times in the preset future period is input into the flow-load correlation model to obtain the air conditioning refrigerant flow at different times in the preset future period; According to the air conditioning refrigerant flow at different times in the preset future period, a two-dimensional coordinate system is constructed with time as the X-axis and the air conditioning refrigerant flow as the Y-axis, and a curve of the air conditioning refrigerant flow changing with time is plotted to obtain a time-flow change curve; In the two-dimensional coordinate system where the time-flow rate variation curve is located, a first air-conditioning refrigerant satisfaction line and a second air-conditioning refrigerant satisfaction line are constructed respectively based on the first air-conditioning refrigerant satisfaction flow rate and the second air-conditioning refrigerant satisfaction flow rate; In the two-dimensional coordinate system where the time-flow rate variation curve is located, the area between the first air-conditioning refrigerant satisfaction line and the second air-conditioning refrigerant satisfaction line is marked as the air-conditioning refrigerant satisfaction area; The time-flow variation curve outside the air-conditioning refrigerant satisfaction zone is marked as the refrigerant non-satisfaction curve; Measure the time length corresponding to the refrigerant non-satisfaction curve on the X-axis to obtain the refrigerant non-satisfaction duration. The refrigerant non-satisfaction duration reflects the abnormal duration during which the air conditioner refrigerant flow is not within the air conditioner refrigerant satisfaction zone within the preset future period. Calculate the ratio between the refrigerant non-satisfaction duration and the corresponding duration of the preset future period to obtain the air conditioning refrigerant deviation duration value; The air conditioning refrigerant deviation duration value and the air conditioning refrigerant deviation degree value are summed to obtain the air conditioning refrigerant satisfaction value; Comparing the air conditioning refrigerant satisfaction value with the air conditioning refrigerant satisfaction threshold; If the air conditioning refrigerant satisfaction value is greater than or equal to the air conditioning refrigerant satisfaction threshold, it means that the current fan coil unit's wind speed level cannot meet the preset future time period; If the air conditioning refrigerant satisfaction value is less than the air conditioning refrigerant satisfaction threshold, it means that the current fan coil wind speed level meets the preset future time period; Wind speed level adjustment module: Based on the wind speed level adjustment signal, the module performs a correlation analysis on the fan coil unit's wind speed and the air conditioning refrigerant demand flow rate to determine whether there is a correlation change relationship between the fan coil unit's wind speed and the air conditioning refrigerant demand flow rate. If so, the module determines the optimal wind speed level for the fan coil unit within the preset future period based on the predicted air conditioning refrigerant demand flow rate within the preset future period. The process of determining the optimal wind speed level of the fan coil unit in a preset future period based on the predicted demand flow of air conditioning refrigerant in the preset future period is as follows: Based on the wind speed group and the air conditioning refrigerant demand flow group, a two-dimensional coordinate system is constructed with the air conditioning refrigerant demand flow as the X-axis and the wind speed as the Y-axis. A curve showing the change of wind speed with the air conditioning refrigerant demand flow is plotted to obtain a wind speed-flow change curve. The wind speed-flow variation curve is fitted using the least squares method to determine the wind speed-flow correlation model; The indoor load demand in a preset future time period is input into the wind speed-flow correlation model, and the optimal wind speed of the fan coil unit in the preset future time period is output. Based on the optimal wind speed of the fan coil unit, the design specifications of the fan coil unit and the air conditioning system are queried to determine the optimal wind speed level of the fan coil unit.

[0021] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for controlling the wind speed of a fan coil unit, characterized in that: include: Through correlation analysis, determine whether there is a correlation change relationship between the air conditioning refrigerant flow and the indoor load; If there is a correlation between the air conditioning refrigerant flow rate and the indoor load, the indoor load demand in the preset future period is predicted, and the predicted demand flow of the air conditioning refrigerant in the preset future period is determined based on the correlation between the air conditioning refrigerant flow rate and the indoor load; Based on the predicted demand for air conditioning refrigerant, the system analyzes and determines whether the current fan coil unit's wind speed level meets the preset future time period. If not, a wind speed level adjustment signal is generated. Based on the wind speed level adjustment signal, a correlation analysis is performed on the wind speed of the fan coil unit and the air conditioning refrigerant demand flow to determine whether there is a correlation change relationship between the wind speed of the fan coil unit and the air conditioning refrigerant demand flow. If so, the optimal wind speed level of the fan coil unit in the preset future time period is determined based on the air conditioning refrigerant predicted demand flow in the preset future time period.

2. The method for controlling the wind speed of a fan coil unit according to claim 1, wherein: The process of determining whether there is a correlation change relationship between the air conditioning refrigerant flow rate and the indoor load includes: According to the data integration of different indoor loads and air conditioning refrigerant flow, indoor load groups and air conditioning refrigerant flow groups are obtained; The indoor load group and the air conditioning refrigerant flow group are processed using the Pearson correlation coefficient method to obtain the load flow correlation value. If the load flow correlation value is within the preset correlation range, it means that there is an associated change relationship, otherwise, it does not exist.

3. The method for controlling the wind speed of a fan coil unit according to claim 1, wherein: The method for predicting the indoor load demand in the preset future period is as follows: The predicted values of indoor load at different times in the preset future period are obtained by time series analysis, and the indoor load demand in the preset future period is obtained by averaging.

4. The method for controlling the wind speed of a fan coil unit according to claim 1, wherein: The process of determining the predicted demand flow of air conditioning refrigerant in a preset future period is as follows: The flow-load variation curve drawn based on the indoor load group and the air conditioning refrigerant flow group is fitted using the least squares method to determine the flow-load correlation model; The indoor load demand in the preset future period is used as the input of the flow-load correlation model, and the predicted demand flow of air-conditioning refrigerant in the preset future period is output.

5. The method for controlling the wind speed of a fan coil unit according to claim 1, wherein: The wind speed gear adjustment signal is generated as follows: The deviation of the air conditioning refrigerant flow rate corresponding to the fan coil unit at the current wind speed level and the air conditioning refrigerant demand flow rate predicted in the preset future period is analyzed to obtain the air conditioning refrigerant deviation degree value; Analyze the persistence of the deviation of the air conditioning refrigerant flow at different times in the preset future period to obtain the air conditioning refrigerant deviation persistence value; The sum of the air-conditioning refrigerant deviation degree value and the air-conditioning refrigerant deviation duration value is calculated to obtain the air-conditioning refrigerant satisfaction value. If the air-conditioning refrigerant satisfaction value is greater than or equal to the air-conditioning refrigerant satisfaction threshold, a wind speed gear adjustment signal is generated.

6. The method for controlling the wind speed of a fan coil unit according to claim 5, wherein: The specific method for obtaining the air conditioning refrigerant deviation value is as follows: Calculate the deviation between the air conditioning refrigerant flow rate corresponding to the fan coil unit at the current wind speed level and the air conditioning refrigerant predicted demand flow rate in a preset future time period to obtain the air conditioning refrigerant deviation amount; If the air-conditioning refrigerant deviation is not within the air-conditioning refrigerant normal flow error range, the air-conditioning refrigerant deviation is subjected to absolute deviation ratio processing with the nearest air-conditioning refrigerant normal flow error range endpoint value to obtain the air-conditioning refrigerant deviation degree value.

7. The method for controlling the wind speed of a fan coil unit according to claim 5, wherein: The specific method for obtaining the air conditioning refrigerant deviation persistence value is as follows: Input the predicted values of indoor load at different times in the preset future period into the flow-load correlation model to obtain the air conditioning refrigerant flow at different times in the preset future period and draw a time-flow change curve; By constructing a first air-conditioning refrigerant satisfaction line and a second air-conditioning refrigerant satisfaction line, the two-dimensional coordinate system where the time-flow change curve is located is marked as an air-conditioning refrigerant satisfaction area; The time-flow variation curve outside the air-conditioning refrigerant satisfaction zone is marked as the refrigerant non-satisfaction curve; The duration of the refrigerant non-satisfaction curve on the X-axis is measured, and the ratio between the duration and the preset future time period is used to obtain the air conditioning refrigerant deviation duration value.

8. The method for controlling the wind speed of a fan coil unit according to claim 7, wherein: The method for obtaining the mark of the air conditioning refrigerant satisfaction zone is: The first air conditioner refrigerant flow rate and the second air conditioner refrigerant flow rate are calculated based on the corresponding air conditioner refrigerant flow rate at the current wind speed level as the reference value and the endpoint value of the normal air conditioner refrigerant flow rate error range. The first air-conditioning refrigerant satisfaction flow rate and the second air-conditioning refrigerant satisfaction flow rate are used to construct the first air-conditioning refrigerant satisfaction line and the second air-conditioning refrigerant satisfaction line respectively. In the two-dimensional coordinate system where the time-flow change curve is located, the area between the first air-conditioning refrigerant satisfaction line and the second air-conditioning refrigerant satisfaction line is marked as the air-conditioning refrigerant satisfaction area.

9. The method for controlling the wind speed of a fan coil unit according to claim 1, wherein: The optimal wind speed gear of the fan coil unit is obtained as follows: Obtain the air conditioning refrigerant demand flow corresponding to the fan coil unit at different wind speeds, and integrate the data of different wind speeds and different air conditioning refrigerant demand flow rates to obtain wind speed groups and air conditioning refrigerant demand flow rate groups; Calculate the Pearson correlation coefficient between the wind speed group and the air conditioning refrigerant demand flow group to obtain the wind speed and flow correlation value; If the wind speed and flow correlation value is within the preset correlation range, it means that there is a correlation between the wind speed of the fan coil unit and the air conditioning refrigerant demand flow rate. The wind speed-flow change curve drawn according to the wind speed group and the air conditioning refrigerant demand flow rate group is fitted using the least squares method to determine the wind speed-flow correlation model; The indoor load demand in the preset future period is input into the wind speed-flow correlation model, and the optimal wind speed of the fan coil unit in the preset future period is output, thereby determining the optimal wind speed gear of the fan coil unit.

10. A wind speed level control system for a fan coil unit, characterized by: include: Flow-load correlation analysis module: Through correlation analysis, it determines whether there is a correlation change relationship between the air conditioning refrigerant flow and the indoor load; Refrigerant flow demand analysis module: If there is a correlation between the air conditioning refrigerant flow and the indoor load, the indoor load demand in the preset future period is predicted, and the predicted air conditioning refrigerant demand flow in the preset future period is determined based on the correlation between the air conditioning refrigerant flow and the indoor load. Wind speed level matching analysis module: Based on the predicted demand for air conditioning refrigerant, it analyzes and determines whether the current fan coil unit wind speed level meets the preset future time period. If not, it generates a wind speed level adjustment signal; Wind speed level adjustment module: Based on the wind speed level adjustment signal, the correlation analysis is performed on the wind speed of the fan coil unit and the air conditioning refrigerant demand flow to determine whether there is a correlation change relationship between the wind speed of the fan coil unit and the air conditioning refrigerant demand flow. If so, the optimal wind speed level of the fan coil unit in the preset future time period is determined based on the predicted demand flow of the air conditioning refrigerant in the preset future time period.

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