Debugging and energy-saving control method for refrigerating and heating system

Abstract

The invention belongs to the technical field of refrigeration and heating management and control, and particularly relates to a refrigeration and heating system debugging and energy-saving control method, which comprises the steps of setting a target temperature value and determining a working mode of a refrigeration and heating system, judging an optimal operation state, executing the optimal operation state, and carrying out operation fitness detection and management and control comprehensive evaluation. The refrigerating and heating system operates according to the corresponding optimal operation state in the corresponding working mode, and the operation efficiency of the refrigerating and heating system can be automatically and reasonably controlled, so that the operation energy consumption of the refrigerating and heating system is remarkably reduced while the heating and refrigerating effects are ensured; and the operation deviation condition of the refrigeration and heating system during operation can be accurately judged in real time, management personnel can be timely reminded to take corresponding adjustment treatment measures, the operation performance of the refrigeration and heating system can be comprehensively evaluated, subsequent supervision can be enhanced when a management and control abnormal signal is generated, and the intelligent degree is high.

Description

Technical Field

[0001] The present invention relates to the technical field of refrigeration and heating management and control, and in particular to a refrigeration and heating system debugging and energy-saving control method. Background Art

[0002] The refrigeration and heating system is mainly composed of a compressor, a heat exchanger, an expansion valve and an evaporator. By controlling the circulation and state change of the refrigerant, the energy transfer and reuse are realized, thereby achieving the purpose of heating and cooling. Due to the high efficiency and environmental protection of the refrigeration and heating system, it is widely used in industry, agriculture, commerce and home.

[0003] With the widespread application of refrigeration and heating equipment in daily life and industrial production, how to control the energy saving of refrigeration and heating systems has become an urgent problem to be solved. Traditional energy-saving control methods are difficult to automatically and reasonably control the operating efficiency of refrigeration and heating systems and accurately judge the operating deviation of refrigeration and heating systems. They are also unable to comprehensively evaluate the operating performance of refrigeration and heating systems, have low intelligence and are difficult to manage.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a refrigeration and heating system debugging and energy-saving control method, which solves the problems that the prior art is difficult to automatically and reasonably control the operating efficiency of the refrigeration and heating system and accurately judge its operating deviation status, as well as unable to comprehensively evaluate the operating performance of the refrigeration and heating system, has a low degree of intelligence and is difficult to manage.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for debugging and energy-saving control of a refrigeration and heating system comprises the following steps:

[0008] Step 1: Set the target temperature value, determine the working mode of the refrigeration and heating system, and the energy-saving control module enables the refrigeration and heating system to operate in the corresponding working mode; wherein the working mode includes a refrigeration mode and a heating mode;

[0009] Step 2: The state decision module determines through analysis that the most suitable operating state of the refrigeration and heating system in the corresponding working mode is a high-efficiency operating state, a medium-efficiency operating state or a low-efficiency state;

[0010] Step 3: The state decision module sends the state decision information to the energy-saving control module, and the energy-saving control module enables the refrigeration and heating system to operate in the corresponding optimal operating state under the corresponding working mode;

[0011] Step 4: The operation fit evaluation module monitors various operation parameters of the refrigeration and heating system, determines the operation fit status of the refrigeration and heating system and generates a high fit signal or a low fit signal, and causes the intelligent display module to issue an early warning when a low fit signal is generated;

[0012] Step 5: The comprehensive management and control evaluation module comprehensively evaluates the operating performance of the refrigeration and heating system to generate a qualified management and control signal or an abnormal management and control signal, and causes the intelligent display module to issue an early warning when an abnormal management and control signal is generated.

[0013] Furthermore, in step 2, the specific analysis process of the state decision module is as follows:

[0014] The deviation value of the average temperature in the detection period compared with the set target temperature value is collected and marked as the temperature adjustment value, and two sets of preset temperature adjustment thresholds W1 and W2 are set in advance, and W2>W1>0; the temperature adjustment value is numerically compared with the two sets of preset temperature adjustment thresholds. If the temperature adjustment value ≥W2, it is determined that the optimal operating state of the refrigeration and heating system in the corresponding working mode is a high-efficiency operating state;

[0015] If W2>temperature adjustment value≥W1, it is judged that the optimal operating state of the refrigeration and heating system in the corresponding working mode is the medium-efficiency operating state; if the temperature adjustment value is <W1, it is judged that the optimal operating state of the refrigeration and heating system in the corresponding working mode is the low-efficiency operating state; wherein, the refrigeration or heating efficiency of the high-efficiency operating state is higher than that of the medium-efficiency operating state, and the refrigeration or heating efficiency of the medium-efficiency operating state is higher than that of the low-efficiency operating state.

[0016] Furthermore, in step 4, the specific analysis and judgment process of the operation fit evaluation module is as follows:

[0017] Obtain the operating parameters that need to be monitored for the refrigeration and heating system under the corresponding optimal operating state, collect parameter data of the corresponding operating parameters in real time, and determine whether the parameter data of the corresponding operating parameters meet the corresponding data requirements. If the parameter data of the corresponding operating parameters do not meet the corresponding data requirements, mark the corresponding operating parameters as table deviation parameters;

[0018] If there is no surface bias parameter, a high fit signal is generated.

[0019] Furthermore, if there is a table bias parameter, the deviation value of the parameter data corresponding to the table bias parameter compared to the corresponding data requirement is marked as a bias value, each set of operating parameters is set in advance to correspond to a set of preset weight values, and the product of the bias value of the corresponding table bias parameter and the corresponding preset weight value is marked as a bias value;

[0020] The deviation values ​​of all table deviation parameters are obtained and summed up to obtain the fit influence value, and the fit influence value is numerically compared with the preset fit influence threshold. If the fit influence value exceeds the preset fit influence threshold, a low fit signal is generated; if the fit influence value does not exceed the preset fit influence threshold, a high fit signal is generated.

[0021] Furthermore, in step five, the specific operation process of the management and control comprehensive evaluation module is as follows:

[0022] A detection period is set, the number of times the low fit signal is generated during the detection period is collected and marked as a low fit detection value, the low fit detection value is ratio-calculated with the total operating time of the refrigeration and heating system during the detection period to obtain a low fit assessment value, the low fit assessment value is numerically compared with the preset low fit assessment threshold, and if the low fit assessment value exceeds the preset low fit assessment threshold, a control abnormal signal is generated.

[0023] Further, if the low fit evaluation value does not exceed the preset low fit evaluation threshold, the number of times the corresponding operating parameter is marked as a table deviation parameter during the detection period is collected and the ratio is calculated with the total operation time of the refrigeration and heating system during the detection period to obtain a parameter detection value, and the parameter detection value is numerically compared with the corresponding preset parameter detection threshold. If the parameter detection value exceeds the corresponding preset parameter detection threshold, a judgment symbol HK-1 is assigned to the corresponding operating parameter;

[0024] The number of operating parameters assigned with the judgment symbol HK-1 during the detection period is obtained and marked as out-of-table reference detection values, and the ratio of the parameter detection value of the corresponding operating parameter to the corresponding preset parameter detection threshold is marked as a reference coefficient, all reference coefficients are averaged to obtain a reference decision value, and the reference coefficient with the largest value is marked as a reference amplitude measurement value;

[0025] The parameter evaluation value is obtained by numerically calculating the outlier parameter inspection value, reference decision value and reference amplitude measurement value, and the parameter evaluation value is numerically compared with the preset parameter evaluation threshold. If the parameter evaluation value exceeds the preset parameter evaluation threshold, a control abnormality signal is generated.

[0026] Furthermore, if the parameter evaluation value does not exceed the preset parameter evaluation threshold, the total time during which the real-time temperature of the refrigeration and heating system is not within the preset suitable temperature range during the operation of the refrigeration and heating system during the detection period is calculated by ratio to the total operation time of the refrigeration and heating system during the detection period to obtain the non-optimal operation value; wherein the median value of the preset suitable temperature range is the target temperature value;

[0027] When the real-time temperature is not within the preset suitable temperature range, the deviation value of the real-time temperature compared with the corresponding preset suitable temperature range is marked as a temperature deviation value, and the average of all temperature deviation values ​​in the operation of the cooling and heating system during the detection period is calculated to obtain a temperature non-optimal value;

[0028] The operation efficiency inspection value is obtained by numerically calculating the operation non-optimal value and the temperature non-optimal value, and the operation efficiency inspection value is numerically compared with the preset operation efficiency inspection threshold. If the operation efficiency inspection value exceeds the preset operation efficiency inspection threshold, a control abnormality signal is generated; if the operation efficiency inspection value does not exceed the preset operation efficiency inspection threshold, a control qualified signal is generated.

[0029] Furthermore, the management and control comprehensive evaluation module is communicatively connected with the cleaning timeliness analysis module. The management and control comprehensive evaluation module sends the management and control qualified signal to the cleaning timeliness analysis module. When the management and control qualified signal is received, the cleaning timeliness analysis module determines whether to generate a cleaning warning signal through cleaning timeliness analysis, and sends the cleaning warning signal to the intelligent display module. When the intelligent display module receives the cleaning warning signal, it issues a corresponding warning.

[0030] Furthermore, the specific analysis process of cleaning timeliness analysis is as follows:

[0031] The time of the last inspection and cleaning of the refrigeration and heating system is obtained and marked as the initial cleaning time, the interval between the current time and the initial cleaning time is marked as the cleaning interval value, and the cleaning interval value is compared with the preset cleaning interval threshold. If the cleaning interval value exceeds the preset cleaning interval threshold, a cleaning warning signal is generated.

[0032] Furthermore, if the cleaning interval value does not exceed the preset cleaning interval threshold, the operation duration of each operation of the refrigeration and heating system in the interval between the current moment and the initial cleaning moment is collected, the operation duration is compared with the preset operation duration threshold, and the number of occurrences of the operation duration exceeding the preset operation duration threshold in the corresponding interval is marked as the over-operation detection value;

[0033] The cleaning decision value is obtained by numerically calculating the total operating time of the refrigeration and heating system within the corresponding interval, the cleaning interval value and the over-operation detection value, and the cleaning decision value is numerically compared with the preset cleaning decision threshold. If the cleaning decision value exceeds the preset cleaning decision threshold, a cleaning warning signal is generated.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1. In the present invention, the state decision module is used to analyze and determine the optimal operating state of the refrigeration and heating system under the corresponding working mode. The energy-saving control module enables the refrigeration and heating system to operate in the corresponding working mode according to the corresponding optimal operating state, and can automatically and reasonably control the operating efficiency of the refrigeration and heating system, thereby ensuring the heating and cooling effect while significantly reducing its operating energy consumption. The operating parameters of the refrigeration and heating system are monitored by the operating compliance evaluation module to accurately and in real time determine the operating deviation of the refrigeration and heating system during operation, thereby ensuring the energy-saving, efficient and safe operation of the refrigeration and heating system.

[0036] 2. In the present invention, the operating performance of the refrigeration and heating system is comprehensively evaluated through the management and control comprehensive evaluation module to generate a management and control qualified signal or a management and control abnormal signal. When the management and control abnormal signal is generated, the subsequent supervision is strengthened to further ensure the subsequent operating effect. When the management and control qualified signal is generated, the timeliness of cleaning is analyzed to determine whether to generate a cleaning warning signal. When the cleaning warning signal is generated, the management personnel are reminded to check and clean the refrigeration and heating system in time, further ensuring the subsequent safe, stable, efficient and energy-saving operation of the refrigeration and heating system, with a high degree of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0038] Figure 1 This is a flow chart of the method of Embodiment 1 of the present invention;

[0039] Figure 2 This is a system block diagram of Embodiment 1 of the present invention;

[0040] Figure 3 This is a system block diagram of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Embodiment 1: Figure 1-2 As shown, a refrigeration and heating system debugging and energy-saving control method proposed by the present invention comprises the following steps:

[0043] Step 1: Set the target temperature value, determine the working mode of the refrigeration and heating system, and the energy-saving control module enables the refrigeration and heating system to operate in the corresponding working mode; wherein the working mode includes a refrigeration mode and a heating mode.

[0044] Step 2: The state decision module determines through analysis whether the most suitable operating state of the refrigeration and heating system in the corresponding working mode is a high-efficiency operating state, a medium-efficiency operating state or a low-efficiency operating state; wherein the refrigeration or heating efficiency of the high-efficiency operating state is higher than that of the medium-efficiency operating state, and the refrigeration or heating efficiency of the medium-efficiency operating state is higher than that of the low-efficiency operating state; the specific analysis process of the state decision module is as follows:

[0045] The deviation value of the average temperature in the detection period compared with the set target temperature value is collected and marked as the temperature adjustment value, and two sets of preset temperature adjustment thresholds W1 and W2 are set in advance, and W2>W1>0; the temperature adjustment value is numerically compared with the two sets of preset temperature adjustment thresholds. If the temperature adjustment value ≥W2, it is determined that the optimal operating state of the refrigeration and heating system in the corresponding working mode is a high-efficiency operating state;

[0046] If W2>temperature adjustment value≥W1, it is judged that the optimal operating state of the refrigeration and heating system in the corresponding working mode is a medium-efficiency operating state; if the temperature adjustment value is <W1, it is judged that the optimal operating state of the refrigeration and heating system in the corresponding working mode is a low-efficiency operating state.

[0047] Step three, the state decision module sends the state decision information to the energy-saving control module. The energy-saving control module enables the refrigeration and heating system to operate in the corresponding optimal operating state under the corresponding working mode, and can automatically and reasonably control the operating efficiency of the refrigeration and heating system, thereby ensuring the heating and cooling effect while significantly reducing its operating energy consumption, thereby playing a role in energy saving and environmental protection.

[0048] Step 4: The operation conformity assessment module monitors the various operating parameters of the refrigeration and heating system, determines the operation conformity of the refrigeration and heating system and generates a high conformity signal or a low conformity signal. When a low conformity signal is generated, the intelligent display module issues an early warning, which can reasonably analyze and accurately determine the operation deviation of the refrigeration and heating system during operation in real time, and promptly remind the management personnel to make corresponding adjustment measures, further ensuring the energy-saving, efficient and safe operation of the refrigeration and heating system. The specific analysis and judgment process of the operation conformity assessment module is as follows:

[0049] Obtain the operating parameters (such as evaporation temperature, condensation temperature, compressor speed, etc.) that need to be monitored for the refrigeration and heating system under the corresponding optimal operating state, collect parameter data of the corresponding operating parameters in real time, and determine whether the parameter data of the corresponding operating parameters meet the corresponding data requirements. If the parameter data of the corresponding operating parameters do not meet the corresponding data requirements, indicating that the real-time performance of the corresponding operating parameters is poor, the corresponding operating parameters are marked as table deviation parameters; if there are no table deviation parameters, a high fit signal is generated;

[0050] If there is a table bias parameter, the deviation value of the parameter data of the corresponding table bias parameter compared to the corresponding data requirement is marked as a bias value, and each group of operating parameters is set in advance to correspond to a group of preset weight values. It should be noted that the values ​​of the preset weight values ​​are all positive numbers, and the greater the adverse effect caused by the deviation of the corresponding operating parameter, the greater the value of the corresponding preset weight value; the product of the bias value of the corresponding table bias parameter and the corresponding preset weight value is marked as a bias value;

[0051] The deviation values ​​of all table deviation parameters are obtained and summed up to obtain the fitting influence value, wherein the larger the value of the fitting influence value is, the worse the real-time operation performance of the refrigeration and heating system is; the fitting influence value is numerically compared with the preset fitting influence threshold value, if the fitting influence value exceeds the preset fitting influence threshold value, it indicates that the real-time operation performance of the refrigeration and heating system is poor, and a low fitting signal is generated; if the fitting influence value does not exceed the preset fitting influence threshold value, it indicates that the real-time operation performance of the refrigeration and heating system is good, and a high fitting signal is generated.

[0052] Step 5: The comprehensive evaluation module of the control and management will comprehensively evaluate the operating performance of the refrigeration and heating system to generate a qualified control signal or a control abnormality signal. When the control abnormality signal is generated, the intelligent display module will issue an early warning, which can comprehensively evaluate the performance of the refrigeration and heating control. When the corresponding early warning is issued, the cause investigation and analysis will be carried out and subsequent supervision will be strengthened, and the refrigeration and heating system will be inspected and cleaned as needed to ensure the subsequent operation effect. The specific operation process of the comprehensive evaluation module of the control and management is as follows:

[0053] A detection period is set, preferably, the detection period is fifteen days; the number of times the low fit signal is generated during the detection period is collected and marked as a low fit detection value, the low fit detection value is calculated by ratio with the total operation time of the refrigeration and heating system during the detection period to obtain a low fit evaluation value, the low fit evaluation value is numerically compared with a preset low fit evaluation threshold, if the low fit evaluation value exceeds the preset low fit evaluation threshold, it indicates that the operation condition of the refrigeration and heating system during the detection period is poor, and a control abnormality signal is generated;

[0054] If the low fit evaluation value does not exceed the preset low fit evaluation threshold, the number of times the corresponding operating parameter is marked as a table deviation parameter during the detection period is collected and the ratio is calculated with the total operation time of the refrigeration and heating system during the detection period to obtain the parameter detection value, and the parameter detection value is numerically compared with the corresponding preset parameter detection threshold. If the parameter detection value exceeds the corresponding preset parameter detection threshold, it indicates that the control performance of the corresponding operating parameter during the detection period is worse, and the judgment symbol HK-1 is assigned to the corresponding operating parameter;

[0055] The number of operating parameters assigned with the judgment symbol HK-1 during the detection period is obtained and marked as out-of-table reference detection values, and the ratio of the parameter detection value of the corresponding operating parameter to the corresponding preset parameter detection threshold is marked as a reference coefficient, all reference coefficients are averaged to obtain a reference decision value, and the reference coefficient with the largest value is marked as a reference amplitude measurement value;

[0056] The parameter evaluation value QR is obtained by numerically calculating the out-of-table reference value QL, the reference decision value QK and the reference amplitude measurement value QM through the formula QR=a1*QL+(a2*QK+a3*QM / )2, wherein a1, a2 and a3 are preset proportional coefficients whose values ​​are greater than zero, and the larger the value of the parameter evaluation value QR is, the worse the parameter control performance of the refrigeration and heating system is in the detection period; the parameter evaluation value QR is numerically compared with the preset parameter evaluation threshold value, and if the parameter evaluation value QR exceeds the preset parameter evaluation threshold value, it indicates that the parameter control performance of the refrigeration and heating system is in the detection period. In this case, a control abnormality signal is generated;

[0057] If the parameter evaluation value QR does not exceed the preset parameter evaluation threshold, the total time during which the real-time temperature of the refrigeration and heating system is not within the preset suitable temperature range during the operation of the detection period is calculated by ratio with the total operation time of the refrigeration and heating system during the detection period to obtain the non-optimal value of operation; wherein the median value of the preset suitable temperature range is the target temperature value;

[0058] When the real-time temperature is not within the preset suitable temperature range, the deviation value of the real-time temperature compared with the corresponding preset suitable temperature range is marked as a temperature deviation value, and the average of all temperature deviation values ​​in the operation of the cooling and heating system during the detection period is calculated to obtain a temperature non-optimal value;

[0059] The operation non-optimum value LY and the temperature non-optimum value LS are numerically calculated by the formula LX=rh1*LY+rh2*LS / rh1 to obtain the operation efficiency inspection value LX, wherein rh1 and rh2 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the operation efficiency inspection value LX, the worse the temperature regulation management performance of the refrigeration and heating system during the detection period;

[0060] The operating efficiency inspection value LX is numerically compared with the preset operating efficiency inspection threshold. If the operating efficiency inspection value LX exceeds the preset operating efficiency inspection threshold, it indicates that the temperature regulation management performance of the refrigeration and heating system during the detection period is poor, and a control abnormality signal is generated; if the operating efficiency inspection value LX does not exceed the preset operating efficiency inspection threshold, it indicates that the refrigeration and heating control performance during the detection period is good overall, and a control qualified signal is generated.

[0061] Embodiment 2: Figure 3As shown, the difference between this embodiment and the first embodiment is that the control comprehensive evaluation module is connected to the cleaning timeliness analysis module in communication, the control comprehensive evaluation module sends the control qualified signal to the cleaning timeliness analysis module, and the cleaning timeliness analysis module determines whether to generate a cleaning warning signal through cleaning timeliness analysis when receiving the control qualified signal, and sends the cleaning warning signal to the intelligent display module. When the intelligent display module receives the cleaning warning signal, it issues a corresponding warning to remind the management personnel to check and clean the refrigeration and heating system in time, further ensuring the subsequent safe, stable, efficient and energy-saving operation of the refrigeration and heating system, and the degree of intelligence is high; the specific analysis process of the cleaning timeliness analysis is as follows:

[0062] The time when the refrigeration and heating system was inspected and cleaned immediately before is obtained and marked as the initial cleaning time. The interval between the current time and the initial cleaning time is marked as the cleaning interval value. The cleaning interval value is numerically compared with the preset cleaning interval threshold. If the cleaning interval value exceeds the preset cleaning interval threshold, it indicates that the cleaning interval is long and the refrigeration and heating system needs to be inspected and cleaned in time to ensure its stable operation. Then, a cleaning warning signal is generated.

[0063] Furthermore, if the cleaning interval value does not exceed the preset cleaning interval threshold, the operation duration of each operation of the refrigeration and heating system in the interval between the current moment and the initial cleaning moment is collected, the operation duration is compared with the preset operation duration threshold, and the number of occurrences of the operation duration exceeding the preset operation duration threshold in the corresponding interval is marked as the over-operation detection value;

[0064] By formula The total operation time TS of the cooling and heating system within the corresponding interval, the cleaning interval value TF and the over-operation detection value TP are numerically calculated to obtain the cleaning decision value TN, wherein wt1, wt2 and wt3 are preset proportional coefficients, wt3>wt1>wt2>0;

[0065] Moreover, the larger the value of the cleaning decision value TN is, the more timely it is necessary to check and clean the refrigeration and heating system; the cleaning decision value TN is compared with the preset cleaning decision threshold. If the cleaning decision value TN exceeds the preset cleaning decision threshold, it indicates that the refrigeration and heating system needs to be checked and cleaned in time, and a cleaning warning signal is generated.

[0066] The working principle of the present invention is as follows: when in use, the state decision module is used to analyze to determine the most suitable operating state of the refrigeration and heating system under the corresponding working mode. The energy-saving control module enables the refrigeration and heating system to operate in the corresponding working mode according to the corresponding most suitable operating state, and can automatically and reasonably control the operating efficiency of the refrigeration and heating system, thereby ensuring the heating and refrigeration effect while significantly reducing its operating energy consumption. The operating parameters of the refrigeration and heating system are monitored through the operating fit evaluation module to accurately and in real time determine the operating deviation of the refrigeration and heating system during operation and promptly remind the management personnel to make corresponding adjustment and processing measures to ensure the energy-saving, efficient and safe operation of the refrigeration and heating system. The operating performance of the refrigeration and heating system is comprehensively evaluated through the comprehensive management and control evaluation module to generate a qualified management and control signal or an abnormal management and control signal. When the abnormal management and control signal is generated, subsequent supervision is strengthened to further ensure the subsequent operating effect, and the degree of intelligence is high.

[0067] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A method for debugging and energy-saving control of a refrigeration and heating system, characterized in that: The following steps are involved: Step 1: Set the target temperature value, determine the working mode of the refrigeration and heating system, and the energy-saving control module enables the refrigeration and heating system to operate in the corresponding working mode; Step 2: The state decision module determines through analysis that the most suitable operating state of the refrigeration and heating system in the corresponding working mode is a high-efficiency operating state, a medium-efficiency operating state or a low-efficiency state; Step 3: The state decision module sends the state decision information to the energy-saving control module, and the energy-saving control module enables the refrigeration and heating system to operate in the corresponding optimal operating state under the corresponding working mode; Step 4: The operation fit evaluation module monitors various operation parameters of the refrigeration and heating system, determines the operation fit status of the refrigeration and heating system and generates a high fit signal or a low fit signal, and causes the intelligent display module to issue an early warning when a low fit signal is generated; Step 5: The comprehensive management and control evaluation module comprehensively evaluates the operating performance of the refrigeration and heating system to generate a qualified management and control signal or an abnormal management and control signal, and causes the intelligent display module to issue an early warning when an abnormal management and control signal is generated.

2. A refrigeration and heating system debugging and energy-saving control method according to claim 1, characterized in that: In step 2, the specific analysis process of the state decision module is as follows: The deviation value of the average temperature in the detection period compared with the set target temperature value is collected and marked as the temperature adjustment value, and two sets of preset temperature adjustment thresholds W1 and W2 are set in advance, and W2>W1>0; the temperature adjustment value is numerically compared with the two sets of preset temperature adjustment thresholds. If the temperature adjustment value ≥W2, it is determined that the optimal operating state of the refrigeration and heating system in the corresponding working mode is a high-efficiency operating state; If W2>temperature adjustment value≥W1, it is judged that the optimal operating state of the refrigeration and heating system in the corresponding working mode is the medium-efficiency operating state; If the temperature control value is less than W1, it is judged that the optimal operating state of the refrigeration and heating system in the corresponding working mode is an inefficient operating state; wherein, the refrigeration or heating efficiency of the high-efficiency operating state is higher than that of the medium-efficiency operating state, and the refrigeration or heating efficiency of the medium-efficiency operating state is higher than that of the inefficient operating state.

3. A refrigeration and heating system debugging and energy-saving control method according to claim 1, characterized in that: In step 4, the specific analysis and judgment process of running the fit evaluation module is as follows: Obtain the operating parameters that need to be monitored for the refrigeration and heating system under the corresponding optimal operating state, collect parameter data of the corresponding operating parameters in real time, and determine whether the parameter data of the corresponding operating parameters meet the corresponding data requirements. If the parameter data of the corresponding operating parameters do not meet the corresponding data requirements, mark the corresponding operating parameters as table deviation parameters; If there is no surface bias parameter, a high fit signal is generated.

4. A refrigeration and heating system debugging and energy-saving control method according to claim 3, characterized in that: If there is a table bias parameter, the deviation value of the parameter data corresponding to the table bias parameter compared to the corresponding data requirement is marked as a bias value, and each set of operating parameters is set in advance to correspond to a set of preset weight values, and the product of the bias value of the corresponding table bias parameter and the corresponding preset weight value is marked as a bias value; The deviation values ​​of all table deviation parameters are obtained and summed up to obtain the fit influence value, and the fit influence value is numerically compared with the preset fit influence threshold. If the fit influence value exceeds the preset fit influence threshold, a low fit signal is generated; if the fit influence value does not exceed the preset fit influence threshold, a high fit signal is generated.

5. A cooling and heating system debugging and energy-saving control method according to claim 1, characterized in that: In step 5, the specific operation process of the management and control comprehensive evaluation module is as follows: A detection period is set, the number of times the low fit signal is generated during the detection period is collected and marked as a low fit detection value, the low fit detection value is ratio-calculated with the total operating time of the refrigeration and heating system during the detection period to obtain a low fit assessment value, the low fit assessment value is numerically compared with the preset low fit assessment threshold, and if the low fit assessment value exceeds the preset low fit assessment threshold, a control abnormal signal is generated.

6. A cooling and heating system debugging and energy-saving control method according to claim 5, characterized in that: If the low fit evaluation value does not exceed the preset low fit evaluation threshold, the number of times the corresponding operating parameter is marked as a table deviation parameter during the detection period is collected and the ratio is calculated with the total operation time of the refrigeration and heating system during the detection period to obtain a parameter detection value, and the parameter detection value is numerically compared with the corresponding preset parameter detection threshold. If the parameter detection value exceeds the corresponding preset parameter detection threshold, the judgment symbol HK-1 is assigned to the corresponding operating parameter; The number of operating parameters assigned with the judgment symbol HK-1 during the detection period is obtained and marked as out-of-table reference detection values, and the ratio of the parameter detection value of the corresponding operating parameter to the corresponding preset parameter detection threshold is marked as a reference coefficient, all reference coefficients are averaged to obtain a reference decision value, and the reference coefficient with the largest value is marked as a reference amplitude measurement value; The parameter evaluation value is obtained by numerically calculating the outlier parameter inspection value, reference decision value and reference amplitude measurement value, and the parameter evaluation value is numerically compared with the preset parameter evaluation threshold. If the parameter evaluation value exceeds the preset parameter evaluation threshold, a control abnormality signal is generated.

7. A cooling and heating system debugging and energy-saving control method according to claim 6, characterized in that: If the parameter evaluation value does not exceed the preset parameter evaluation threshold, the total time during which the real-time temperature of the refrigeration and heating system is not within the preset suitable temperature range during the operation of the refrigeration and heating system during the detection period is calculated by ratio to the total operation time of the refrigeration and heating system during the detection period to obtain the non-optimal operation value; wherein the median value of the preset suitable temperature range is the target temperature value; When the real-time temperature is not within the preset suitable temperature range, the deviation value of the real-time temperature compared with the corresponding preset suitable temperature range is marked as a temperature deviation value, and the average of all temperature deviation values ​​in the operation of the cooling and heating system during the detection period is calculated to obtain a temperature non-optimal value; The operation efficiency inspection value is obtained by numerically calculating the operation non-optimal value and the temperature non-optimal value, and the operation efficiency inspection value is numerically compared with the preset operation efficiency inspection threshold. If the operation efficiency inspection value exceeds the preset operation efficiency inspection threshold, a control abnormality signal is generated; if the operation efficiency inspection value does not exceed the preset operation efficiency inspection threshold, a control qualified signal is generated.

8. A cooling and heating system debugging and energy-saving control method according to claim 1, characterized in that: The management and control comprehensive evaluation module is communicatively connected with the cleaning timeliness analysis module. The management and control comprehensive evaluation module sends the management and control qualified signal to the cleaning timeliness analysis module. When receiving the management and control qualified signal, the cleaning timeliness analysis module determines whether to generate a cleaning warning signal through cleaning timeliness analysis, and sends the cleaning warning signal to the intelligent display module. When the intelligent display module receives the cleaning warning signal, it issues a corresponding warning.

9. A cooling and heating system debugging and energy-saving control method according to claim 8, characterized in that: The specific analysis process of cleaning timeliness analysis is as follows: The time of the last inspection and cleaning of the refrigeration and heating system is obtained and marked as the initial cleaning time, the interval between the current time and the initial cleaning time is marked as the cleaning interval value, and the cleaning interval value is compared with the preset cleaning interval threshold. If the cleaning interval value exceeds the preset cleaning interval threshold, a cleaning warning signal is generated.

10. A cooling and heating system debugging and energy-saving control method according to claim 9, characterized in that: If the cleaning interval value does not exceed the preset cleaning interval threshold, the operation duration of each operation of the cooling and heating system in the interval between the current time and the initial cleaning time is collected, the operation duration is compared with the preset operation duration threshold, and the number of occurrences of the operation duration exceeding the preset operation duration threshold in the corresponding interval is marked as the over-operation detection value; The cleaning decision value is obtained by numerically calculating the total operating time of the refrigeration and heating system within the corresponding interval, the cleaning interval value and the over-operation detection value, and the cleaning decision value is numerically compared with the preset cleaning decision threshold. If the cleaning decision value exceeds the preset cleaning decision threshold, a cleaning warning signal is generated.

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