Central air conditioner energy-saving control system and method based on artificial intelligence

Abstract

The invention discloses a central air conditioner energy-saving control system and method based on artificial intelligence, relates to the technical field of air conditioner energy-saving control, and solves the technical problems that in the prior art, when a central air conditioner operates, temperature detection evaluation cannot be conducted on the central air conditioner, and it cannot be guaranteed that the temperature detection performance of the central air conditioner meets the requirement. The marking module is used for marking a central air conditioner coverage area as a control area, obtaining a main circulation route and a secondary circulation route of the control area and determining an air supply point; taking the air supply point as a starting point and the main circulation route as a track, dividing the main circulation route into a plurality of sub-positions, and according to the sub-positions, inferring air supply point effects, high effects, energy-saving regulation and control, low effects and frequency conversion control so as to meet control requirements; temperature floating speed deviation information and temperature floating control area information are collected, and temperature detection analysis control is conducted according to information analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of air-conditioning energy-saving control, and in particular to an artificial intelligence-based central air-conditioning energy-saving control system and method. Background Art

[0002] Central air conditioning is a system that centrally handles air conditioning loads. It generates cold or heat through one or more central refrigeration or heating equipment (such as chillers, heat pumps, etc.), and then uses a pipe system to transport hot and cold water or refrigerants to the terminal equipment in each air-conditioned area (such as fan coil units, air-conditioning boxes, etc.) for air conditioning. The energy-saving control of central air conditioning is a complex system involving multiple aspects.

[0003] However, in the prior art, the central air conditioner cannot be temperature-detected and evaluated while it is running, and it is impossible to ensure that the temperature detection performance of the central air conditioner meets the requirements, resulting in a decrease in temperature control efficiency. It is also impossible to infer whether the current energy consumption control is qualified through temperature detection and evaluation. In addition, it is impossible to perform frequency conversion adjustment adaptation analysis on the central air conditioner.

[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 solve the above-mentioned problems and to propose an energy-saving control system and method for central air conditioning based on artificial intelligence.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An artificial intelligence-based central air-conditioning energy-saving control system includes an energy-saving control platform, and the energy-saving control platform is connected to:

[0008] The regional temperature detection and analysis unit is used to mark the area covered by the central air conditioner as the control area, obtain the main flow route and the secondary flow route of the control area, and determine the air supply point; take the air supply point as the starting point and the main flow route as the trajectory, divide the main flow route into several sub-positions, and infer the role of the air supply point according to the sub-position. If the role is high, energy-saving regulation is performed, and if the role is low, variable frequency control is performed to meet the control requirements; collect temperature floating speed deviation information and temperature floating control area information, and perform temperature detection analysis and control based on information analysis;

[0009] The frequency conversion adjustment adaptation analysis unit is used to divide the frequency conversion adjustment of the central air conditioner into active frequency conversion and passive frequency conversion, collect active control data and passive control data, and infer whether the energy-saving analysis is normal based on data analysis. If yes, proceed to the next step, otherwise, perform adaptive adjustment;

[0010] The real-time operation analysis unit is used to collect real-time operation parameters and substitute them into the formula to obtain the real-time operation analysis coefficient. According to the coefficient comparison, it is inferred whether the operation analysis is qualified. If yes, it will proceed to the next step, otherwise, it will be regulated;

[0011] The load forecasting control and analysis unit is used to collect demand frequency data and reference demand data, make load forecasts based on the data ratio, and perform energy supply regulation.

[0012] As a preferred embodiment of the present invention, the role of the air supply point is inferred as follows:

[0013] Obtain the deviation between the mean temperature of each sub-position in the control area and the control temperature;

[0014] Obtain the regional concentration density of the non-controlled temperature in each sub-position in the current main flow route;

[0015] If the deviation value between the mean temperature and the control temperature is not within the temperature deviation threshold range, or the regional concentration density of the non-controlled temperature is not within the regional density threshold range, it is inferred that the air supply points in the control area are of low effect; if the deviation value between the mean temperature and the control temperature is within the temperature deviation threshold range, and the regional concentration density of the non-controlled temperature is within the regional density threshold range, it is inferred that the air supply points in the control area are of high effect.

[0016] As a preferred embodiment of the present invention, the temperature floating speed deviation information and the temperature floating control area information are respectively the temperature floating speed deviation of the two corresponding sub-positions of the mainstream passage route far away from the air supply point and the sub-positions close to the air supply point in the control area when the central air-conditioning is running, and the ratio of the number of sub-positions in the mainstream passage route where the temperature floating speed is satisfied and the number of sub-positions far away from the air supply point where the temperature floating speed is not satisfied.

[0017] As a preferred embodiment of the present invention, if the temperature floating speed deviation information exceeds the floating speed deviation threshold, or the corresponding quantity ratio of the number of sub-positions that the temperature floating control area information does not meet does not exceed the quantity ratio threshold, a temperature detection control signal is generated and sent to the energy-saving control platform; if the temperature floating speed deviation information does not exceed the floating speed deviation threshold, and the corresponding quantity ratio of the number of sub-positions that the temperature floating control area information does not meet exceeds the quantity ratio threshold, a fixed angle signal is generated and sent to the energy-saving control platform.

[0018] As a preferred embodiment of the present invention, the active control data and the passive control data are respectively the reciprocating floating span of the deviation time between the moment when the ambient temperature is not in the control temperature range and the moment when the frequency conversion is executed during active frequency conversion, and the numerical ratio of the corresponding spans of the rising span of the ambient temperature control amount in the control area and the falling span of the temperature deviation of each sub-position in the control area during passive frequency conversion.

[0019] As a preferred embodiment of the present invention, if the active control data exceeds the time length reciprocating floating span threshold, or the passive control data exceeds the span value ratio threshold, it is inferred that the variable frequency control energy-saving analysis is abnormal; if the active control data does not exceed the time length reciprocating floating span threshold, and the passive control data does not exceed the span value ratio threshold, it is inferred that the variable frequency control energy-saving analysis is normal.

[0020] As a preferred embodiment of the present invention, the real-time operating parameters collected include the deviation time between the operating time period controlled by the start-stop timing device in the central air conditioner and the corresponding time period of the control area occupancy period, the corresponding span parameter ratio of the floating span of the increase in compressor power consumption in the central air conditioner and the pressure floating value decrease span of the refrigerant not within the pressure deviation range, and the rising span of the growth rate of the number of dust particles in the current control area during the stage when the ambient temperature in the control area of ​​the central air conditioner is controlled to the set temperature.

[0021] As a preferred embodiment of the present invention, if the real-time operation analysis coefficient of the central air-conditioning operation stage exceeds the real-time operation analysis coefficient threshold, an abnormal operation signal is generated; if the real-time operation analysis coefficient of the central air-conditioning operation stage does not exceed the real-time operation analysis coefficient threshold, a normal operation signal is generated.

[0022] As a preferred embodiment of the present invention, the demand frequency data and the reference demand data are respectively the frequency numerical ratio of the reciprocating floating frequency of the ambient temperature in the control area to the interval value of the ambient temperature from the set temperature range, and the maximum floating span of the energy consumption demand of the buildings covered by the power grid in the control area at the same stage in the history when the demand frequency data of the control area increases.

[0023] As a preferred embodiment of the present invention, if the demand frequency data exceeds the frequency value ratio threshold, and the reference demand data exceeds the maximum floating span value, then the load forecast peak trend is inferred; if the demand frequency data does not exceed the frequency value ratio threshold, or the reference demand data does not exceed the maximum floating span value, then the load forecast flat trend is inferred.

[0024] A central air-conditioning energy-saving control method based on artificial intelligence, the specific control method process is as follows:

[0025] Regional temperature detection analysis, marking the central air-conditioning coverage area as the control area, obtaining the main flow route and secondary flow route of the control area, and determining the air supply point;

[0026] Taking the air supply point as the starting point and the main flow route as the trajectory, the main flow route is divided into several sub-positions. The role of the air supply point is inferred according to the sub-position. If the role is high, energy-saving regulation is performed, and if the role is low, frequency conversion control is performed to meet the control requirements.

[0027] Collect temperature floating speed deviation information and temperature floating control area information, and perform temperature detection analysis and control based on information analysis;

[0028] Frequency conversion adjustment adaptation analysis, divide the frequency conversion adjustment of central air conditioners into active frequency conversion and passive frequency conversion, collect active control data and passive control data, and infer whether the energy-saving analysis is normal based on data analysis. If yes, proceed to the next step, otherwise, perform adaptive control;

[0029] Real-time operation analysis, collection of real-time operation parameters, and substitution into the formula to obtain the real-time operation analysis coefficient. Based on the coefficient comparison, it is inferred whether the operation analysis is qualified. If yes, proceed to the next step, otherwise, conduct regulation;

[0030] Load forecasting control analyzes and collects demand frequency data and reference demand data, and makes load forecasts and performs energy supply regulation based on data ratios.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. In the present invention, a regional temperature detection evaluation is performed on the operating coverage area of ​​the central air conditioner to infer whether the real-time regional temperature detection during the operation stage of the central air conditioner meets the demand, so as to avoid the inability to accurately detect the regional temperature demand during the operation of the central air conditioner, which easily causes the control temperature to be too low or the ambient temperature to be too high. At the same time, the central air conditioner can also be controlled in real time according to the temperature detection performance evaluation and regulation, so as to accurately control the energy consumption while meeting the air conditioner operation demand and avoid unnecessary additional energy consumption;

[0033] Adaptation analysis is performed on the frequency conversion regulation of the central air conditioner. Through the frequency conversion regulation adaptation analysis, it is inferred whether the current operating efficiency of the central air conditioner meets the control area requirements, and the efficiency detection accuracy of the central air conditioner is improved, so that energy-saving control can be reasonably performed when the efficiency detection is accurate. It can also ensure the current operation is reasonable according to the frequency conversion regulation, avoid frequency conversion regulation caused by unreasonable air supply, and generate unnecessary energy consumption, thereby indirectly playing a role in energy saving and improving the user's quality of use.

[0034] 2. In the present invention, the central air conditioner is analyzed in real time. The current operating efficiency of the central air conditioner is inferred based on the real-time operating analysis of the internal components of the central air conditioner. At the same time, it is inferred whether the current energy-saving control meets the actual needs, ensuring that there is no waste of energy consumption during operation, playing the role of energy-saving control, and improving the cost-effectiveness of the central air conditioner.

[0035] Carry out load forecasting control on the central air-conditioning. By combining the energy consumption of the central air-conditioning with the current power grid energy consumption, the load is forecasted for timely regulation to avoid excessive peak load on the power grid causing increased energy consumption. Overall regulation and load forecasting can effectively carry out energy-saving control. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0037] Figure 1 This is a principle block diagram of Embodiment 1 of the present invention;

[0038] Figure 2 This is a principle block diagram of the second embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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.

[0040] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0041] Embodiment 1

[0042] See also Figure 1 As shown, an energy-saving control system for central air conditioners based on artificial intelligence includes an energy-saving control platform, wherein the energy-saving control platform is communicatively connected with a regional temperature detection analysis unit, a frequency conversion adjustment adaptation analysis unit, and a real-time operation analysis unit;

[0043] The energy-saving control platform generates a regional temperature detection analysis signal and sends the regional temperature detection analysis signal to the regional temperature detection analysis unit. After receiving the regional temperature detection analysis signal, the regional temperature detection analysis unit conducts a regional temperature detection evaluation on the operating coverage area of ​​the central air conditioner, and infers whether the real-time regional temperature detection during the central air conditioner operation stage meets the demand, so as to avoid the inability to accurately detect the regional temperature demand during the operation of the central air conditioner, which may easily cause the control temperature to be too low or the ambient temperature to be too high. At the same time, according to the temperature detection performance evaluation and regulation, the central air conditioner can also perform real-time energy consumption control, accurately control energy consumption while meeting the air conditioner operation demand, and avoid unnecessary additional energy consumption;

[0044] The area covered by the central air conditioner is marked as the control area, and the spatial structure of the control area is analyzed. The inlet and outlet areas of the control area are obtained according to the inlet and outlet areas of the control area, and the air circulation routes are obtained according to the locations of the inlet and outlet areas. The main circulation routes and secondary circulation routes are obtained according to the spatial volumes corresponding to each air circulation route. In actual scenarios, the air circulation routes generated by large vents will reduce the effect of the air conditioning circulation routes of small outlets, and this application is also based on the main circulation routes.

[0045] Determine the central air conditioning position in the control area and set it as the air supply point; in the central air conditioning operation stage, take the air supply point as the starting point and the main flow route as the trajectory, divide the main flow route into several sub-positions, obtain the deviation value of the temperature mean and the control temperature of each sub-position in the control area, and obtain the regional concentration density of the non-controlled temperature in each sub-position in the current main flow route, and compare the deviation value of the temperature mean and the control temperature of each sub-position in the control area and the regional concentration density of the non-controlled temperature in each sub-position in the current main flow route with the temperature deviation threshold range and the regional density threshold range respectively:

[0046] If the deviation between the temperature mean of each sub-position in the control area and the control temperature is not within the temperature deviation threshold range, or the regional concentration density of the non-controlled temperature in each sub-position in the current mainstream flow route is not within the regional density threshold range, it is inferred that the air supply point in the control area has low function, and a low function signal is generated and sent to the energy-saving control platform. After receiving the low function signal, the energy-saving control platform performs frequency conversion control to quickly meet the temperature requirements of the control area;

[0047] If the deviation between the temperature mean of each sub-position in the control area and the control temperature is within the temperature deviation threshold range, and the regional concentration density of the non-controlled temperature in each sub-position in the current mainstream flow route is within the regional density threshold range, it is inferred that the air supply point in the control area has a high effect, and a high effect signal is generated and sent to the energy-saving control platform. After receiving the high effect signal, the energy-saving control platform performs frequency conversion control without affecting the temperature demand of the control area and reduces the power at the same time;

[0048] The temperature floating speed deviation of the two corresponding terminals of the mainstream passage route far from the air supply point and close to the air supply point in the control area when the central air conditioner is running is obtained, and at the same time, the corresponding number ratio of the number of sub-positions in the mainstream passage route close to the air supply point that meet the temperature floating speed and the number of sub-positions far from the air supply point that do not meet the temperature floating speed is obtained. The temperature floating speed deviation of the two corresponding terminals of the mainstream passage route far from the air supply point and close to the air supply point in the control area when the central air conditioner is running, and the corresponding number ratio of the number of sub-positions in the mainstream passage route close to the air supply point that meet the temperature floating speed and the number of sub-positions far from the air supply point that do not meet the temperature floating speed are marked as temperature floating speed deviation information and temperature floating control area information, and are compared with the floating speed deviation threshold and the number ratio threshold respectively:

[0049] If the temperature floating speed deviation of the two corresponding sub-positions of the mainstream passage line far from the air supply point and the two corresponding sub-positions close to the air supply point in the control area during the operation of the central air conditioner exceeds the floating speed deviation threshold, or the number of sub-positions in the mainstream passage line that meet the temperature floating speed requirement and the number of sub-positions far from the air supply point that do not meet the temperature floating speed requirement does not exceed the number ratio threshold, a temperature detection control signal is generated and sent to the energy-saving control platform. The energy-saving control platform adjusts the air supply angle of the air supply point according to the current power, and sets the duration of the air supply angle according to the temperature control of the sub-positions of the real-time mainstream passage line. Combined with the ambient temperature fluctuation span in the control area, the air supply angle is controlled to change back and forth so as to control the overall temperature of the control area, ensure power stability to save energy, and avoid inaccurate temperature detection and blindly lowering the temperature, resulting in excessive temperature control in some areas.

[0050] If the temperature floating speed deviation of the two corresponding sub-positions of the mainstream passage route far from the air supply point and the two corresponding sub-positions close to the air supply point in the control area during the operation of the central air conditioner does not exceed the floating speed deviation threshold, and the number of sub-positions in the mainstream passage route that meet the temperature floating speed requirement close to the air supply point and the number of sub-positions far from the air supply point that do not meet the temperature floating speed requirement exceed the number ratio threshold, a fixed angle signal is generated and sent to the energy-saving control platform. After receiving the signal, the energy-saving control platform keeps the current air conditioning power and air supply angle constant, and after generating the temperature detection control signal, the air supply angle begins to float;

[0051] After completing the regional temperature detection analysis, a variable frequency adjustment adaptation analysis signal is generated and sent to the variable frequency adjustment adaptation analysis unit. After receiving the variable frequency adjustment adaptation analysis signal, the variable frequency adjustment adaptation analysis unit performs adaptation analysis on the central air-conditioning variable frequency adjustment. Through the variable frequency adjustment adaptation analysis, it is inferred whether the current central air-conditioning operation efficiency meets the control area requirements, and the efficiency detection accuracy of the central air-conditioning is improved, so that energy-saving control can be reasonably performed when the efficiency detection is accurate. It can also ensure the current operation is reasonable according to the variable frequency adjustment, avoid the variable frequency control caused by unreasonable air supply, and generate unnecessary energy consumption, thereby playing an energy-saving role and improving the user's use quality at the same time;

[0052] The frequency conversion regulation of the central air conditioner in the control area is divided into active frequency conversion and passive frequency conversion. Active frequency conversion means that when the central air conditioner is running, it is detected that the temperature control efficiency is insufficient or sufficient, and frequency conversion control is performed to ensure that the control demand is met. Passive frequency conversion means that when the central air conditioner is running, it is detected that the temperature control efficiency is abnormal and the frequency conversion or frequency conversion control effect is small, and the user performs frequency conversion control by means of temperature adjustment or air volume adjustment.

[0053] During the operation stage of the central air conditioner, the deviation time reciprocating floating span between the moment when the ambient temperature is not in the control temperature range and the moment when the frequency conversion is executed is obtained when the frequency conversion is active, and the span value ratio of the rising span of the ambient temperature control amount in the control area and the temperature deviation falling span of each sub-position in the control area is obtained when the frequency conversion is passive. The deviation time reciprocating floating span between the moment when the ambient temperature is not in the control temperature range and the moment when the frequency conversion is executed, and the span value ratio of the rising span of the ambient temperature control amount in the control area and the temperature deviation falling span of each sub-position in the control area when the frequency conversion is active are marked as active control data and passive control data, respectively, and compared with the time reciprocating floating span threshold and the span value ratio threshold, respectively:

[0054] If the deviation time reciprocating floating span between the time when the ambient temperature is not in the control temperature range and the time when the frequency conversion is executed during active frequency conversion exceeds the time reciprocating floating span threshold, or the span value ratio of the rising span of the ambient temperature control amount in the control area and the falling span of the temperature deviation of each sub-position in the control area during passive frequency conversion exceeds the span value ratio threshold, it is inferred that the energy-saving analysis of the frequency conversion control is abnormal, and an adaptation inefficiency signal is generated and sent to the energy-saving control platform. After receiving the adaptation inefficiency signal, the energy-saving control platform controls the frequency conversion adjustment of the central air conditioner, identifies and timely adjusts the active frequency conversion adjustment, shortens the identification time, and performs temperature detection intervention on the passive frequency conversion adjustment to avoid excessive adjustment;

[0055] If the deviation time reciprocating floating span between the moment when the ambient temperature is not in the control temperature range and the moment when the frequency conversion is executed during active frequency conversion does not exceed the time reciprocating floating span threshold, and the span value ratio of the rising span of the ambient temperature control amount in the control area and the falling span of the temperature deviation of each sub-position in the control area during passive frequency conversion does not exceed the span value ratio threshold, it is inferred that the energy-saving analysis of the frequency conversion control is normal, and an adaptation high-efficiency signal is generated and sent to the energy-saving control platform;

[0056] Then, a real-time operation analysis signal is generated and sent to the real-time operation analysis unit. After receiving the real-time operation analysis signal, the real-time operation analysis unit performs real-time operation analysis on the central air conditioner. According to the real-time operation analysis of the internal components of the central air conditioner, it is inferred whether the current operation efficiency of the central air conditioner is qualified. At the same time, it is inferred whether the current operation energy-saving control meets the actual needs, ensuring that there is no waste of energy consumption during the operation process, playing the role of energy-saving control, and also improving the cost-effectiveness of the central air conditioner.

[0057] Obtain the deviation time between the operation time period controlled by the start-stop timing device in the central air conditioner and the corresponding time period of the control area occupancy period, and mark the deviation time between the operation time period controlled by the start-stop timing device in the central air conditioner and the corresponding time period of the control area occupancy period as WPs;

[0058] At the same time, the corresponding span parameter ratio of the floating span of the power consumption increase of the compressor in the central air conditioner to the pressure floating value decrease span when the refrigerant is not within the pressure deviation range is obtained, and the corresponding span parameter ratio of the floating span of the power consumption increase of the compressor in the central air conditioner to the pressure floating value decrease span when the refrigerant is not within the pressure deviation range is marked as KDc;

[0059] Obtain the rising span of the growth rate of the number of dust particles in the current control area during the stage when the ambient temperature in the control area of ​​the central air conditioner is controlled to the set temperature, and mark the rising span of the growth rate of the number of dust particles in the current control area during the stage when the ambient temperature in the control area of ​​the central air conditioner is controlled to the set temperature as SDk;

[0060] The above collected information is uniformly marked as real-time operation parameters, and substituted into the formula to obtain the real-time operation analysis coefficient of the central air-conditioning operation stage, where the formula is: Among them, YX is the real-time operation analysis coefficient, mh1, mh2 and mh3 are preset proportional coefficients, e is a natural constant, and β is an error correction factor with a value of 1.16;

[0061] Compare the real-time operation analysis coefficient of the central air conditioning operation stage with the real-time operation analysis coefficient threshold:

[0062] If the real-time operation analysis coefficient of the central air-conditioning operation stage exceeds the real-time operation analysis coefficient threshold, it is inferred that the operation analysis of the current central air-conditioning operation stage is unqualified, and an operation abnormality signal is generated and sent to the energy-saving control platform. After receiving the operation abnormality signal, the energy-saving control platform suspends the current variable frequency control and performs self-inspection and maintenance on the internal components. After the maintenance is completed, control is performed according to the real-time control task. If the control task still cannot be completed, the variable frequency control is executed. At this time, the energy consumption continues to rise and the control efficiency is low, and an early warning is issued;

[0063] If the real-time operation analysis coefficient of the central air-conditioning operation stage does not exceed the real-time operation analysis coefficient threshold, it is inferred that the operation analysis of the current central air-conditioning operation stage is qualified, and a normal operation signal is generated and sent to the energy-saving control platform;

[0064] Embodiment 2

[0065] See also Figure 2 As shown, the system is equipped with a load prediction control and analysis unit. During the operation of the central air conditioner, the energy-saving control platform generates a load prediction control and analysis signal and sends the load prediction control and analysis signal to the load prediction control and analysis unit. After receiving the load prediction control and analysis signal, the load prediction control and analysis unit performs load prediction control on the central air conditioner. By combining and analyzing the energy consumption of the central air conditioner with the current power grid energy consumption, the load is predicted for timely regulation to avoid excessive peak load of the power grid causing increased energy consumption. Overall regulation and load prediction can effectively perform energy-saving control.

[0066] Obtain the frequency value ratio of the reciprocating floating frequency of the ambient temperature in the control area to the frequency corresponding to the shortened interval value of the ambient temperature from the set temperature range, and mark the frequency value ratio of the reciprocating floating frequency of the ambient temperature in the control area to the frequency corresponding to the shortened interval value of the ambient temperature from the set temperature range as the required frequency data;

[0067] Obtain the maximum floating span of energy consumption demand of buildings covered by the power grid in the control area at the same historical stage when the demand frequency data of the control area increases, and mark the maximum floating span of energy consumption demand of buildings covered by the power grid in the control area at the same historical stage when the demand frequency data of the control area increases as reference demand data;

[0068] The demand frequency data and reference demand data are compared with the frequency value ratio threshold and the maximum floating span value respectively:

[0069] If the demand frequency data exceeds the frequency value ratio threshold, and the reference demand data exceeds the maximum floating span value, the load forecast peak trend is inferred, where the peak trend is represented by the peak shape of the load waveform, and the current central air-conditioning is controlled to shift the peak, reduce the control time or control power of the central air-conditioning, and facilitate the peak energy use with the power grid. Similarly, when other power-consuming ends of the power grid are suitable for peak shifting, the central air-conditioning performs the control task, where the control time and control power are the time to reduce the control temperature to offset the time for other power-consuming ends of the power grid, and the control power is controlled to reduce the speed to ensure that all power-consuming ends of the power grid can start running but will not be at peak power operation. According to different power demands, the number of power-consuming ends decreases, and the power is slowly adjusted;

[0070] If the demand frequency data does not exceed the frequency value ratio threshold, or the reference demand data does not exceed the maximum floating span value, it is inferred that the load forecast is flat and the energy supply to the power consumption end is carried out normally;

[0071] A central air-conditioning energy-saving control method based on artificial intelligence, the specific control method process is as follows:

[0072] Regional temperature detection analysis, marking the central air-conditioning coverage area as the control area, obtaining the main flow route and secondary flow route of the control area, and determining the air supply point;

[0073] Taking the air supply point as the starting point and the main flow route as the trajectory, the main flow route is divided into several sub-positions. The role of the air supply point is inferred according to the sub-position. If the role is high, energy-saving regulation is performed, and if the role is low, frequency conversion control is performed to meet the control requirements.

[0074] Collect temperature floating speed deviation information and temperature floating control area information, and perform temperature detection analysis and control based on information analysis;

[0075] Frequency conversion adjustment adaptation analysis, divide the frequency conversion adjustment of central air conditioners into active frequency conversion and passive frequency conversion, collect active control data and passive control data, and infer whether the energy-saving analysis is normal based on data analysis. If yes, proceed to the next step, otherwise, perform adaptive control;

[0076] Real-time operation analysis, collection of real-time operation parameters, and substitution into the formula to obtain the real-time operation analysis coefficient. Based on the coefficient comparison, it is inferred whether the operation analysis is qualified. If yes, proceed to the next step, otherwise, conduct regulation;

[0077] Load forecasting control analyzes and collects demand frequency data and reference demand data, and makes load forecasts and performs energy supply regulation based on data ratios.

[0078] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technicians in this field according to actual conditions;

[0079] When the present invention is in use, the regional temperature detection and analysis unit marks the central air-conditioning coverage area as the control area, obtains the mainstream circulation route and the secondary circulation route of the control area, and determines the air supply point; takes the air supply point as the starting point and the mainstream circulation route as the trajectory, divides the mainstream circulation route into a number of sub-positions, and infers the effect of the air supply point according to the sub-position. If the effect is high, energy-saving regulation is performed, and if the effect is low, frequency conversion control is performed to meet the control requirements; collects temperature floating speed deviation information and temperature floating control area information, and performs temperature detection analysis and control according to information analysis; the frequency conversion adjustment adaptation analysis unit divides the frequency conversion adjustment of the central air-conditioning into active frequency conversion and passive frequency conversion, collects active control data and passive control data, and infers whether the energy-saving analysis is normal according to data analysis. If yes, proceed to the next step, otherwise, adaptive regulation is performed; the real-time operation analysis unit collects real-time operation parameters, and substitutes them into the formula to obtain the real-time operation analysis coefficient, and infers whether the operation analysis is qualified according to the coefficient comparison. If yes, proceed to the next step, otherwise, regulation is performed; the load prediction control analysis unit collects demand frequency data and reference demand data, performs load prediction according to the data ratio, and performs energy supply regulation.

[0080] 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 content 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 those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A central air-conditioning energy-saving control system based on artificial intelligence, characterized in that: Including energy-saving control platform, the energy-saving control platform communication connections are: The regional temperature detection and analysis unit is used to mark the central air-conditioning coverage area as the control area, obtain the main flow route and the secondary flow route of the control area, and determine the air supply point; taking the air supply point as the starting point and the main flow route as the trajectory, the main flow route is divided into several sub-positions, and the role of the air supply point is inferred according to the sub-position. If the role is high, energy-saving regulation is performed, and if the role is low, frequency conversion control is performed to meet the control requirements; Collect temperature floating speed deviation information and temperature floating control area information, and perform temperature detection analysis and control based on information analysis; The frequency conversion adjustment adaptation analysis unit is used to divide the frequency conversion adjustment of the central air conditioner into active frequency conversion and passive frequency conversion, collect active control data and passive control data, and infer whether the energy-saving analysis is normal based on data analysis. If yes, proceed to the next step, otherwise, perform adaptive adjustment; The real-time operation analysis unit is used to collect real-time operation parameters and substitute them into the formula to obtain the real-time operation analysis coefficient. According to the coefficient comparison, it is inferred whether the operation analysis is qualified. If yes, it will proceed to the next step, otherwise, it will be regulated; The load forecasting control and analysis unit is used to collect demand frequency data and reference demand data, make load forecasts based on the data ratio, and perform energy supply regulation.

2. According to claim 1, a central air-conditioning energy-saving control system based on artificial intelligence is characterized in that: Inference of the role of air supply points: Obtain the deviation between the mean temperature of each sub-position in the control area and the control temperature; Obtain the regional concentration density of the non-controlled temperature in each sub-position in the current main flow path; If the deviation value between the mean temperature and the control temperature is not within the temperature deviation threshold range, or the regional concentration density of the non-controlled temperature is not within the regional density threshold range, it is inferred that the air supply points in the control area are of low effect; if the deviation value between the mean temperature and the control temperature is within the temperature deviation threshold range, and the regional concentration density of the non-controlled temperature is within the regional density threshold range, it is inferred that the air supply points in the control area are of high effect.

3. The central air-conditioning energy-saving control system based on artificial intelligence according to claim 2 is characterized in that: The temperature floating speed deviation information and the temperature floating control area information are respectively the temperature floating speed deviation of the two corresponding sub-positions of the mainstream route far away from the air supply point and the sub-positions close to the air supply point in the control area when the central air-conditioning is running, and the ratio of the number of sub-positions in the mainstream route close to the air supply point that meet the temperature floating speed to the number of sub-positions far away from the air supply point that do not meet the temperature floating speed.

4. The central air-conditioning energy-saving control system based on artificial intelligence according to claim 3 is characterized in that: If the temperature floating speed deviation information exceeds the floating speed deviation threshold, or the corresponding quantity ratio of the number of sub-positions that the temperature floating control area information does not meet does not exceed the quantity ratio threshold, a temperature detection control signal is generated and sent to the energy-saving control platform; If the temperature floating speed deviation information does not exceed the floating speed deviation threshold, and the corresponding quantity ratio of the number of sub-positions that the temperature floating control area information does not meet exceeds the quantity ratio threshold, a fixed angle signal is generated and sent to the energy-saving control platform.

5. The central air-conditioning energy-saving control system based on artificial intelligence according to claim 1 is characterized in that: The active control data and passive control data are respectively the reciprocating floating span of the deviation time between the moment when the ambient temperature is not in the control temperature range and the moment when the frequency conversion is executed during active frequency conversion, and the numerical ratio of the rising span of the ambient temperature control amount in the control area during passive frequency conversion to the falling span of the temperature deviation of each sub-position in the control area.

6. The central air-conditioning energy-saving control system based on artificial intelligence according to claim 5 is characterized in that: If the active control data exceeds the time-length reciprocating floating span threshold, or the passive control data exceeds the span value ratio threshold, it is inferred that the variable frequency control energy saving analysis is abnormal; If the active control data does not exceed the duration reciprocating floating span threshold, and the passive control data does not exceed the span value ratio threshold, it is inferred that the variable frequency control energy saving analysis is normal.

7. The central air-conditioning energy-saving control system based on artificial intelligence according to claim 1 is characterized in that: The real-time operating parameters collected include the deviation duration between the operating time period controlled by the start-stop timing device in the central air conditioner and the corresponding time period of occupancy of the control area, the corresponding span parameter ratio of the floating span of the power consumption growth of the compressor in the central air conditioner and the pressure floating value decrease span of the refrigerant that is not within the pressure deviation range, and the rising span of the growth rate of the number of dust particles in the current control area when the ambient temperature in the control area of ​​the central air conditioner is controlled to the set temperature.

8. The central air-conditioning energy-saving control system based on artificial intelligence according to claim 7 is characterized in that: If the real-time operation analysis coefficient during the central air-conditioning operation stage exceeds the real-time operation analysis coefficient threshold, an abnormal operation signal is generated; if the real-time operation analysis coefficient during the central air-conditioning operation stage does not exceed the real-time operation analysis coefficient threshold, a normal operation signal is generated.

9. The central air-conditioning energy-saving control system based on artificial intelligence according to claim 1 is characterized in that: The demand frequency data and the reference demand data are respectively the frequency value ratio of the reciprocating floating frequency of the ambient temperature in the control area to the interval value of the ambient temperature from the set temperature range, and the maximum floating span of the energy consumption demand of the buildings covered by the power grid in the control area at the same stage of history when the demand frequency data of the control area increases; If the demand frequency data exceeds the frequency value ratio threshold, and the reference demand data exceeds the maximum floating span value, the load forecast current peak trend is inferred; If the demand frequency data does not exceed the frequency value ratio threshold, or the reference demand data does not exceed the maximum floating span value, a flat trend in load forecast is inferred.

10. A central air conditioning energy-saving control method based on artificial intelligence, characterized in that: An artificial intelligence-based central air-conditioning energy-saving control system as described in any one of claims 1 to 9 above.

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