Refrigerating machine room health prediction diagnosis and control system and method based on intelligent electric meter data analysis

Abstract

The invention provides a refrigerating machine room health prediction diagnosis and control system and method based on intelligent electric meter data analysis. The system comprises a plurality of control devices; the intelligent electric meters are configured in one-to-one correspondence with the control devices so as to monitor power utilization data of the devices in real time, and each control device and the matched intelligent electric meter form a control loop; the power utilization data at least comprise three-phase voltage, three-phase current and three-phase power; and the control system is connected with each control loop and is used for performing early warning analysis according to monitoring data of the intelligent electric meters in the control loops and performing state adjustment on the control loops based on an early warning analysis result. Real-time comparative analysis is carried out by combining rated working condition data of equipment, abnormal operation of the system is found in time, corresponding faults are automatically controlled and processed, and stable operation of the system is guaranteed. And meanwhile, an electric energy use strategy can be optimized, and by identifying high-energy-consumption equipment or time periods, measures are taken in a targeted manner to reduce energy consumption and optimize and adjust the operation condition of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of HVAC automatic control, and in particular to a refrigeration room health prediction diagnosis and control system and method based on smart meter data analysis. Background Art

[0002] With the increasing requirements for indoor environment and comfort, as well as the popularization of energy conservation, emission reduction and green environmental protection concepts, automatic control technology is used to achieve precise adjustment of HVAC systems. Without direct human involvement, the control system can automatically judge and make decisions based on the real-time collected state quantities, so that the HVAC system can operate in a predetermined manner or the controlled parameters can be maintained at the specified values, ensuring the reasonable operation of the system, which can not only meet people's needs for a comfortable environment, but also achieve the purpose of energy saving.

[0003] Various sensors (such as temperature sensors, humidity sensors, pressure or differential pressure sensors, flow sensors, etc.) are used to collect parameters such as air temperature, air humidity, water flow, air supply speed, differential pressure, etc. of buildings and places, and transmit them to the controller for analysis and processing. The controller controls the terminal equipment (such as air valves, water valves, inverters, etc.) according to the built-in program and the set control strategy.

[0004] In the intelligent HVAC control system, based on the IoT cloud platform, the heating, ventilation, air conditioning and other systems are connected in series with the management cloud platform through hardware devices such as intelligent air conditioning controllers, infrared remote controllers, sensors, controllers, and intelligent gateways. The sensors collect environmental data online and transmit it to the management platform. The cloud platform automatically controls fans, water pumps, valves and other equipment according to the preset control logic, adjusts the operating status of heating, ventilation and air conditioning equipment, and realizes precise control of indoor environment conditions such as temperature, humidity, oxygen content, etc.

[0005] At present, a large number of HVAC systems have gradually replaced traditional meters with smart meters. On the basis of data collection, they can also be combined with PLC control systems and smart meters. Through certain data collection and analysis, some alarms and corresponding controls can be given to the operating status of the system equipment, so that the system can operate more safely, more reasonably and more effectively. Summary of the invention

[0006] The purpose of the present invention is to provide a refrigeration room health prediction diagnosis and control system and method based on smart meter data analysis, configure corresponding smart meters for control equipment, read the data of the smart meters, and conduct real-time comparative analysis in combination with the rated operating data of the equipment, which is conducive to timely discovering abnormal conditions of the system operation circuit, such as overload, short circuit, overcurrent, phase loss, etc., and providing real-time alarm and warning information.

[0007] Another object of the present invention is to automatically control and process corresponding fault information based on the abnormal conditions of the system operation circuit determined by analysis, which is conducive to the stable operation of the system.

[0008] According to a first aspect of the present invention, a refrigeration room health prediction diagnosis and control system based on smart meter data analysis is proposed, comprising:

[0009] Multiple control devices;

[0010] A smart meter configured in one-to-one correspondence with each control device is used to monitor and record the power consumption data of the control device in real time. Each control device and its matching smart meter constitute a control loop; the power consumption data includes at least three-phase voltage, three-phase current and three-phase power;

[0011] The control system is connected to each control loop and is used to perform early warning analysis based on the monitoring data of the smart meter in the control loop, and to perform state adjustment on the control loop based on the early warning analysis result.

[0012] As an optional embodiment, the control system is configured with a data acquisition subroutine, a data analysis subroutine and an execution control subroutine:

[0013] The data acquisition subroutine acquires the power consumption data of each control loop when being executed;

[0014] When the data analysis subroutine is executed, it analyzes and judges the acquired power consumption data in a preset manner and outputs the judgment result;

[0015] The execution control subroutine, when being run, executes a predetermined control strategy for controlling and adjusting a control loop according to the judgment result.

[0016] According to a second aspect of the present invention, a refrigeration room health prediction diagnosis and control method is provided, comprising the following steps:

[0017] Establishing a communication connection between the smart meter in each control loop of the HVAC system and the control system through the MODBUS RTU protocol, wherein the control loop is composed of a control device of the HVAC system and its supporting smart meter; the control device includes at least one of an air handling unit, a cooling tower, a water pump, a chiller, a humidifier, and a surface cooler;

[0018] The control system reads the power consumption data collected by the smart meter in each control loop in real time, including three-phase voltage, three-phase current and three-phase power;

[0019] According to the power consumption data in each control loop, it is judged that the smart meter is abnormal or the loop is abnormal, and an alarm signal is output;

[0020] Execute the predetermined control strategy according to the abnormality type and adjust the state of the control loop.

[0021] Compared with the prior art, the automatic warning and control system and method of the HVAC system of the present invention have the following significant advantages:

[0022] The present invention acquires the power consumption data collected by the smart meter in real time through the PLC control system, and performs real-time comparative analysis in combination with the rated operating data of the equipment, which is conducive to timely discovering abnormal conditions in the system operation circuit, such as overload, short circuit, overcurrent, lack of phase, etc., providing real-time alarm and warning information, and adjusting and processing the corresponding fault information through PLC control, which is conducive to the stable operation of the system.

[0023] At the same time, through the data analysis provided by smart meters, users can better understand the power usage patterns of each circuit, optimize power usage strategies, and take targeted measures to reduce energy consumption and optimize system operating conditions by identifying high-energy consumption equipment or time periods.

[0024] It should be understood that all combinations of the aforementioned concepts and the additional concepts described in more detail below can be considered as part of the inventive subject matter of the present disclosure as long as such concepts are not mutually inconsistent. In addition, all combinations of the claimed subject matter are considered as part of the inventive subject matter of the present disclosure.

[0025] The foregoing and other aspects, embodiments and features of the present invention can be more fully understood from the following description in conjunction with the accompanying drawings. Other additional aspects of the present invention, such as the features and / or beneficial effects of the exemplary embodiments, will be apparent from the following description or learned from the practice of the specific embodiments according to the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings are not intended to be drawn to scale. In the accompanying drawings, each identical or nearly identical component shown in each figure may be represented by the same reference numeral. For clarity, not every component is labeled in each figure. Embodiments of various aspects of the present invention will now be described by way of example and with reference to the accompanying drawings.

[0027] Figure 1 It is a system diagram of a refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to an embodiment of the present invention.

[0028] Figure 2 4 is a schematic diagram of a smart meter data communication network according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to better understand the technical content of the present invention, specific embodiments are given and described as follows in conjunction with the accompanying drawings.

[0030] Various aspects of the present invention are described in this disclosure with reference to the accompanying drawings, in which many illustrative embodiments are shown. The embodiments of the present disclosure are not necessarily intended to include all aspects of the present invention. It should be understood that the various concepts and embodiments introduced above, as well as those described in more detail below, can be implemented in any of many ways, because the concepts and embodiments disclosed by the present invention are not limited to any implementation. In addition, some aspects disclosed by the present invention can be used alone or in any appropriate combination with other aspects disclosed by the present invention.

[0031] {Example 1}

[0032] Combination Figure 1 , 2 In the example shown, the refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to this embodiment includes:

[0033] Multiple control devices, such as the illustrated HVAC system unit and multiple devices;

[0034] A smart meter configured in one-to-one correspondence with each control device is used to monitor and record the power consumption data of the control device in real time. Each control device and its matching smart meter constitute a control loop; the power consumption data includes at least three-phase voltage, three-phase current and three-phase power;

[0035] The control system is connected to each control loop and is used to perform early warning analysis based on the monitoring data of the smart meter in the control loop, and to perform state adjustment on the control loop based on the early warning analysis result.

[0036] like Figure 2 As shown, as an example, the control system can adopt a PLC-based industrial control system and communicate with the smart meter in the control loop based on the MODBUS RTU protocol to realize the collection of user data.

[0037] As an optional embodiment, the control system is configured with a data acquisition subroutine, a data analysis subroutine and an execution control subroutine.

[0038] The data acquisition subroutine acquires the power consumption data of each control loop when being executed.

[0039] When the data analysis subroutine is executed, it analyzes and judges the acquired power consumption data in a preset manner and outputs the judgment result.

[0040] The execution control subroutine, when being run, executes a predetermined control strategy for controlling and adjusting a control loop according to the judgment result.

[0041] As an optional embodiment, when the data analysis subroutine is run, based on the three-phase power supply voltage data in each control loop, when there is no data for any phase voltage, a voltage phase loss alarm signal is output; correspondingly, when the execution control subroutine is run, the following control strategy is executed based on the voltage phase loss alarm signal: stop all control devices on the voltage phase loss control loop.

[0042] As an optional embodiment, when the data analysis subroutine is being run, based on the three-phase power supply voltage data in each control loop and the preset voltage allowable range, if the voltage data exceeds the preset voltage allowable range and continues to exceed the preset time range, a voltage over-limit alarm signal is output; correspondingly, when the execution control subroutine is being run, the following control strategy is executed based on the voltage over-limit alarm signal: control devices that have not yet been running on the voltage over-limit control loop are prohibited from starting, and control devices that are already running are controlled to shut down immediately.

[0043] As an example, the voltage data of the three-phase power supply is collected through the smart meter, and the allowable voltage range of the equipment operation is preset according to the manual of the control device. The actual collected voltage value is compared to see whether it is within the allowable voltage range, that is, whether it is lower than the lower limit of the set range, or higher than the upper limit of the set range. If it exceeds the allowable voltage range, it is further determined whether the voltage fluctuation continues to exceed the upper limit for a certain period of time or continues to be lower than the lower limit for a certain period of time (the preset time range can be pre-configured or modified in the control system), and an alarm signal is output. Based on this control, the equipment that has not yet been running is prohibited from starting, and the equipment that is already running is immediately shut down.

[0044] As an optional embodiment, when the data analysis subroutine is run, based on the three-phase power data in each control loop, when any power value is less than 0, it indicates that the voltage phase and current phase of the smart meter installation do not match, and an abnormal power feedback alarm signal is output; correspondingly, when the execution control subroutine is run, the following control strategy is executed according to the abnormal power feedback alarm signal: prompting the operator to check the installation line of the smart meter.

[0045] As an optional embodiment, when the data analysis subroutine is run, it outputs a voltage imbalance exceeding limit alarm signal according to the voltage imbalance degree in each control loop exceeding the first preset threshold range; correspondingly, when the execution control subroutine is run, it executes the following control strategy according to the voltage imbalance exceeding limit alarm signal: shut down the control device in the control loop where the voltage imbalance exceeds the limit.

[0046] As an example, the larger the value of voltage imbalance, the higher the voltage imbalance, which may cause problems such as overheating of power equipment, power loss, unstable motor operation, etc. Therefore, in the power system, it is necessary to monitor and control the voltage imbalance to ensure the normal operation of the power system and the safety of the equipment.

[0047] In the embodiment of the present invention, the voltage imbalance is expressed as a percentage and is calculated by the following formula:

[0048] Voltage unbalance = (maximum phase voltage - minimum phase voltage) / average phase voltage × 100%;

[0049] When the voltage imbalance is >5%, the system will give an alarm to prompt the staff to check; when the voltage imbalance is >10%, the currently running equipment will be directly shut down. If there is a spare device, the spare device will be started through the PLC control system.

[0050] As an optional embodiment, when the data analysis subroutine is run, it outputs a current imbalance exceeding limit alarm signal according to the current imbalance rate in each control loop exceeding the second preset threshold range; correspondingly, when the execution control subroutine is run, it executes the following control strategy according to the current imbalance exceeding limit alarm signal: shut down the control device in the control loop where the current imbalance exceeds the limit.

[0051] As an example, the larger the value of the current imbalance rate, the higher the degree of current imbalance, which may cause power loss. Current imbalance will lead to unbalanced three-phase load, thereby increasing the total power loss of the system; it will also shorten the life of the equipment. Current imbalance will cause equipment overload and overheating, resulting in equipment life being affected. Therefore, in the power system, it is necessary to monitor and control the current imbalance rate to ensure the normal operation of the power system and the safety of the equipment.

[0052] In the embodiment of the present invention, the current unbalance rate is expressed as a percentage, and the calculation formula is as follows:

[0053] Current unbalance rate = (maximum phase current - minimum phase current) / maximum phase current × 100%;

[0054] When the current imbalance rate is >5%, the system will give an alarm to prompt the staff to check; when the current imbalance rate is >10%, the currently running equipment will be directly shut down. If there is a spare device, the spare device will be started through the PLC control system.

[0055] As an optional embodiment, when the data analysis subroutine is run, according to the actual current value in each control loop and the rated current value of the control device, if the actual current value exceeds the preset current allowable range, a current over-limit alarm signal is output; correspondingly, when the execution control subroutine is run, the following control strategy is executed according to the current over-limit alarm signal:

[0056] 1) For control equipment equipped with a frequency converter, the operating frequency of the control equipment is reduced to stabilize the operating current below the rated current;

[0057] 2) For control equipment without a frequency converter installed, if the actual current value exceeds the system preset overcurrent threshold and continues for more than the preset time range, the control equipment will shut down.

[0058] As an example, the user can preset the rated current value in the control system according to the nameplate information or manual of the control device. When the device is running, the real-time current value of the device is collected through the PLC, and compared and analyzed with the rated current value. When the current collected during actual operation exceeds the rated current of the device, the control system outputs an alarm reminder. Among them, for control devices equipped with frequency converters, the operating frequency of the device is reduced through PLC control so that its operating current is stabilized below the rated current. For control devices without frequency converters, if the actual current value exceeds the overcurrent threshold preset by the system and continues to exceed the preset time range (the preset time range can be pre-configured or modified in the control system), the device is stopped.

[0059] In a preferred example, the current threshold is particularly set to be the product of the rated current and the overcurrent safety factor k. The value of k can be determined according to the overload capacity of the system, and is usually 1.1 to 1.2.

[0060] As an optional embodiment, when the data analysis subroutine is run, based on the power deviation between the real-time power value and the theoretical power value in each control loop, if the power deviation exceeds a preset range, a power abnormality alarm signal is output; correspondingly, when the execution control subroutine is run, the following control strategy is executed based on the power abnormality alarm signal: the control device in the control loop where the power abnormality is located is shut down.

[0061] In this embodiment, for belt-driven fan equipment, such as cooling towers, air conditioning processing units, etc., by monitoring the abnormal power status of the equipment, it can be determined that the belt is loose or broken, and it is necessary to intervene in the operation of the equipment and control the equipment to stop for inspection and replacement to avoid danger and safety accidents.

[0062] As an example, the user can preset the rated power value P1 in the control system according to the nameplate information or the instruction manual of the device, and collect the real-time power P2 of the device during operation through the PLC.

[0063] According to the law that the shaft power of the motor is proportional to the cube of the frequency during operation, the PLC is used to collect the real-time frequency H of the device during operation, and the theoretical power P3 of the device is calculated according to the following relationship:

[0064] P3 = (H / 50.0)^3 * P1;

[0065] Furthermore, by comparing and analyzing the power deviation between the theoretical power P3 and the real-time power P2, in one example, the reasonable error range of the device is defaulted to 10% of P1. When P3 - P2 < P1 * 10%, it indicates that the actual power of the device during operation is much smaller than the theoretical value, then it is determined that the belt is loose or broken, an abnormal power alarm signal is output, and the device is controlled to stop.

[0066] It should be understood that in the examples shown in the appendix Figure 1 and the above embodiments, taking the chiller, water pump, cooling tower, and air handling unit as examples for illustration, according to the teachings of the present invention, more types and more quantities of devices in the HVAC system (i.e., the refrigeration machine room) can be diagnosed and controlled according to the methods of the above embodiments of the present invention, realizing automatic intelligent diagnosis and early warning and automatic control, improving the energy consumption of the refrigeration machine room system, and optimizing and adjusting the operating conditions of the HVAC system.

[0067] {Embodiment 2}

[0068] Based on the implementation of the refrigeration machine room health prediction diagnosis and control system according to the above embodiments by analyzing intelligent meter data, the present disclosure also proposes a refrigeration machine room health prediction diagnosis and control method, including the following steps:

[0069] Establish a communication connection between the intelligent meters in each control loop of the HVAC system and the control system through the MODBUS RTU protocol. The control loop is composed of a control device of the HVAC system and its supporting intelligent meter; the control device includes at least one of an air handling unit, a cooling tower, a water pump, a chiller, a humidifying unit, and a surface cooler;

[0070] The control system reads in real time the power consumption data collected by the intelligent meters in each control loop, including three-phase voltage, three-phase current, and three-phase power;

[0071] Judge whether the intelligent meter is abnormal or the loop is abnormal according to the power consumption data in each control loop, and output an alarm signal; and

[0072] Execute a predetermined control strategy according to the type of abnormality to adjust the state of the control loop.

[0073] It should be understood that the aforementioned judgment of smart meter abnormality or loop abnormality based on the power consumption data in each control loop and output of an alarm signal refers especially to the monitoring and analysis of voltage phase loss, voltage overlimit, loop power feedback zero value abnormality, voltage imbalance, current imbalance rate, equipment power abnormality and overcurrent status in the control loop through the operation of the data analysis subroutine written in the aforementioned control system.

[0074] It should be understood that the aforementioned execution of a predetermined control strategy according to the type of abnormality and adjustment of the state of the control loop particularly refers to the corresponding device control through the operation of the execution control subroutine written in the aforementioned control system, and the operating conditions of the equipment are optimized by adjusting the operating parameters of the control loop where the abnormality occurs, or the operation of the equipment is stopped.

[0075] Among them, for the abnormality of the loop power feedback value of 0, it is determined that the voltage phase and current phase of the meter installation do not match, and the output power feedback abnormal alarm signal is prompted to check the installation line of the meter.

[0076] Although the present invention has been disclosed as above with preferred embodiments, it is not intended to limit the present invention. A person with ordinary knowledge in the technical field to which the present invention belongs may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be determined by the definition of the claims.

Claims

1. A refrigeration room health prediction diagnosis and control system based on smart meter data analysis, characterized in that: include: Multiple control devices; A smart meter configured in one-to-one correspondence with each control device is used to monitor and record the power consumption data of the control device in real time. Each control device and its matching smart meter constitute a control loop; the power consumption data includes at least three-phase voltage, three-phase current and three-phase power; The control system is connected to each control loop and is used to perform early warning analysis based on the monitoring data of the smart meter in the control loop, and to perform state adjustment on the control loop based on the early warning analysis result.

2. The refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to claim 1 is characterized in that: The control system is configured with a data acquisition subroutine, a data analysis subroutine and an execution control subroutine: The data acquisition subroutine acquires the power consumption data of each control loop when being executed; When the data analysis subroutine is executed, it analyzes and judges the acquired power consumption data in a preset manner and outputs the judgment result; The execution control subroutine, when being run, executes a predetermined control strategy for controlling and adjusting a control loop according to the judgment result.

3. The refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to claim 2 is characterized in that: When the data analysis subroutine is executed, according to the three-phase power supply voltage data in each control loop, when there is no data for any phase voltage, a voltage phase loss alarm signal is output; When the execution control subroutine is run, the following control strategy is executed according to the voltage phase loss alarm signal: all control devices on the voltage phase loss control loop are stopped.

4. The refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to claim 2 is characterized in that: When the data analysis subroutine is executed, based on the three-phase power supply voltage data in each control loop and the preset voltage allowable range, if the voltage data exceeds the preset voltage allowable range and continues to exceed the preset time range, a voltage over-limit alarm signal is output; When the execution control subroutine is executed, the following control strategy is executed according to the voltage over-limit alarm signal: the control equipment that has not been running on the voltage over-limit control loop is prohibited from starting, and the control equipment that has been running is controlled to stop immediately.

5. The refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to claim 2 is characterized in that: When the data analysis subroutine is run, according to the three-phase power data in each control loop, when any power value is less than 0, it indicates that the voltage phase and current phase of the smart meter installation do not match, and an abnormal power feedback alarm signal is output; When the execution control subroutine is run, the following control strategy is executed according to the power feedback abnormality alarm signal: prompting an operator to check the installation line of the smart meter.

6. The refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to claim 2 is characterized in that: When the data analysis subroutine is executed, according to the voltage imbalance in each control loop exceeding the first preset threshold range, a voltage imbalance exceeding limit alarm signal is output; When the execution control subroutine is run, the following control strategy is executed according to the voltage imbalance exceeding limit alarm signal: the control device in the control loop where the voltage imbalance exceeding limit is controlled is shut down.

7. The refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to claim 2 is characterized in that: When the data analysis subroutine is executed, according to the current imbalance rate in each control loop exceeding the second preset threshold range, a current imbalance exceeding limit alarm signal is output; When the execution control subroutine is executed, the following control strategy is executed according to the current imbalance exceeding limit alarm signal: the control device in the control loop where the current imbalance exceeding limit is controlled is shut down.

8. The refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to claim 2 is characterized in that: When the data analysis subroutine is executed, according to the actual current value in each control loop and the rated current value of the control device, if the actual current value exceeds the preset current allowable range, an over-current alarm signal is output; When the execution control subroutine is run, the following control strategy is executed according to the current over-limit alarm signal: 1) For control equipment equipped with a frequency converter, the operating frequency of the control equipment is reduced to stabilize the operating current below the rated current; 2) For control equipment without a frequency converter installed, if the actual current value exceeds the system preset overcurrent threshold and continues for more than the preset time range, the control equipment will shut down.

9. The refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to claim 2 is characterized in that: When the data analysis subroutine is executed, according to the power deviation between the real-time power value and the theoretical power value in each control loop, if the power deviation exceeds a preset range, a power abnormality alarm signal is output; When the execution control subroutine is executed, the following control strategy is executed according to the power abnormality alarm signal: the control device in the control loop where the power abnormality is located is controlled to shut down.

10. The refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to any one of claims 1 to 9, characterized in that: The control system is a PLC industrial control system, and communicates with the smart meter in the control loop based on the MODBUS RTU protocol to realize the collection of user data.

11. A refrigeration room health prediction diagnosis and control method based on the refrigeration room health prediction diagnosis and control system based on smart meter data analysis according to any one of claims 1 to 9, characterized in that: The method comprises the following steps: Establishing a communication connection between the smart meter in each control loop of the HVAC system and the control system through the MODBUS RTU protocol, wherein the control loop is composed of a control device of the HVAC system and its supporting smart meter; the control device includes at least one of an air handling unit, a cooling tower, a water pump, a chiller, a humidifier, and a surface cooler; The control system reads the power consumption data collected by the smart meter in each control loop in real time, including three-phase voltage, three-phase current and three-phase power; According to the power consumption data in each control loop, it is judged that the smart meter is abnormal or the loop is abnormal, and an alarm signal is output; Execute the predetermined control strategy according to the abnormality type and adjust the state of the control loop.

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