A method and system for automatically identifying load characteristics

Abstract

The application discloses a kind of methods and systems for automatically identifying load characteristics, wherein the method comprises the following steps: S1, data acquisition: periodically collect the instantaneous value of active power P and reactive power Q of each output branch, and calculate the average value of active power Pavg and the average value of reactive power Qavg within a power frequency cycle;S2, load characteristic identification: preset reactive power determination threshold Qth, and grade judgment is carried out on the average value of reactive power Qavg of each output branch S3, result output: the identification result containing branch number, load type, Pavg, Qavg is output synchronously, and display is carried out.The application improves power quality, operation stability and intelligent level of machine room operation and maintenance of distribution system.

Description

Technical Field

[0001] This invention relates to the fields of power electronics, power management, and data center power distribution infrastructure. Specifically, it relates to an identification method and system for intelligent PDU branches that automatically distinguishes resistive, capacitive, and inductive load characteristics based on real-time reactive power detection. This method is applicable to AC power distribution monitoring and refined power control scenarios in communication equipment rooms, data centers, and industrial workshops. Background Technology

[0002] Data centers, communication equipment rooms, and industrial power distribution systems commonly use intelligent PDUs to power terminal loads such as servers, switches, and industrial control equipment. Load electrical characteristics are categorized into three types: resistive, capacitive, and inductive. The reactive power characteristics of different loads vary significantly, directly impacting power quality, power system stability, and equipment operating efficiency. Capacitive loads generate negative reactive power and are prone to resonance with inductive components in the line, raising voltage. Inductive loads consume positive reactive power, reducing the system power factor. Purely resistive loads have approximately zero reactive power, causing no reactive power disturbance to the power grid. Accurate identification of load characteristics is a fundamental prerequisite for refined power distribution management, harmonic mitigation, resonance risk warning, and power-on sequence optimization.

[0003] Existing intelligent PDU load identification solutions have three obvious drawbacks: (1) Manual configuration of load type scheme Maintenance personnel can manually preset the load type (server, network device, etc.) for each output port in the PDU backend management interface.

[0004] Defects: It relies entirely on manual operation, has a large number of ports in the computer room, requires a lot of configuration work, cannot update the configuration synchronously after the load is changed, and fails to identify; the preset equipment type does not have a strict correspondence with the actual electrical capacitance / resistance / inductance, and the control strategy has a low matching degree.

[0005] (2) Roughly determine the scheme based solely on the total power factor Some PDUs calculate the overall power factor (PF) using total active power and total apparent power, and use the PF value to determine the nature of the load.

[0006] Defects: The same power factor cannot distinguish the load type: the power factor of a purely resistive load is PF=1, and the power factor of a capacitive-inductive parallel resonant circuit can also be close to 1, but the reactive power characteristics and grid hazards of the two are completely different; it only supports the total load of the whole machine and cannot realize the load identification at the port level of a single branch. The control granularity is coarse and it is not possible to implement differentiated control by port.

[0007] (3) Traditional PDU without load identification function Basic PDUs on the market only support voltage, current, active power metering and on / off control, and lack the ability to identify load characteristics.

[0008] Defects: The control logic is simple and cannot optimize the power-on timing, suppress inrush current, or provide targeted harmonic compensation based on the reactive power characteristics of the load; it cannot monitor the risk of capacitive load accumulation in real time, and cannot provide early warning of power supply faults such as resonance and voltage abnormalities, resulting in poor system reliability; it lacks load reactive power data support, making it difficult to achieve quantitative analysis and optimization of data center energy efficiency. Summary of the Invention

[0009] To address the aforementioned technical problems, this invention provides a method and system for automatically identifying load characteristics.

[0010] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A method for automatically identifying load characteristics includes the following steps: S1. Data Acquisition: Periodically acquire the instantaneous values ​​of active power P and reactive power Q of each output branch, and calculate the average active power Pavg and the average reactive power Qavg within one power frequency cycle. S2. Load Characteristic Identification: A preset reactive power judgment threshold Qth is used to classify and judge the average reactive power Qavg of each output branch. If Qavg < -Qth, the branch load is determined to be a capacitive load; If |Q_avg|≤Qth, the branch load is determined to be a resistive load; If Qavg > Qth, the branch load is determined to be an inductive load; S3. Result Output: The identification results, including branch number, load type, Pavg, and Qavg, will be output synchronously and displayed. S4. Linkage Control: Based on the identification results, execute at least one linkage strategy: capacitive load overload warning, differentiated power-on timing control, inductive load overload protection, and data center energy efficiency statistics.

[0011] As a further improvement, in step S1, the sampling period is set to N seconds, and the instantaneous values ​​of active power P and reactive power Q are collected H times within N seconds, and then the average value is calculated.

[0012] As a further improvement, in step S3, displaying the output results specifically involves displaying them on the PDU LCD screen and marking the corresponding branch positions detected, with capacitive loads marked as C, resistive loads as R, and inductive loads as L.

[0013] As a further improvement, the capacitive load overload warning strategy in step S4 is as follows: If the branch load is a capacitive load, specifically: sum up the total capacitive reactive power of all branches with capacitive loads. When the total capacitive reactive power exceeds the power distribution safety threshold, push out a risk warning for resonance or voltage rise.

[0014] As a further improvement, in step S4, the differentiated power-on timing control strategy is as follows: when the whole machine is powered on sequentially, the closing sequence of the capacitive load branch is delayed, and the inductive and resistive load branches are switched on first to reduce the impact of the closing inrush current on the power supply bus.

[0015] As a further improvement, in step S4, the inductive load overload protection strategy is as follows: when the reactive power value of a single branch inductive load continuously exceeds the protection threshold, the power supply to that branch is cut off, and fault information is reported simultaneously.

[0016] As a further improvement, in step S4, the data collection strategy for data center energy efficiency is to summarize the reactive power ratio of all branch resistive loads, capacitive loads, and inductive loads to generate a visual energy efficiency analysis dashboard.

[0017] A system for automatically identifying load characteristics includes an energy metering chip, a main control MCU, a local display module, a communication interface, an output control module, and a data center management platform. The energy metering chip, the local display module, the communication interface, and the output control module are respectively connected to the main control MCU, and the main control MCU communicates with the data center management platform through the communication interface.

[0018] As a further improvement, the communication interface adopts the SNMP or Modbus protocol to remotely upload the identification results to the data center management platform.

[0019] The present invention has the following beneficial technical effects: 1. Automation and Precision: It realizes automatic real-time identification of load electrical characteristics without manual intervention. The identification results are based on direct electrical measurements and have high accuracy.

[0020] 2. Provides a foundation for intelligent control: It enables PDU to transform from blind control to perception control, providing key data input for implementing refined power management strategies that match load characteristics.

[0021] 3. Improve energy efficiency and power quality: By optimizing control, additional losses caused by load characteristic mismatch can be reduced, and early warning and intervention can be provided for situations that may affect power quality.

[0022] 4. Enhance system reliability: Early detection of problems such as abnormal accumulation of capacitive loads, preventing them from developing into faults that affect the safety of the entire power supply system.

[0023] 5. Reduced operation and maintenance costs: Reduced the workload of manual configuration and maintenance, and reduced fault handling costs through preventive early warning. Attached Figure Description

[0024] Figure 1 This is a schematic diagram illustrating the principle of the present invention; Figure 2 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0025] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0026] In the description of this invention, it should be understood that if terms such as "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise" are used to indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, they are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0027] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can refer to a mechanical connection or an electrical connection. They can refer to a direct connection or an indirect connection through an intermediate medium, and they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances.

[0028] In AC circuits, the power consumed by a load includes active power P and reactive power Q. Resistive loads (such as incandescent lamps and heating elements) consume only active power, with reactive power Q ≈ 0. Capacitive loads (such as the input terminals of some switching power supplies and compensation capacitors) generate capacitive reactive power (usually defined as negative in power systems, i.e., Q < 0). Inductive loads (such as motors and transformers) consume inductive reactive power (Q > 0). By accurately measuring the sign and magnitude of the instantaneous reactive power Q in each branch, its dominant characteristics can be clearly distinguished.

[0029] like Figure 2 As shown, a method for automatically identifying load characteristics includes the following steps: S1. Data Acquisition: Periodically acquire the instantaneous values ​​of active power P and reactive power Q of each output branch, and calculate the average active power Pavg and average reactive power Qavg within one power frequency cycle. Assume the acquisition period is 1 second, and 10 acquisitions are made within 1 second, thus obtaining 10 sets of active power P and reactive power Q.

[0030] S2. Load Characteristic Identification: A preset reactive power judgment threshold Qth is used to classify and judge the average reactive power Qavg of each output branch. If Qavg < -Qth, the branch load is determined to be a capacitive load; If |Q_avg|≤Qth, the branch load is determined to be a resistive load; If Qavg > Qth, the branch load is determined to be an inductive load.

[0031] S3. Result Output: The identification results, including branch number, load type, Pavg, and Qavg, will be output synchronously and displayed.

[0032] S4. Linkage Control: Based on the identification results, execute at least one linkage strategy: capacitive load overload warning, differentiated power-on timing control, inductive load overload protection, and data center energy efficiency statistics.

[0033] In step S3, displaying the output results specifically involves displaying them on the PDU LCD screen and marking the corresponding branch positions detected, with capacitive loads marked as C, resistive loads as R, and inductive loads as L.

[0034] The capacitive load overload warning strategy in step S4 is as follows: If the branch load is a capacitive load, specifically: sum up the total capacitive reactive power of all branches with capacitive loads. When the total capacitive reactive power exceeds the power distribution safety threshold, push out a risk warning for resonance or voltage rise.

[0035] In step S4, the differentiated power-on timing control strategy is as follows: when the whole machine is powered on sequentially, the closing sequence of the capacitive load branch is delayed, and the inductive and resistive load branches are switched on first to reduce the impact of the closing inrush current on the power supply bus.

[0036] In step S4, the inductive load overload protection strategy is as follows: when the reactive power value of a single branch inductive load continuously exceeds the protection threshold, the power supply to that branch is cut off, and fault information is reported simultaneously to avoid damage to the power distribution components caused by the starting impact of inductive equipment.

[0037] In step S4, the data statistics strategy for data center energy efficiency is to summarize the reactive power ratio of all branch resistive loads, capacitive loads, and inductive loads, generate a visual energy efficiency analysis dashboard, and guide the optimization and transformation of power distribution.

[0038] A system for automatically identifying load characteristics includes an energy metering chip, a main control MCU, a local display module, a communication interface, an output control module, and a data center management platform. The energy metering chip, the local display module, the communication interface, and the output control module are respectively connected to the main control MCU, and the main control MCU communicates with the data center management platform through the communication interface.

[0039] The communication interface uses the SNMP or Modbus protocol to remotely upload the identification results to the data center management platform.

[0040] Take a smart PDU in a data center rack as an example: 1. Data Acquisition: The PDU's MCU reads the instantaneous values ​​of active power P and reactive power Q of the circuit 10 times per second from the metering chip connected to "Outlet 5" via the serial bus, and calculates their average value over 1 second. Assume Pavg = 150W and Qavg = -25Var.

[0041] 2. Algorithm identification: The preset reactive power threshold Q_th = 10Var in the MCU. Compare Qavg (-25Var) with the threshold: Since -25 < -10, the condition Q < -Qth is satisfied, so the load connected to "Outlet 5" is determined to be a capacitive load.

[0042] 3. Results Output and Application: a) On the PDU's LCD screen, a capacitor symbol "C" is displayed next to the "Outlet 5" label.

[0043] b) The MCU reports the information "Outlet 5: Capacitive load, P=150W, Q=-25Var" to the data center management platform via the SNMP protocol.

[0044] c) On the data center management platform, the view of the PDU in this rack is updated synchronously, and the total reactive power of all loads identified as capacitive on this PDU is counted. If the total is found to exceed the safety tolerance of the data center power distribution design, an alarm message will be sent to the maintenance personnel: "Warning: The capacitive reactive power of the PDU in rack A05 exceeds the standard, and there is a risk of resonance. It is recommended to check the load equipment." d) At the same time, the PDU's MCU can use this identification result to schedule the capacitive load branch to be powered on at a later time when performing the "sequential power-on" function, so as to reduce the impact of the closing inrush current on the system.

[0045] It should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. However, any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for automatically identifying load characteristics, characterized in that, Includes the following steps: S1. Data Acquisition: Periodically acquire the instantaneous values ​​of active power P and reactive power Q of each output branch, and calculate the average active power Pavg and the average reactive power Qavg within one power frequency cycle. S2. Load Characteristic Identification: A preset reactive power judgment threshold Qth is used to classify and judge the average reactive power Qavg of each output branch. If Qavg < -Qth, the branch load is determined to be a capacitive load; If |Q_avg|≤Qth, the branch load is determined to be a resistive load; If Qavg > Qth, the branch load is determined to be an inductive load; S3. Result Output: The identification results, including branch number, load type, Pavg, and Qavg, will be output synchronously and displayed. S4. Linkage Control: Based on the identification results, execute at least one linkage strategy: capacitive load overload warning, differentiated power-on timing control, inductive load overload protection, and data center energy efficiency statistics.

2. The method for automatically identifying load characteristics according to claim 1, characterized in that, In step S1, the sampling period is set to N seconds. Within N seconds, H instantaneous values ​​of active power P and reactive power Q are collected, and then the average value is calculated.

3. The method for automatically identifying load characteristics according to claim 1, characterized in that, In step S3, displaying the output results specifically involves displaying them on the PDU LCD screen and marking the corresponding branch positions detected, with capacitive loads marked as C, resistive loads as R, and inductive loads as L.

4. The method for automatically identifying load characteristics according to claim 1, characterized in that, The capacitive load overload warning strategy in step S4 is as follows: If the branch load is a capacitive load, specifically: sum up the total capacitive reactive power of all branches with capacitive loads. When the total capacitive reactive power exceeds the power distribution safety threshold, push out a risk warning for resonance or voltage rise.

5. The method for automatically identifying load characteristics according to claim 1, characterized in that, In step S4, the differentiated power-on timing control strategy is as follows: when the whole machine is powered on sequentially, the closing sequence of the capacitive load branch is delayed, and the inductive and resistive load branches are switched on first to reduce the impact of the closing inrush current on the power supply bus.

6. The method for automatically identifying load characteristics according to claim 1, characterized in that, In step S4, the inductive load overload protection strategy is as follows: when the reactive power value of a single branch inductive load continuously exceeds the protection threshold, the power supply to that branch is cut off, and fault information is reported simultaneously.

7. The method for automatically identifying load characteristics according to claim 1, characterized in that, In step S4, the data collection strategy for data center energy efficiency is to summarize the reactive power ratio of all branch resistive loads, capacitive loads, and inductive loads to generate a visual energy efficiency analysis dashboard.

8. A system for automatically identifying load characteristics, characterized in that, It includes an energy metering chip, a main control MCU, a local display module, a communication interface, an output control module, and a data center management platform. The energy metering chip, the local display module, the communication interface, and the output control module are all connected to the main control MCU, and the main control MCU communicates with the data center management platform through the communication interface.

9. The system for automatically identifying load characteristics according to claim 8, characterized in that, The communication interface uses the SNMP or Modbus protocol to remotely upload the identification results to the data center management platform.

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