Methods, devices and systems for monitoring abnormal electricity use

Abstract

This invention discloses a method, device, and system for monitoring abnormal electricity consumption. An energy monitoring node monitors the abnormal electricity consumption state of an electrical load: when the load is in a potentially abnormal state, a safety monitoring mode is activated; when the abnormal state variable meets the critical abnormal condition, a critical monitoring mode is immediately activated; when the abnormal state variable meets the transient abnormal condition, a transient abnormal response is obtained. When the load is in a critical abnormal state, transient abnormal characteristic parameters are obtained through critical real-time tracking processing; through critical feedback monitoring, the pre-trigger conditions corresponding to the transient abnormal conditions are adjusted; when the monitored front-end input signal meets the pre-trigger conditions, a transient abnormal response is obtained. The device is an energy monitoring node; the system consists of several energy monitoring nodes. This invention is geared towards electricity safety monitoring and has the advantages of high security, flexible monitoring modes, and rapid and accurate response to transient abnormalities.

Description

Technical Field

[0001] This invention relates to the technical field of edge intelligence and measurement and control in the wireless Internet of Things, mainly to edge collaborative sensing networks and intelligent hardware devices for power monitoring and safety monitoring, and particularly to a method, device and system for monitoring abnormal power consumption. Background Technology

[0002] The comprehensive utilization efficiency of electrical energy is mainly reflected in safety, energy saving, and economy. With the development of IoT smart technology, power monitoring and safety management not only focus on power production, transmission, and distribution, but also need to cover the entire power consumption process of distributed power consumption nodes more broadly and deeply, and monitor the power load objects and terminal equipment in different power consumption scenarios within the user's scope.

[0003] With the rapid development of technologies such as wireless communication, the Internet of Things, and monitoring and control, information service systems that combine distributed, low-power, big data, continuous, and edge-central intelligent management are needed for monitoring and managing electrical equipment in industrial environments. These systems can monitor, summarize, evaluate, and guide the energy utilization efficiency and safety level of power consumption nodes, providing real-time safety monitoring and decision-making basis for continuously improving energy efficiency and safety management.

[0004] Power monitoring node devices (such as power meters, power metering sensors, power metering sockets, etc.) can support the acquisition of power monitoring data and realize many intelligent management capabilities through status monitoring, location sensing, remote control and anomaly handling. However, their security still needs to be further improved in terms of power equipment matching, transient anomaly response and protection.

[0005] Existing power monitoring technologies have the following main shortcomings in terms of safety monitoring of electricity consumption:

[0006] 1) Lack of relevance to target scenarios in security protection: When existing technologies monitor power based on IoT edge networks, the field environment is monitored by distributed power monitoring nodes, which collect monitoring data (and upload it to the host). As each of the multiple power monitoring nodes is a relatively independent target monitoring node, there is a lack of necessary collaborative services among them, including collaborative sensing and monitoring, collaborative data processing, collaborative communication and collaborative protection, as well as the flexibility to dynamically adjust power monitoring strategies and plans for different target scenario states.

[0007] 2) Lack of safety protection for transient connection and disconnection: Existing safety protection technologies mainly target the operation of electrical loads, but lack more targeted and effective protection for the transient processes of load connection and disconnection (plugging and unplugging). For hot-plugging of loads in special industrial environments, it is necessary to adopt special arc protection technologies that are too complex in structure and extremely expensive in order to prevent arcing.

[0008] 3) Balancing Energy Efficiency and Safety Monitoring Capabilities: Existing power monitoring technologies lack the ability to flexibly select and adapt to different operating states of the load (e.g., unconnected or normally operating after connection, potential anomalies, or critical anomalies) based on the current target scenario and load status. Indiscriminate real-time monitoring data processing not only leads to unnecessary loss of sensitive resources (such as power consumption, computing power, and bandwidth) and a large amount of data redundancy, but also results in a lack of more real-time and effective anomaly handling capabilities when key target loads experience transient anomalies.

[0009] 4) The balance between real-time performance and stability: Existing technologies have not adequately addressed the balance between real-time performance and stability in transient protection. If the abnormal protection responds based on the effective value over a period of time, the lack of real-time performance leads to excessively long transient anomaly response times. Furthermore, when transient distortions occur in the power signal, the effective value cannot accurately reflect the transient impact. However, responding to transient monitoring values ​​will result in significant errors and instability, especially when transient pulse distortion is large.

[0010] Therefore, how to flexibly adjust the monitoring mode of electrical load objects to have a safer monitoring capability for load objects in abnormal states, and how to track and monitor transient abnormal characteristic parameters to quickly and accurately obtain the trigger response of transient abnormalities, have become urgent technical problems to be solved. Summary of the Invention

[0011] The technical problem this invention aims to solve is that, based on the abnormal state level of the current load object, the power monitoring node adjusts the monitoring mode so that when the abnormal state variable meets the transient abnormal condition, it can quickly obtain a transient abnormal response, thereby solving the balance between energy saving and safety monitoring capabilities; by performing critical real-time tracking processing and critical feedback monitoring on the transient abnormal characteristic parameters, it can quickly obtain a pre-triggered response during transient abnormalities, thereby solving the balance between real-time performance and stability.

[0012] To address the above problems, this invention proposes a method, device, and system for monitoring abnormal electricity consumption.

[0013] In a first aspect, this invention discloses a method for monitoring abnormal electricity consumption. A power monitoring node acts as the target monitoring node, monitoring the abnormal electricity consumption status of its associated and bound power load objects. The method includes the following steps: performing state evaluation processing on the current target monitoring information according to graded abnormal conditions to obtain abnormal status information of the load object; based on the abnormal status information, when the load object is in a potential abnormal state, activating a safety monitoring mode: performing safety tracking monitoring on the abnormal status variables of the load object; when the abnormal status variables meet critical abnormal conditions, activating a critical monitoring mode; when the abnormal status variables meet transient abnormal conditions, obtaining a transient abnormal response.

[0014] Secondly, this invention discloses another method for monitoring abnormal electricity consumption. A certain power monitoring node serves as the target monitoring node, which monitors the abnormal electricity consumption status of the associated and bound power load objects. The method includes the following steps: when the load object is in a critical abnormal state, the transient abnormal characteristic parameters of the load object are obtained through critical real-time tracking processing; based on the transient abnormal characteristic parameters, the pre-trigger conditions corresponding to the transient abnormal conditions are adjusted through critical feedback monitoring; when the tracked and monitored front-end input signal meets the pre-trigger conditions, a transient abnormal response is obtained.

[0015] Optionally, when the power monitoring node receives a transient anomaly response, it immediately triggers its own and / or associated node's transient protection control module to perform transient anomaly protection on the load object in the transient anomaly state; the power monitoring node selects an appropriate transient protection mode based on the urgency and coverage of the current protection needs for the associated load object, and based on a balance assessment of the protection needs and protection costs.

[0016] Optionally, the graded anomaly conditions include potential anomaly conditions, critical anomaly conditions, and transient anomaly conditions; the power monitoring node performs state mode parsing based on the graded anomaly conditions, including: judging the target scenario state associated with the load object based on the graded anomaly conditions: 1) when the potential anomaly conditions are met, entering the potential anomaly state; 2) when the critical anomaly conditions are met, entering the critical anomaly state; 3) when the transient anomaly conditions are met, immediately triggering transient anomaly protection processing.

[0017] Optionally, the power monitoring node dynamically adjusts the pre-trigger conditions corresponding to the graded abnormal conditions to track and monitor different levels of abnormal states; the power monitoring node adjusts the pre-trigger conditions by setting a rated comparison signal and / or a tracking monitoring time step.

[0018] Optionally, the power monitoring node performs transient anomaly protection in at least one of the following ways according to the transient protection mode: Method 1, single-point transient protection: the power monitoring node immediately triggers the transient protection control module of its own node device to perform transient anomaly protection on the load object; Method 2, linkage transient protection: the power monitoring node triggers the associated protection node to perform transient anomaly protection on the load object through wireless scene linkage.

[0019] Optionally, the surrounding associated protection nodes activate the transient anomaly protection according to the received abnormal trigger signal and the trigger response priority: when the protection level is low, only the associated protection nodes with higher priority need to activate the transient anomaly protection; while when the required protection level is high, the associated protection nodes with lower priority need to activate the transient anomaly protection; until all associated protection nodes activate the transient anomaly protection when necessary.

[0020] Thirdly, the present invention also discloses an electricity consumption anomaly monitoring device. The device uses an energy monitoring node as the target monitoring node to monitor the electricity consumption anomaly status of its associated and bound electricity load objects. The device consists of the following modules: a state mode parsing module, used to perform state evaluation processing on the current target monitoring information according to graded anomaly conditions to obtain the anomaly status information of the load object; a potential anomaly monitoring module, used to activate a safety monitoring mode when the load object is in a potential anomaly state, based on the anomaly status information, to perform safety tracking and monitoring of the anomaly status variables of the load object; a critical anomaly monitoring module, used to activate a critical monitoring mode when the anomaly status variables meet critical anomaly conditions; and a transient anomaly response module, used to obtain a transient anomaly response when the anomaly status variables meet transient anomaly conditions.

[0021] Fourthly, the present invention also discloses another power consumption anomaly monitoring device. This device uses a power monitoring node as the target monitoring node to monitor the power consumption anomaly status of its associated bound power load objects. The device consists of the following modules: a critical real-time tracking module, used to obtain transient anomaly characteristic parameters of the load object through critical real-time tracking processing when the load object is in a critical anomaly state; a critical feedback monitoring module, used to adjust the pre-triggered conditions corresponding to the transient anomaly conditions based on the transient anomaly characteristic parameters through critical feedback monitoring; and a pre-triggered response module, which obtains a transient anomaly response when the monitored front-end input signal meets the pre-triggered conditions.

[0022] Fifthly, the present invention also discloses an abnormal power consumption monitoring system, which is a system established using the abnormal power consumption monitoring methods described in the first and second aspects. The system consists of several power monitoring nodes; wherein different power monitoring nodes serve as target monitoring nodes and / or collaborative sensing nodes to monitor the abnormal power consumption status of associated and bound power load objects; the system is an edge collaborative sensing network system, which includes at least a target monitoring module and a collaborative processing module.

[0023] As can be seen from the technical solution provided by the present invention, the power monitoring node of the present invention monitors the abnormal power consumption status of the power load object. When the load object is in a potentially abnormal state, the safety monitoring mode is activated. When the abnormal state variable meets the critical abnormal condition, the critical monitoring mode is activated. This avoids excessive occupation of sensitive resources by power monitoring when the load object is in a normal state, thereby solving the problem of balancing energy saving and safety monitoring capabilities in the monitoring mode.

[0024] The present invention provides an energy monitoring node that monitors the abnormal power consumption status of an electrical load. When the load is in a critical abnormal state, it obtains transient abnormal characteristic parameters and critical feedback monitoring through critical real-time tracking processing. It adjusts the pre-trigger conditions corresponding to the transient abnormal conditions so that when the front-end input signal being tracked meets the pre-trigger conditions, a transient abnormal response is quickly obtained, thereby solving the balance problem between real-time performance and stability.

[0025] Therefore, compared with existing technologies, this invention addresses the challenges of balancing and flexibly managing power consumption anomalies, including real-time data processing and resource consumption, stability and response speed, and energy efficiency and security. Consequently, it offers advantages such as high security, flexible monitoring modes, and rapid and accurate response to transient anomalies. Specifically, this is manifested in the following aspects:

[0026] 1) At the load access and outgoing stages, the power monitoring node identifies and senses the access of the power load; it performs object matching verification on the received object identification signal to configure and adjust the monitoring mode parameters that match the current load object, thereby solving the problems of matching security and monitoring mode flexibility for the current load object.

[0027] 2) The power monitoring node adopts a low-power energy-saving monitoring mode for power loads under normal conditions. When the load is not connected (no load) or is operating normally, the power monitoring node is in energy-saving monitoring mode, which helps to save power consumption and reduce data redundancy; especially in order to reduce installation costs in narrowband wireless communication, flexible data upload reduces wireless interference and data resource competition.

[0028] 3) Based on target scenario state perception and monitoring information processing, the real-time performance and security of monitoring data are improved by upgrading the monitoring mode level for load objects in abnormal states through state mode evaluation; when a load object is in a potentially abnormal state, the potential abnormal monitoring mode is activated; this facilitates rapid abnormal response and abnormal response handling, including recording the abnormal process, protecting data, and abnormal alarms.

[0029] 4) When the load object is in a critical abnormal state, the power monitoring node obtains transient abnormal characteristic parameters through critical real-time tracking processing, which is beneficial to improve the real-time performance and consistency of the abnormal response. By sending abnormal trigger status beacons with higher activity, the trigger response is fast and the priority is high, enabling the collaborative sensing node to obtain the pre-trigger response quickly and reliably in a short time.

[0030] 5) In the critical anomaly monitoring mode, the power monitoring node obtains transient anomaly characteristic parameters by performing critical real-time tracking processing on state variables, and solves the stability and consistency problem of transient anomaly response through transient impact quantity prediction and critical feedback monitoring; when transient distortion occurs in the power signal, it can still obtain a fast and accurate response to the transient anomaly, thus solving the balance problem between real-time performance and stability.

[0031] 6) Power monitoring nodes (such as power meters, power metering sensors, power metering sockets, etc.) can support the acquisition of power monitoring data; based on the perception and identification of load objects, power signal monitoring and abnormal response processing are carried out, and more targeted and effective protection is provided for the transients of load objects being connected or disconnected (plugged in and out).

[0032] 7) The power monitoring nodes are based on edge collaborative sensing networks and are oriented towards power consumption scenarios. All or some of the power monitoring nodes can serve as both target monitoring nodes and collaborative sensing nodes, which makes the power monitoring node equipment have good hardware reusability and wireless interoperability.

[0033] 8) The system of the present invention has the collaborative service capability of edge collaborative computing for application: the collaborative sensing node not only provides wireless network communication services, but also has the service capability of providing collaborative data processing as edge collaborative computing for sensing and monitoring applications (such as location tracking, energy monitoring, and lighting control), strong collaborative concurrent service capability, good network configuration convenience, self-healing capability, and high stability. Attached Figure Description

[0034] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0035] Figure 1 This is a flowchart of the first method for monitoring abnormal electricity consumption disclosed in an embodiment of the present invention;

[0036] Figure 2 This is a second flowchart of the power consumption anomaly monitoring method disclosed in an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the first module structure of the power consumption anomaly monitoring device disclosed in an embodiment of the present invention;

[0038] Figure 4 This is a schematic diagram of the second module structure of the power consumption anomaly monitoring device disclosed in an embodiment of the present invention;

[0039] Figure 5 This is a schematic diagram of the role relationship between power monitoring nodes and various sensing nodes in the power consumption anomaly monitoring system disclosed in this embodiment of the invention. In this diagram, G1 and G2 represent general wireless base stations (as cooperative sensing nodes), R1 to R4 represent multiplexed wireless base stations (as cooperative sensing nodes), E1 to E5 represent power monitoring nodes (target and / or cooperative sensing nodes), and S1 to S9 represent target objects (target sensing nodes): including power monitoring nodes (as target monitoring nodes) and other various target positioning / monitoring devices.

[0040] Figure 6 This is a software architecture diagram of an abnormal power consumption monitoring system disclosed in an embodiment of the present invention;

[0041] Figure 7 This is a software structure diagram of the target monitoring module running in the power monitoring node (as the target monitoring node) as disclosed in an embodiment of the present invention;

[0042] Figure 8 This is a software structure diagram of the collaborative processing module in the power monitoring node disclosed in the embodiments of the present invention (running on the target sensing node or the collaborative sensing node);

[0043] Figure 9 This is a software structure diagram of the edge collaborative information processing module in the power monitoring node disclosed in the embodiments of the present invention (running on the target sensing node or the collaborative sensing node).

[0044] When the power monitoring node acts as a target sensing node and / or a collaborative sensing node, it runs different software module configurations. Please refer to [the relevant documentation]. Figure 7 , Figure 8 , Figure 9 The corresponding software module structure diagram. Detailed Implementation

[0045] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the described embodiments are part of, but not all, of this invention, and are only used to explain the invention, not to limit it.

[0046] Example 1, please refer to Figure 1 This is a flowchart of the first method for monitoring abnormal electricity consumption according to an embodiment of the present invention. A power monitoring node in the edge domain of the Internet of Things (IoT) acts as a target monitoring node and / or a collaborative sensing node to monitor the abnormal electricity consumption status of its associated and bound power load objects. The method includes the following steps:

[0047] Step S101: The power monitoring node performs state assessment and state pattern parsing on the target monitoring information of the current power load object according to the graded abnormal conditions to obtain the abnormal state information of the load object.

[0048] Step S102: Based on the abnormal state information, when the load object is in a potentially abnormal state, start the security monitoring mode (i.e., the second monitoring mode): perform security tracking and monitoring on the abnormal state variables of the load object;

[0049] Step S103: When the abnormal state variable meets the critical abnormal condition, the power monitoring node starts the critical monitoring mode (i.e., the third monitoring mode): performs critical real-time tracking and monitoring of the abnormal state variable.

[0050] Step S104: When the abnormal state variable (in the tracked and monitored state) meets the transient abnormal condition, the power monitoring node obtains the transient abnormal response.

[0051] The implementation of the above steps is further explained as follows:

[0052] The power monitoring node obtains the target status information of the load object in energy-saving monitoring mode.

[0053] In an electricity consumption scenario, at least one power monitoring node (as a type of energy measurement node) obtains the first monitoring information (i.e., real-time monitoring data) of several target state variables of the load object in the time domain by inputting the power signal of the load object in the current monitoring mode and performing coupled acquisition and data processing in a specified signal coupling acquisition mode.

[0054] The power monitoring node, as a target monitoring node, monitors the power consumption of one or more power load objects as target objects. When the portable power socket is bound to the load object, the power socket, as a target tracking / monitoring node, has the following node role characteristics: 1) Active / passive positioning: actively discovers surrounding cooperative positioning base stations (location trust level: positioning nodes such as routers, gateways, lighting controls, and Bluetooth beacons); 2) Mobile positioning upload: only uploads positioning information when it determines that its own environmental location status (a scene status) has changed; 3) Potential anomaly triggering (a scene trigger): at least one target state variable comes from the front-end sensing node.

[0055] An edge monitoring / surveillance network system, consisting of several energy / electricity monitoring nodes (as target sensing nodes and / or collaborative sensing nodes), serves as a subset of the wireless collaborative sensing network and provides information services for energy / energy efficiency monitoring and management to surrounding target scene objects.

[0056] The energy / energy efficiency monitoring includes monitoring and metering of energy-consuming / electrical equipment (i.e., load objects) to conduct related monitoring of energy efficiency, safety, and equipment utilization.

[0057] The power / target monitoring node receives a pre-signal input from the target scene object, obtains the collected data through signal coupling based on signal front-end processing, and performs the first monitoring data processing on the collected data to obtain the first monitoring information.

[0058] The electrical energy / energy monitoring includes real-time or cumulative monitoring of any or a combination of the following electrical energy physical quantities related to electrical energy / energy supply and consumption: 1) location / area (range), 2) load node status (e.g., on / off, power-on time), 3) real-time monitored physical quantities: such as power, 4) cumulative monitored physical quantities (e.g., electricity consumption).

[0059] Electrical load includes the load consisting of electrical equipment / appliances within a specified range; the electrical load object (hereinafter referred to as the load object or electrical load) is the target object that is monitored as the electrical load;

[0060] The load object corresponds to a physical object or range of physical objects (such as electrical equipment / components, power nodes / branches), and is composed of one or more electrical equipment and / or power nodes; the load object serves as a target object in a specified power consumption scenario and corresponds to the power / target monitoring node.

[0061] An electrical load object can correspond to one or more electrical devices or electrical nodes; typically, an electrical load object or electrical device corresponds to an equipment asset code.

[0062] Multiple electrical devices can collectively form a power consumption node (intermediate node), and a single electrical device can also contain multiple power consumption nodes (branch nodes), such as power consumption nodes that monitor several branches within a computer and monitor, or a refrigerator compressor.

[0063] The aforementioned power monitoring refers to the status monitoring of power consumption, efficiency, and safety for power load objects.

[0064] The aforementioned power state variables are state variables oriented towards power monitoring, and are a type of target state variable that reflects the power consumption scenario and its power load objects.

[0065] The power consumption scenario status refers to the various physical states associated with the power consumption scenario and the load objects it contains, including current power supply parameters, energy consumption, safety and surrounding environment.

[0066] The status of the power consumption scenario includes the status of the power signal and / or the status of the load object; it may also include the environmental status related to power safety, including the internal environment of the power equipment and the surrounding environment (such as temperature, humidity, smoke, gas concentration, etc.).

[0067] Electrical energy signal status: refers to the physical state of electrical energy (AC, DC, air coupling) input / output and its coupled signals; for AC power supply, electrical energy signal status refers to AC signal status.

[0068] Load object status: refers to the transient and cumulative consumption of electrical energy by the electrical load, as well as other physical states related to the electrical load and the electrical environment.

[0069] The aforementioned safety protection state is a state in which the electrical load is tentatively detected through a safety protection circuit to determine whether an electrical load is connected and whether the safety matching conditions are met.

[0070] The probing test is a type of safety test, which is safer than direct normal power supply (i.e., without the safety test).

[0071] The exploratory detection is to detect and identify the transient state of electrical loads connected to the power supply port. It has no (or minimal) impact on normal electrical load connections, but can identify abnormal electrical load connections.

[0072] The safety protection circuit refers to the circuit that is in a state of safety detection signal when the electrical load is connected to the power supply port, including one or a combination of the following: 1) safety voltage, 3) high impedance weak signal, 4) transient overload protection.

[0073] The safety detection signal can be a step-down signal, a high-impedance signal, a weak pulse signal, a carrier signal, a mutual inductance coupling signal, a voltage divider signal, a DC signal, etc.; the safety circuit / safety voltage is used for transient detection and protection when the power supply port is in an open circuit state, from the open circuit of the electrical load to the connection of the load.

[0074] In specific implementation, the safety voltage can be a step-down signal output, a voltage divider detection circuit, or a DC detection circuit; the high-impedance weak signal refers to a protection device (such as a simple protection resistor, which can prevent transient poor contact, transient arcing, etc.) connected in series in the safety protection circuit; the overload protection includes short-circuit protection, power protection, overcurrent protection, and leakage protection.

[0075] The safety matching conditions include object matching verification of load characteristic parameters of the connected electrical load: by detecting the load characteristic parameters (including transient and / or steady-state characteristic range and stability), it is determined whether it is a normal load connection within the set matching range, and abnormal loads and / or abnormal connections are excluded, such as dummy loads, transient short circuits or poor contact, and abnormal load start-up characteristics (such as starting power, resistance and capacitance characteristics).

[0076] When the load characteristic parameters meet the critical anomaly conditions, the critical anomaly response processing can be initiated immediately; the critical anomaly conditions are included in the graded anomaly conditions.

[0077] The power socket is a power monitoring node (as a target monitoring node) that performs object matching verification on the power timing signal of the power load to determine whether it meets the safety matching conditions.

[0078] When the target monitoring node detects and identifies a load object accessing the system, the power monitoring node performs object matching verification based on the association information between the load object and the power timing signal, and determines whether the access status of the load object meets the security matching conditions.

[0079] The power timing refers to the characteristic timing of the combination of power-on and / or coupled signals, such as the zero-crossing point, signal peak, or specific phase point after a certain power-on time (or a certain AC counting cycle).

[0080] The load object is coupled with an electrical signal and responds to an electrical timing signal (as a verification trigger signal) in a response manner to send an object identification signal.

[0081] When the load object is connected to the power monitoring node during the power-on transient, the load object (or object identification tag) sends an object identification signal associated with the power timing through power signal coupling (such as peak phase coupling).

[0082] The load object or object identification tag is triggered by the association of the power timing signal and sends an object identification signal containing object identification information in an active or responsive manner.

[0083] The power / target monitoring node performs object matching and verification based on the object identification information, establishes an association and binding relationship with the load object, and obtains the monitoring mode parameter Pi through the association index of the object identification information.

[0084] The monitoring modes include energy-saving monitoring mode, safety monitoring mode, and critical monitoring mode;

[0085] The power monitoring node adjusts the corresponding monitoring mode parameters according to the current monitoring mode code, specifically including: 1) when the load is in normal operation, adopting the energy-saving monitoring mode (first monitoring mode); 2) when the load is in a potentially abnormal state, adopting the safety monitoring mode (second monitoring mode); 3) when the load enters a critical abnormal state, adopting the critical monitoring mode (third monitoring mode).

[0086] The energy-saving and critical monitoring modes are defined as monitoring modes from low to high; if necessary, the above three basic monitoring modes can be further subdivided into different sub-modes.

[0087] It should be noted that for any relatively low-level monitoring mode, when it is determined that any higher-level abnormal condition is met (including directly obtaining a hardware trigger response), it can directly enter any corresponding higher-level monitoring mode; for example, in energy-saving or safety monitoring mode, when it is determined that a transient abnormal condition is met, there is no need to enter the critical monitoring mode first, that is, the transient abnormal trigger response can be obtained directly.

[0088] Abnormal electrical conditions include potential abnormal conditions, critical abnormal conditions, and manifest abnormal conditions: 1) Potential abnormal condition: a potential or hidden abnormal operating condition that has not yet reached a critical or manifest abnormal condition; 2) Critical abnormal condition: a critical state in which a manifest abnormal condition may appear in the transient state; 3) Manifest abnormal condition: an abnormal condition that has occurred and has not yet been resolved.

[0089] The normal operating status includes the current load object being in a state of normal maintenance, shutdown (load open circuit), or a specified operating parameter range;

[0090] The potential abnormal states may include: unsafe hazards, proximity anomalies, trend anomalies, and other states that require safety monitoring / tracking.

[0091] The critical abnormal state is an unstable state that may enter an explicit abnormal state within a transient period, or it may revert to a potential abnormal state or a normal operating state.

[0092] The energy / electricity monitoring node derives the monitoring mode code based on the scenario status code Ns corresponding to the current target status information, so as to adjust the corresponding monitoring mode;

[0093] The monitoring mode code (corresponding to the target status information / scene status code Ns) is a code that reflects the potential risk range of the target object's current operating status associated with the target scene.

[0094] For example, if the target object is an electrical load object, the operating state can refer to the relative energy consumption state, which is the ratio of the current energy consumption state to the benchmark or historical year-on-year energy consumption state.

[0095] When the current load object is in normal operating condition, and before any abnormal state occurs, the monitoring mode defaults to the energy-saving monitoring mode (first monitoring mode), which is an energy-saving oriented monitoring mode.

[0096] Once the power monitoring node determines that the current load object has any level of abnormal state, it immediately enters the corresponding non-energy-saving abnormal monitoring mode, which includes a safety monitoring mode and a critical monitoring mode.

[0097] It should be noted that the adjustment methods for the mode parameters of the energy-saving monitoring mode include:

[0098] 1) Set the data acquisition / processing mode parameters corresponding to lower power consumption (such as reducing the data acquisition cycle and processing cycle);

[0099] 2) Reduce the amount of data collected or calculated: such as time-sliding statistics, reduce the tracking and calculation of state variables;

[0100] 3) Set the low-power wireless mode parameter Pi (such as reducing wireless scanning activity, broadcast frequency and power), and periodically turn on other wireless modes (such as WiFi, Ethernet, 4G / 5G) or reduce their duty cycle.

[0101] 4) Reduce the data upload frequency (e.g., extend the scheduled upload period) or reduce the data upload volume (e.g., increase the time interval for variable data, remove variable data with small changes).

[0102] The monitoring mode includes a safety monitoring mode, which is executed when the power monitoring node determines that the current load object is in a potentially abnormal state.

[0103] The security monitoring mode is between the energy-saving and critical monitoring modes. It requires more resources (such as computing power, power consumption, data storage and uploading) than the energy-saving monitoring mode to solve problems such as real-time sensitive response, monitoring records and anomaly handling.

[0104] Compared to the energy-saving monitoring mode, the purpose and main problems to be solved by the safety monitoring mode include:

[0105] 1) Sensitive Response: By performing security tracking and monitoring / processing of abnormal state variables, it has a more sensitive response speed and stronger resource processing capabilities for more advanced critical or transient anomaly triggers.

[0106] 2) Monitoring records: Save more complete and continuous anomaly monitoring information, such as anomaly sensitive point variable tracking (first monitoring information), anomaly segment statistics (second monitoring information), and anomaly handling logs;

[0107] 3) Anomaly handling: Perform pre-planned anomaly handling (or preprocessing) based on the current anomaly level (before higher-level anomalies): such as data protection (for high-priority data), anomaly indication, and alarms.

[0108] The monitoring mode includes a critical monitoring mode, which is executed when the power monitoring node determines that the current load object is in a critical abnormal state.

[0109] Compared to the security monitoring mode, the critical monitoring mode requires concentrated computing power to perform real-time tracking and processing of abnormal state variables. By predicting transient abnormal characteristics in real time, the pre-trigger conditions are adjusted in response to the transient abnormality, thereby achieving a faster (lower latency) sensitive response to the triggering of transient abnormalities.

[0110] Critical monitoring mode refers to the process of real-time tracking of abnormal state variables. Based on the degree of convergence between the current transient abnormality characteristic parameters and the transient abnormality conditions, the pre-trigger conditions are dynamically adjusted by feedback to the front-level (including the front-level node and / or the front end of this node). This allows for more sensitive acquisition of the corresponding transient abnormality trigger response when the transient abnormality conditions are met.

[0111] The abnormal power consumption status includes any or a combination of the following abnormal statuses:

[0112] 1) Transient abnormal state: refers to the abnormal state of the value of any state variable in one or a short period of time, such as N sampling cycles;

[0113] 2) Cumulative abnormal state: An abnormal state of indicators occurs due to the evaluation of one or more combinations of state variables within a certain period of time.

[0114] The power monitoring node (based on signal acquisition data) obtains the first monitoring information through first monitoring data processing; then (by the node itself or surrounding collaborative sensing nodes) obtains the second monitoring information through second monitoring data processing (a limited sensitivity processing) based on the first monitoring information.

[0115] The power monitoring node itself and / or surrounding collaborative sensing nodes respond to the scene state and, facing the target scene object, obtain the target state information by evaluating the target state information through the target monitoring information; the target monitoring information includes first monitoring information and second monitoring information.

[0116] The target state assessment is a limited sensitivity process, which includes the screening, citation, and assessment of the first and second monitoring information.

[0117] The power monitoring node obtains the first monitoring information (i.e., real-time monitoring data acquisition) of several state variables Xi (in the time domain) of the current load object through power signal acquisition and processing;

[0118] The power monitoring node (as a target monitoring node) makes a real-time judgment on the first monitoring information based on the critical anomaly conditions: whether the load object is in a critical anomaly state.

[0119] The power signal acquisition and processing includes obtaining the first monitoring information (i.e., real-time acquisition monitoring data) of several state variables Xi (in the time domain) through coupled acquisition and data processing of the power signal input.

[0120] The data processing includes first monitoring data processing of the collected power signal data, including: pre-digital filtering, feature variable extraction, and variable tracking processing.

[0121] The coupling acquisition refers to signal coupling and AD acquisition of DC or AC (single-phase or multi-phase) electrical energy (transmission or supply); the signal coupling includes one or a combination of the following methods:

[0122] 1) Current coupling: direct sampling coupling (such as alloy resistors), current transformer coupling; 2) Voltage coupling: detection transformer / transformer, step-down / voltage divider unit; 3) pre-signal isolation coupling; 4) signal amplification and filtering unit.

[0123] The power monitoring node performs second monitoring data processing on the first monitoring information according to the current monitoring mode to obtain second monitoring information. Then, it derives the monitoring mode code and mode parameters (corresponding to the power consumption scenario status code Ns) through state mode parsing (based on scenario state parsing). Based on the monitoring mode code and its associated mode parameter Pi, it executes the monitoring mode and mode processing corresponding to the monitoring mode code.

[0124] The power monitoring node performs state mode analysis based on the graded abnormal conditions matched with the load object. When the load object is assessed to be in an abnormal state, the corresponding abnormal monitoring mode is immediately activated, including: 1) when the load object is in a potential abnormal state, the safety monitoring mode is activated; 2) when the load object is in a critical abnormal state, the critical monitoring mode is activated.

[0125] The judgment conditions for entering or exiting different levels of abnormal states are asymmetric (in the time domain and / or value domain): from normal to abnormal state, it takes effect immediately when the current characteristic parameter conditions are met; conversely, from abnormal to normal state (or from high-level abnormal to low-level abnormal state), after the current characteristic parameter conditions are met, a certain observation period is required as the judgment condition for the abnormality to be resolved.

[0126] The state mode parsing is as follows: the power monitoring node evaluates the monitoring mode in terms of safety, energy saving, real-time response capability and system data requirements based on the current target state information and energy efficiency assessment feedback (in a dynamic balance manner / strategy); the target state information is obtained by processing several state variables in the current target monitoring information through state evaluation.

[0127] The monitoring mode code (a scenario status code) is obtained by dynamically parsing the target state information, and the corresponding monitoring mode parameters are obtained according to the index of the monitoring mode code.

[0128] The aforementioned balance orientation assessment refers to a weighting strategy that balances factors such as resource power consumption, response speed, and data processing capability based on balance orientation parameters when selecting the current monitoring mode.

[0129] Wireless collaborative sensing network (hereinafter referred to as sensing network) is a wireless network in the edge domain of the Internet of Things (IoT) that consists of collaborative sensing nodes (as network service nodes) and provides collaborative sensing services (including object identification, location tracking, status monitoring, control monitoring and information push) to surrounding target devices.

[0130] The collaborative sensing node is a network node role with collaborative sensing service capabilities, that is, a wireless network node in the collaborative sensing network that has the ability to provide collaborative sensing services to surrounding target devices.

[0131] The collaborative sensing node is a collaborative service node that faces surrounding target objects and other sensing nodes. It can be a wireless base station device or a general sensing node. The sensing node is a network node that can perform sensing and monitoring of target objects.

[0132] The collaborative sensing refers to the process by which multiple sensing nodes in a wireless network perform sensing monitoring and related services through collaborative sensing processing, targeting a common target scene or a subset thereof (including the target object).

[0133] The target scene object is the target object associated with the target scene;

[0134] The target scene (hereinafter referred to as scene) is a combination of several target objects and their location environment within a given physical space-time; the target scene may contain several subsets of target scenes.

[0135] Sensing and monitoring equipment refers to devices with wireless sensing and monitoring capabilities, including target sensing nodes (as target object devices or scene sensors) that directly perform sensing and monitoring of target scene objects, or collaborative sensing nodes that perform sensing and monitoring of front-end sensing nodes.

[0136] Target state information refers to information describing the state of the target scene and its changes;

[0137] The collaborative sensing node obtains target status information by sensing and monitoring target objects within the wireless coverage area associated with the target scene (using wireless scanning detection).

[0138] A cooperative positioning base station is a wireless network node (base station equipment) with wireless cooperative positioning service capabilities;

[0139] The collaborative positioning base station is a device role that constitutes the collaborative sensing network, and its physical form includes, but is not limited to, light control sensing nodes.

[0140] As a type of energy monitoring node, the power monitoring node is a target monitoring node used to monitor the power consumption of electrical load objects. Its node role can be either a target sensing node or a collaborative sensing node.

[0141] The power monitoring node is a collaborative service node with multiple device roles, including a target monitoring / monitoring / tracking node, a wireless linkage node / beacon base station, and a collaborative sensing node / positioning base station.

[0142] The lighting control sensing node / power monitoring node can be reused as a target / cooperative sensing node, providing cooperative sensing services to surrounding target objects based on wireless data reception response.

[0143] The mode parameters are associated with the scene state and include data information such as code, index, process, and parameters corresponding to the given mode;

[0144] The pattern processing, or pattern data processing, includes the process of data processing and information services such as data calculation, operation / control / monitoring, data storage / transmission / upload / push for a given pattern.

[0145] Target perception node / target monitoring node is a network node role that directly perceives and monitors target objects (using built-in sensors);

[0146] Target sensing nodes are the target objects served by the collaborative sensing network and its collaborative sensing nodes, including target positioning / tracking / monitoring nodes, and sensing and monitoring devices that have established association or binding relationships with the target objects they serve.

[0147] The mode parameters include the operation target parameters and / or operation mode parameters. Adjustments to the mode parameters include parameter assignment, parameter increment, parameter function calculation, and other adjustment operations.

[0148] Implementation example: Data structure for scene-triggered response:

[0149] 1) Sensor (Unknown type): [Search] Device name / Device ID or MAC --> Device type code;

[0150] 2) Sensor (known class), [index] Device type code --> Scene status code, [Monitoring variable 1,...Monitoring variable n];

[0151] The sensor refers to the target sensing node.

[0152] The power socket is a smart socket with safety protection capabilities, and also a metering and monitoring socket, serving as a target monitoring node for monitoring the power consumption of the load.

[0153] The power socket includes multiple power outlets. When the power socket detects that a power load is connected to a particular power outlet, it establishes a dynamic power node pairing between the power outlet and the power load through object matching verification. Each power outlet in the power socket is an independent target monitoring node.

[0154] The pairing operation enables the power monitoring node / power socket to obtain the identification ID information of the load object (and save and / or upload it), thus establishing a pairing relationship between the target monitoring node and the power load.

[0155] The object identification information may include object ID, associated attributes, and pattern parameters, etc.

[0156] The object identification information comes from the built-in and / or external object identification tag (virtual digital tag or hardware electronic tag) module / device of the load object.

[0157] In specific implementation, the pairing operation includes any one or a combination of the following methods:

[0158] 1) Wireless pairing operation: Enter pairing mode through hardware triggering (such as button pressing), wireless triggering (such as initiating connection), and / or automatic pairing through proximity recognition (such as judging RSSI or RFID sensing);

[0159] 2) Use authorized software tools (such as APP) to read or input the object identification information and write (send) it to the power monitoring node / power socket;

[0160] 3) The host computer or collaborative server configures and writes the ID information into the target monitoring node / power socket.

[0161] The sensing node / target monitoring node can enter a monitoring mode with different value orientation strategies (such as monitoring accuracy / real-time performance, data upload continuity / real-time performance, and its own power consumption) by adjusting the following mode parameters and their combinations (such as high-speed / full-speed acquisition, real-time / timed upload, low-power energy saving, etc.).

[0162] It should be noted that, typically, the monitoring modes include:

[0163] 1) Signal coupling acquisition mode: signal coupling parameters, AD acquisition mode parameters (such as acquisition period), acquisition preprocessing mode (such as filtering mode parameters), etc.; types and default modes of various state variables;

[0164] 2) Monitoring data processing mode: data processing parameters (processing cycle, sensitive processing parameters, data selection / removal / statistical parameters), process variable types and algorithm accuracy, data storage area management parameters and data storage mode, etc.;

[0165] 3) Wireless data transmission mode: On / off of wireless mode (such as BLE, WiFi, Ethernet, 4G / 5G), wireless communication mode (such as power level and modulation method, scanning / broadcast time period, interval / phase, time slot width, duty cycle, etc.);

[0166] 4) Data upload mode: The target monitoring node, as an edge node, uploads data to the host or management system in real time, on a timed basis, actively or passively.

[0167] Example 2, please refer to Figure 2 This is a flowchart of the second method for monitoring abnormal electricity consumption disclosed in an embodiment of the present invention. A power monitoring node in the IoT edge domain acts as a target monitoring node and / or a collaborative sensing node to monitor the abnormal electricity consumption status of its associated bound power load objects. The method includes the following steps:

[0168] Step S201: When the load object is in a critical abnormal state, the power monitoring node obtains the transient abnormal characteristic parameters of the load object through critical real-time tracking processing.

[0169] Step S202: Based on the transient anomaly characteristic parameters, the power monitoring node adjusts the pre-trigger conditions corresponding to the transient anomaly conditions through critical feedback monitoring.

[0170] Step S203: When the front-end input signal being tracked and monitored meets the pre-triggered condition, the power monitoring node obtains a transient abnormal response.

[0171] The implementation of the above steps is further explained as follows:

[0172] The power monitoring node (as a collaborative sensing node) obtains the corresponding mode parameter Pi by indexing the scene state code Ns according to the abnormal / scene response plan (associated with the scene trigger response) corresponding to the critical abnormal state, and performs the critical abnormal response processing based on the mode parameter (mode processing flow).

[0173] The anomaly response handling is a type of mode handling, including scene mode control / group control, monitoring data processing / limited sensitivity processing, and other scene-related information services (such as service beacon broadcasting, collaborative positioning and tracking, and anomaly alarms).

[0174] Regarding the aforementioned Figure 1 , Figure 2 The implementation of the flowchart steps is further explained below:

[0175] When the power monitoring node receives a transient anomaly response, it immediately triggers its own and / or associated node's transient protection control module to perform transient anomaly protection on the load object in the transient anomaly state.

[0176] The transient abnormal states include: 1) Power supply abnormalities: such as undervoltage, overvoltage, power failure, three-phase imbalance, distortion, flicker and interference, etc.; 2) Overload abnormalities: such as overcurrent, overvoltage, overload power; 3) Leakage abnormalities: ground wire leakage current, current difference between live wire and neutral wire, live wire leakage current when the power is off; 4) Abnormal power environment: such as overheating inside the electrical equipment, high ambient air temperature or humidity.

[0177] The transient anomaly state is a state that meets the transient anomaly condition (matches the transient anomaly characteristic parameter); the transient anomaly condition is included in the hierarchical anomaly condition;

[0178] Transient anomaly protection is implemented using either flashover protection or time-delay protection based on the transient anomaly characteristic parameters and their corresponding classifications.

[0179] The aforementioned flashover protection refers to cutting off the power supply to the power supply line or power circuit with minimal transient delay, or switching to a safety protection circuit.

[0180] The time-delay protection refers to the protection measure that restores the power supply to normal through a backup power source (such as an inverter) when the power supply voltage is abnormal.

[0181] The power monitoring node selects an appropriate transient protection mode and corresponding coverage range that matches the assessment based on the urgency and coverage of the current protection needs for the associated load objects and the balance assessment between the protection needs and the protection costs. The transient anomaly protection is then lifted or the current transient anomaly state is mitigated.

[0182] In the specific implementation process, the target monitoring node itself has a weak ability to protect its associated load objects from anomalies, and the associated protection node is required to protect the load objects from anomalies.

[0183] The target monitoring node (regardless of whether it has strong abnormal protection capabilities) does not need to adopt a transient protection method with high protection costs based on the current abnormal power consumption state (for example, stopping its power load operation may incur associated risks). However, it is necessary to first adopt a more appropriate transient protection method (such as simply cutting off power to a branch or accessory equipment to relieve or mitigate the current critical abnormal state).

[0184] The associated protection node refers to a node that has the ability to provide associated protection for some or all of the load objects currently monitored by the target monitoring node; that is, the load objects that the associated protection node can protect have an associated subset with the power load objects currently monitored by the power monitoring node.

[0185] The associated protection node refers to a node that can protect the current transient abnormal state of the associated object node; the associated object node includes power supply node, power consumption node, monitoring node and other protection node, and the power consumption node includes power load equipment and its power branch node.

[0186] The associated protection node adopts different transient protection methods in different ways, at different levels, and in different sequences for different transient abnormal characteristics of the associated object node, including: mitigation (such as reducing the power consumption of branch loads or non-critical load objects), suppression (such as enhancing the ability to suppress transient abnormal pulse signals), switching (such as switching to a backup or safety circuit), and power outage (such as cutting off the associated load or its upstream power supply or downstream branch).

[0187] The associated protection nodes include switches, devices (smart sockets, smart switches), protectors, and other equipment that provide transient protection for power supply lines / nodes and power branch circuits / nodes; the associated protection nodes may or may not be target monitoring nodes or collaborative sensing nodes.

[0188] When the power monitoring node receives the transient anomaly response, it triggers the associated protection node to perform linked transient protection on the load object (or subset) by sending an anomaly trigger signal.

[0189] The abnormality trigger signal includes abnormality status and abnormality level information;

[0190] The abnormality trigger signal is an abnormality trigger status beacon that includes an abnormality status identifier; the abnormality status identifier is a status identifier that includes an abnormality / scenario status code.

[0191] The protection cost refers to the direct or risk cost incurred by providing transient protection to the associated load object; the coverage area refers to the coverage area of ​​the associated protection node for the electrical load object.

[0192] The protection cost of selecting a certain transient protection mode is the sum of the protection costs for all associated electrical load objects under the selected transient protection mode for the associated protection nodes within the coverage area to perform transient anomaly protection.

[0193] The triggering state beacon is a state beacon (such as a radio beacon or carrier beacon) sent by a forward sensing node at a higher activity level than the non-triggering normal state by adjusting its beacon broadcast / modulation parameters, thereby triggering surrounding associated cooperative sensing nodes to receive and respond.

[0194] The trigger status beacon is a status beacon containing specific trigger information; the trigger information is used to indicate / remind the recipient of a response.

[0195] The activity level refers to the adjustment of the radio frequency signal capability and / or specific dominant channel occupancy of a status beacon based on beacon broadcast / modulation parameters; the beacon broadcast / modulation parameters include the beacon broadcast interval, duration, power level, phase slot, frequency channel, and other modulation parameters.

[0196] The target monitoring node performs object matching verification by receiving the object identification signal sent by the load object and the corresponding object identification information, so as to configure and adjust the monitoring mode parameters that match the currently accessed load object. The monitoring mode parameters include at least the corresponding hierarchical abnormal conditions and / or abnormal handling plans.

[0197] The monitoring mode parameters include the mode parameter Pi for the target monitoring node to process the monitoring data of the load object, and the hierarchical abnormal conditions for parsing the state mode based on the current monitoring information.

[0198] The abnormal states include abnormal power supply from the power grid and / or abnormal power consumption by the load; the abnormal conditions refer to the judgment conditions corresponding to different levels of abnormal states.

[0199] The abnormal state levels include potential abnormal states (latent abnormal states), critical abnormal states, and explicit abnormal states.

[0200] It should be noted that the graded anomaly conditions include the judgment conditions for the current variable characteristic parameter range and its time-domain change characteristic parameter range; typically, the judgment conditions for entering or exiting different levels of anomaly states have asymmetry in the time domain and / or value domain; for example, from normal to anomaly state (or from low-level anomaly to high-level anomaly state), it can take effect immediately when the current characteristic parameter conditions are met; conversely, from anomaly to normal state (or from high-level anomaly to low-level anomaly state), after the current characteristic parameter conditions are met, a certain observation period is still required as a cooling-off time for the anomaly to be resolved.

[0201] The hierarchical anomaly conditions include potential anomaly conditions, critical anomaly conditions, and transient anomaly conditions;

[0202] The power monitoring node performs state mode parsing based on the graded anomaly conditions (for the current target monitoring information), including: judging the target scene state associated with the load object based on the graded anomaly conditions: 1) when the potential anomaly conditions are met, enter the potential anomaly state; 2) when the critical anomaly conditions are met, enter the critical anomaly state; 3) when the transient anomaly conditions are met, immediately trigger transient anomaly protection processing.

[0203] Based on the aforementioned graded anomaly conditions, determine the classification / level of the anomaly state:

[0204] The graded abnormal conditions also include the judgment of the operating status of the power monitoring node (or system) itself, such as the abnormal conditions for judging the status of network outage, power-on restart, communication timeout, self-test abnormality, etc.

[0205] The critical anomaly condition is the condition used to determine whether the load object has entered a critical anomaly state based on the current state variable and its transient expected value. The state variable is included in the first monitoring information.

[0206] The potential anomaly conditions are the conditions used to determine whether a load object is in a potential anomaly state when performing state pattern parsing.

[0207] The aforementioned abnormal handling plan refers to the scenario response plan for a critical abnormal state (a critical triggering state);

[0208] Critical anomaly response handling is a type of critical response handling (anomaly handling based on critical response); while setting critical feedback monitoring, data protection, anomaly alarms, and anomaly protection can be performed in parallel, or any combination thereof.

[0209] The critical feedback monitoring refers to the current collaborative sensing node or its preceding sensing node, under critical triggering conditions, (based on the current sensing and monitoring mode) adjusting the signal front end of its own node or preceding node based on the monitoring and collection information of the target state variable in the time domain and the judgment (including calculation or query) of the approach degree of the transient triggering response, so as to compare and monitor the current front-end input signal in real time, and obtain the transient triggering response when the preceding triggering conditions are met.

[0210] The front-end input signal is a coupling signal before data acquisition of the target state variable;

[0211] The feedback adjustment includes signal coupling adjustment (such as adjusting the coupling loop, attenuating the gain) and / or adjusting the reference or rated value of the rated comparison signal;

[0212] The feedback adjustment methods include one or a combination of the following: 1) the collaborative sensing node performs feedback control on the target monitoring node as a front-end node (such as sending active control information); 2) the back-end processing unit of the target monitoring node sets the feedback of its own signal front-end (processing module).

[0213] The target sensing / monitoring node, based on the critical signal feedback unit (included in the signal front-end processing module), performs real-time comparison between the front-end input signal and the current rated comparison signal to obtain a transient trigger response when the pre-triggered conditions are met.

[0214] In a critical abnormal state, the critical abnormal response refers to the response obtained when the transient pulse corresponding to a certain electrical energy / target state variable is about to reach a specified abnormal value.

[0215] The critical anomaly response refers to the preparatory response with a certain transient time advance obtained when the transient pulse reaches the critical anomaly value but has not yet reached the specified anomaly value.

[0216] During the access or operation of the power load object, the power monitoring node performs critical real-time tracking and processing of power state variables, including calculating / judging the current value and / or predicted value, and dynamically adjusting the pre-trigger conditions of the critical feedback monitoring based on the degree of convergence of the current critical abnormal state to the transient abnormal characteristic parameters.

[0217] The aforementioned pre-triggered condition refers to the trigger condition set by the power monitoring node for its monitoring signal front end, which can be directly formed without further monitoring data processing.

[0218] By setting pre-trigger conditions for different levels of anomalies based on the feedback of graded anomalies, a corresponding level of anomaly trigger response can be obtained when the graded anomaly conditions are met.

[0219] The power monitoring node dynamically adjusts the pre-trigger conditions corresponding to the graded abnormal conditions through feedback, thereby tracking and monitoring abnormal states at different levels.

[0220] The power monitoring node adjusts the pre-triggered conditions by setting a rated comparison signal and / or tracking the monitoring time step.

[0221] The front-end input signal is a signal that has been adjusted by signal coupling. Through pre-comparison signal correction, the front-end input signal is made comparable to the rated comparison signal.

[0222] The rated comparison signal refers to the reference signal output through the D / A conversion feedback. The monitoring signal front end (such as a voltage comparator) compares the front end input signal with the rated comparison signal to obtain the corresponding abnormal trigger response when the pre-trigger condition is met.

[0223] The classification anomaly handling includes data protection processing:

[0224] The data protection process is performed on unprotected data (data not saved offline and whose upload has not been confirmed) in order of priority, according to the following different monitored data types:

[0225] First priority: Current clock, device hardware status, data area management pointer;

[0226] Second priority: Current real-time monitoring data buffer data, current logs (such as clock correction logs, exception handling logs);

[0227] Third priority: Current historical monitoring data buffer data.

[0228] The data protection process will be activated under the following abnormal conditions: 1) In the offline state, data protection processing will be performed periodically for abnormal state data that has not been uploaded; 2) Data protection processing will be activated immediately upon power failure detection interruption response or other transient abnormal response.

[0229] The data protection process refers to backing up and saving the data to be protected to non-volatile storage.

[0230] The data protection includes offline protection of the clock calibration log:

[0231] When the target monitoring node restarts due to power failure or fault reset, a power-on ID is generated immediately after power-on, and at least one corresponding time correction record is generated and added to the clock correction log within the subsequent continuous time period; if a power-on ID cannot successfully correspond to a time correction record, it is treated as an uncorrectable time.

[0232] The classified anomaly handling includes sending anomaly triggering status beacons via wireless broadcast to push anomaly triggering information. Surrounding collaborative sensing nodes then provide anomaly alarms and / or anomaly protection based on the wireless sensing response.

[0233] When the load object is in an abnormal state, the power monitoring node will implant the abnormal state identifier and several associated state variables into an abnormal trigger state beacon (a scenario service beacon containing abnormal level information).

[0234] The abnormal protection includes: providing various abnormal protections (flashover protection, time delay protection, or power outage protection) to the power supply lines or circuits of the electrical load in a direct or linked manner.

[0235] When the lighting control sensing node receives the abnormal trigger status beacon, it performs one or a combination of the following mode processing in a multi-role mode:

[0236] 1) Role 1. Tracking and Monitoring: The light control sensing node acts as a cooperative positioning base station to provide tracking and monitoring services for the power monitoring node, which is the target tracking node;

[0237] 2) Role 2 linkage response: The lighting control sensing node acts as a collaborative sensing node, providing linkage response services to the power monitoring node, which acts as a front-end sensing node;

[0238] 3) Role 3 Abnormal Alarm: The lighting control sensing node, as a lighting load, responds to the trigger status beacon sent by the power monitoring node, which includes an abnormal status identifier, and executes the corresponding scene mode control / group control in a wireless linkage alarm manner.

[0239] Based on the aforementioned pattern processing -- scene pattern control / group control

[0240] Send linked alarm information via scenario service beacons / targeted service beacons.

[0241] In a critical abnormal state, the target monitoring node, based on the tracking and acquisition of power / target state variables, identifies that the currently monitored load object is in a critical abnormal state, and (through critical abnormal response processing) performs real-time monitoring and processing of transient abnormal characteristic parameters: when the transient abnormal conditions are met, a transient abnormal trigger response is obtained, and the transient protection control module (of itself and / or associated nodes) is immediately triggered to perform transient abnormal protection on the load object (in a transient abnormal state).

[0242] The transient anomaly condition is the state that matches the transient anomaly characteristic parameters and meets the transient anomaly condition.

[0243] The power monitoring node performs transient anomaly protection in at least one of the following ways according to the transient protection mode:

[0244] Method 1, Single-point transient protection: The power monitoring node immediately triggers the transient protection control module of its own node device to perform transient anomaly protection on the load object;

[0245] Method 2, Linked Transient Protection: The power monitoring node (based on the current scenario status code) triggers the associated protection node (as a power monitoring node or a collaborative sensing node) to perform the transient anomaly protection on the load object through wireless scenario linkage.

[0246] The transient protection mode is included in the anomaly handling plan information, or depends on the default mode corresponding to its own node attributes.

[0247] The surrounding associated protection nodes activate the transient anomaly protection according to the received anomaly trigger signal and the trigger response priority:

[0248] When the required protection level is low, only the associated protection nodes with higher priority need to activate transient anomaly protection; while when the required protection level is high, the associated protection nodes with lower priority need to activate transient anomaly protection; until all associated protection nodes activate transient anomaly protection when necessary.

[0249] The abnormal trigger signal includes (associated with the scene status code) a transient protection mode (or has a corresponding relationship);

[0250] The transient protection mode includes the currently required protection level code (or a corresponding relationship).

[0251] The power monitoring node performs critical real-time tracking processing (indexing / calculation / judgment) on the power / target state variable X(t) based on the critical anomaly response. At the rising edge of the transient pulse, the transient impact quantity Px is monitored and predicted in real time through critical feedback monitoring. If the transient impact quantity Px will reach or exceed its preset transient impact rating value Pm, a transient anomaly trigger response is immediately obtained (and the transient anomaly protection is triggered).

[0252] The transient impact quantity Px refers to the destructive impact quantity (energy) of the electrical energy signal predicted by the algorithm (correlated with the characteristic parameters of the load object) based on the time-domain change characteristics of the electrical energy / target state variable in a critical abnormal state.

[0253] In actual implementation, the transient impact quantity Px or its increment is calculated based on the transient impact time δt exceeding the critical value Xr.

[0254] The target monitoring node is based on the critical anomaly response and performs critical feedback monitoring on the transient impact quantity Px of the transient pulse: when the transient anomaly condition is met, a transient anomaly trigger response is obtained, and transient anomaly protection for the load object is immediately triggered.

[0255] Its advantage lies in that, based on the critical anomaly response, by predicting the anomaly characteristics in real time (and adjusting the pre-triggering conditions), the transient anomaly protection can be triggered more quickly before the transient overload is reached, so that the transient anomaly protection can be triggered more timely (with minimal transient delay).

[0256] At the rising edge of the transient pulse, the critical real-time tracking process is used to determine the critical abnormal response when the state variable X(t) reaches the critical value Xr as the critical abnormal condition.

[0257] Based on real-time prediction of transient impact Px, critical feedback monitoring is performed, and when the pre-triggered condition (as a transient anomaly condition) is met, the transient anomaly trigger response is obtained.

[0258] Its advantage lies in the fact that if we rely solely on real-time judgment of transient anomalies, it may be impossible to judge overload in a timely and accurate manner due to insufficient time-domain resolution of power signal acquisition and / or software delay issues, resulting in additional delay before triggering transient anomaly protection.

[0259] Based on the critical anomaly response, according to the critical phase φr or the corresponding critical time corresponding to the critical value Xr, the tracking monitoring time step Δt and / or the rated comparison signal Xm are set by feedback to perform the critical feedback monitoring on the front-end input signal, so that when the pre-trigger condition is met, the transient anomaly trigger response can be obtained directly without any further monitoring data processing.

[0260] Based on the transient impact quantity Px formed by the state variable X(t) and the tracking and monitoring time step Δt, the rated comparison signal Xm is calculated and derived from the transient increment of the transient impact quantity Px.

[0261] The transient impact quantity Px is based on the state variable X(t) reaching the critical value Xr. That is, at the critical time, the transient impact quantity Px = 0. Thereafter, the transient increment is calculated successively. Before the transient abnormality trigger response is reached, the time step Δt of the tracking and monitoring is repeatedly fed back and / or the rated comparison signal Xm until the critical abnormality state is exited.

[0262] For an AC power signal with a current period of T, when the power monitoring node obtains a critical abnormal response, it predicts and calculates the transient impact by indexing the critical transient function P(φr) and using the formula Px = T * P(φr).

[0263] The critical transient function P(φr) is a monotonic (decreasing) function that reflects the relationship between the transient impact quantity and the critical phase φr, and is within the rising edge interval of a single transient pulse (φr(0,π / 2)).

[0264] Once the critical value Xr is given, the critical transient function P(φr) can be pre-calculated (e.g., during initialization) to form a corresponding array that can be indexed quickly in real time;

[0265] By using this feedback to set the tracking and monitoring time step Δt and / or the rated comparison signal Xm, the critical feedback monitoring of the front-end input signal can be performed directly without any further monitoring data processing, and a rapid trigger response that meets the transient abnormal conditions can be obtained directly.

[0266] In critical monitoring mode, based on the transient rated value Xm given for a certain power state variable, the corresponding minimum allowable critical phase φr and the corresponding tracking monitoring time step Δt are calculated.

[0267] Within the time step Δt, once the power monitoring variable reaches the transient rated value Xm, a transient anomaly trigger response is directly obtained.

[0268] Outside of the time step Δt, even if the critical abnormal response is obtained, the transient abnormal trigger response cannot be obtained directly.

[0269] The rated comparison signal Xm is compared with the front-end input signal X(t) by a voltage comparator to quickly obtain the trigger response corresponding to the pre-triggered condition.

[0270] The rated comparison signal Xm is a transient voltage waveform signal generated by D / A conversion, which is used to compare with the front-end input signal X(t) to form a hardware trigger signal for fast comparison;

[0271] By performing pre-comparison signal correction (e.g., inverse correction by signal gain), the front-end input signal (after signal coupling adjustment) is made comparable to the rated comparison signal.

[0272] The power monitoring node, based on the transient impact quantity Px, predicts the allowable transient impact increment Pm–Px within the currently given tracking and monitoring time step Δt, and sets and adjusts the transient rated value Xm of the rated comparison signal:

[0273] Pm–Px=Q((X(t)+Xm) / 2)Δt, where Q(X) is the transient impact simulation calculation function;

[0274] Approximately, Pm–Px=((X(t)+Xm) / 2–Xr)Δt, where Xr is the critical value for the state variable X(t) to form a transient shock, and Pm is the rated value of the transient shock.

[0275] The transient voltage rating Vm(φ) or transient current rating Im(φ) is obtained from the transient rating Xm(φ) through equivalent conversion. Then, a rated comparison signal corresponding to the transient voltage rating in reverse signal gain is generated through D / A conversion. The monitored front-end input signal is compared with the rated comparison signal through a comparator to quickly obtain the trigger response corresponding to the transient rating Xm.

[0276] When the transient impact quantity Px is an impact quantity exceeding the preset power threshold value Wr,

[0277] Monitoring the transient power rating Xm(φ) can be approximately transformed into monitoring the transient voltage rating Vm(φ) and / or the transient current rating Im(φ) respectively.

[0278] During implementation, the following approximate judgment can be made: Vm(φ)=Xm(φ) / I(φ), Im(φ)=Xm(φ) / V(φ).

[0279] Under critical abnormal conditions, the transient impact quantity Px refers to the (destructive) impact quantity formed by the electrical energy / target state variable X(t) within an impact time δt exceeding the preset critical value Xr:

[0280] Px=∫Q(X(t))dt, where Q(X) is the transient impact simulation calculation function;

[0281] It can be approximately expressed as: Px=∫(X(t)-Xr)dt, where X-Xr is the average impact amount of X(t) exceeding the critical value Xr within the impact time δt.

[0282] The state variable X(t) can refer to variables such as current i(t), voltage u(t), and power w(t);

[0283] It should be noted that the absolute value is taken in different phase intervals (or the critical value Xr is equivalently adjusted to be in phase with X(t));

[0284] The transient impact time δt refers to the (destructive) transient pulse width time from the rising edge of the state variable reaching the critical value Xr to the falling edge of Xr.

[0285] Under critical abnormal conditions, for AC power signals, the transient pulse is a given periodic transient pulse, and the transient impact quantity Px is the impact quantity formed within a single period exceeding a preset critical value Xr within the transient impact time δt; by replacing the transient time t with the transient phase φ, the predicted value of the transient impact quantity can be obtained:

[0286] Px=∫Q(X(φ)-Xr)dφ=Px=T*P(φr),

[0287] For a given critical value Xr, in the current AC signal period T, the predicted value of the transient impact quantity is only related to the critical transient function P(φr), where φr is the critical phase φr corresponding to the rising edge of the transient pulse and the critical value Xr.

[0288] According to the current timing system, the transient phase has a certain linear correspondence with the current timing value or count value; typically, the transient phase is a zero-crossing phase.

[0289] If the transient pulse is approximately an AC sinusoidal pulse, the transient impact quantity Px is the impact quantity formed within the transient impact time δt that exceeds the preset current threshold value Xr; by replacing the zero-crossing time t with the zero-crossing phase φ, the predicted value of the transient impact quantity Px can be obtained:

[0290] Px=∫(X(t)-Xr)dt, where X(t)=Xp*sin(ωt),

[0291] therefore,

[0292] Px=1 / ω∫ φr π-φr (Xp*sinφ-Xr)dφ=T / 2π*Xr*(2cotφr+2φr-π).

[0293] Where φ = ωt, ω = 2π / T, ω and T are the angular frequency and period of the AC signal, respectively; Xr = Xp * Sinφr, Xp is the amplitude of the AC current signal.

[0294] If the transient pulse is approximately an AC sinusoidal pulse, and the transient impact quantity Px is the impact quantity exceeding the preset power threshold value Xr within the transient impact time δt, then by replacing the zero-crossing time t with the zero-crossing phase φ, the predicted value of the transient impact quantity Px can be obtained:

[0295] Px=∫(X(t)-Xr)dt, where X(t)=Xp*sin 2 (ωt), therefore

[0296] Px=1 / ω∫φrπ-φr(Xp*sin 2 φ-Xr)dφ

[0297] =1 / ω*(Xp(π / 2-φr)+Xr(cotφr+2φr-π));

[0298] Where φ = ωt, ω = 2π / T, ω and T are the angular frequency and period of the AC signal, respectively; Xr = Xp * Sin 2 φr and Xp are the amplitudes of the AC power signal.

[0299] When the critical value Xr approaches or equals the transient peak value, based on the critical feedback monitoring of the transient peak value: when the predicted value Xp of the transient peak value exceeds the preset value Xp', a transient anomaly trigger response is obtained in advance.

[0300] If the transient pulse is approximately an AC peak pulse, and the critical abnormal response corresponds to the critical zero-crossing phase φr, then the predicted value of the transient peak is: Xp = Xr / Sinφr.

[0301] The critical zero-crossing phase φr is the phase difference (0 < φr < π / 2) between the critical abnormal response and the zero-crossing point (positive or negative).

[0302] Predicted transient value: X(φ) = Xp * Sinφ = Xp * Sin(ωt),

[0303] Where Xp is the predicted value of the transient peak: Xp = Xr / Sinφr,

[0304] If the critical abnormal response occurs at or after the AC peak, i.e., φ>=π / 2, then no transient abnormal trigger response will be obtained.

[0305] The transient protection control module includes a critical abnormality response unit, an impact feedback unit, and a flashover protection control unit.

[0306] The impact feedback unit refers to the unit that provides feedback on the overload impact of the pulse signal in the transient state before the circuit switching.

[0307] In a critical abnormal state, when the target monitoring node determines that the transient impact of the power signal state variable has reached or exceeded its preset critical value, it outputs a critical pulse (with critical reference voltage) and activates the impact feedback unit.

[0308] The impact feedback unit provides electrical feedback on the transient impact of the electrical energy state variable (the state variable) in response to the critical pulse, so that when the transient impact of the state variable (the state variable) exceeds the overload rating, the flashover protection control unit is immediately triggered (with minimal transient delay).

[0309] For example, overload protection based on monitoring of electrical energy / target state variables can be achieved by X(t): AC overcurrent protection: i(t) → X(t), AC overvoltage protection: u(t) → X(t), AC power overload protection: w(t) → X(t), and overtemperature protection: T(t) → X(t).

[0310] The abnormal state identifier includes abnormal level information. The abnormal level is information obtained by performing a level conversion based on the upper limit X1 and the lower limit X2 of the graded abnormal conditions on which a certain abnormal state variable is judged.

[0311] For example: Let the abnormal state variable X = X1 be level 0, and let X = X2 be level N.

[0312] Therefore, the level corresponding to the linear gradation transformation of the abnormal state variable X is:

[0313] G(X)=INT(N*(X-X1) / (X2-X1))+0.5).

[0314] The target scene state, or scene state for short, is a physical state of the specified target scene that is associated with it (and can be a combination of several subsets or object states).

[0315] Scene status: such as the people in a specified area / room (occupied / unoccupied).

[0316] The target state variable (referred to as state variable) is a physical state variable that is contained in the target state information and is associated with the target scene object, reflecting the target object and its associated environment.

[0317] Target state variables include direct variables or indirect indices related to predetermined scenarios such as environmental state, target object, and event triggering. Target state variables are physical quantities or intermediate control state variables that constitute the elements for judging the state of the target scenario and its changes.

[0318] When a scenario needs to be described by multiple target state variables, different state variables can be contained in the same or multiple state beacons; that is, not all target state variables must be contained in the same state beacon.

[0319] An object status beacon (or simply status beacon) is a radio beacon or carrier beacon sent by a target device that reflects the device's own status and the status of the associated target device.

[0320] A forward sensing node refers to the preceding collaborative sensing node from which the current wireless reception response of the collaborative sensing node originates. It can be the most forward target sensing node or an intermediate sensing node. The forward sensing node refers to the sensing and monitoring device that obtains and sends state variables to the current collaborative sensing node.

[0321] The preceding sensing nodes include target sensing nodes that obtain the target state variable Xi through direct or indirect sensing or intermediate sensing nodes that receive and process data.

[0322] The scenario response plan is a data structure that associates different scenario status codes with one or a set of mode parameters / mode processing procedures and mode processing.

[0323] The pattern parameter Pi includes the index / call parameters for the pattern processing flow;

[0324] Execute the corresponding mode processing flow according to the operation mode parameters included in the mode parameters;

[0325] The mode processing flow includes scene linkage processing such as scene linkage control, scene linkage configuration, and scene linkage communication.

[0326] The mode processing flow includes data calculation and communication processes based on local or multi-machine collaboration, such as mode adjustment, data configuration, linkage processing, data saving and uploading, etc.

[0327] When the network performance of data upload is abnormal (such as network outage or failure to meet predetermined requirements), the real-time monitoring data in the upload buffer is filtered, extracted and saved (according to the current data saving mode) as historical monitoring data.

[0328] After network performance is restored, (depending on the data upload mode) the edge node uploads the historical monitoring data to the host / cooperative service or management system in a first-in-first-out manner (through the management of data tags or data pointers).

[0329] For each consecutive time segment sequence number (TSSN), any edge node needs to perform network time correction and save it to the clock correction log.

[0330] The TSSN refers to the sequence number corresponding to each finite continuous time; any interruption of continuous time (active or passive interruption, power-on or power-off restart, segmented time correction) will cause the TSSN to change (usually +1).

[0331] Example 3: This embodiment of the invention discloses a first type of power consumption anomaly monitoring device. Please refer to [link / reference]. Figure 3 The device uses an energy monitoring node as the target monitoring node (and / or a collaborative sensing node) to monitor the abnormal power consumption status of its associated and bound power load objects. The device includes a state mode parsing module 301, a potential anomaly monitoring module 302, a critical anomaly monitoring module 303, and a transient anomaly response module 304, which are described in detail below:

[0332] State pattern parsing module 301: used to perform state evaluation processing and state pattern parsing on the current target monitoring information according to the hierarchical anomaly conditions, and obtain the abnormal state information of the load object;

[0333] Potential anomaly monitoring module 302: When the load object is in a potential anomaly state, based on the anomaly state information, it activates a security monitoring mode (i.e., the second monitoring mode) to perform security tracking and monitoring of the anomaly state variables of the load object.

[0334] Critical anomaly monitoring module 303: When the abnormal state variable meets the critical anomaly condition, (the power monitoring node) will start the critical monitoring mode (i.e., the third monitoring mode: to perform critical real-time tracking and monitoring of the abnormal state variable).

[0335] Transient anomaly response module 304: When the abnormal state variable (in the tracked and monitored state) meets the transient anomaly conditions, (the power monitoring node) obtains a transient anomaly response.

[0336] Example 4: This embodiment of the invention discloses a second type of power consumption anomaly monitoring device. Please refer to [link / reference]. Figure 4 The device uses an energy monitoring node as the target monitoring node to monitor the abnormal power consumption status of its associated and bound power load objects. The device includes: a critical real-time tracking module 401, a critical feedback monitoring module 402, and a pre-triggered response module 403, as detailed below:

[0337] Critical Real-Time Tracking Module 401: Used to obtain transient abnormal characteristic parameters of the load object through critical real-time tracking processing when the load object is in a critical abnormal state;

[0338] Critical feedback monitoring module 402: Based on the transient anomaly characteristic parameters, it adjusts the pre-trigger conditions corresponding to the transient anomaly conditions through critical feedback monitoring;

[0339] Pre-triggered response module 403: used to obtain a transient abnormal response when the front-end input signal being tracked and monitored meets the pre-triggered conditions.

[0340] In actual implementation, the device is a computer device. The processor executes computer instructions to implement the aforementioned embodiments of the power consumption anomaly monitoring device. Those skilled in the art will understand that all or part of the processes or modules in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium.

[0341] Example 5: This embodiment of the invention also discloses an abnormal electricity consumption monitoring system, which is a system established using the aforementioned abnormal electricity consumption monitoring method;

[0342] The system consists of several power monitoring nodes (in the edge domain of the Internet of Things); wherein, different power monitoring nodes serve as target monitoring nodes and / or collaborative sensing nodes to monitor the abnormal power consumption status of associated and bound power load objects.

[0343] The system is an edge collaborative sensing network system, which includes at least a target monitoring module and a collaborative processing module.

[0344] The implementation of the above system is further explained as follows:

[0345] The target monitoring module runs within the target monitoring node, and different sub-modules in the collaborative processing module run within the target monitoring node and / or several collaborative sensing nodes, performing security monitoring of the load object under a specified monitoring mode based on wireless collaborative sensing.

[0346] The target monitoring module includes a signal front-end processing module and an anomaly response processing module; the collaborative processing module includes a target monitoring data processing module and a status monitoring mode management module.

[0347] The system also includes edge collaborative information processing (running on the target monitoring node and / or collaborative sensing node), which includes a classification anomaly processing module and an edge monitoring data management module.

[0348] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art can make other variations or modifications based on the above description. These should also be considered within the scope of protection of this invention, and will not affect the effectiveness of the invention or the practicality of the patent. It is neither necessary nor possible to exhaustively list all embodiments here. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims. Obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for monitoring abnormal electricity consumption, characterized in that, A specific power monitoring node acts as the target monitoring node, monitoring the abnormal power consumption status of its associated and bound power load objects. The method includes the following steps: Based on the graded abnormal conditions, the target monitoring information of the current power load object is subjected to state assessment processing and state pattern parsing to obtain the abnormal state information of the power load object; wherein, the state pattern parsing is to conduct a balanced orientation assessment of the monitoring mode in terms of safety, energy saving, real-time response capability and system data requirements based on energy efficiency assessment feedback. Based on the abnormal state information, when the electrical load object is in a potentially abnormal state, the safety monitoring mode is activated: the abnormal state variables of the electrical load object are monitored for safety tracking. When the abnormal state variable meets the critical abnormal condition, the critical monitoring mode is activated to perform critical real-time tracking processing on the abnormal state variable; based on the degree of convergence of the current transient abnormal characteristic parameter to the transient abnormal condition, the pre-trigger condition is adjusted by dynamic feedback to the previous level, and when the abnormal state variable meets the transient abnormal condition, the transient abnormal response is obtained.

2. The method for monitoring abnormal electricity consumption as described in claim 1, characterized in that, When the power monitoring node receives a transient anomaly response, it immediately triggers the transient protection control module of itself and / or associated nodes to perform transient anomaly protection on the power load object in the transient anomaly state. The power monitoring node selects an appropriate transient protection mode based on the urgency and coverage of the current protection needs for the associated power load objects, and on a balance assessment between the protection needs and the protection costs.

3. The method for monitoring abnormal electricity consumption as described in claim 1, characterized in that, The hierarchical anomaly conditions include potential anomaly conditions, critical anomaly conditions, and transient anomaly conditions; The power monitoring node performs state mode parsing based on the graded anomaly conditions, including: judging the target scenario state associated with the power load object based on the graded anomaly conditions: 1) when the potential anomaly conditions are met, it enters the potential anomaly state; 2) When the critical anomaly condition is met, the system enters a critical anomaly state; 3) When the transient anomaly condition is met, the transient anomaly protection process is immediately triggered.

4. The method for monitoring abnormal electricity consumption as described in claim 1, characterized in that, The power monitoring node dynamically adjusts the pre-trigger conditions corresponding to the graded abnormal conditions through feedback, thereby tracking and monitoring abnormal states at different levels. The power monitoring node adjusts the pre-triggered conditions by setting a rated comparison signal and / or tracking the monitoring time step.

5. The method for monitoring abnormal electricity consumption as described in claim 2, characterized in that, The power monitoring node performs transient anomaly protection in at least one of the following ways according to the transient protection mode: Method 1, Single-point transient protection: The power monitoring node immediately triggers the transient protection control module of its own node device to perform transient anomaly protection on the power load object; Method 2, Linked Transient Protection: The power monitoring node triggers the associated protection node to perform transient anomaly protection on the power load object through wireless scene linkage.

6. The method for monitoring abnormal electricity consumption as described in claim 2, characterized in that, The associated protection node activates the transient anomaly protection according to the received anomaly trigger signal and the trigger response priority: When the required protection level is low, only the associated protection nodes with higher priority need to activate transient anomaly protection; while when the required protection level is high, the associated protection nodes with lower priority need to activate transient anomaly protection; until all associated protection nodes activate transient anomaly protection.

7. A method for monitoring abnormal electricity consumption, characterized in that, A specific power monitoring node acts as the target monitoring node, monitoring the abnormal power consumption status of its associated and bound power load objects. The method includes the following steps: When the electrical load object is in a critical abnormal state, the transient abnormal characteristic parameters of the electrical load object are obtained through critical real-time tracking processing; Based on the transient anomaly characteristic parameters, the pre-trigger conditions corresponding to the transient anomaly conditions are adjusted through critical feedback monitoring. The critical feedback monitoring involves adjusting the signal front end of the node itself or the preceding node based on the monitoring and collection information of the target state variable in the time domain and the judgment of the degree of approach of the transient trigger response, so as to compare and monitor the current front-end input signal in real time. When the tracked and monitored front-end input signal meets the preceding trigger condition, a transient abnormal response is obtained.

8. The method for monitoring abnormal electricity consumption as described in claim 7, characterized in that, When the power monitoring node receives a transient anomaly response, it immediately triggers the transient protection control module of itself and / or associated nodes to perform transient anomaly protection on the power load object in the transient anomaly state. The power monitoring node selects an appropriate transient protection mode based on the urgency and coverage of the current protection needs for the associated power load objects, and on a balance assessment between the protection needs and the protection costs.

9. The method for monitoring abnormal electricity consumption as described in claim 7, characterized in that, The power monitoring node dynamically adjusts the pre-trigger conditions corresponding to the graded abnormal conditions through feedback, thereby tracking and monitoring abnormal states at different levels. The power monitoring node adjusts the pre-triggered conditions by setting a rated comparison signal and / or tracking the monitoring time step.

10. The method for monitoring abnormal electricity consumption as described in claim 8, characterized in that, The power monitoring node performs transient anomaly protection in at least one of the following ways according to the transient protection mode: Method 1, Single-point transient protection: The power monitoring node immediately triggers the transient protection control module of its own node device to perform transient anomaly protection on the power load object; Method 2, Linked Transient Protection: The power monitoring node triggers the associated protection node to perform transient anomaly protection on the power load object through wireless scene linkage.

11. The method for monitoring abnormal electricity consumption as described in claim 8, characterized in that, The associated protection node activates the transient anomaly protection according to the received anomaly trigger signal and the trigger response priority: When the required protection level is low, only the associated protection nodes with higher priority need to activate transient anomaly protection; while when the required protection level is high, the associated protection nodes with lower priority need to activate transient anomaly protection; until all associated protection nodes activate transient anomaly protection.

12. A power consumption anomaly monitoring device, characterized in that, The device uses an energy monitoring node as the target monitoring node to monitor the abnormal power consumption status of its associated and bound power load objects. The device consists of the following modules: State pattern parsing module: used to perform state assessment processing and state pattern parsing on the target monitoring information of the current power load object according to the graded abnormal conditions, and obtain the abnormal state information of the power load object; wherein, the state pattern parsing is to perform a balanced orientation assessment of the monitoring mode in terms of safety, energy saving, real-time response capability and system data requirements based on energy efficiency assessment feedback. Potential anomaly monitoring module: used to activate the safety monitoring mode when the electrical load object is in a potential abnormal state based on the abnormal state information: to perform safety tracking and monitoring of the abnormal state variables of the electrical load object; Critical anomaly monitoring module: When the abnormal state variable meets the critical anomaly condition, it activates the critical monitoring mode to perform critical real-time tracking processing on the abnormal state variable; and adjusts the pre-trigger condition by dynamically feeding back to the previous stage according to the degree of convergence of the current transient anomaly characteristic parameters to the transient anomaly condition. Transient anomaly response module: used to obtain a transient anomaly response when the anomaly state variable meets the transient anomaly condition.

13. A power consumption anomaly monitoring device, characterized in that, The device uses an energy monitoring node as the target monitoring node to monitor the abnormal power consumption status of its associated and bound power load objects. The device consists of the following modules: Critical Real-Time Tracking Module: Used to obtain transient abnormal characteristic parameters of the electrical load object through critical real-time tracking processing when the electrical load object is in a critical abnormal state; Critical Feedback Monitoring Module: Based on the transient anomaly characteristic parameters, it adjusts the pre-trigger conditions corresponding to the transient anomaly conditions through critical feedback monitoring; wherein, the critical feedback monitoring is to adjust the signal front end of its own node or the pre-node based on the monitoring and acquisition information of the target state variable in the time domain and the judgment of the degree of approach of the transient trigger response, so as to compare and monitor the current front end input signal in real time. Pre-triggered response module: used to obtain transient abnormal response when the front-end input signal being tracked and monitored meets the pre-triggered conditions.

14. A power consumption anomaly monitoring system, characterized in that, The system is a system established using the power consumption anomaly monitoring method according to any one of claims 1 to 6 or any one of claims 7 to 11. The system consists of a plurality of power monitoring nodes. Different power monitoring nodes serve as target monitoring nodes and / or collaborative sensing nodes to monitor the power consumption anomaly status of associated and bound power load objects. The system is an edge collaborative sensing network system, which includes at least a target monitoring module and a collaborative processing module.

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