Power grid monitoring display method, system and device and computer equipment

Abstract

The invention relates to the technical field of 3D simulation, and discloses a power grid monitoring display method, system and device and computer equipment, and the method comprises the steps: collecting the data of bottom equipment on a monitoring point in a power grid in real time; calculating electric parameter data based on bottom equipment data, calculating current distribution and voltage drop based on the bottom equipment data, and judging the current flow direction based on the current distribution and the voltage drop; performing power grid fault diagnosis and power grid state judgment based on a size relationship between the bottom equipment data and a preset equipment data threshold value, a size relationship between the electric parameter data and a preset electric parameter threshold value and a current flow direction; constructing a 3D simulation scene by adopting 3D simulation software based on the underlying equipment data, the electric parameter data, the current flow direction, the power grid fault and the power grid state; and displaying power grid monitoring based on the 3D simulation scene. According to the method, the power grid is restored through the 3D simulation scene, complex data are converted into visual graphs or animations to be displayed to a user, and a fault location can be quickly positioned.

Description

Technical Field

[0001] The present invention relates to the field of 3D simulation technology, and particularly to a display method, system, device and computer equipment for power grid monitoring. Background Art

[0002] With the development of social economy and the improvement of people's living standards, the demand for electricity continues to grow, putting higher requirements on the stability and reliability of the power system. At the same time, with the large-scale access of renewable energy such as solar energy and wind energy, the complexity of the power system is also increasing. To address these challenges, power companies need to manage and control the power grid more precisely. In this context, power grid flow monitoring has become one of the key technologies to ensure the safe and stable operation of the power system.

[0003] Existing systems usually rely on two-dimensional charts and text reports to display data, which are not easily understood for complex systems. In the event of an abnormality on-site, it is impossible to quickly locate the fault and visually see the real-time current flow in the power grid. Summary of the Invention

[0004] In view of this, the present invention provides a display method, system, device and computer equipment for power grid monitoring to solve the problems of being unable to visually see the real-time current flow in the power grid and unable to quickly locate faults.

[0005] In a first aspect, the present invention provides a display method for power grid monitoring, the method comprising:

[0006] Real-time collecting the underlying device data at monitoring points in the power grid;

[0007] Calculating electrical parameter data based on the underlying device data, simultaneously calculating the current distribution and voltage drop based on the underlying device data, and judging the current flow direction based on the current distribution and voltage drop;

[0008] Conducting power grid fault diagnosis and power grid status judgment based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction;

[0009] Constructing a 3D simulation scene using 3D simulation software based on the underlying device data, electrical parameter data, current flow direction, power grid faults and power grid status;

[0010] Displaying the power grid monitoring based on the 3D simulation scene.

[0011] A method for displaying power grid monitoring provided by the present invention widely deploys various intelligent sensors at key monitoring points of the power grid, and can comprehensively collect underlying device data such as current, voltage, temperature, power, etc. According to the underlying device data, electrical parameter data such as active power, reactive power, apparent power, power factor, and frequency are accurately calculated. The Kirchhoff's law is used to calculate the current distribution, and the Ohm's law is used to calculate the voltage drop, so as to accurately judge the current flow direction. The accurate electrical parameter and current flow direction information helps to deeply understand the operation state of the power grid and provides a solid data basis for subsequent fault diagnosis and state assessment. Based on the underlying device data, electrical parameter data, current flow direction, power grid faults and power grid states, a 3D simulation software is used to construct a 3D simulation scene, and the power grid monitoring is displayed based on the 3D simulation scene. The on-site situation is restored 1:1 through the 3D simulation scene, and the flow direction of a certain current is dynamically sensed and displayed in real time in the 3D simulation scene. At the same time, the type of this line can also be distinguished by color. Through the current flow direction, the power generation state of the photovoltaic system, the charge and discharge state of the energy storage system, the flow direction of the mains power, etc. can be directly seen. The complex data is converted into intuitive graphics or animations and displayed to the user, and the fault location can be quickly located, solving the problems that the current flow direction in the real-time power grid cannot be intuitively seen and the fault cannot be quickly located.

[0012] In an optional implementation manner, the underlying device data includes photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data, and power supply data;

[0013] Calculating the electrical parameter data based on the underlying device data includes:

[0014] Calculating the active power, reactive power, apparent power, and power factor based on the power sensor data, energy-consuming device data, and power supply data;

[0015] Calculating the output power of the photovoltaic system in the power grid based on the photovoltaic data;

[0016] Calculating the SOC change of the energy storage system in the power grid based on the energy storage data;

[0017] Calculating the total current and total voltage of the monitoring point based on the distribution network data;

[0018] Taking the active power, reactive power, apparent power, power factor, output power of the photovoltaic system, SOC change of the energy storage system, total current and total voltage of the monitoring point as the electrical parameter data.

[0019] A method for displaying power grid monitoring provided by the present invention takes the active power, reactive power, apparent power, power factor, output power of the photovoltaic system, SOC change of the energy storage system, total current and total voltage of the monitoring point as the electrical parameter data, realizes the calculation of the electrical parameter data of each monitoring point, photovoltaic system and energy storage system, and provides conditions for subsequent 3D modeling.

[0020] In an alternative embodiment, the current distribution and voltage drop are calculated based on the underlying device data, and the current flow direction is determined based on the current distribution and voltage drop, including:

[0021] The current distribution is calculated based on the photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data, and power supply data using Kirchhoff's law;

[0022] The voltage drop is calculated based on the photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data, and power supply data using Ohm's law;

[0023] The current flow direction is calculated based on the current distribution and voltage drop. The current flow direction includes: for an AC circuit, according to Kirchhoff's current law, at any node in the circuit, the sum of the currents flowing into any node is equal to the sum of the currents flowing out of any node; for a DC circuit, the current flows from the positive pole of the power supply through the load and back to the negative pole of the power supply. When the DC circuit is a DC circuit containing an energy storage device, when the energy storage device is charging, the current direction points to the energy storage device; when the energy storage device is discharging, the current direction flows out of the energy storage device.

[0024] A display method for power grid monitoring provided by the present invention can monitor the current flow direction at each monitoring point by calculating the current flow direction based on the current distribution and voltage drop, providing conditions for subsequent 3D modeling.

[0025] In an alternative embodiment, the display method for power grid monitoring further includes:

[0026] Set the device shutdown priority for the devices in the power grid. The device shutdown priority includes low-priority shutdown devices and high-priority shutdown devices; low-priority shutdown devices are key devices in the power grid that are not allowed to be easily powered off, and high-priority shutdown devices are interruptible non-critical auxiliary devices or devices operating at less than full load and will not change production and / or service operation;

[0027] When the device load in the power grid exceeds the preset load threshold, the relevant devices are shut down or the device load is changed based on the device shutdown priority, so that the device load is less than or equal to the preset load threshold to change the current flow direction of the power grid.

[0028] In an alternative embodiment, power grid fault diagnosis is performed based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction, including:

[0029] When any one of the data in the underlying device data exceeds the preset device threshold, it is determined that the corresponding underlying device has a fault;

[0030] When any one of the electrical parameter data exceeds the preset electrical parameter threshold, it is determined that the corresponding monitoring point is faulty;

[0031] When the current flow direction shows a reverse flow or there is current in a branch where there should be no current, it is determined that there is a line fault, a ground fault, or equipment damage.

[0032] In an optional implementation manner, based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction, the power grid state is judged, including:

[0033] If the SOC change of the energy storage system increases, it is determined that the energy storage system is charging and the current direction points to the energy storage device; if the SOC change of the energy storage system decreases, it is determined that the energy storage system is discharging and the current direction deviates from the energy storage device;

[0034] If the output power of the photovoltaic system is greater than the preset value, it is determined that the photovoltaic system is generating electricity and the current direction deviates from the photovoltaic system, otherwise it is determined that the photovoltaic system is not generating electricity;

[0035] When the underlying device data is within the preset device data threshold range, the electrical parameter data is within the preset electrical parameter threshold range, and the current flow direction conforms to the design expectation, it is judged that the power grid is in a normal operation state; otherwise, the power grid is in a faulty state.

[0036] In an optional implementation manner, based on the underlying device data, electrical parameter data, current flow direction, power grid fault, and power grid state, a 3D simulation scenario is constructed using 3D simulation software, including:

[0037] Calculate the point distance between two monitoring points through the current flow direction, and generate a pipeline with a corresponding length and a current velocity model in the pipeline using 3D simulation software based on the point distance; the current flow direction velocity model in the pipeline is represented by the following formula:

[0038] U = V·B / R;

[0039] Where, u is the current velocity, V is the voltage, B is the magnetic induction intensity, and R is the resistance;

[0040] Based on the pipeline, the current velocity in the pipeline, the underlying device data, the electrical parameter data, the current flow direction, the power grid fault, and the power grid state, different color line codes are generated using 3D simulation software;

[0041] Mark the pipeline, the current velocity in the pipeline, the current flow direction, the power generation state of the photovoltaic system, the charge and discharge state of the energy storage system, and the power grid fault state for different color line codes, and generate a 3D simulation scenario after marking.

[0042] A display method for power grid monitoring provided by the present invention creates a realistic power grid environment through 3D modeling and rendering, synchronizes real-time data, can dynamically display the current flow direction, distinguishes voltage levels through color coding, can also achieve multi-level data presentation from the global to local details, and can automatically identify faults and dynamically generate information related to each node.

[0043] In a second aspect, the present invention provides a display system for power grid monitoring, which includes:

[0044] A data acquisition layer for real-time acquisition of underlying device data at monitoring points;

[0045] A monitoring center for calculating electrical parameter data based on the underlying device data, calculating current distribution and voltage drop based on the underlying device data, and judging the current flow direction based on the current distribution and voltage drop; performing power grid fault diagnosis and power grid state judgment based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction;

[0046] An application display layer for constructing a 3D simulation scene using 3D simulation software based on the underlying device data, electrical parameter data, current flow direction, power grid faults, and power grid states; displaying power grid monitoring based on the 3D simulation scene.

[0047] In a third aspect, the present invention provides a display device for power grid monitoring, which includes:

[0048] A data acquisition module for real-time acquisition of underlying device data at monitoring points;

[0049] A data calculation module for calculating electrical parameter data based on the underlying device data, calculating current distribution and voltage drop based on the underlying device data, and judging the current flow direction based on the current distribution and voltage drop;

[0050] A fault diagnosis and power grid state judgment module for performing power grid fault diagnosis and power grid state judgment based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction;

[0051] A 3D simulation scene construction module for constructing a 3D simulation scene using 3D simulation software based on the underlying device data, electrical parameter data, current flow direction, power grid faults, and power grid states;

[0052] A display module for displaying power grid monitoring based on the 3D simulation scene.

[0053] Fourth aspect, the present invention provides a computer device, comprising: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the power grid monitoring display method according to the first aspect or any corresponding embodiment thereof.

[0054] Fifth aspect, the present invention provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the power grid monitoring display method according to the first aspect or any corresponding embodiment thereof.

[0055] Sixth aspect, the present invention provides a computer program product, comprising computer instructions, and the computer instructions are used to cause a computer to execute the power grid monitoring display method according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required to be used in the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0057] Figure 1 is a schematic flowchart of the power grid monitoring display method according to an embodiment of the present invention;

[0058] Figure 2 is a schematic flowchart of another power grid monitoring display method according to an embodiment of the present invention;

[0059] Figure 3 is a schematic flowchart of yet another power grid monitoring display method according to an embodiment of the present invention;

[0060] Figure 4 is a structural block diagram of the power grid monitoring display system according to an embodiment of the present invention;

[0061] Figure 5 is a schematic diagram of a 3D simulation scene according to an embodiment of the present invention;

[0062] Figure 6 is a structural block diagram of the power grid monitoring display device according to an embodiment of the present invention;

[0063] Figure 7 is a schematic hardware structure diagram of the computer device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0064] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0065] According to an embodiment of the present invention, an embodiment of a display method for power grid monitoring is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0066] In this embodiment, a display method for power grid monitoring is provided, which can be used for a power grid monitoring platform. As Figure 4 shown, the power grid monitoring platform includes a bottom device layer, a monitoring center, an application display layer, and a dispatching center that communicate with each other in sequence. The communication resources select the communication method in a hierarchical progressive manner. First, Bluetooth is tried for short-distance communication. When Bluetooth cannot meet the requirements, HPLC (High-Speed Power Line Communication), Ethernet, 4G, and 5G are tried in sequence. These communication resources can maximize the use of existing communication resources and provide the optimal communication solution in different environments. Figure 1 is a flowchart of the display method for power grid monitoring according to an embodiment of the present invention. As Figure 1 shown, the process includes the following steps:

[0067] Step S101, collect the bottom device data at the monitoring points in the power grid in real time.

[0068] Specifically, the bottom device data includes relevant power equipment data and sensor data deployed on each power equipment. The points to be monitored in the power grid are used as monitoring points. The monitoring points can be each power equipment and / or sensor data. The monitoring points are connected to each other to form nodes in the power grid. The bottom device data is collected in real time through sensors (such as current transformers, voltage transformers, temperature sensors, etc.) deployed at key nodes in the power grid.

[0069] Step S102, calculate the electrical parameter data based on the bottom device data, calculate the current distribution and voltage drop based on the bottom device data at the same time, and judge the current flow direction based on the current distribution and voltage drop.

[0070] Specifically, after the underlying device layer collects the underlying device data, it is transmitted to the monitoring center through the gateway. The monitoring center calculates electrical parameter data such as active power, the power generation output power of the photovoltaic system in the power grid, and the SOC change data of the energy storage system in the power grid based on the underlying device data.

[0071] Calculate the current distribution and voltage drop based on the underlying device data, and judge the current flow direction based on the current distribution and voltage drop. For example, at a simple T-type AC circuit node, if the current inflows of two branches are known and their sum is equal to the current outflow of the third branch, the current flow direction from the inflow branch to the outflow branch can be determined. For a DC circuit, the current starts from the positive pole of the power supply, flows through the load, and finally returns to the negative pole of the power supply. For a DC circuit containing an energy storage device (such as a battery), the current flow direction can be judged by detecting the status signal of the energy storage device charge and discharge controller, or monitoring the change trend of the voltage and current at both ends of the battery.

[0072] It should be noted that before calculating the electrical parameters, it is necessary to perform data preprocessing and storage on the collected underlying device data. Edge computing nodes, monitoring centers, and databases are required during the data preprocessing and storage process. Edge computing nodes are used to perform preliminary processing on data that requires quick response near the data source to reduce the pressure on the main server. The monitoring center is used to receive data from each monitoring point, perform centralized storage, cleaning, conversion, and prepare for subsequent data analysis. A database is used to store a large amount of historical data and the collected real-time data. A stream processing framework (such as Apache Kafka + Flink / Spark Streaming) is used to process real-time data streams during the data preprocessing and storage process.

[0073] Step S103, perform power grid fault diagnosis and power grid status judgment based on the size relationship between the underlying device data and the preset device data threshold, the size relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction.

[0074] Specifically, based on the comparison of the underlying device data and the electrical parameter data with the corresponding thresholds, rapid diagnosis of power grid faults can be achieved. The power grid status includes the power generation status of the photovoltaic system in the power grid, the charge and discharge status of the energy storage system, the power grid fault status, and the normal operation status, etc.

[0075] For example, compare the underlying device data with the preset device data threshold: the underlying device data such as device temperature, vibration amplitude, etc. are compared with the preset normal operation threshold range. For example, the oil temperature of a transformer usually fluctuates within a certain range during normal operation. If the real-time collected oil temperature exceeds the preset high-temperature threshold, the system will mark that the transformer may have an overheating fault.

[0076] For another example, the calculated electrical parameter data, such as voltage deviation, current overload, abnormal power factor, etc., are compared with the corresponding preset thresholds. If the current of a certain transmission line continuously exceeds its rated current threshold, the system determines that the line may have an overload fault; when the power factor is lower than the preset normal range, it may mean that there is a problem of insufficient reactive power compensation in the power grid.

[0077] An abnormal current flow is often an important indication of a power grid fault. For example, under normal circumstances, the current should flow along the designed circuit path. If it is detected that the current has a reverse flow or there is current in a branch where there should be no current, it may indicate problems such as line short circuit, grounding fault, or equipment damage. By comprehensively analyzing the underlying device data, electrical parameter data, and abnormal current flow conditions, and using fault diagnosis algorithms (such as rule-based reasoning algorithms, neural network algorithms, etc.), the fault location and type can be accurately located.

[0078] Step S104, construct a 3D simulation scenario based on the underlying device data, electrical parameter data, current flow, power grid faults, and power grid status using 3D simulation software.

[0079] Specifically, the 3D simulation software can restore the power grid and its surrounding environment (buildings, roads) at a true scale of 1:1. Based on the underlying device data, electrical parameter data, current flow, power grid faults, and power grid status, the 3D simulation software is used to truly restore the power grid lines, forming a 3D simulation scenario of the power grid.

[0080] Step S105, display the power grid monitoring based on the 3D simulation scenario.

[0081] The power grid monitoring display method provided in this embodiment widely deploys a variety of intelligent sensors at key power grid monitoring points, which can comprehensively collect underlying device data such as current, voltage, temperature, and power. According to the underlying device data, electrical parameter data such as active power, reactive power, apparent power, power factor, and frequency are accurately calculated. The Kirchhoff's law is used to calculate the current distribution, and the Ohm's law is used to calculate the voltage drop, so as to accurately judge the current flow direction. The accurate electrical parameter and current flow direction information helps to deeply understand the power grid operation status and provides a solid data basis for subsequent fault diagnosis and status assessment. Based on the underlying device data, electrical parameter data, current flow direction, power grid faults, and power grid status, a 3D simulation software is used to construct a 3D simulation scenario, and the power grid monitoring is displayed based on the 3D simulation scenario. The on-site situation is restored 1:1 through the 3D simulation scenario, and the flow direction of a certain current is dynamically sensed and displayed in real time in the 3D simulation scenario. At the same time, the type of this line can also be distinguished by color. Through the current flow direction, the power generation status of the photovoltaic system, the charge and discharge status of the energy storage system, the flow direction of the mains electricity, etc. can be directly seen. The complex data is converted into intuitive graphics or animations and displayed to the user, and the fault location can be quickly located, solving the problems of being unable to intuitively see the current flow direction in the real-time power grid and being unable to quickly locate faults.

[0082] In this embodiment, a power grid monitoring display method is provided, which can be used in a power grid monitoring platform, such as Figure 4 shown, the power grid monitoring platform includes an underlying device layer, a monitoring center, an application display layer, and a dispatching center that communicate in sequence. The communication resources select the communication method in a hierarchical progressive manner. First, Bluetooth is tried for short-distance communication. When Bluetooth cannot meet the requirements, HPLC (High-Speed Power Line Communication), Ethernet, 4G, and 5G are tried in sequence. These communication resources can maximize the use of existing communication resources and provide the optimal communication solution in different environments. Figure 2 is a flowchart of the power grid monitoring display method according to an embodiment of the present invention, such as Figure 2 shown, the process includes the following steps:

[0083] Step S201, real-time collect the underlying device data at the monitoring points in the power grid. For details, please refer to Figure 1 Step S101 of the embodiment shown, which will not be elaborated here.

[0084] Step S202, calculate the electrical parameter data based on the underlying device data, and at the same time calculate the current distribution and voltage drop based on the underlying device data, and judge the current flow direction based on the current distribution and voltage drop.

[0085] Specifically, as Figure 4As shown, the underlying device data includes photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data, and power supply data; the above step S202 includes:

[0086] Step S2021, calculate the active power, reactive power, apparent power, and power factor based on the power sensor data, energy-consuming device data, and power supply data.

[0087] Specifically, the calculation formulas for active power, reactive power, apparent power, and power factor are as follows:

[0088] P = V × I × cos(φ) (1);

[0089] Q = V × I × sin(φ) (2);

[0090] S = V × I (3);

[0091]

[0092] Among them, V and I respectively represent the effective values of voltage and current in the circuit, φ represents the phase difference angle between voltage and current; P represents the active power in the circuit, which refers to the part of power actually used for work in an AC circuit; cos(φ) is the power factor, which reflects the proportion of active power in apparent power.

[0093] Step S2022, calculate the output power of the photovoltaic system in the power grid based on the photovoltaic data.

[0094] Specifically, the photovoltaic data includes the output power of the photovoltaic inverter, and the output power provided by the photovoltaic inverter is used as the output power P of the photovoltaic system PV . Through the output power P provided by the photovoltaic inverter PV It can be judged whether the photovoltaic system is generating electricity.

[0095] Step S2023, calculate the SOC change of the energy storage system in the power grid based on the energy storage data.

[0096] Specifically, the SOC change formula of the energy storage system is as follows:

[0097]

[0098] Among them, ΔE is the energy change amount, and C is the energy storage battery capacity.

[0099] It should be noted that the charge and discharge state of the energy storage system can also be judged by calculating the frequency. The frequency is calculated through the status signal of the charge and discharge controller. The frequency calculation formula is: Where T is the period.

[0100] Step S2024: Calculate the total current and total voltage of the monitoring point based on the distribution network data.

[0101] Specifically, Kirchhoff's Current Law (KCL): At a circuit node, the total current flowing into the node is equal to the total current flowing out of the node. The formula is as follows:

[0102]

[0103] where, I k represents the current in the k-th branch.

[0104] Kirchhoff's Voltage Law (KVL): Along any closed loop, the algebraic sum of the voltages across all elements is equal to zero. The formula is as follows:

[0105]

[0106] where, V k represents the voltage in the k-th branch.

[0107] Step S2025: Take the active power, reactive power, apparent power, power factor, output power of the photovoltaic system, SOC change of the energy storage system, total current and total voltage of the monitoring point as electrical parameter data.

[0108] Step S2026: Calculate the current distribution based on the photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming equipment data, and power supply data using Kirchhoff's laws.

[0109] Specifically, according to Kirchhoff's Laws, calculate the current distribution at the node. The formula can be calculated according to formula (6).

[0110] Step S2027: Calculate the voltage drop based on the photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming equipment data, and power supply data using Ohm's law.

[0111] Specifically, use Ohm's Law (V = I × R or V = I × R) to calculate the voltage drop.

[0112] Step S2028: Calculate the current direction based on the current distribution and voltage drop; the current direction includes: for an AC circuit, according to Kirchhoff's Current Law, at any node in the circuit, the sum of the currents flowing into any node is equal to the sum of the currents flowing out of any node; for a DC circuit, the current flows from the positive pole of the power supply through the load and back to the negative pole of the power supply. When the DC circuit is a DC circuit containing an energy storage device, when the energy storage device is charging, the current direction points to the energy storage device; when the energy storage device is discharging, the current direction flows out of the energy storage device.

[0113] Specifically, the current direction of a node is determined by the inflow and outflow of current at the node. It may be difficult to judge the inflow and outflow of current through the positive and negative signs of voltage, and the positive and negative signs of voltage depend on the relative positions of power sources and resistors in the circuit.

[0114] Furthermore, for an AC circuit: According to Kirchhoff's Current Law (KCL), at any node in the circuit, the sum of the currents flowing into the node is equal to the sum of the currents flowing out of the node. By comparing the magnitudes and directions of the currents collected by the branch sensors and combining the circuit topology, the current flow direction between nodes is determined. For example, at a simple T-type circuit node, if the currents flowing into two branches are known and their sum is equal to the current flowing out of the third branch, the current flow from the inflowing branches to the outflowing branch can be clearly determined.

[0115] For a DC circuit: In a DC circuit, the current starts from the positive pole of the power source, flows through the load, and finally returns to the negative pole of the power source. For a DC circuit containing an energy storage device (such as a battery), when the battery is charging, the current direction points to the battery; when discharging, the current direction flows out of the battery. The current flow direction can be judged by detecting the status signal of the energy storage device charge and discharge controller or monitoring the change trend of the voltage and current at both ends of the battery.

[0116] Step S203, based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction, perform power grid fault diagnosis and power grid status judgment.

[0117] Specifically, the above step S203 includes:

[0118] Step S2031, when any one of the data in the underlying device data exceeds the preset device threshold, it is determined that the corresponding underlying device fails.

[0119] Specifically, the underlying device data includes photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data, and power supply data. For example, when the data of the power sensor data deployed on the power device exceeds the preset device threshold, it is determined that the power device fails.

[0120] Furthermore, for various types of underlying devices, such as transformers, power distribution cabinets, transmission lines, energy storage devices, photovoltaic inverters, etc., a normal operating threshold range for a series of key data is set based on the device's design specifications, historical operating data, and industry standards. The preset device thresholds are set according to the actual situation and are not specifically limited here. These key data cover device temperature, vibration amplitude, pressure value, rotational speed, etc., and the key data concerned by different devices vary. For example, when a transformer is operating normally, its winding temperature is generally between 60°C and 80°C, and the oil temperature is between 40°C and 60°C; the temperature of key parts inside the power distribution cabinet usually does not exceed 50, and the vibration amplitude should be maintained at an extremely low level.

[0121] Real-time data collection and comparison: Intelligent sensors continuously collect various data of the underlying devices at a millisecond-level frequency and quickly transmit them to the data aggregation node through wired or wireless communication links, and then reach the front-end server of the monitoring center via the communication gateway. In the monitoring center, a special data processing module compares the real-time collected data with the pre-set device thresholds one by one.

[0122] Fault marking and alarm triggering: Once it is found that any one of the data of a certain underlying device exceeds the pre-set threshold range, the system immediately marks that the device has a fault and triggers the corresponding alarm mechanism.

[0123] Step S2032, when any one of the electrical parameter data exceeds the pre-set electrical parameter threshold, it is determined that the corresponding monitoring point has a fault.

[0124] Specifically, based on the operating characteristics of the power grid, safety standards, and the actual requirements of the location where the monitoring point is located, a reasonable threshold range is set for the electrical parameter data of each monitoring point. These electrical parameters include voltage deviation, current overload, abnormal power factor, frequency fluctuation, etc. For example, for the monitoring point of the transmission line, the voltage deviation during normal operation should be controlled within ±5% of the rated voltage, and the current should not exceed the rated current-carrying capacity of the line; for the monitoring point of the distribution system, the power factor generally requires to be maintained above 0.9, and the frequency should be stable within the range of 50Hz ± 0.5Hz.

[0125] Calculation and acquisition of electrical parameter data: Using the collected data of the underlying devices, various electrical parameter data are calculated through specific calculation formulas (such as the active power P = V × I × cos(φ), reactive power Q = V × I × sin(φ), etc. mentioned above). The calculation process is completed in the data analysis module of the monitoring center to ensure the accuracy and timeliness of the data.

[0126] Data comparison and fault determination: Compare the calculated electrical parameter data with the preset electrical parameter thresholds. If any electrical parameter data of a certain monitoring point exceeds the threshold, the system determines that a fault has occurred at this monitoring point and records the relevant fault information, including the fault occurrence time, fault type (such as overvoltage, current overload, etc.) and the specific electrical parameter values involved.

[0127] Exemplarily, when calculating the active power, the voltage thresholds are set as Vmax and Vmin. When the real-time collected voltage data V < Vmin or V > Vmax, the corresponding monitoring point has a fault and an alarm is triggered simultaneously.

[0128] Step S2033, when there is a reverse current flow or a current appears in a branch where there should be no current, it is determined that there is a line fault, a ground fault or equipment damage.

[0129] Specifically, based on Kirchhoff's current law (KCL) and the designed topological structure of the power grid, clarify the inflow and outflow directions of the current at each node and the current distribution that should exist in each branch under normal operating conditions. Through the analysis and modeling of a large amount of normal operating data, determine the standard mode of the normal current flow direction, which is used as the basis for judging the abnormal current flow direction.

[0130] Real-time monitoring and analysis of current flow direction: Use current sensors installed at each branch and node to collect real-time data on the magnitude and direction of the current. The monitoring system uses data analysis algorithms to compare and analyze the real-time collected current flow direction data with the preset normal current flow direction mode.

[0131] Abnormal situation identification and fault determination: Once it is detected that there is a reverse current flow (i.e., opposite to the normal flow direction), or a current is detected in a branch where there should be no current, the system immediately determines that there are problems such as a line fault, a ground fault or equipment damage. At this time, the system will automatically lock the position where the abnormal current flow occurs and record the relevant abnormal data, such as the magnitude of the abnormal current, the occurrence time and the duration.

[0132] Step S2034, if the SOC of the energy storage system increases, it is determined that the energy storage system is charging and the current direction points to the energy storage device; if the SOC of the energy storage system decreases, it is determined that the energy storage system is discharging and the current direction deviates from the energy storage device.

[0133] Specifically, the core state indicator of the energy storage system is its state of charge (SOC), which represents the percentage of the remaining power of the energy storage battery at present. According to the working principle of the energy storage system, when the external power supply delivers electric energy to the energy storage battery, the power of the battery increases, that is, the SOC change shows an upward trend, and at this time, the energy storage system is in the charging state; on the contrary, when the energy storage battery releases electric energy to the external load, the battery power decreases, and the SOC change shows a downward trend, indicating that the energy storage system is in the discharging state.

[0134] When the energy storage system is in the charging state, it means that it is absorbing and storing electric energy from the power grid or other power sources. This helps to store excess electric energy during the low electricity consumption period and provide supplementation during the high electricity consumption period, playing the role of peak shaving and valley filling, and improving the stability of the power grid and the power utilization efficiency. At the same time, the current inflow during the charging process will affect the local current distribution of the power grid, which may cause the line current connected to the energy storage device to increase. It is necessary to closely monitor the line current-carrying capacity to prevent overload.

[0135] When the energy storage system discharges, it releases the stored electric energy to the power grid or load. This can quickly provide power support to maintain the stability of the power grid voltage and frequency when there is a sudden increase in the load of the power grid or insufficient power supply. However, during the discharging process, the current flows out of the energy storage device, which will also change the current distribution of the power grid. And as the discharging progresses, the SOC of the energy storage system gradually decreases. It is necessary to reasonably plan the discharging strategy to ensure that there is sufficient electric energy available during critical periods.

[0136] Step S2035, if the output power of the photovoltaic system is greater than the preset value, it is determined that the photovoltaic system is generating electricity, and the current direction is away from the photovoltaic system; otherwise, it is determined that the photovoltaic system is not generating electricity.

[0137] Specifically, the main output indicator of the photovoltaic system is its output power, which directly reflects the ability of the photovoltaic system to convert solar energy into electric energy. Through long-term operation monitoring and data analysis of the photovoltaic system, combined with the rated power of the photovoltaic modules and the actual operating environmental conditions, a reasonable output power preset value is set. When the actual output power of the photovoltaic system is greater than this preset value, it indicates that the photovoltaic system is working normally and effectively converts solar energy into electric energy. At this time, the current is generated from the photovoltaic modules and flows to the external power grid or load, and the direction is away from the photovoltaic system; if the output power is less than or equal to the preset value, it may be due to reasons such as insufficient light, photovoltaic module failure, and line connection problems, resulting in the photovoltaic system not generating electricity normally.

[0138] For example, the preset value is 0. If P PV > 0, it means generating electricity; if P PV = 0, it means not generating electricity.

[0139] If the real-time output power is greater than the preset value, the system determines that the photovoltaic system is generating electricity, and at the same time determines that the current direction is away from the photovoltaic system; if the output power is less than or equal to the preset value, it is determined that the photovoltaic system is not generating electricity. The determination results are intuitively displayed on the display screen of the local photovoltaic system controller on the one hand, and uploaded to the power grid monitoring platform on the other hand for operation and maintenance personnel to remotely monitor.

[0140] When the photovoltaic system is generating electricity normally, it injects green electric energy into the power grid, reduces the dependence on traditional energy sources, reduces carbon emissions, and has positive significance for improving the energy structure and environmental quality. When the photovoltaic system is not generating electricity, it may affect the power supply balance of the power grid, especially in areas with a large dependence on photovoltaic power. Operation and maintenance personnel need to promptly check the cause of the failure based on the determination results, combined with the operating parameters of the photovoltaic system (such as component temperature, open-circuit voltage, short-circuit current, etc.) and environmental data (such as light intensity, temperature, humidity, etc.).

[0141] Step S2036, when the underlying device data is within the preset device data threshold range, the electrical parameter data is within the preset electrical parameter threshold range, and the current flow direction conforms to the design expectation, it is determined that the power grid is in a normal operating state; otherwise, the power grid is in a fault state.

[0142] Specifically, the stable operation of the power grid depends on the normal operation of the underlying devices, the stability of electrical parameters, and the current flow direction conforming to the design plan. For the underlying devices, based on the type, specifications, and long-term operation experience of the devices, reasonable threshold ranges are set for their key operating data (such as temperature, pressure, vibration, etc.) to ensure that the devices can operate safely and efficiently within this range. For electrical parameters, considering the voltage level, load characteristics, and power transmission requirements of the power grid, strict thresholds are set for electrical parameters such as voltage deviation, current overload, power factor, and frequency to ensure power quality and the reliable operation of the power grid. At the same time, based on the topological structure of the power grid and the results of power flow calculations, the normal current flow pattern of each node and branch is determined as the basis for judging whether the current flow direction is normal.

[0143] If both the underlying device data and the electrical parameter data are within their respective preset threshold ranges, and the current flow direction is consistent with the design expectation, the system determines that the power grid is in a normal operating state; as long as any one of these conditions is not met, it is determined that the power grid is in a fault state. The system displays the operation state determination results in a visual manner on the power grid monitoring interface. The normal state is usually marked in green, and the fault state is marked with a red warning.

[0144] Step S204, based on the underlying device data, electrical parameter data, current flow direction, power grid faults, and power grid status, use 3D simulation software to construct a 3D simulation scenario. For details, please refer to Figure 1 Step S104 of the illustrated embodiment, which will not be elaborated here.

[0145] Step S205: Display power grid monitoring based on the 3D simulation scenario. For details, please refer to Figure 1 Step S105 of the embodiment shown, which will not be elaborated here.

[0146] The power grid monitoring display method provided in this embodiment takes active power, reactive power, apparent power, power factor, output power of the photovoltaic system, SOC change of the energy storage system, total current and total voltage of the monitoring point as electrical parameter data, realizes the calculation of electrical parameter data of each monitoring point, photovoltaic system and energy storage system, and can monitor the current flow direction of each monitoring point by calculating the current distribution and voltage drop, providing conditions for subsequent 3D modeling.

[0147] In this embodiment, a power grid monitoring display method is provided, which can be used in a power grid monitoring platform, such as Figure 4 shown, the power grid monitoring platform includes a bottom device layer, a monitoring center, an application display layer and a dispatching center that communicate in sequence. The communication resources select the communication method in a hierarchical progressive manner. First, Bluetooth is tried for short-distance communication. When Bluetooth cannot meet the requirements, HPLC (High-Speed Power Line Communication), Ethernet, 4G and 5G are tried in sequence. These communication resources can maximize the utilization of existing communication resources and provide the optimal communication solution in different environments. Figure 3 is a flowchart of the power grid monitoring display method according to an embodiment of the present invention. As Figure 3 shown, the process includes the following steps:

[0148] Step S301: Real-time collect bottom device data on monitoring points in the power grid. For details, please refer to Figure 2 Step S201 of the embodiment shown, which will not be elaborated here.

[0149] Step S302: Calculate electrical parameter data based on the bottom device data, calculate the current distribution and voltage drop based on the bottom device data at the same time, and judge the current flow direction based on the current distribution and voltage drop. For details, please refer to Figure 2 Step S202 of the embodiment shown, which will not be elaborated here.

[0150] Step S303: Set the shutdown priorities for the devices in the power grid. The shutdown priorities include low-priority shutdown devices and high-priority shutdown devices. Low-priority shutdown devices are critical devices in the power grid that are not allowed to be easily powered off, and high-priority shutdown devices are interruptible non-critical auxiliary devices or devices operating at less than full load without changing production and / or service operations. When the device load in the power grid exceeds the preset load threshold, relevant devices are shut down or their loads are changed based on the shutdown priorities, so that the device load is less than or equal to the preset load threshold, thereby changing the current flow direction of the power grid.

[0151] Specifically, by monitoring the loads of other devices in the entire power grid, if the device load is too high and exceeds the preset load threshold, the load of the power grid is changed, or a certain device is shut down to stop its operation, thereby changing the current flow direction of the power grid.

[0152] The principles for shutting down devices include: For some critical devices that are not allowed to be easily powered off, such as communication base stations, etc., they are set as low-priority shutdown devices. For some interruptible loads, such as non-critical auxiliary devices and high-power electrical appliances in production, etc., they can be preferentially considered as shutdown targets, that is, set as high-priority shutdown devices. Preferentially shut down high-priority shutdown devices that are operating at less than full load and have less impact on overall production or service. If a device itself has a fault or is under maintenance and repair, then when the load needs to be reduced, such devices can be preferentially selected for shutdown. When shutting down a device, the impact on upstream and downstream devices also needs to be considered to avoid affecting other devices and causing losses.

[0153] The relationship between the location of the shutdown device and the power grid flow direction includes: Shutting down the device close to the power supply side may cause more power output from the power supply to flow to other branches; while shutting down the device close to the load terminal may change the load distribution in that area and redistribute the power within the local power grid.

[0154] The linkage between the power grid devices and the power grid load is achieved through step S303.

[0155] Step S304: Based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction, perform power grid fault diagnosis and power grid status judgment. For details, please refer to Figure 2 Step S203 of the embodiment shown, which will not be elaborated here.

[0156] Step S305: Use 3D simulation software to construct a 3D simulation scenario based on the underlying device data, electrical parameter data, current flow direction, power grid faults, and power grid status.

[0157] Specifically, the above step S305 includes:

[0158] Step S3051, calculate the point distance between two monitoring points through the current flow direction, and generate a pipeline with a corresponding length and a current velocity model in the pipeline based on the point distance by using 3D simulation software; the current flow velocity model in the pipeline is expressed by the following formula:

[0159] U = V·B / R;

[0160] where, u is the current velocity, V is the voltage, B is the magnetic induction intensity, and R is the resistance.

[0161] Specifically, in the topological structure of the power grid, the current flows from one monitoring point to another along the transmission line. Assuming that the path of the current between the two monitoring points is a straight line (in an actual complex power grid, the tortuous line can be simplified to an equivalent straight line through the line topology algorithm for preliminary calculation), using the geographical coordinate information (such as longitude and latitude or plane rectangular coordinates) of the monitoring points, with the help of the distance calculation formula in mathematics. For example, in the plane rectangular coordinate system, if the coordinates of the two monitoring points are (x1, y1) and (x2, y2) respectively; then the distance between the two points is:

[0162] d = (x2 - x1) 2 +(y2 - y1) 2 (8).

[0163] In the 3D simulation software, according to the calculated point distance between the two monitoring points, use the modeling tool of the software to create a 3D pipeline model and a current velocity model in the pipeline, that is, the flow velocity in the pipeline changes with the change speed of the voltage and current. The formula of the current velocity model in the pipeline is as follows:

[0164] First, establish a hypothetical basic model (the flow velocity is proportional to the voltage and magnetic field intensity and inversely proportional to the resistance):

[0165] U = V·B / R (9);

[0166] where, u is the current velocity, V is the voltage, B is the magnetic induction intensity, and R is the resistance.

[0167] Exemplarily, when the voltage and current in the circuit change, and the collected parameters are used to call this current velocity model to generate a 3D pipeline and the corresponding current change and current flow velocity model. The countercurrent flow velocity affects the geometric shape of the 3D pipeline, such as the size of the pipeline, the inlet and outlet, etc. For example, the default radius of the pipeline size is 0.05m, and then multiplying by the result of V·B / R represents the change of the current flow velocity. The size of the pipeline is determined by the radius of the pipeline.

[0168] To visually display the current speed in a 3D scene, a visual model can be created. For example, a particle flow representing the current flow is generated inside the pipeline, and the movement speed of the particles is set according to the calculated current speed. By adjusting the properties of the particles such as color, size, and density, the visualization effect of the current speed model is enhanced.

[0169] Step S3052: Based on the pipeline, the current speed in the pipeline, the underlying device data, the electrical parameter data, the current direction, the power grid fault, and the power grid status, use 3D simulation software to generate line encodings of different colors.

[0170] Specifically, by collecting the magnitudes of the voltage and current at key nodes, calculating the differences, and using 3D software to dynamically generate a 3D current effect model between connection points (nodes), the generated dynamic effect model has the same current direction as in the real environment. On this basis, color encodings are dynamically generated to identify different voltage levels (such as high voltage, low voltage, etc.).

[0171] Step S3053: Label the pipeline, the current speed in the pipeline, the current direction, the power generation status of the photovoltaic system, the charge and discharge status of the energy storage system, and the power grid fault status with line encodings of different colors. After the labeling is completed, a 3D simulation scene is generated.

[0172] For example, high-voltage lines can be encoded in red because red usually represents high energy and danger, which is in line with the characteristics of high-voltage electricity. Low-voltage lines are encoded in blue, and blue gives people a feeling of stability and safety, which is in line with the relatively low-risk characteristics of low-voltage lines. Green power lines (such as those from renewable energy sources like solar and wind) are encoded in green, and green symbolizes environmental protection and sustainable energy.

[0173] Normally operating lines use bright and vivid colors. For example, a normal high-voltage line is bright red, and a normal low-voltage line is bright blue, etc., to highlight their normal operating state. When a line fails, the color changes to a flashing warning color. For example, a faulty high-voltage line becomes a flashing dark red, and a faulty low-voltage line becomes a flashing dark blue, so that the operation and maintenance personnel can quickly identify the faulty line. For lines in a warning state, colors between normal and faulty are used. For example, a high-voltage warning line is orange, and a low-voltage warning line is light blue, to remind the operation and maintenance personnel to pay attention to potential risks.

[0174] According to the magnitude of the current speed, the color of the pipeline is encoded with a gradient. The faster the current speed, the more the pipeline color tends to be yellow (representing high-speed flow); the slower the current speed, the more the color tends to be the original color of the pipeline. For example, for high-voltage lines, when the current speed reaches a certain threshold, it gradually fades from red to orange-yellow. For the current direction, arrow marks can be added to the pipeline, and the arrow color is the same as the line color encoding to visually display the current direction.

[0175] Step S306: Display power grid monitoring based on the 3D simulation scenario.

[0176] Specifically, the above step S306 includes:

[0177] Step S3061: Dynamically display real-time data of power grid monitoring based on the 3D simulation scenario, including:

[0178] Establish an efficient data update channel to ensure that the data of underlying devices, electrical parameter data, current flow direction data, etc. collected by the monitoring center can be transmitted to the 3D simulation display platform in real time. In the 3D simulation scenario, the real-time data changes are displayed through dynamic effects. For example, for the current magnitude of the transmission line, it is represented by the height of the dynamic light column on the pipeline surface. The larger the current, the higher and more colorful the light column; for the device temperature, the color of the device model gradually turns red as the temperature rises and becomes a flashing red warning when it exceeds the threshold.

[0179] Use the method of chart and number superposition to intuitively display electrical parameter data in the 3D scenario or on the information panel. For example, display the active power comparison of different lines in the form of a bar chart, directly display the real-time voltage, current values, as well as parameters such as power factor and frequency next to the device model, so that users can quickly obtain key data without additional operations.

[0180] Step S3062: Highlight faults and anomalies in power grid monitoring based on the 3D simulation scenario, including:

[0181] Fault identification design: When a power grid fault occurs, the faulty lines and devices are prominently identified in the 3D simulation scenario. In addition to changing the faulty line to a flashing warning color according to the previously set color coding rules, obvious fault icons such as a red cross or exclamation mark are added at the fault location. For the faulty device, the whole device model changes color to red, and a detailed fault information window including fault type, occurrence time, possible reasons, etc. pops up above the device. In the fault warning area of the information panel, all current faults are listed in detail in a list, sorted by fault severity or occurrence time. Each fault record contains key information such as the name and location of the faulty line or device and the fault description, accompanied by a sound warning prompt to ensure that maintenance personnel do not miss any fault information.

[0182] Abnormal Tracking and Analysis: Provide the tracking function for faults and anomalies. When the user clicks on the fault identifier or the record in the alarm list, the 3D simulation scene automatically focuses on the fault location, and shows the change of the current flow before and after the fault occurs in the form of animation, helping the operation and maintenance personnel analyze the cause and scope of influence of the fault. Combine historical data and real-time monitoring data to generate a fault analysis report in the 3D scene. The report is presented in a combination of visual charts and text descriptions, such as showing the trend changes of the device operation parameters in a period of time before the fault occurs, and the comparative analysis with the normal operation data, providing a strong basis for the operation and maintenance personnel to formulate a fault repair plan.

[0183] Step S3063, perform multi-scenario display and collaboration for power grid monitoring based on the 3D simulation scene, including:

[0184] According to different application scenarios and display requirements, create multiple 3D simulation scene views. For example, set up a daily monitoring scene to focus on showing the normal operation status and real-time data of the power grid; an emergency disposal scene to highlight the fault lines, equipment and the execution steps of the emergency plan; a training and teaching scene to simplify the scene complexity, increase detailed annotations and explanations for the training and learning of new employees.

[0185] Remote Collaboration Display: Rely on network communication technology to achieve remote sharing and collaboration of the 3D simulation scene. Multiple users can view and operate the same 3D power grid monitoring scene at the same time through their respective terminal devices (such as computers, tablets) in different geographical locations. Support real-time voice communication and text chat functions to facilitate communication and exchange among users during the remote collaboration process.

[0186] The built 3D simulation scene is as Figure 5 shown. The 3D simulation scene has the ability to be refined step by step, allowing users to drill down to more specific levels to view detailed information, and can clearly indicate the specific location of the problem when any anomaly is detected. Provide more detailed level divisions when needed, enabling users to view the detailed information of a specific floor or area, and be able to promptly feedback any problems in that area. Allow users to perform in-depth access to a single monitoring point, providing detailed operation parameters and other relevant information to help users better understand the working status of this monitoring point.

[0187] The display method of power grid monitoring provided in this embodiment, through 3D modeling and rendering, creates a realistic power grid environment, synchronizes real-time data, can dynamically display the current flow, distinguishes voltage levels through color coding, can also achieve multi-level data display, from the global to the local details, and can automatically identify faults and dynamically generate information related to each node. It can also be applied to smart water, such as the flow direction of the water pipe network in smart water and fault location.

[0188] In this embodiment, a display system for power grid monitoring is also provided. As Figure 4 shown, this system can be implemented by a power grid monitoring platform, including:

[0189] A data acquisition layer for real-time acquisition of the data of underlying devices at monitoring points;

[0190] A monitoring center for calculating electrical parameter data based on the data of underlying devices, calculating current distribution and voltage drop based on the data of underlying devices at the same time, and judging the current flow direction based on the current distribution and voltage drop; performing power grid fault diagnosis and power grid status judgment based on the magnitude relationship between the data of underlying devices and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction;

[0191] An application display layer for constructing a 3D simulation scene using 3D simulation software based on the data of underlying devices, electrical parameter data, current flow direction, power grid faults and power grid status; displaying power grid monitoring based on the 3D simulation scene.

[0192] As Figure 4 shown, between the data acquisition layer and the monitoring center, and between the monitoring center and the application display layer, the communication method is selected in a hierarchical progressive manner. First, Bluetooth is tried for short-distance communication. When Bluetooth cannot meet the requirements, HPLC (High-Speed Power Line Communication), Ethernet, 4G, and 5G are tried in turn. These communication resources can maximize the utilization of existing communication resources and provide the optimal communication solution in different environments. The hierarchical progressive communication method not only improves the robustness of the system, but also can flexibly adjust the communication method according to the requirements of different application scenarios to ensure the continuity and quality of data transmission.

[0193] In this embodiment, a display device for power grid monitoring is also provided. This device is used to implement the above embodiment and the preferred implementation manner, and those that have been described will not be repeated. As used hereinafter, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0194] This embodiment provides a display device for power grid monitoring. As Figure 6 shown, it includes:

[0195] A data acquisition module 601 for real-time acquisition of the data of underlying devices at monitoring points;

[0196] The data calculation module 602 is used to calculate electrical parameter data based on the underlying device data, calculate the current distribution and voltage drop based on the underlying device data, and determine the current flow direction based on the current distribution and voltage drop;

[0197] The fault diagnosis and power grid status judgment module 603 is used to perform power grid fault diagnosis and power grid status judgment based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction;

[0198] The 3D simulation scene construction module 604 is used to construct a 3D simulation scene using 3D simulation software based on the underlying device data, electrical parameter data, current flow direction, power grid faults, and power grid status;

[0199] The display module 605 is used to display the power grid monitoring based on the 3D simulation scene.

[0200] In some optional embodiments, the underlying device data includes photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data, and power supply data; the data calculation module 602 includes:

[0201] The power calculation unit is used to calculate the active power, reactive power, apparent power, and power factor based on the power sensor data, energy-consuming device data, and power supply data.

[0202] The output power calculation unit of the photovoltaic system is used to calculate the output power of the photovoltaic system in the power grid based on the photovoltaic data.

[0203] The SOC change unit is used to calculate the SOC change of the energy storage system in the power grid based on the energy storage data.

[0204] The total current and total voltage calculation unit is used to calculate the total current and total voltage of the monitoring point based on the distribution network data.

[0205] The electrical parameter data determination unit is used to use the active power, reactive power, apparent power, power factor, output power of the photovoltaic system, SOC change of the energy storage system, total current and total voltage of the monitoring point as electrical parameter data.

[0206] The current distribution calculation unit is used to calculate the current distribution using Kirchhoff's law based on the photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data, and power supply data.

[0207] The voltage drop calculation unit is used to calculate the voltage drop using Ohm's law based on the photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data, and power supply data.

[0208] A current flow calculation unit for calculating the current flow direction based on the current distribution and voltage drop; the current flow direction includes: for an AC circuit, according to Kirchhoff's current law, at any node in the circuit, the sum of the currents flowing into any node is equal to the sum of the currents flowing out of any node; for a DC circuit, the current flows from the positive pole of the power supply through the load and back to the negative pole of the power supply. When the DC circuit is a DC circuit containing an energy storage device, when the energy storage device is charging, the current direction points to the energy storage device; when the energy storage device is discharging, the current direction flows out of the energy storage device.

[0209] In some alternative embodiments, the display device for power grid monitoring further includes:

[0210] A device load linkage module for setting the shutdown device priority for the devices in the power grid. The shutdown device priority includes low-priority shutdown devices and high-priority shutdown devices; the low-priority shutdown devices are key devices in the power grid that are not allowed to be easily powered off, and the high-priority shutdown devices are interruptible non-critical auxiliary devices or devices operating at less than full load and will not change the production and / or service operation; when the device load in the power grid exceeds the preset load threshold, the relevant devices are shut down or the device load is changed based on the shutdown device priority, so that the device load is less than or equal to the preset load threshold to change the current flow direction of the power grid.

[0211] In some alternative embodiments, the fault diagnosis and power grid status judgment module 603 includes:

[0212] A bottom-layer device fault judgment unit for determining that the corresponding bottom-layer device is faulty when any one of the data in the bottom-layer device data exceeds the preset device threshold.

[0213] A monitoring point fault judgment unit for determining that the corresponding monitoring point is faulty when any one of the data in the electrical parameter data exceeds the preset electrical parameter threshold.

[0214] A current flow direction fault judgment unit for determining that there is a line fault, a ground fault or device damage when the current flow direction has a reverse flow or a current appears in a branch where there should be no current.

[0215] An energy storage system status judgment unit for determining that the energy storage system is charging and the current direction points to the energy storage device if the SOC change of the energy storage system increases; and determining that the energy storage system is discharging and the current direction deviates from the energy storage device if the SOC change of the energy storage system decreases.

[0216] A photovoltaic system power generation status judgment unit, which determines that the photovoltaic system is generating power and the current direction deviates from the photovoltaic system if the output power of the photovoltaic system is greater than the preset value, otherwise determines that the photovoltaic system is not generating power.

[0217] A power grid status judgment unit is configured to judge that the power grid is in a normal operation state when the underlying device data is within a preset device data threshold range, the electrical parameter data is within a preset electrical parameter threshold range, and the current flow direction conforms to the design expectation; otherwise, the power grid is in a fault state.

[0218] In some alternative embodiments, the 3D simulation scene construction module 604 includes:

[0219] A pipeline and current velocity model construction unit is configured to calculate the point distance between two monitoring points based on the current flow direction, and generate a pipeline with a corresponding length and a current velocity model in the pipeline by using 3D simulation software; the current flow velocity model in the pipeline is represented by the following formula:

[0220] U = V·B / R;

[0221] where, u is the current velocity, V is the voltage, B is the magnetic induction intensity, and R is the resistance.

[0222] A line coding generation unit is configured to generate line codings of different colors by using 3D simulation software based on the pipeline, the current velocity in the pipeline, the underlying device data, the electrical parameter data, the current flow direction, the power grid fault, and the power grid status.

[0223] A 3D simulation scene construction unit is configured to label the pipeline, the current velocity in the pipeline, the current flow direction, the power generation status of the photovoltaic system, the charge and discharge status of the energy storage system, and the power grid fault status with line codings of different colors, and generate a 3D simulation scene after the labeling is completed.

[0224] The further function descriptions of the above-mentioned modules and units are the same as those in the corresponding embodiments above, and will not be elaborated here.

[0225] The power grid monitoring display device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0226] The embodiment of the present invention further provides a computer device having the above-mentioned Figure 6 shown power grid monitoring display device.

[0227] Please refer to Figure 7 , Figure 7 which is a schematic structural diagram of a computer device provided by an alternative embodiment of the present invention. As shown in Figure 7As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting the components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if needed, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (such as an array of servers, a set of blade servers, or a multi-processor system). Figure 7 Take one processor 10 as an example in Figure 7 .

[0228] The processor 10 can be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 can further include a hardware chip. The above hardware chip can be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The above programmable logic device can be a complex programmable logic device, a field programmable gate array, a generic array logic, or any combination thereof.

[0229] Among them, the memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments.

[0230] The memory 20 can include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the computer device, etc. In addition, the memory 20 can include high-speed random access memory and can also include non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 can optionally include a memory remotely set relative to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0231] The memory 20 can include volatile memory, such as random access memory; the memory can also include non-volatile memory, such as flash memory, a hard disk, or a solid-state drive; the memory 20 can also include a combination of the above types of memory.

[0232] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 may be connected by a bus or other means. Figure 7 Take the connection by bus as an example.

[0233] The input device 30 can receive input digital or character information and generate key signal inputs related to the user settings and function controls of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED), a tactile feedback device (e.g., a vibration motor), etc. The above display device includes, but is not limited to, a liquid crystal display, a light-emitting diode, a display, and a plasma display. In some alternative embodiments, the display device may be a touch screen.

[0234] The embodiments of the present invention also provide a computer-readable storage medium. The methods according to the embodiments of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code that is originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the methods described herein can be processed by such software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium may also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by the computer, the processor, or the hardware, the methods shown in the above embodiments are implemented.

[0235] A part of the present invention can be applied as a computer program product, such as computer program instructions. When executed by a computer, through the operation of the computer, the methods and / or technical solutions according to the present invention can be invoked or provided. Those skilled in the art should be able to understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0236] Although embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A display method for power grid monitoring, characterized in that The method includes: Collecting in real time the underlying device data at monitoring points in the power grid; Calculating electrical parameter data based on the underlying device data, calculating the current distribution and voltage drop based on the underlying device data at the same time, and judging the current flow direction based on the current distribution and voltage drop; Conducting power grid fault diagnosis and power grid state judgment based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current flow direction; Constructing a 3D simulation scenario using 3D simulation software based on the underlying device data, electrical parameter data, current flow direction, power grid faults and power grid states; Displaying the power grid monitoring based on the 3D simulation scenario.

2. The method according to claim 1, wherein The underlying device data includes photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data and power supply data; The calculating the electrical parameter data based on the underlying device data includes: Calculating the active power, reactive power, apparent power and power factor based on the power sensor data, energy-consuming device data and power supply data; Calculating the output power of the photovoltaic system in the power grid based on the photovoltaic data; Calculating the SOC change of the energy storage system in the power grid based on the energy storage data; Calculating the total current and total voltage of the monitoring point based on the distribution network data; Taking the active power, reactive power, apparent power, power factor, output power of the photovoltaic system, SOC change of the energy storage system, total current and total voltage of the monitoring point as electrical parameter data.

3. The method according to claim 2, wherein Calculating the current distribution and voltage drop based on the underlying device data, and judging the current flow direction based on the current distribution and voltage drop, includes: Calculating the current distribution using Kirchhoff's law based on the photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data and power supply data; Calculating the voltage drop using Ohm's law based on the photovoltaic data, energy storage data, distribution network data, power sensor data, energy-consuming device data and power supply data; Calculating the current flow direction based on the current distribution and voltage drop, the current flow direction includes: for an AC circuit, according to Kirchhoff's current law, at any node in the circuit, the sum of the currents flowing into the any node is equal to the sum of the currents flowing out of the any node; for a DC circuit, the current flows from the positive pole of the power supply through the load and back to the negative pole of the power supply. When the DC circuit is a DC circuit containing an energy storage device, when the energy storage device is charging, the current direction points to the energy storage device; when the energy storage device is discharging, the current direction flows out of the energy storage device.

4. The method according to claim 1, wherein The method further includes: Setting the shutdown device priority for the devices in the power grid, the shutdown device priority includes low-priority shutdown devices and high-priority shutdown devices; the low-priority shutdown devices are key devices in the power grid and do not allow easy power outage, and the high-priority shutdown devices are interruptible non-critical auxiliary devices or devices operating at less than full load and will not change production and / or service operation; When the device load in the power grid exceeds the preset load threshold, closing the relevant devices or changing the device load based on the shutdown device priority, so that the device load is less than or equal to the preset load threshold, so as to change the current flow direction of the power grid.

5. The method according to claim 1, characterized in that, Grid fault diagnosis is carried out based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current direction, including: When any one of the data in the underlying device data exceeds the preset device threshold, it is determined that the corresponding underlying device fails; When any one of the data in the electrical parameter data exceeds the preset electrical parameter threshold, it is determined that the corresponding monitoring point fails; When the current direction shows a reverse flow or there is current in a branch where there should be no current, it is determined that there is a line fault, a ground fault, or equipment damage.

6. The method according to claim 1, wherein Grid status judgment is carried out based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current direction, including: If the SOC of the energy storage system increases, it is determined that the energy storage system is charging and the current direction points to the energy storage device; if the SOC of the energy storage system decreases, it is determined that the energy storage system is discharging and the current direction deviates from the energy storage device; If the output power of the photovoltaic system is greater than the preset value, it is determined that the photovoltaic system is generating electricity and the current direction deviates from the photovoltaic system, otherwise it is determined that the photovoltaic system is not generating electricity; When the underlying device data is within the preset device data threshold range, the electrical parameter data is within the preset electrical parameter threshold range, and the current direction conforms to the design expectation, it is judged that the power grid is in normal operation; otherwise, the power grid is in a fault state.

7. The method according to claim 1, characterized in that, A 3D simulation scenario is constructed using 3D simulation software based on the underlying device data, electrical parameter data, current direction, grid fault, and grid status, including: The point distance between two monitoring points is calculated through the current direction, and pipelines of corresponding lengths and the current velocity model in the pipelines are generated using 3D simulation software based on the point distance; Different colored line codes are generated using 3D simulation software based on the pipelines, the current velocity in the pipelines, the underlying device data, the electrical parameter data, the current direction, the grid fault, and the grid status; The pipelines, the current velocity in the pipelines, the current direction, the power generation status of the photovoltaic system, the charge and discharge status of the energy storage system, and the grid fault status are marked for the different colored line codes. After marking, a 3D simulation scenario is generated; The current flow velocity model in the pipeline is represented by the following formula: U = V·B / R; Where, u is the current velocity, V is the voltage, B is the magnetic induction intensity, and R is the resistance.

8. A display system for power grid monitoring, characterized in that, The system includes: A data acquisition layer for real-time acquisition of the underlying device data at the monitoring points; A monitoring center for calculating the electrical parameter data based on the underlying device data, calculating the current distribution and voltage drop based on the underlying device data at the same time, and judging the current direction based on the current distribution and voltage drop; carrying out grid fault diagnosis and grid status judgment based on the magnitude relationship between the underlying device data and the preset device data threshold, the magnitude relationship between the electrical parameter data and the preset electrical parameter threshold, and the current direction; An application display layer for constructing a 3D simulation scenario using 3D simulation software based on the underlying device data, electrical parameter data, current direction, grid fault, and grid status; displaying the grid monitoring based on the 3D simulation scenario.

9. A display device for power grid monitoring, characterized in that, The device includes: A data acquisition module for real-time acquisition of the underlying device data at the monitoring points; A data calculation module, configured to calculate electrical parameter data based on the underlying device data, calculate current distribution and voltage drop based on the underlying device data at the same time, and determine the current flow direction based on the current distribution and voltage drop; A fault diagnosis and power grid status judgment module, configured to perform power grid fault diagnosis and power grid status judgment based on the magnitude relationship between the underlying device data and a preset device data threshold, the magnitude relationship between the electrical parameter data and a preset electrical parameter threshold, and the current flow direction; A 3D simulation scene construction module, configured to construct a 3D simulation scene by using 3D simulation software based on the underlying device data, electrical parameter data, current flow direction, power grid fault, and power grid status; A display module, configured to display power grid monitoring based on the 3D simulation scene.

10. A computer device, characterized in that, Comprising: A memory and a processor, which are communicatively connected to each other. Computer instructions are stored in the memory, and the processor executes the computer instructions to execute the power grid monitoring display method according to any one of claims 1 to 7.

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