Active acquisition positioning identification device and method

Abstract

The present invention relates to an active acquisition, positioning and identification device and method. The active acquisition, positioning and identification device includes an electrical signal sensor for detecting electrical parameter data; a temperature sensor for detecting temperature data; a positioning module for detecting position data; a power carrier module for transmitting and receiving power carrier signals based on OFDM technology; a data processing module for using electrical parameter data to perform load forecasting, temperature perception based on temperature data, position recording based on position data, and calculating and predicting carrier channel input impedance based on power carrier signals to determine whether power switching occurs. The active acquisition, positioning and identification method includes a load forecasting method, a temperature perception method, a position recording method and a power switching judgment method. The present invention integrates energy information flow to realize multiple functions such as load forecasting, temperature perception, position recording and power switching judgment, which can better serve energy users and reduce the workload of staff.

Description

Technical Field

[0001] The present invention belongs to the field of power metering, communication and collection, and specifically relates to an active collection and positioning identification device and method suitable for the collection and processing of data in the marketing department of a power grid company, the location positioning of a terminal, temperature perception and the communication industry. Background Art

[0002] The industrialization of human civilization is accompanied by the large-scale application of electric energy, from the original steam locomotive to the rapidly developing high-speed rail, from the polluting fuel vehicles to the clean and efficient electric vehicles, from the dim kerosene lamps to the energy-saving lamps that have entered thousands of households. The proportion of electric energy in the terminal energy consumption side is increasing, and the popularization of electric energy has greatly improved people's living conditions and promoted the improvement of productivity.

[0003] As a commodity of energy consumption, electric energy is accompanied by the communication of electric energy measurement and terminal metering equipment. The measurement and communication of electric energy have always been the core issues of the utilization of electric energy consumption. From the old mechanical meter to the smart meter, the data acquisition terminal of the power grid marketing department has undergone several generations of innovation and transformation. The mechanical energy meter uses the electromagnetic force generated during the flow of electric energy to drive the movable part of the measuring mechanism to produce a corresponding proportional mechanical action to react to the power flowing through the energy meter. The mechanical energy meter was mainly used in the last century. Its structure is relatively simple and can realize basic functions such as voltage, current, power, frequency and phase. The disadvantages of the mechanical energy meter are obvious. The simple structure leads to low measurement accuracy. Once it lacks maintenance for a long time, the error of the metering device will increase. At the same time, the mechanical energy meter has a single function and does not have the functions of phase sequence measurement, anti-theft, maximum demand measurement, etc. The lack of communication function makes it impossible to transmit the real-time collected electric energy data back to the operation and maintenance unit. It has to rely on traditional manual copying of meter data. At that time, the data collection and operation and maintenance work of the marketing department of the power grid company was complicated and inefficient. With the changes in electronic information technology and the improvement of manufacturing processes, a new generation of smart meters has been introduced into the data collection and operation and maintenance of power grids. In addition to the basic functions of mechanical meters for energy measurement, smart meters can also realize two-way billing of multiple rates, relay control on the user side, two-way communication of multiple data transmission modes, real-time data call, anti-electricity theft and other functions. The high-precision AD digital-to-analog conversion acquisition module of smart meters improves the accuracy of energy meter measurement, effectively supports the lean management and operation of the power grid consumption side, and to a certain extent meets the requirements of power grid companies for terminal metering communication. The increasing scale of my country's power grid, the continuous growth of electricity demand, and the exponential growth of terminal equipment have put forward new requirements for terminal equipment in the new era. Although the existing energy meters have made great progress compared with traditional mechanical energy meters, they still have great limitations. With the development of communication technologies represented by 5G and the development of high-precision location services represented by Beidou, conditions have been created for the improvement of metering communication of energy terminals and the development of non-metering functions of terminals. The communication of existing mainstream electricity meters is mainly connected to the terminal through RS-485 lines, and the terminal realizes data transmission with the background main station through the mobile public network or wireless private network. Another mainstream data communication method is to use the collector to realize two-way data communication with the concentrator through the narrowband / broadband carrier of the power line. The communication signal transmission of the smart meter using carrier communication uses the power line that transmits energy to realize the integration of energy information flow. The lean management of terminal energy consumption by power grid companies and the development of emerging industries such as smart energy and integrated energy have put forward higher requirements for the acquisition and operation of terminals. High-precision, low-cost, high-reliability, and integration of multiple non-metering functions are the development direction of power grid smart terminals. The existing data acquisition communication storage diagram of the power grid company is shown below Figure 1 shown.

[0004] The application and large-scale popularization of smart meters have met the requirements for electricity metering and collection to a certain extent, and promoted the intelligent and lean operation and maintenance of terminals. However, with the expansion of the scale of the power grid and the increasing complexity of the operation and maintenance areas, the requirements for the accuracy and type of collected data have increased, and the existing smart meters have been difficult to adapt to current application requirements. Data transmission technology represented by 5G communication has greatly accelerated the efficiency and capacity of data transmission, creating technical conditions for the development of high-speed, low-latency and high-reliability data collection terminals. The mature application of satellite navigation systems represented by Beidou has created space for all-weather real-time positioning and precise timing. The problems and shortcomings of existing smart meters are concentrated in the following four points:

[0005] 1) A considerable number of existing smart meters rely on RS-485 lines to achieve short-distance communication between the meter and the terminal. The RS-485 structure is relatively simple, with only the physical layer and link layer. It cannot achieve automatic arbitration of the bus and does not support star and tree structure wiring. The use of RS-485 lines will also occupy the already tight terminal equipment installation space resources, wasting certain financial and human resources. The development direction is to develop integrated terminals based on carrier signals to achieve the integration of energy information flows;

[0006] 2) Existing smart meters only have metering functions but no communication functions. The power carrier module used is not integrated in the electric energy meter, and there is a problem of mismatching between communication protocols. Although the existing carrier-based communication has achieved the fusion of energy information flow, the signal-to-noise ratio is relatively low, and the data signal is submerged in the energy flow, resulting in low data transmission accuracy. The limitation of broadband carrier frequency bands leads to low transmission efficiency and mutual interference. Using algorithms to improve the accuracy of data transmission without increasing hardware costs is the difficulty of using carrier communication;

[0007] 3) Developing non-metering functions for power grid company terminal equipment is in line with the trend of building an energy Internet with electricity as the core. The functions of existing smart meters are mainly metering functions developed from the perspective of power grid company operation and maintenance management. Breaking through the limitations of terminal equipment metering and developing and expanding the collection of non-electrical signals of terminal equipment is the proper meaning of realizing smart energy, and is more conducive to using collected data to serve electricity consumers. The terminal equipment can realize real-time collection and transmission of weather signals such as temperature and humidity, supporting a more refined weather forecast and early warning system. Existing terminal equipment is generally installed in difficult-to-find locations such as underground civil air defense, and even some old meters cannot find their specific locations, which brings certain difficulties to operation and maintenance work. Developing the positioning function of smart terminals is an issue that needs to be solved urgently;

[0008] 4) How to use the collected data to realize load identification based on big data and automatic identification of substations without increasing the complexity of hardware is a difficult problem to be solved. Existing data acquisition terminals can only realize data collection and communication but do not have data processing and automatic identification functions. The loads of substations are diverse, and the loads of different substations have different complex characteristics. Relying on the collected multi-dimensional data statistics to realize load identification is the direction of development. The data acquisition terminals under the substations will be inconsistent with the spatial position relationship in the background main station due to power outages and other operations. It is also an urgent problem to realize the active identification and self-analysis of the substation to which the smart terminal belongs. Problems with existing smart meters include Figure 2 shown. Summary of the invention

[0009] The purpose of the present invention is to provide an active acquisition, positioning and identification device integrating multiple functions.

[0010] In order to achieve the above object, the technical solution adopted by the present invention is:

[0011] An active acquisition positioning and identification device, comprising:

[0012] An electrical signal sensor, the electrical signal sensor is used to detect electrical parameter data;

[0013] A temperature sensor, wherein the temperature sensor is used to detect temperature data;

[0014] A positioning module, wherein the positioning module is used to detect position data;

[0015] A power carrier module, which is used to transmit and receive power carrier signals based on OFDM technology;

[0016] A data processing module, the data processing module is used to use the electrical parameter data to perform load forecasting, perform temperature sensing based on the temperature data, perform position recording based on the position data, and calculate and predict the carrier channel input impedance based on the power carrier signal to determine whether power switching occurs;

[0017] The electrical signal sensor, the temperature sensor, the positioning module, and the power carrier module are all connected to the data processing module.

[0018] The electrical signal sensor includes a current sensor and a voltage sensor.

[0019] The active acquisition positioning and identification device also includes:

[0020] A display connected to the data processing module;

[0021] A display driving module, wherein the data processing module is connected to the display through the display driving module;

[0022] A data storage module, the data storage module is connected to the data processing module;

[0023] an infrared communication circuit, the infrared communication circuit being connected to the data processing module;

[0024] 485 communication circuit, the 485 communication circuit is connected to the data processing module.

[0025] The active acquisition positioning and identification device also includes:

[0026] A clock module, the clock module is connected to the data processing module;

[0027] A crystal oscillator, the crystal oscillator is connected to the clock module;

[0028] A power module, the power module is connected to the data processing module;

[0029] An online programming port, the online programming port being connected to the data processing module;

[0030] An IO port, the IO port being connected to the data processing module;

[0031] A communication port, the communication port being connected to the data processing module;

[0032] A power supply module is connected to the data processing module.

[0033] The data processing module is connected to the background main station through a wireless public network, and the data processing module is used to integrate and upload the electrical parameter data, the temperature data, the position data and the power carrier signal to the background main station.

[0034] The present invention also provides an active acquisition, positioning and identification method adopted by the above-mentioned active acquisition, positioning and identification device, and the active acquisition, positioning and identification method includes a load prediction method, a temperature sensing method, a position recording method and a power supply switching judgment method.

[0035] The load prediction method is: detecting electrical parameter data, determining the load type of the substation according to the substation clustering division scheme, using the electrical parameter data to train the BP neural network corresponding to the load type of the substation, and then using the trained BP neural network to perform load prediction.

[0036] The power switching judgment method is: based on OFDM technology, power carrier signals are transmitted and received, the power carrier signals are used to calculate and predict the carrier channel input impedance, and whether power switching occurs in the corresponding area is judged according to whether the carrier channel input impedance changes.

[0037] The power carrier signal of different frequencies is transmitted.

[0038] Due to the application of the above technical scheme, the present invention has the following advantages compared with the prior art: the present invention integrates energy information flow to realize multiple functions such as load forecasting, temperature perception, location recording and power switching judgment, which can better serve energy-consuming customers and reduce the workload of staff. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Attached Figure 1 This is a schematic diagram of the existing data acquisition, communication and storage system of the power grid company.

[0040] Attached Figure 2 This is a schematic diagram of the problems existing in existing smart meters.

[0041] Attached Figure 3 It is a schematic diagram of the active acquisition positioning and identification device of the present invention.

[0042] Attached Figure 4 This is a layout diagram of the active acquisition, positioning and identification device of the present invention.

[0043] Attached Figure 5 The figure is a flow chart of the active acquisition positioning and identification method of the present invention.

[0044] Attached Figure 6 Schematic diagram of the impedance measurement method of the power line carrier communication channel.

[0045] Attached Figure 7 This is a simplified topological diagram of the substation.

[0046] Attached Figure 8 Identify schematics for dual power switching.

[0047] Attached Fig. 9 Identify the circuit diagram for dual power switching.

[0048] Attached Fig.10 It is an energy propagation path diagram for power generation, transmission and distribution.

[0049] Attached Fig.11 This is the schematic diagram of the carrier signal transmitting and receiving device.

[0050] Attached Fig.12 Schematic diagram of typical pulse interference in power lines.

[0051] Attached Fig.13Schematic diagram of the channel model of low-voltage power lines.

[0052] Attached Fig.14 This is a schematic diagram of a two-port network model.

[0053] Attached Fig.15 This is a typical structural diagram of a low-voltage residential power network.

[0054] Attached Fig.16 This is a diagram of the transmission matrix model of a two-port network of low-voltage power lines.

[0055] Attached Fig.17 This is the two-port input impedance characteristic model diagram.

[0056] Attached Fig.18 This is the circuit model diagram of a uniform transmission line.

[0057] Attached Fig.19 This is the structural diagram of the overhead line.

[0058] Attached Fig. 20 This is the structure diagram of a four-core symmetrical cable.

[0059] Attached Fig.21 This is a time domain diagram of 4 subcarriers.

[0060] Attached Fig. 22 This is a spectrum diagram of 4 subcarriers.

[0061] Attached Fig.23 This is the schematic diagram of OFDM signal transmission.

[0062] Attached Fig.24 This is a three-layer BP neural network structure diagram.

[0063] Attached Fig.25 Schematic diagram of user power line channel impedance measurement.

[0064] Attached Fig.26 This is a schematic diagram of the data collected in the area in one day.

[0065] Attached Fig. 27 This is a schematic diagram of data collection for power line carrier input impedance in a normal substation area.

[0066] Attached Fig.28 This is a schematic diagram of data collection for power line carrier input impedance in abnormal substation areas.

[0067] Attached Fig.29 This is a schematic diagram of the model prediction results for low-voltage residential areas.

[0068] Attached Fig.30 This is a schematic diagram of the second example of low-voltage residential area model prediction results.

[0069] Attached Fig.31This is a schematic diagram of the third example of low-voltage residential area model prediction results. DETAILED DESCRIPTION

[0070] The present invention will be further described below in conjunction with the embodiments shown in the accompanying drawings.

[0071] Embodiment 1: In order to solve the problems existing in the existing smart meters, a new active collection, positioning and identification device based on the fusion of energy information flow has been developed. In order to get rid of the dependence on RS-485 wired data transmission, this solution adopts a data transmission mode based on carrier communication, which uses the original power transmission line to send and receive carrier signals, realizes the fusion and decoupling of energy flow and information flow, and reduces the space occupied and the manpower and material resources spent on the construction of dedicated signal transmission channels. Use temperature sensors and other devices to perceive the temperature signals around the smart terminal. Use communication modules / satellite positioning modules to realize terminal positioning and real-time communication. In addition to being used for communication and data transmission, carrier signals can also be used for carriers to realize load identification and automatic judgment of substations, and build a home energy efficiency improvement ecosystem based on smart energy. The specific plan is as follows:

[0072] As attached Figure 3 and attached Figure 4 As shown, an active acquisition positioning and identification device mainly includes an electrical signal sensor, a temperature sensor, a positioning module, a power carrier module and a data processing module (MCU). The electrical signal sensor, the temperature sensor, the positioning module and the power carrier module are all connected to the data processing module. The electrical signal sensor is used to detect electrical parameter data, which includes a current sensor and a voltage sensor. The temperature sensor is used to detect the temperature data of the location. The positioning module is a satellite positioning module (based on the Beidou system) for detecting position data. The power carrier module is used to transmit and receive power carrier signals based on OFDM technology, thereby realizing communication functions and providing support for the calculation of subsequent carrier channel input impedance. The data processing module is used to use electrical parameter data for load forecasting, temperature perception based on temperature data, location recording based on location data, and calculation and prediction of carrier channel input impedance based on power carrier signals to determine whether power switching occurs. The data processing module is connected to the background master station through a wireless public network or other communication methods, so that the data processing module is used to integrate and upload electrical parameter data, temperature data, location data and the power carrier signal to the background master station. The background master station is used to receive electrical parameter data, temperature data, location data and power carrier signals.

[0073] In addition, the active acquisition positioning and identification device may also include one or a combination of (LCD) display, display driver module, data storage module, infrared communication circuit, 485 communication circuit, clock module, crystal oscillator, power module, online programming port, IO port, communication port, etc. The data processing module is connected to the display through the display driver module, and the display is used to display various data. The data storage module (including RAM and / or FLASH) is connected to the data processing module for storing various data. The infrared communication circuit is connected to the data processing module for realizing infrared data communication. The 485 communication circuit is connected to the data processing module for realizing 485 data communication. The clock module is connected to the data processing module to provide a clock signal for the data processing module, and the crystal oscillator is connected to the clock module. The power module is connected to the data processing module, which can provide a variety of voltages of working power for the data processing module, and can also be connected to other modules that require power to realize power supply. The online programming port is connected to the data processing module for loading and updating programs into the data processing module. The IO port is connected to the data processing module for realizing the input and output of various signals. The communication port is connected to the data processing module, including multiple serial ports, simulated serial ports, etc.

[0074] The active data acquisition, positioning and identification device adopts an active data acquisition, positioning and identification method, which includes a load prediction method, a temperature sensing method, a location recording method and a power supply switching judgment method.

[0075] The load prediction method is as follows: (electrical signal sensor) detects electrical parameter data, (data processing module) determines the load type of the substation according to the substation clustering division scheme, and uses the electrical parameter data to train the BP neural network corresponding to the load type of the substation, so as to use the trained BP neural network for load prediction.

[0076] The power switching judgment method is as follows: (power carrier module) transmits and receives power carrier signals based on OFDM technology, (data processing module) uses power carrier signals to calculate and predict the carrier channel input impedance, and judges whether power switching occurs in the corresponding substation according to whether the carrier channel input impedance changes. In this power switching judgment method, power carrier signals of different frequencies are transmitted to achieve frequency sweeping of input impedance. The BP neural network trained with historical data of carrier channel input impedance can be used to predict the carrier channel input impedance. If the error between the calculated value and the predicted value of the currently calculated carrier channel input impedance is large and reaches a certain limit, it is judged that a dual power switching event has occurred and the substation topology has changed.

[0077] The temperature sensing method is: (using a temperature sensor) detecting temperature data, thereby (data processing module) realizing temperature sensing. The location recording method is: (using a positioning module) detecting location data, thereby (data processing module) realizing location recording.

[0078] The specific process is as attached Figure 5 As shown, the specific steps include:

[0079] Step 1: performing data acquisition, including using an electrical signal sensor (current sensor and voltage sensor) to detect electrical parameter data (including current data and voltage data), using a temperature sensor to detect temperature data, using a positioning module to detect positioning data, and using a power carrier module to transmit and receive power carrier signals, so as to calculate the input impedance of the carrier channel;

[0080] Step 2: The data processing module integrates and packages the above data and uploads it to the backend main station via the wireless public network;

[0081] Step 3: The data processing module performs preliminary cleaning and filtering on the data, which can be achieved by using common data preprocessing methods;

[0082] Step 4: The data processing module clusters the distribution network area corresponding to the collected data and divides it into corresponding area clusters. Different area clusters have different power consumption attributes.

[0083] Step 5: The data processing module calculates the input impedance of the carrier channel using the power carrier signal to obtain the current input impedance calculation value;

[0084] Step 6: The data processing module uses the historical data of the electrical parameter data to train the BP neural network for load prediction corresponding to the substation clustering, and uses the historical data of the carrier channel input impedance to train the BP neural network for input impedance prediction;

[0085] Step 7: The data processing module inputs the current input impedance calculation value into the BP neural network for input impedance prediction to obtain the input impedance prediction value;

[0086] Step 8: The data processing module compares the calculated input impedance value with the predicted input impedance value to determine whether power switching occurs in the corresponding distribution network;

[0087] Step 9: The data processing module performs temperature sensing, location recording, dual power switching judgment and load prediction.

[0088] The following is an explanation of the above scheme:

[0089] 1. Channel analysis of power lines

[0090] 1.1 Input Impedance

[0091] As a unique communication method for power systems, power line carrier communication refers to a technology that uses the existing power line network architecture to transmit data in the form of a carrier signal with a smaller amplitude and higher frequency. The biggest advantage of power line carrier communication is that there is no need to rebuild the communication network. Only the existing power energy transmission lines are needed to transmit and communicate data.

[0092] As a channel for energy transmission, power lines have the advantages of being simple and reliable. The basic principle of power line carrier communication is to superimpose a communication signal with a higher frequency and a smaller amplitude on an energy channel with a lower frequency and a larger amplitude. The input impedance of the power line carrier communication channel is the factor that affects the data transmission effect that we need to consider first. Figure 6 The figure shows the method for measuring the impedance of the power line carrier communication channel, and the measured resistance Connect a standard high precision resistor in series A standard sinusoidal excitation signal is applied externally Measure separately and The divided voltage on and The input impedance can be calculated The specific value of is calculated as shown in formula (1):

[0093]

[0094] The values ​​of power line carrier input impedance vary greatly in different areas, at different time points, and even at different measurement points, making it difficult to perform normalized processing and analysis. In addition, the power line carrier is affected by signal attenuation and noise interference, making it difficult to use the carrier signal to accurately sense and identify the load, limiting its application areas. Nevertheless, the characteristics of the power line carrier channel input impedance still have potential value.

[0095] A simplified topological structure of the station area is as follows: Figure 7 As shown, the structures of the two substations (Substation 1 and Substation 2) are completely different, forming a "one main and one backup" dual power supply to important load 1 and important load 2. The input impedance value is measured at both ends of the important load to form a topological structure in which the important load is connected in parallel with other loads. Since the impedance value of the important load is relatively stable, the value of the input impedance does not change much when dual power switching does not occur. When the dual power load is switched from Substation 1 to Substation 2, the structure of other loads changes, causing a large change in the input impedance value of the measurement point of the important load. Therefore, this principle can be used to determine whether dual power switching occurs. The schematic diagram is shown in Figure 8 As shown, the circuit diagram is as Fig. 9 shown.

[0096] like Fig. 9 As shown, the input impedance of the important load point can be divided into important load impedance Z 重要负荷 and other load impedance Z 其它负荷 In the form of parallel connection, carrier signals of different frequencies are injected through the carrier source, and the input impedance at different frequencies is measured to realize the frequency sweep of input impedance. Important loads that need to be powered by dual power supplies must remain stable in most time periods. When the dual power supplies are switched, the topology of other loads changes, and the impedance of other loads changes, causing the input impedance of the carrier source input point to change.

[0097] 1.2 Signal Attenuation

[0098] Power lines not only produce voltage drop, current loss and other attenuation during energy transmission, but also signal attenuation during signal transmission. Different power line materials and different connected power loads will have a great impact on the attenuation and reflection process of signal transmission. Typical energy transmission paths for power generation, transmission and distribution are as follows: Fig.10 shown.

[0099] Fig.10 In the process, the electric energy generated by the power plant is transmitted to the power grid through the step-up transformer, and then transmitted to the transformer in the low-voltage residential area through the backbone network and the distribution network. Due to the signal isolation function of the transformer, the carrier signal can only be transmitted within the area of ​​one transformer. Fig.10 The power supply in the substation area of ​​the old residential area may still use overhead lines and other methods, while the new residential areas are mostly powered by underground cables. Fig.11 As shown, it is generally composed of components such as a signal source receiving device, a coupling unit, a modulator and a demodulator. Since the design is an active acquisition, positioning and identification device based on a broadband carrier, the test frequency range of the device developed later is 0-30MHz.

[0100] 1.3 Noise Interference

[0101] Compared with the RS-485 proprietary line communication method, the biggest challenge of data transmission based on power line carrier communication is the noise interference problem of the channel. The fusion transmission of energy flow and information flow makes it difficult to improve the signal-to-noise ratio. It is necessary to use relevant algorithms to achieve data cleaning, noise reduction and classification. The noise interference models of different substations are different, and even the noise interference in different time periods is inconsistent. The steadily distributed background Gaussian white noise is mainly distributed in the low-frequency band. The instantaneous opening and closing of AC motors and household appliances, and the rectification and inversion process of thyristors are pulse interference. Even meteorological conditions such as weather and humidity will cause a certain degree of interference to power line carrier communication transmission. Typical pulse interference in power lines is such as Fig.12 shown.

[0102] Based on the above analysis, a channel model of low-voltage power lines is established, such as Fig.13 As shown. The attenuation in low-voltage power line transmission is the superposition of coupling attenuation and line attenuation. The coupling attenuation represents the input impedance characteristics of different nodes at different times in different areas, and the line attenuation characteristics represent the influence of line characteristics, materials, length, etc. on the carrier signal. After the noise is superimposed, it is the influence of the power line transmission channel on the signal sending end to the signal receiving end. It is necessary to classify and cluster the impedance characteristics, attenuation characteristics and noise to establish a corresponding model.

[0103] 2. Theoretical analysis

[0104] 2.1 Carrier Channel Modeling

[0105] From the power line channel analysis, we know that we need to model the carrier channel of the power equipment in the low-voltage area to consider the input impedance of the power line, the impact of signal attenuation and noise interference on data transmission. The signal will produce radiation loss and heat loss during the power line transmission process. The corresponding two-port network model is established as follows Fig.14 shown.

[0106] The port characteristics of a two-port network can be represented by the transmission matrix T. A, B, C, and D are the parameters of the transmission matrix, and the voltage-current relationship of the two-port network is given by formula (2).

[0107]

[0108] Low-voltage power grids generally present a tree-like radiation structure, and the network structure is complex and diverse. The typical structure of low-voltage residential power grids is as follows: Fig.15 shown.

[0109] Power transmission line segments l1, l2, ... l n The impedance characteristics of the performance can be expressed by using the two-port network transmission matrix Indicates that, similarly, for the parallel loads Z1, Z2, ... Z n , we can also use the corresponding transmission matrix It can be seen that the power transmission network can be represented by a cascade of transmission matrix two-port networks, such as Fig.16 As shown in Figure 2, the corresponding two-port parameters can be obtained by considering the characteristic properties of various transmission lines.

[0110] Considering the influence of the input impedance characteristics of the power line on the carrier signal, the two-port input impedance characteristic model is established as follows: Fig.17 As shown, A, B, C, and D are the input impedance parameters to be solved. Its input impedance Z in It can be expressed as:

[0111]

[0112] The current mainstream narrowband carrier communication frequency in China is several hundred kilohertz, and the broadband carrier communication frequency is tens of megahertz. The theoretical propagation speed of electromagnetic waves is the speed of light, so the wavelength of the carrier signal is about tens of meters. In the low-voltage area, it is not possible to directly establish a centralized parameter model for analysis and processing. It is necessary to establish a distributed parameter model of the transmission line, such as Fig.18 shown.

[0113] The distributed parameter model of uniform transmission line can be represented by a series of integrated tiny components, that is, it can be composed of many infinitesimal unit length elements dx. Each section dx can be represented as a resistive load R0dx and an inductive load L0dx. The capacitance and conductivity components between two sections of unit conductors can be represented by C0dx and G0dx, respectively. According to the transmission line theoretical model, we can get:

[0114]

[0115]

[0116] The structure of low-voltage transmission lines in my country is complex, and the materials used to make the lines are also different. The parameter characteristics of the circuit parameter model of the established uniform transmission line are related to the nature of the line. Considering two typical power transmission equipment, the channel of the overhead line and the cable is modeled. The structure diagram is as follows: Fig.19 and 20 shown.

[0117] Most of the overhead lines in my country now use steel core aluminum conductors, while the three-phase four-wire underground cables that are increasingly used in residential areas are generally copper conductors. Due to their different materials, they need to be classified and analyzed for characteristic parameters such as resistance, inductance, and capacitance. The electrical parameters of overhead lines can be obtained from the data in the national standard, as shown in Table 1.

[0118] Table 1 Estimated data of electrical parameters of low voltage overhead lines

[0119]

[0120] As cities expand, low-voltage power stations are increasingly using underground cables to supply power. Fig. 20 The four-core symmetrical cable in the circuit is taken as the analysis object, and the mathematical models of resistance, inductance, capacitance and conductance are established.

[0121] When high-frequency current flows through a conductor, the current distribution density in the conductor cross section is uneven, which is called the skin effect. The function expression between the depth δ of the skin effect and the frequency f is:

[0122]

[0123] The resistance of the transmission line model composed of a single-core conductor can be expressed as:

[0124]

[0125] Since low-voltage residential areas in reality use four-core wires (A, B, C and neutral wire) instead of single-core wires, a correction factor X is introduced. R .

[0126]

[0127] The resistance formula of the multi-core twisted conductor is obtained as follows:

[0128] R=X R ·R d (9)

[0129] The inductance parameter of a single wire can be expressed as:

[0130]

[0131] The mutual inductance between parallel wires can be expressed as:

[0132]

[0133] The inductance parameters of the four-core transmission cable are obtained as follows:

[0134]

[0135] The capacitance parameter represents the coupling effect between wires per unit length and is given by the following formula:

[0136]

[0137] The conductivity parameters of the four-core cable can be obtained by the following formula:

[0138]

[0139] Based on the above analysis, the mathematical model of overhead lines and cable conductors is established, and the calculation formulas or estimated values ​​of resistance, inductance and capacitance parameters are given. Next, the corresponding model is established for household electrical equipment such as charging piles, air conditioners, energy-saving lamps, etc. with large loads in low-voltage residential areas.

[0140] By modeling and decomposing the electricity consumption behavior and main loads of low-voltage residential users, the fitting of electricity consumption data and load forecasting are achieved. The main electricity loads are mainly divided into the number of users, lighting, air conditioning, elevators, property electricity, charging piles, etc.

[0141] The number of users is accurately recorded in the marketing business system of the power grid company. The number of users reflects the complexity of the substation. Generally, the substation with a large number of users is an old substation, where the power consumption of a single user is small, the substation is relatively old, and the capacity margin of the substation is small. It is also the key substation for monitoring and prediction. N represents the number of users in the substation. Taking the inverse and multiplying it by the correlation coefficient can represent the impact of the number of users on the substation load.

[0142] With the massive access to power electronic equipment and the need for green development, the lighting equipment in my country's communities has gradually been replaced with energy-saving lamps. Therefore, this patent considers the lighting load modeling of user households based on incandescent lamps. When the voltage fluctuation range is not large, the active power of energy-saving lamps remains basically unchanged and can be considered as a constant value. The lighting load model is established:

[0143]

[0144] Where: p1 and p2 represent the estimated average lighting power consumption in the previous period of the area, A1 and A2 represent the corresponding coefficients, which depend on the type of area. The division of time periods such as t1, t2, t3, t4, etc. also depends on the type of area, and b is the basic load of household electricity such as lighting.

[0145] Air conditioning load modeling is mainly affected by two factors: temperature. The prediction of air conditioning load requires the input of external area temperature information. The established model is as follows:

[0146]

[0147] In the formula: k1, k2, k3 are temperature coefficients, T is the temperature corresponding to time t, when the temperature is high or low, the growth slope of the air-conditioning load is not large, and k2 should be the air-conditioning load coefficient with the largest slope.

[0148] The elevator load peak is usually during the morning, afternoon and evening rush hours when people frequently go up and down stairs. The elevator load is relatively short-lived, and the model is as follows:

[0149]

[0150] In the formula: r represents the rated power of the elevator in the area, A3, A4, A5 represent the coefficients of the corresponding time period, which depends on the type of area divided. 10 The time period division also depends on the type of station, and c is the basic load of the elevator standby.

[0151] Public power equipment such as property also accounts for a considerable proportion of the load in the low-voltage residential area. During the day, there will be public power such as pump rooms in the property, and there will also be loads such as street lights at night. The fluctuation of property power consumption is relatively smoother and has a quadratic relationship with time. The established model is as follows:

[0152] V(t)=A6t 2 +A7t+d (18)

[0153] The public power load such as property changes in a 24-hour cycle. A6 and A7 are the time correlation coefficients, and d is the basic component of the corresponding public power load.

[0154] With the introduction of new infrastructure, the state and State Grid Corporation are vigorously promoting the construction and layout of charging piles, and the construction of charging piles in residential areas will inevitably be further expanded. Unlike other loads, the peak of charging pile power load is at night. The established model is as follows:

[0155]

[0156] Where: q is the total capacity of the charging piles in the area, A8 is the corresponding correlation coefficient, which is related to the area type, e is the basic component of the charging pile load, t 11 ,t 12 The time period mainly refers to the night time period.

[0157] 2.2OFDM (Orthogonal Frequency Division Multiplexing)

[0158] OFDM is the abbreviation of orthogonal frequency division multiplexing technology. The biggest technical feature of OFDM is that it realizes the independent orthogonality between multiple subcarriers. Each data stream is transmitted on a subcarrier. OFDM does not need to use a bandpass filter to achieve subcarrier isolation. The core of OFDM is to orthogonalize multiple subchannels across the entire frequency band. One subchannel is modulated on one subcarrier and then transmitted in parallel. It is narrowband transmission on a separate subcarrier. The subcarriers that are overlapped but still orthogonal to each other are extracted through the fast Fourier transform (FFT). Because the subcarriers are orthogonal in the OFDM transmission mode, the frequency band can be reused, so the frequency band can be fully occupied while reducing the interference between subcarriers. The time domain diagram and frequency domain diagram of a typical 4 subcarriers are shown below. Fig.21 and Fig. 22 shown.

[0159] OFDM can resist strong external pulse noise because OFDM integrates over a long period and the effect of the pulse is diluted. The OFDM modulation mode divides the signal into a large number of subcarriers. Although this significantly reduces the transmission rate, it also makes the signal period in a single channel longer than the multipath delay, thus reducing the interference of the multipath effect on the transmission. OFDM generally multiplexes adjacent signals in the frequency band, so there will be a certain degree of inter-code interference, so it is necessary to add cyclic prefixes and time domain equalization to solve these problems. The principle of OFDM signal modulation mode is as follows: Fig.23 shown.

[0160] The OFDM modulation mode can stably transmit multiple signals at the same time, mainly because the OFDM mode can monitor the transmission status on the line at any time, and then adopt the corresponding modulation method for the corresponding subcarrier with obvious attenuation. OFDM has obvious technical advantages such as good resistance to signal attenuation, avoiding narrowband interference, achieving full utilization of carrier frequency band, and being able to be used for high-speed transmission of carrier signals.

[0161] 2.3BP Neural Network Algorithm

[0162] The load perception of low-voltage residential areas is not a simple linear relationship between input and output, but a nonlinear multi-correlated input and output problem. According to the principle of classification modeling of different types of areas, a rough mathematical model of power load was established, which made it difficult to accurately calculate the coefficients of the model. Different types of areas are greatly affected by random power consumption behaviors, making it difficult to track the coefficients of specific areas in real time. Since the coefficients of the model of a specific area are difficult to determine, and considering that the load of the area is a nonlinear multidimensional system with multiple inputs and multiple outputs, the BP neural network algorithm is introduced to achieve real-time tracking and correction of coefficients of different types of areas. The BP neural network algorithm is an active cognitive algorithm for adaptive autonomous learning, which is very suitable for nonlinear multi-input and multi-output networks. The autonomous learning process of the BP neural network algorithm can be divided into the forward propagation process of the signal and the back propagation process of the error. The input signal is given a certain weight and threshold by the input layer and enters the hidden layer. After the hidden layer is reprocessed, the output layer is obtained. When the error value between the fitting information of the output layer and the true value exceeds the threshold, it is back-propagated again, and the error is distributed to each weight factor to achieve re-learning and re-tracking, and finally the fitting error result is within the preset range. A three-layer BP neural network with one hidden layer is as follows: Fig.24 shown.

[0163] 2.4 Temperature and Positioning

[0164] To obtain the temperature signal, you only need to install a temperature signal sensor on the terminal and transmit the sensor signal to the terminal's MCU. While collecting the temperature signal around the terminal, it can also serve as a temperature warning and early detection of fires caused by electricity. The positioning signal can be used through the satellite positioning module provided by Beidou to accurately locate the terminal module, making it easier for maintenance personnel to find the problem terminal as soon as possible when a terminal fails, and it also serves as an anti-theft function.

[0165] 3. Device hardware design, software design and system flow chart

[0166] In order to verify the correctness of the proposed active acquisition positioning and identification method based on carrier channel input impedance, the aforementioned intelligent data acquisition terminal based on power line carrier communication, namely, the active acquisition positioning and identification device, is designed. Figure 3 As shown. The voltage and current information in the three-phase circuit is collected through current and voltage transformers to realize the most basic functions of the electric energy device. Since the measurement of electric energy parameters is already a very mature and developed industry, a proprietary electric energy metering module is selected to realize the measurement and calculation of electric energy parameters, and data communication and exchange are carried out between the SPI bus and the MCU. External RAM and FLASH chips are used to store data, and relays and control circuits are used to realize weak current signal control of mechanical devices. The added temperature sensor and satellite positioning module realize temperature perception and real-time positioning. The LCD screen displays the collected and calculated parameters when it wakes up. In order to realize the real-time measurement of the input impedance of the power carrier line, a power line carrier communication circuit is designed to realize real-time monitoring and perception of the power line topology. The layout diagram of the device is shown in Figure 4 As shown in the figure, the device can be divided into power supply, JTAG interface, LCD, MCU, voltage sensor, current sensor, communication module, temperature sensor and carrier transmission unit. While taking into account the traditional smart meter, it also adds four functions: real-time positioning, dual power supply identification, temperature perception and load prediction. Compared with the traditional power processing function, it is more powerful and smarter. MSP430F449 is selected as the MCU of the device to achieve ultra-low power consumption operation of the metering device. PLCI36GM-III spread spectrum communication chip is used as the sending and receiving device of the carrier signal.

[0167] The active data acquisition, positioning and identification device must first be programmed, various functions must be debugged, and various basic functions must be tested in the laboratory. Fig.25 The corresponding figure is the schematic diagram of the device user power line channel impedance measurement, in which the transformer plays the role of isolation, using the channel impedance Z X With high precision impedance Z S The channel impedance is calculated from the ratio of the voltages.

[0168] The working principle of the active acquisition positioning and identification device is to use OFDM technology to measure the input impedance of the terminal location in the power line carrier communication channel. The software design is mainly based on C language using the JTAG interface and IAR software to control the MSP430 microcontroller to achieve the entire data acquisition and communication work. The concentrator and the meter are used in the meter box. The active acquisition positioning and identification device is connected in series next to the energy meter, connected to the power supply, and the three-phase signal is collected in real time and transmitted to the MCU for data processing, and dual power supply identification, load prediction, real-time positioning and temperature perception are performed.

[0169] 4. Experimental results and analysis

[0170] The data collected by the temperature signal of the active acquisition positioning identification device is sent every 15 minutes. 96 temperature data points can be collected in one day. The data collected in one area for one day is as follows: Fig.26 As shown. Fig.26 It can be seen that the active data collection, positioning and identification device can accurately collect and save the temperature near the terminal, realize intelligent temperature perception, and support a temperature perception weather forecast system with lower granularity.

[0171] The active location information collection device collects location information every 15 minutes and transmits the obtained location information to the background main station for storage. The location information collected by an active location information collection device for two hours is shown in Table 2.

[0172] Table 2 Location information collected by the active location identification device

[0173]

[0174] As shown in Table 2, the active acquisition positioning and identification device records the real-time location information of the terminal every 15 minutes, realizing real-time perception of the terminal location information.

[0175] The power line carrier input impedance collected by the active acquisition positioning identification device is used to predict the input impedance parameters after training with the BP neural network algorithm. Whether there is a large error between the predicted result and the actual result is used to determine whether there is an event such as dual power switching that changes the topology structure of the substation area. The two collected data about the power line carrier input impedance are as follows: Fig. 27 and Fig.28 shown.

[0176] Comparison Chart Fig. 27 and Fig.28It can be seen that the predicted value of the input impedance of the normal substation is basically consistent with the measured value, but in the case of dual power switching, the input impedance value of the abnormal substation has a large deviation, reflecting that the topological structure of the substation has changed, thereby sending an alarm to the background main station. A three-layer BP neural network with one hidden layer is used. Since it is a short-term power load forecast, it is usually predicted for 24 hours a day, so the 24 hours a day are divided into 12 times for forecasting, that is, a forecast is made every 2 hours, and these 2 hours are divided into 8 time points for forecasting, so the number of neuron nodes output by the network is determined to be 8. In addition, the impact of weather and climate factors and random events on power load must also be considered. The node table of the input layer of the prediction model of this patent is shown in Table 3.

[0177] Table 3 Input layer nodes

[0178]

[0179] The experimental samples are the load history data of Suzhou area in March. The samples are collected at 24 points every day as experimental data. The unprocessed original load signal and the load signal processed by wavelet denoising are respectively input into the neural network prediction model as input samples for experimental comparison, namely, the four models shown in Table 4:

[0180] Table 4 Four prediction models established in the experiment

[0181]

[0182] Three examples of prediction results from four models are shown below: Figures 29 to 31 As shown. Figures 29 to 31 The results show that after denoising by the wavelet denoising method, the prediction results obtained by the improved BP neural network prediction model are the best. Model 4 captures the characteristics of the load data very well, and its relative error is also low. It can be seen that the wavelet denoising algorithm effectively reduces the variance of the original load signal and is fully suitable for the denoising of the load signal in load forecasting. It provides a good data source for the next step of neural network training and effectively improves the prediction accuracy of the load forecasting model.

[0183] The beneficial effects of the present invention are as follows: an active acquisition positioning identification device and method based on energy information flow fusion is proposed. Experimental results show that the proposed power line communication technology based on broadband carrier can realize the active acquisition of terminal measurement data, can realize the perception and identification of loads, can realize the automatic judgment of load switching in dual power supply areas, and increase the reading of non-metering data such as temperature and positioning. The specific advantages are as follows:

[0184] 1) The measurement accuracy of electric energy is further improved. The accuracy of traditional electric energy meters is at the 0.5S level, that is, the error accuracy is 0.5%. After the optimization and transformation of the circuit board and the test of the electromagnetic compatibility of the device, the measurement accuracy of the device is improved. The results of the field experiment show that the measurement error is 0.057%, reaching the accuracy level of 0.1S, which is fully capable of meeting the requirements of the power grid company for metering devices;

[0185] 2) Compared with the RS-485 wired communication method, the data communication method based on carrier signals saves the cost of materials such as wires and reduces the complexity of wiring in equipment such as meter boxes. The proposed OFDM technology realizes data transmission of broadband carrier communication. Compared with the traditional method, it not only avoids the disadvantages of wired wiring but also improves the signal-to-noise ratio and the speed and accuracy of data transmission;

[0186] 3) The proposed algorithm based on BP neural network realizes active learning and active training of existing input impedance raw data, establishes characteristic parameter components for specific substations, and uses the trained parameter matrix to predict the future input impedance of the substation. When problems such as dual power switching occur in the substation, the input impedance of the substation will change significantly. This feature can be used to realize active and real-time monitoring of dual power switching problems. The power consumption behavior of load terminals is characterized and self-trained to achieve accurate prediction and analysis of load switching situations, perform energy consumption analysis, and use power grid collected data to serve energy users;

[0187] 4) The development and utilization of non-metering functions of power grid user terminals have been realized. The temperature sensor in the terminal device is used to sense and measure the terminal temperature, which can monitor the ambient temperature and whether the power equipment is overheating. Relying on the huge power terminal network, the granularity and accuracy of weather forecast perception are refined. The satellite positioning device module in the device is used to accurately locate the terminal device. The power equipment is generally located in a remote and difficult-to-find location at the metering terminal. This technology can be used to achieve real-time positioning of the terminal, which greatly reduces the workload of terminal operation and maintenance personnel, and at the same time prevents the terminal from being stolen and lost.

[0188] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with the technology to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. An active acquisition positioning and identification device, characterized in that: The active acquisition positioning and identification device comprises: An electrical signal sensor, the electrical signal sensor is used to detect electrical parameter data; A temperature sensor, wherein the temperature sensor is used to detect temperature data; A positioning module, wherein the positioning module is used to detect position data; A power carrier module, which is used to transmit and receive power carrier signals based on OFDM technology; A data processing module, the data processing module is used to use the electrical parameter data to perform load forecasting, perform temperature sensing based on the temperature data, perform position recording based on the position data, and calculate and predict the carrier channel input impedance based on the power carrier signal to determine whether power switching occurs; The electrical signal sensor, the temperature sensor, the positioning module, and the power carrier module are all connected to the data processing module; The active acquisition, positioning and identification method adopted by the active acquisition, positioning and identification device includes a load prediction method, a temperature sensing method, a position recording method and a power supply switching judgment method; The power switching judgment method is as follows: based on OFDM technology, power carrier signals are transmitted and received, the power carrier signals are used to calculate and predict the carrier channel input impedance, and whether power switching occurs in the corresponding substation is determined according to whether the carrier channel input impedance changes; a BP neural network trained with historical data of the carrier channel input impedance is used to predict the carrier channel input impedance. If the error between the calculated value and the predicted value of the currently calculated carrier channel input impedance reaches a limit value, it is determined that a dual power switching has occurred and the substation topology has been changed.

2. The active acquisition, positioning and identification device according to claim 1, characterized in that: The electrical signal sensor includes a current sensor and a voltage sensor.

3. The active acquisition, positioning and identification device according to claim 1, characterized in that: The active acquisition positioning and identification device also includes: A display connected to the data processing module; A display driving module, wherein the data processing module is connected to the display through the display driving module; A data storage module, the data storage module is connected to the data processing module; an infrared communication circuit, the infrared communication circuit being connected to the data processing module; 485 communication circuit, the 485 communication circuit is connected to the data processing module.

4. The active acquisition, positioning and identification device according to claim 3, characterized in that: The active acquisition positioning and identification device also includes: A clock module, the clock module is connected to the data processing module; A crystal oscillator, the crystal oscillator is connected to the clock module; A power module, the power module is connected to the data processing module; An online programming port, the online programming port being connected to the data processing module; An IO port, the IO port being connected to the data processing module; A communication port, the communication port being connected to the data processing module; A power supply module is connected to the data processing module.

5. The active acquisition, positioning and identification device according to claim 3, characterized in that: The data processing module is connected to the background main station through a wireless public network, and the data processing module is used to integrate and upload the electrical parameter data, the temperature data, the position data and the power carrier signal to the background main station.

6. The active acquisition, positioning and identification device according to claim 1, characterized in that: The load prediction method is: detecting electrical parameter data, determining the load type of the substation according to the substation clustering division scheme, using the electrical parameter data to train the BP neural network corresponding to the load type of the substation, and then using the trained BP neural network to perform load prediction.

7. The active acquisition, positioning and identification device according to claim 1, characterized in that: The power carrier signal of different frequencies is transmitted.

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