A power supply communication method and device based on power carrier communication

Abstract

The application discloses a power supply communication method and device based on power carrier communication, and relates to the technical field of power supply communication; the prior art has problems of signal attenuation, insufficient anti-interference ability, insufficient stability of power supply communication and insufficient intelligent path switching ability; the application adopts high sampling rate PSD analysis, STFT and LSTM to predict noise power time sequence data, and establishes a noise-load rate coupling model; secondly, based on the transmission line theory, the channel time variation is researched, the signal reflection and multipath effect are calculated, and the channel coherence time is calculated through the sliding window; for signal attenuation, low, medium and high frequency band models are respectively established, the path attenuation is calculated, and the channel capacity is optimized; finally, through real-time stability analysis, the short-term and long-term SNR stability is calculated, the path selection is optimized in combination with the load rate, and the communication quality is ensured; through comprehensive channel modeling, time variation analysis and path optimization, the reliability and stability of the power carrier communication are improved.

Description

Technical Field

[0001] This invention relates to the field of power supply communication technology, specifically to a power supply communication method and apparatus based on power line carrier communication. Background Technology

[0002] Power line communication (PLC) is a technology that utilizes power lines to simultaneously transmit electrical energy and data signals. Its background technology primarily stems from the power system's need for efficient and economical communication methods. With the development of smart grids, PLC has been widely applied in fields such as automated electricity metering, remote meter reading, smart home control, and street light management due to its advantage of not requiring additional communication lines. This technology modulates high-frequency carrier signals and superimposes them onto the power line's frequency current, utilizing existing power infrastructure to achieve data transmission, significantly reducing deployment costs.

[0003] However, this method still has the following main drawbacks:

[0004] Insufficient signal attenuation and anti-interference capabilities: In low-voltage distribution networks, dynamic load changes can cause impedance abrupt changes, affecting signal propagation quality and reducing communication reliability. Power lines also contain pulse noise caused by power frequency current, radio broadcast interference, and transient interference from household appliance switches. These noises reduce the signal-to-noise ratio and degrade communication quality. During peak electricity consumption periods, signal attenuation is aggravated by impedance drops, leading to communication link instability.

[0005] The blocking effect of distribution transformers limits the communication coverage. Due to the blocking effect of distribution transformers on high-frequency carrier signals, the carrier communication range is usually limited to a single transformer area, and direct communication across transformer areas cannot be achieved. Traditional solutions require the deployment of additional relay equipment, which increases system complexity and operation and maintenance costs.

[0006] The stability and intelligent path switching capabilities of power supply communication are insufficient, the path selection method is difficult to adapt to complex power grid environments, and communication interruptions are prone to occur; the communication path cannot be dynamically adjusted according to channel quality, resulting in unstable data transmission. Summary of the Invention

[0007] The purpose of this invention is to solve the problems mentioned in the background art by proposing a power supply communication method and device based on power line carrier communication.

[0008] The objective of this invention can be achieved through the following technical solutions:

[0009] In a first aspect, the present invention provides a power supply communication method based on power line carrier communication, characterized in that it includes:

[0010] S1: Conduct power carrier communication stability analysis, specifically:

[0011] S101: Conduct channel characteristic modeling correlation analysis to establish a model;

[0012] S102: Calculate real-time stability and attenuation values to obtain instantaneous SNR, equivalent distance attenuation A ,

[0019] , equiv Short-term time-domain stability S time and long-term time-domain stability S freq ;

[0013] S2: Process power supply communication, obtain attenuation values and real-time stability values for processing:

[0014] S201: Conduct path priority dynamic analysis:

[0015] S211: Input parameters: real-time stability value Stability Score , short-term stability S time and long-term stability S freq weighted and obtained, attenuation value A equiv equivalent distance attenuation value calculated by S1, path load rate: power grid load rate of the current path; then conduct path analysis to obtain path status value Path Score ;

[0016] S212: Set path switching logic: Path of the current path Score is lower than the threshold; burst pulse noise is detected; channel coherence time < 1ms; select the path with the highest Path Score from the alternative path library; alternative path generation rule: physically topologically adjacent nodes;

[0017] S202: Conduct signal enhancement: Dynamically adjust signal parameters or enable relays according to attenuation values and channel status to ensure communication reliability;

[0018] S221: Adaptive modulation and power allocation: Dynamically switch modulation methods according to instantaneous SNR: when SNR > 20dB: enable high-order modulation; when 10dB < SNR < 20dB: switch to QPSK; when SNR < 10dB: reduce the order to BPSK; conduct dynamic power allocation: inversely deduce the optimal power spectral density P(f) according to the Shannon formula, and proportionally increase the power for subcarriers with attenuation > 30dB;

[0019] S222: Enable the relay and PCL communication module to conduct relay and encrypted transmission. Relay trigger condition: equivalent attenuation A equiv>60dB / km, no available high-score path in the path scoring database; activate the nearest PCL relay module and perform data segmentation and encryption: raw data → AES-256 encryption → fragmentation into short messages, relay transmission protocol: relay node receives encrypted data, adds CRC check and forwards it; if the target node does not respond, enable "relay relay".

[0020] In a second aspect, the present invention provides a power supply communication device based on power line carrier communication, comprising: a channel noise division module, a channel modulation module, a channel attenuation frequency optimization module, a stable attenuation calculation module, a route selection switching module, and a communication optimization intelligent adjustment module;

[0021] The noise distribution module of Daojian uses high sampling rate power spectrum analysis and LSTM to predict noise timing, analyze the coupling relationship between noise and grid load, and optimize anti-interference capability.

[0022] The channel modulation module calculates multipath attenuation and coherence time, and uses an adaptive equalizer to suppress inter-symbol interference and improve communication stability.

[0023] The channel attenuation frequency optimization module establishes attenuation models for different frequency bands, dynamically optimizes transmit power and subcarrier modulation, and improves channel capacity;

[0024] The stability and attenuation calculation module calculates the channel gain, transmit power, and the impact of environmental noise, removes impulse noise, and analyzes the aging of the line.

[0025] The route selection and switching module calculates the path score and dynamically selects the optimal communication path based on the stability value, attenuation value, and load rate.

[0026] The Tongyou Intelligent Adjustment Module optimizes power supply and communication based on channel characteristics, dynamically manages paths, and adapts to devices to enhance anti-interference capabilities.

[0027] Compared with the prior art, the beneficial effects of the present invention are:

[0028] 1. This invention accurately monitors background noise through high-sampling-rate power spectral analysis and time-frequency analysis methods (such as STFT), and uses an LSTM neural network to predict the temporal changes in noise power, enabling the communication system to anticipate noise spikes. Furthermore, by analyzing the coupling relationship between grid load rate and noise, the system can dynamically adjust during peak electricity consumption periods to ensure communication stability. This mechanism significantly reduces the impact of impedance spikes caused by the start-up and shutdown of household appliances, improving the reliability of data transmission.

[0029] 2. This invention establishes a time-varying channel characteristic model based on transmission line theory to predict changes in channel frequency response and optimizes channel resource allocation through multipath effect analysis. In particular, based on real-time calculation of channel coherence time, the system can adaptively adjust the equalizer (such as LMS or RLS algorithms) under highly time-varying conditions, effectively suppressing inter-symbol interference (ISI). Furthermore, by employing OFDM technology, high-frequency resources are prioritized for short-distance communication, while power allocation is adjusted to low-frequency bands for long-distance communication, maximizing channel capacity and thus improving overall communication efficiency.

[0030] 3. This invention calculates stability by combining short-term and long-term stability indices. Score Path is calculated by combining the equivalent attenuation value and the grid load rate. Score This allows the system to dynamically select the optimal path for communication. When a channel quality degradation or excessive load is detected, the system can determine the optimal path based on the path. Score Automatic path switching is triggered to select the optimal alternative path, avoiding communication interruptions. Furthermore, by monitoring long-term channel changes through rolling averages, line aging issues can be detected early and maintenance warnings can be triggered, ensuring the long-term stable operation of power supply and communication. Attached Figure Description

[0031] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0032] Figure 1 This is a diagram illustrating the method steps of the present invention.

[0033] Figure 2 This is a schematic diagram of the device principle of the present invention. Detailed Implementation

[0034] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0035] It should be understood that the terms “comprising” and “including” used in this disclosure and claims indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0036] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure. As used in this disclosure and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this disclosure and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0037] Please see Figure 1 As shown, the present invention provides a power supply communication method based on power line carrier communication, comprising:

[0038] S1: Perform stability analysis of power line carrier communication, specifically:

[0039] S101: Perform channel characteristic modeling and correlation analysis:

[0040] S111: Analysis of the impact of noise interference on coupling: It should be noted that the starting and stopping of household appliances (such as refrigerators and air conditioners) will cause impedance changes, resulting in broadband background noise (10kHz-30MHz). The power of this noise is positively correlated with the grid load rate, so it is necessary to combine it with the electricity consumption period (such as morning and evening peak hours) for synchronous monitoring and establish a time-dependent model;

[0041] Monitor background noise PSD (power spectral density) using a high sampling rate power spectrum analyzer (or software radio), with a recommended time resolution of seconds to capture abrupt changes.

[0042] Data analysis: Calculate the mean and variance of PSD for different time periods, and extract the characteristic peak power spectral density (PSD). Calculation process: Select an appropriate time window, such as 1 second, 5 seconds, 10 seconds, etc., to divide the data into time periods; perform FFT transformation on each time period and calculate the PSD (using the Welch method or directly using FFT); calculate the mean and variance of PSD for different time periods to measure the stability of the noise signal; identify characteristic peaks (local maxima), which can be done using thresholding methods or peak detection algorithms (such as the findpeaks function); Mathematical formula: Where X(w) is the Fourier transform of the signal, and T is the length of the time window;

[0043] Analyze the noise variation pattern over time using STFT: Select an appropriate window function (such as Hanning window or Hamiltonian window), calculate the short-time Fourier transform, and obtain the time-frequency matrix. Where X(t,f) is the time-frequency matrix after STFT transformation, representing the intensity of the frequency f component at time t; x(n) is the original time-domain signal; w(nt) is a window function (such as Hanning window or Hamiltonian window) used to truncate the local signal so that each transformation only analyzes local data; e -j2πfn The exponential term of the Fourier transform represents the spectral analysis performed on each short time interval;

[0044] Model Establishment: Noise Power Time Series Prediction. A time series dataset of noise power is constructed using an LSTM neural network, divided into training and test sets. An LSTM network (input layer - hidden layer - output layer) is designed. After training, it is used to predict the noise power curve: h t =σ(W h x t +U h h t-1 +b h )

[0045] Establish a noise-load rate coupling model: Select grid load rate data and perform correlation analysis with noise data, using the correlation coefficient calculation formula: And observe the impact of load rate on noise;

[0046] Adjusting model parameters using long-term data: Calculating model prediction error: Where: y true It is the true value, y pred This is the model's predicted value, and N is the number of samples. It should be noted that RMSE is suitable for situations that are sensitive to large errors, and it will amplify the impact of large errors.

[0047] Mean absolute error: MAE is suitable for measuring the overall error magnitude and is not sensitive to extreme errors; by obtaining RMSE and MAE, we can compare the errors of different models and select the optimal model.

[0048] Different models require different hyperparameters to be adjusted: When using LSTM (Long Short-Term Memory) networks, key parameters are obtained: Learning Rate: affects the model's convergence speed; Hidden Units: affects the model's learning ability; Time Steps: determines how many past data points the model considers at a time; Optimal hyperparameters are selected through random search or Bayesian optimization.

[0049] Finally, cross-validation is performed to improve model stability. K-fold cross-validation is used, dividing the data into K parts, using K-1 parts for training each time, and the remaining part for testing. The average error of all folds is calculated to improve the robustness of the model.

[0050] S112: Perform dynamic root cause analysis of channel time-varying characteristics:

[0051] Based on transmission line theory, a signal reflection coefficient model is established at impedance mismatch points such as distribution transformers, branch nodes, and load access points to accurately calculate the amplitude attenuation and time delay spread of multipath signals. In typical low-voltage power grids, the multipath time delay spread ranges from 1 to 5 μs, and the number of multipaths approximately doubles with each additional branch node. Combining the power grid topology (such as the number of branches and differences in line length) and load characteristics, the notch position and depth of the channel frequency response (up to 20–30 dB) are predicted, and the channel transfer function H(f,t) is dynamically generated.

[0052] Dynamic calculation of coherence time: The correlation coefficient of the channel impulse response (CIR) is calculated in real time using a sliding time window (typically 1 second). When the correlation coefficient is lower than the threshold (e.g., 0.9), it is determined that the channel has changed significantly and the channel estimate needs to be updated. If the channel coherence time is less than 10 times the symbol period (e.g., when the OFDM symbol period is 100μs, the coherence time is <1ms), an adaptive equalizer (e.g., LMS or RLS algorithm) is automatically enabled to suppress inter-symbol interference (ISI).

[0053] S113: Frequency-distance joint model assignment for attenuation:

[0054] Perform segmented frequency attenuation model allocation:

[0055] For low-frequency bands (frequency band < 1MHz), a linear attenuation model α(f) = k1 × f + k2 is adopted, where k1 ≈ 0.1dB / km / MHz, which is suitable for low-frequency signal transmission in power distribution cables;

[0056] In the high-frequency band (band > 10MHz), due to the skin effect and increased dielectric loss, an exponential decay model α(f) = e is adopted. af +b, where a≈0.15 / MHz, accurately describes the rapid attenuation characteristics of high-frequency signals;

[0057] For the transition segment (frequency band of 1–10 MHz), based on measured data, cubic spline interpolation or polynomial fitting methods are used to achieve a smooth transition and ensure model continuity.

[0058] Frequency band allocation is based on distance adaptation: When the transmission distance is less than 300 meters, the wide bandwidth resources of the high-frequency band (10-30MHz) are fully utilized, and OFDM technology is used to dynamically allocate subcarriers to improve the transmission rate; when the transmission distance is medium to long distance (300-500 meters), the power allocation of high and low frequency bands is dynamically adjusted according to real-time channel measurement results, giving priority to ensuring the communication quality of the low frequency band (<1MHz); when the transmission distance is long distance (500 meters), the high-frequency signal attenuation exceeds 80dB, and the channel capacity is dominated by the low frequency band. At this time, the high-frequency subcarriers are turned off, and the power is concentrated in the low frequency band to enhance signal coverage.

[0059] Based on Shannon's formula, the channel capacity C is dynamically calculated: Wherein, H(f): channel frequency response, determined by the attenuation model α(f) and multipath effect, P(f): transmit power spectral density, N(f): noise power spectral density (including background noise, impulse noise, etc.), and the channel capacity is maximized by optimizing the transmit power spectral density P(f) and subcarrier modulation method (such as QPSK, 16-QAM) in real time.

[0060] S102: Perform real-time stability and attenuation calculations, and analyze the physical correlation calculated using instantaneous SNR: Where H(f)∣ 2 Reflects channel gain and is directly related to line attenuation and multipath superposition; P tx For transmit power, it is limited by EMC regulations (such as CISPR 22 limiting ≤-50dBm / Hz below 30MHz); if burst impulse noise (such as switching action) is detected, the contaminated subcarriers need to be temporarily removed in the SNR calculation.

[0061] S121: Calculate the attenuation value: Obtain the frequency domain attenuation A(f) formula and perform physical decomposition:

[0062] A(f) = -10log2|H(f)| 2 ;

[0063] Analysis of the attenuation component yields conductor loss (proportional to the square root of the frequency, dominated by the skin effect). and dielectric loss (proportional to frequency) (polarization loss of cable insulation material, ));

[0064] Example: When the frequency band is less than 1MHz, then A(f) = 0.02f + 2dB / km (linear model); when the frequency band is greater than 10MHz, then A(f) = 0.5e 0.1f dB / km (exponential model); It should be noted that: attenuation A over equivalent distance equiv In engineering applications, Frequency selection f max The logic is as follows: The highest operating frequency of the system (e.g., 30MHz) is chosen because its attenuation is greatest, determining the link's maximum distance. If the line has a resonant point (e.g., an attenuation peak caused by impedance mismatch), it needs to be avoided, and the actual passband edge frequency should be selected. When A... equiv When the speed is >60dB / km, repeaters need to be deployed (one every 300-500 meters).

[0065] S122: Short-term time-domain stability is analyzed by setting a sliding window with a window length matched to the channel coherence time (e.g., a 10ms window to track impedance changes caused by appliance start-up and shutdown); the standard deviation σSNR reflects the SNR fluctuation intensity. If it exceeds a threshold (e.g., σ... SNR >5dB) is considered unstable; then the coefficient of variation is normalized: S time =1-(μ) SNR / σ SNR When μ SNR <10dB, even slight fluctuations can cause S time A sudden drop requires a comprehensive assessment based on the absolute SNR value.

[0066] Long-term time-domain stability analysis assigns higher weight to frequency bands containing control signals (e.g., smart meter heartbeat signals concentrated in CENELEC-A Band 3-95kHz); higher-order modulation frequency bands (e.g., subcarriers used in 64QAM) have doubled weight due to their greater sensitivity to SNR; long-term statistics (e.g., 24-hour rolling average) are used to detect line aging: if S... freq A continuous decrease of 0.1 per week triggers a maintenance warning.

[0067] S2: Process the power supply communication, and obtain the attenuation value and real-time stability value for further processing.

[0068] S201: Perform dynamic path priority analysis:

[0069] S211: Input parameter: Real-time stability value Score The short-term stability S calculated from S1 time and long-term stability S freq The weighted average yields the formula: Stability Score =0.6×S time +0.4×S freq (Weights are adjusted according to the application scenario; for example, smart meters focus more on long-term stability), attenuation value A equiv The equivalent distance attenuation value and path load factor are calculated from S1: the grid load factor of the current path (priority is reduced if the peak load factor is >80%); path analysis is performed using the formula: Path Score =Stability Score×e^(-0.1×A equiv )×(1-Load Factor ), where Load Factor The "busyness" level of a power grid line typically ranges from 0 to 1 (or 0% to 100%); Path Score This represents the path coefficient.

[0070] S212: Configure path switching logic:

[0071] Triggering condition: Path of the current path Score Below the threshold (e.g., <0.7); detected burst impulse noise (e.g., a switch action causing an instantaneous SNR drop of >10dB); channel coherence time <1ms (excessively high time-varying characteristics);

[0072] Switching action: Select a Path from the alternative path library Score The highest path; alternative path generation rules: physical topology adjacent nodes (such as adjacent meters, branch lines); avoid lines passing through high-noise equipment (such as air conditioners, frequency converters); prioritize the shortest path directly connected to the distribution transformer;

[0073] Case: Smart meter A sends data to the concentrator. The current path passes through a line with a 90% load factor (load factor = 0.9), and the starting and stopping of the air conditioner is detected, causing S... time =0.5; Calculate:

[0074] Stability Score =0.6×0.5+0.4×0.8=0.62

[0075] A equiv = 45dB / km (medium-to-long distance routes)

[0076] Path Score =0.62×e^(-0.1×45)×(1-0.9)≈0.62×0.011×0.1≈0.00068;

[0077] Path Score The value is well below the threshold of 0.7, triggering a path switching; an alternative path is selected: the relay path through adjacent meter B (load rate 60%, A). equiv =30dB / km), New Path Score ≈0.82, switch successful.

[0078] S202: Strengthen the signal: Dynamically adjust signal parameters or activate relays based on attenuation value and channel status to ensure communication reliability.

[0079] S221: Adaptive Modulation and Power Distribution

[0080] Modulation method adjustment: When SNR > 20dB: Enable high-order modulation (64-QAM) to improve transmission efficiency; When 10dB < SNR < 20dB: Switch to QPSK to balance rate and reliability; When SNR < 10dB: Degrade to BPSK, sacrificing rate for robustness;

[0081] Perform dynamic power allocation: Inversely deduce the optimal power spectral density P(f) according to the Shannon formula: P(f) = max{(2^(C_target / B)-1)×N(f) / |H(f)| 2 , P_EMC}, (P_EMC is the regulatory limit, such as CISPR 22); For subcarriers with attenuation > 30dB (such as > 10MHz), increase the power proportionally (not exceeding the EMC limit).

[0082] S222: Relay and PCL communication module enabled:

[0083] Relay trigger conditions: Equivalent attenuation A equiv > 60dB / km (such as line length > 500 meters), no available high-Score path in the path scoring library;

[0084] Relay operation process: Start the nearest PCL (Power Line Communication) relay module (such as within 300 meters), perform data segment encryption: Original data → AES-256 encryption → Fragmented into short messages (such as 128 bytes), Relay transmission protocol: The relay node receives the encrypted data, appends CRC check and then forwards; If the target node does not respond, enable "relay relay" (multi-hop transmission);

[0085] Case: The photovoltaic inverter needs to upload power generation data to the grid dispatching center over a long distance (800 meters), and the main path A_equiv = 75dB / km;

[0086] Enhanced operations:

[0087] Z01: Detected A equiv > 60dB / km, automatically turn off high-frequency subcarriers (> 10MHz), concentrate power in the low-frequency band (3 - 95kHz);

[0088] Z02: SNR = 8dB (low-frequency band), the modulation method is forced to BPSK, and the data rate is reduced to 5kbps;

[0089] Z03: Enable two-level PCL relay: Inverter → Relay 1 (at 400 meters, A equiv = 40dB / km) → Relay 2 (at 800 meters) → Dispatching center; The data between relays is encrypted with AES-256, and a CRC check and retransmission mechanism is used for each hop;

[0090] The transmission success rate increased from 30% for single-hop to 95% for multi-hop, with a latency increase of 200ms (acceptable).

[0091] Please see Figure 2 As shown, the present invention also provides a power supply communication device based on power line carrier communication, including: a channel noise division module, a channel modulation module, a channel attenuation frequency optimization module, a stable attenuation calculation module, a route selection switching module, and a communication optimization intelligent adjustment module;

[0092] The noise distribution module models the channel characteristics of power line carrier communication, focusing on the coupling effect of noise interference. It monitors the background noise PSD using a high sampling rate power spectrum analyzer and calculates the noise characteristics using methods such as FFT and STFT. It uses an LSTM neural network to predict the noise power time series and establishes the coupling relationship between noise and grid load rate through correlation analysis to optimize the anti-interference capability of power line carrier communication.

[0093] Based on transmission line theory, the channel modulation module analyzes signal reflection phenomena at impedance mismatch points such as distribution transformers, branch nodes, and load access points, and calculates the attenuation and delay spread of multipath signals. It calculates the channel coherence time through a sliding time window. If the coherence time is lower than the threshold, an adaptive equalizer (such as LMS or RLS) is used to suppress inter-symbol interference and improve communication stability.

[0094] The channel attenuation and frequency optimization module establishes signal attenuation models for different frequency bands, including low-frequency linear attenuation, high-frequency exponential attenuation, and a smooth transition model in the range of 1 to 10 MHz; it calculates channel capacity based on Shannon's formula, and dynamically optimizes the transmit power spectral density and subcarrier modulation method in combination with power grid topology and load characteristics to achieve adaptive spectrum allocation of the communication system and improve transmission efficiency.

[0095] The stable attenuation calculation module calculates physical correlation parameters based on instantaneous SNR, analyzes the impact of channel gain, transmit power, and environmental noise, and eliminates interference from burst impulse noise. In terms of attenuation analysis, it analyzes conductor loss and dielectric loss separately and calculates the equivalent distance attenuation value A. equiv To determine the link's maximum distance, a sliding window method is used to evaluate short-term temporal stability, and long-term statistical methods are employed to monitor line aging.

[0096] The route selection switching module calculates the path score based on real-time stability values, attenuation values, and path load rate. Score It is used to dynamically select the optimal communication path; when the score of the current path is lower than the threshold, or when abnormal situations such as sudden impulse noise are detected, the system automatically switches to the alternative path with the highest score to maintain the stability and reliability of communication.

[0097] The Tongyou Intelligent Adjustment Module combines channel characteristics, attenuation, and stability analysis results to optimize power supply communication strategies; it adopts a dynamic path management method to improve the reliability of power line carrier communication and performs intelligent scheduling according to load conditions to ensure that the communication link can achieve optimal performance under different load conditions; in addition, the module also includes adaptation optimization for communication equipment to enhance the overall system stability and anti-interference capability.

[0098] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A power supply communication method based on power line carrier communication, characterized in that, It includes: S1: Conduct power carrier communication stability analysis, specifically: S101: Conduct channel characteristic modeling correlation analysis to establish a model; S102: Perform real-time stability and attenuation calculations to obtain instantaneous SNR and attenuation value A. equiv Short-term time-domain stability S time and long-term time-domain stability S freq ; S2: Process power supply communication, obtain attenuation values and real-time stability values for processing: S201: Conduct dynamic analysis of path priority: S211: Input parameters: via short-term stability S time and long-term stability S freq Weighted average yields the real-time stability value. Score and attenuation value A equiv The path coefficient is obtained by taking it as input as a parameter and calculating it. Score The attenuation value A equiv This is the equivalent distance attenuation value, calculated based on the distance attenuation and frequency attenuation of the communication link; S212: Set path switching logic: Path of the current path Score The following conditions trigger path handover: the path falls below a threshold, a sudden impulse noise is detected, or the channel coherence time is <1ms. Upon triggering, the handover action performed is to select a path from the candidate path library. Score The highest path; S202: Conduct signal enhancement: According to the attenuation value and channel state, dynamically adjust signal parameters or enable relays to ensure communication reliability; S221: Adaptive modulation and power allocation: Dynamically switch modulation methods according to the instantaneous SNR: When SNR > 20dB: Enable high-order modulation; When 10dB < SNR < 20dB: Switch to QPSK; When SNR < 10dB: Degrade to BPSK; Conduct dynamic power allocation: According to the Shannon formula, inversely deduce the optimal power spectral density P(f), and proportionally increase the power for subcarriers with attenuation > 30dB; S222: PCL relay module enabled. The trigger condition for relay and encrypted transmission is: when the attenuation value A... equiv If the score is >60dB / km or there is no available high-score path in the path score database, the nearest PCL relay module will be activated to perform data segmentation and encryption. Data segmentation and encryption includes: the original data is encrypted with AES-256 and then fragmented into short messages. The relay node receives the encrypted data, adds a CRC check, and then forwards it. If the target node does not respond, a multi-hop relay transmission mechanism will be activated.

2. The power supply communication method based on power line carrier communication according to claim 1, characterized in that, The specific process of conducting channel characteristic modeling correlation analysis to establish a model is as follows: S111: Analyze the influence of noise interference during the coupling process: Monitor the background noise PSD through a high-sampling-rate power spectrum analyzer, set the time resolution at the second level, and capture mutation characteristics; Obtain characteristic peaks through data analysis; Analyze the change pattern of noise over time according to STFT and establish a model; S112: Deepen the dynamic root cause of channel time-variation; S113: Conduct frequency-domain - distance joint model allocation of attenuation.

3. The power supply communication method based on power line carrier communication according to claim 2, characterized in that, The specific process of analyzing the change pattern of noise over time according to STFT and establishing a model is as follows: Analysis of noise variation patterns over time using STFT: A window function is selected, and the short-time Fourier transform is calculated to obtain the time-frequency matrix. X(t,f) is the time-frequency matrix after STFT transformation; x(n) is the original time-domain signal; w(n−t) is the window function, e −j2πfn The exponential term of the Fourier transform; Model establishment: Predict the noise power time series. Construct a time series dataset of noise power through an LSTM neural network, divide the training set and test set; Design an LSTM network; After training, use it to predict the noise power curve to obtain the predicted noise power; Establish a noise-load rate coupling model: Select grid load rate data and perform correlation analysis with noise data to calculate the correlation coefficient r; adjust model parameters based on long-term data; calculate model prediction error. y true It is the true value, y pred These are the model predictions, where N is the number of samples, and the mean absolute error is: ; Obtain RMSE and MAE, compare the errors of different models, and select the optimal model; Adjust different models: Adopt LSTM and obtain key parameters: Learning rate; Number of hidden layer units; Select the optimal hyperparameters through random search; Finally, conduct cross-validation to improve the model stability; Adopt K-fold cross-validation, divide the data into K parts, use K - 1 parts for training each time, and the remaining 1 part for testing; Calculate the average error of all folds to improve the model robustness.

4. The power supply communication method based on power line carrier communication according to claim 2, characterized in that, The specific process of deepening the dynamic root cause of channel time-variation is as follows: Based on the transmission line theory, establish a signal reflection coefficient model at impedance mismatches of distribution transformers, branch nodes, and load access points, and accurately calculate the amplitude attenuation and delay spread of multipath signals; In the low-voltage power grid, the multipath delay spread range is 1 - 5μs, and for each additional branch node, the number of multipaths doubles; Combine the power grid topology structure and load characteristics to predict the notch position and depth of the channel frequency response, and dynamically generate the channel transfer function H(f,t); Conduct dynamic calculation of the coherence time: Use a sliding time window to calculate the correlation coefficient of the channel impulse response in real time. When the correlation coefficient is lower than the threshold, it is determined that the channel has changed significantly, and the channel estimation is updated; If the channel coherence time is less than 10 times the symbol period, an adaptive equalizer is automatically enabled.

5. A power supply communication method based on power line carrier communication according to claim 2, characterized in that, The specific process of conducting frequency-domain - distance joint model allocation of attenuation is as follows: Conduct segmented frequency attenuation model allocation: The low-frequency band uses a linear attenuation model; the high-frequency band uses an exponential attenuation model; the transition band is based on measured data and uses cubic spline interpolation to achieve a smooth transition. Frequency band allocation is based on distance adaptation: When the transmission distance is less than 300 meters, the wide bandwidth resources of the high-frequency band are fully utilized, and OFDM technology is used to dynamically allocate subcarriers; when the transmission distance is medium to long distance, the power allocation of high and low frequency bands is dynamically adjusted according to real-time channel measurement results to ensure the communication quality of the low-frequency band; when the transmission distance is long distance, the high-frequency signal attenuation exceeds 80dB, and the channel capacity is dominated by the low-frequency band. At this time, the high-frequency subcarriers are turned off, and the power is concentrated in the low-frequency band to enhance signal coverage. Channel capacity is dynamically calculated based on Shannon's formula.

6. The power supply communication method based on power line carrier communication according to claim 1, characterized in that, The instantaneous SNR and attenuation value A are obtained by performing real-time stability and attenuation value calculations. equiv Short-term time-domain stability S time and long-term time-domain stability S freq The specific process is as follows: For physical associations calculated using instantaneous SNR: H(f)∣ 2 Reflects channel gain and is directly related to line attenuation and multipath superposition; P tx N(f) represents the transmit power; N(f) represents the noise power spectral density; if burst impulse noise is detected, contaminated subcarriers are temporarily removed in the SNR calculation; Calculate the attenuation value: Obtain the frequency domain attenuation A(f) formula and perform physical decomposition: ; The conductor loss and dielectric loss are obtained by analyzing the attenuation components; Analyze the short-term time-domain stability to determine whether the channel is in a short-term unstable state; Long-term time-domain stability is analyzed, and the frequency band where the control signal is located is given higher weight; The weight of higher-order modulation frequency bands is doubled; Long-term statistics are used to detect circuit aging: If S freq A continuous decrease of 0.1 per week triggers a maintenance warning.

7. A power supply communication device based on power line carrier communication, characterized in that, The device is used to implement a power supply communication method based on power line carrier communication as described in any one of claims 1-6. The device includes: a channel noise division module, a channel modulation module, a channel attenuation frequency optimization module, a stable attenuation calculation module, a route selection switching module, and a communication optimization intelligent adjustment module. The noise distribution module of Daojian uses high sampling rate power spectrum analysis and LSTM to predict noise timing, analyze the coupling relationship between noise and grid load, and optimize anti-interference capability. The channel modulation module calculates multipath attenuation and coherence time, and uses an adaptive equalizer to suppress inter-symbol interference and improve communication stability. The channel attenuation frequency optimization module establishes attenuation models for different frequency bands, dynamically optimizes transmit power and subcarrier modulation, and improves channel capacity; The stability and attenuation calculation module calculates the channel gain, transmit power, and the impact of environmental noise, removes impulse noise, and analyzes the aging of the line. The route selection and switching module calculates the path score and dynamically selects the optimal communication path based on the stability value, attenuation value, and load rate. The Tongyou Intelligent Adjustment Module optimizes power supply and communication based on channel characteristics, dynamically manages paths, and adapts to devices to enhance anti-interference capabilities.

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