Distributed photovoltaic multi-protocol communication test method and related equipment

Abstract

The embodiment of the present application relates to the technical field of photovoltaic communication test, and discloses a kind of distributed photovoltaic multi-protocol communication test method and related equipment, the method comprises: communication signal interference is simulated based on network signal attenuation simulator, whether communication protocol is switched according to communication quality parameter and parameter threshold value, communication data is cached based on multi-level data caching mechanism, communication interruption is detected, and interrupted data is continued to be transmitted based on congestion control algorithm, data loss is identified by missing data algorithm, data is completed by completion algorithm, and test report is generated according to data recovery rate, time efficiency index, resource consumption index, protocol adaptability index, protocol switching parameter, caching parameter, continuation parameter and data completion parameter.The embodiment of the present application can simulate the test of communication protocol switching, data caching, interruption identification, data continuation, data loss identification and completion under a variety of weak network environments, and has high test precision and good test effect.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the technical field of photovoltaic communication testing, in particular to a distributed photovoltaic multi-protocol communication testing method and related equipment. BACKGROUND

[0002] The distributed photovoltaic power generation system is an important part of clean energy, and the real-time and integrity of the monitoring data thereof have important effects on system operation and maintenance and power generation efficiency optimization. For example, the absence of power generation data of a power station will cause errors in electricity settlement, will misjudge the abnormal power generation of equipment, and will require manpower and material resources for maintenance. The distributed photovoltaic system can be established in different geographical environments, including complex environments such as mountainous areas, islands and suburbs. Different geographical environments result in differences in communication network quality, and different geographical environments such as high temperature, cold and thunderstorm will also cause communication signals to be weak, forming a weak network environment, so that the communication between photovoltaic devices is greatly affected, and there are mainly the following three typical communication problems:

[0003] 1. Long-time communication interruption caused by insufficient signal coverage;

[0004] 2. Short-time continuous interruption caused by frequent network fluctuations;

[0005] 3. Data transmission anomaly caused by unstable switching of multiple communication protocols.

[0006] The above communication problems seriously affect the accuracy and continuity of system monitoring, and further cause significant negative effects on the operation efficiency and fault early warning energy of the photovoltaic system.

[0007] In the prior art, a single communication protocol is usually used for photovoltaic device-to-photovoltaic device communication data transmission testing, and the testing method mainly simulates the quality of a network link. However, the current photovoltaic devices can switch between multiple communication protocols for communication, and the simulated network link quality cannot accurately simulate multiple weak network environments, so that the testing precision and effect are poor, and the accuracy and continuity of system monitoring cannot be ensured. SUMMARY

[0008] In view of the above problems, the embodiment of the present application provides a distributed photovoltaic multi-protocol communication testing method and related equipment to solve the problems in the prior art.

[0009] According to one aspect of the embodiment of the present application, a distributed photovoltaic multi-protocol communication testing method is provided, applied to a testing system, and the method comprises:

[0010] Interfering with the communication signals of the communication between photovoltaic devices based on a network signal attenuation simulator, the photovoltaic devices communicating through a predetermined communication protocol;

[0011] acquire a communication quality parameter of the communication signal and a corresponding parameter threshold value, determine whether to switch the communication protocol according to the communication quality parameter and the parameter threshold value, if it is determined to switch the communication protocol, switch the communication protocol, and acquire a protocol switching parameter;

[0012] pre-construct a multi-level data caching mechanism, cache communication data generated in a communication process to a predetermined storage medium based on the multi-level data caching mechanism, and acquire a caching parameter of the storage medium;

[0013] detect whether communication interruption occurs between the photovoltaic devices through a preset communication detection method, if communication interruption occurs, dynamically adjust a congestion window value and a slow start threshold value based on a preset congestion control algorithm, so that the interrupted communication data is continued to be transmitted, and acquire a continuation parameter;

[0014] identify whether data is lost in the communication process through a preset missing data algorithm, if data is lost, complete the data through a preset completion algorithm, and acquire a data completion parameter;

[0015] acquire a data recovery rate, a time efficiency index, a resource consumption index, and a protocol adaptability index when the communication is interrupted, and generate a test report according to the data recovery rate, the time efficiency index, the resource consumption index, the protocol adaptability index, the protocol switching parameter, the caching parameter, the continuation parameter, and the data completion parameter.

[0016] In an optional manner, the communication protocol at least includes a 4G LTE protocol, a long-distance wireless communication protocol, and a narrowband Internet of Things protocol, the communication signal for communication between the photovoltaic devices is interfered by the network signal attenuation simulator, including:

[0017] control the signal strength of the communication signal to change in a predetermined first step value within a preset strength range, control the packet loss rate of the communication signal to change in a predetermined second step value within a preset packet loss rate range, and control the time delay of the communication signal to change in a predetermined third step value within a preset time delay range.

[0018] In an optional manner, the communication signal for communication between the photovoltaic devices is interfered by the network signal attenuation simulator, including:

[0019] acquire a typical interference mode library based on actual scene measured data, the actual scene includes a plurality of different geographical environments, the network signal attenuation simulator and the measured data interfere with the communication signal.

[0020] In an alternative mode, before switching the communication protocol, the method further comprises: obtaining a transmission parameter of the communication protocol, and determining a target communication protocol according to the transmission parameter and a preset communication protocol switching decision algorithm;

[0021] The switching of the communication protocol comprises: switching the communication protocol to the target communication protocol.

[0022] In an alternative mode, after constructing the multi-level data cache mechanism in advance, caching communication data generated in a communication process to a predetermined storage medium based on the multi-level data cache mechanism, and obtaining a cache parameter of the storage medium, the method further comprises:

[0023] Performing capacity optimization on the cache of the storage medium according to a preset optimization algorithm.

[0024] In an alternative mode, after obtaining the data recovery rate, the time efficiency index, the resource consumption index, and the protocol adaptability index when the communication is interrupted, and generating a test report according to the data recovery rate, the time efficiency index, the resource consumption index, the protocol adaptability index, the protocol switching parameter, the cache parameter, the resuming parameter, and the data completion parameter, the method further comprises:

[0025] Establishing a time series-based system performance evolution model and a long-term performance prediction model, and analyzing the long-term system performance of the test system based on the system performance evolution model and the long-term performance prediction model.

[0026] In an alternative mode, after obtaining the data recovery rate, the time efficiency index, the resource consumption index, and the protocol adaptability index when the communication is interrupted, and generating a test report according to the data recovery rate, the time efficiency index, the resource consumption index, the protocol adaptability index, the protocol switching parameter, the cache parameter, the resuming parameter, and the data completion parameter, the method further comprises:

[0027] Obtaining the data recovery rate, the time efficiency index, the resource consumption index, and the protocol adaptability index when the communication is interrupted, assigning weights to the data recovery rate, the time efficiency index, the resource consumption index, and the protocol adaptability index according to a preset analytic hierarchy process weight distribution model, calculating a performance score of the test system based on the data recovery rate, the time efficiency index, the resource consumption index, the protocol adaptability index, and the respective weights, and generating the test report according to the data recovery rate, the time efficiency index, the resource consumption index, the protocol adaptability index, the performance score, the protocol switching parameter, the cache parameter, the resuming parameter, and the data completion parameter.

[0028] According to another aspect of the embodiments of the present application, a distributed photovoltaic multi-protocol communication testing device is provided, which comprises:

[0029] a network signal attenuation simulator configured to interfere with a communication signal used for communication between photovoltaic devices that communicate via a predetermined communication protocol;

[0030] a protocol switching testing module configured to acquire a communication quality parameter of the communication signal and a corresponding parameter threshold, determine whether to switch the communication protocol based on the communication quality parameter and the parameter threshold, switch the communication protocol if it is determined to switch the communication protocol, and acquire a protocol switching parameter;

[0031] a cache testing module configured to pre-construct a multi-level data cache mechanism, cache communication data generated in a communication process into a predetermined storage medium based on the multi-level data cache mechanism, and acquire a cache parameter of the storage medium;

[0032] an interrupted continuous transmission testing module configured to detect whether a communication interruption occurs between the photovoltaic devices via a predetermined communication detection method, dynamically adjust a congestion window value and a slow start threshold based on a predetermined congestion control algorithm if the communication interruption occurs, enable continuous transmission of the interrupted communication data, and acquire a continuous transmission parameter;

[0033] a data completion testing module configured to identify whether data is lost in the communication process via a predetermined missing data algorithm, complete the data via a predetermined completion algorithm if the data is lost, and acquire a data completion parameter;

[0034] a generating module configured to acquire a data recovery rate, a time efficiency index, a resource consumption index, and a protocol adaptability index when the communication interruption occurs, generate a testing report based on the data recovery rate, the time efficiency index, the resource consumption index, the protocol adaptability index, the protocol switching parameter, the cache parameter, the continuous transmission parameter, and the data completion parameter.

[0035] According to still another aspect of the embodiments of the present application, a computer device is provided, which comprises a processor, a memory, a communication interface, and a communication bus, the processor, the memory, and the communication interface complete communication with each other via the communication bus; the memory is configured to store at least one executable instruction, and the executable instruction causes the processor to execute the method described above.

[0036] According to still another aspect of the embodiments of the present application, a computer readable storage medium is provided, the storage medium stores at least one executable instruction, and the executable instruction causes a computer device to execute the method described above when the executable instruction runs on the computer device.

[0037] In this embodiment of the invention, photovoltaic devices communicate using multiple communication protocols. A network signal attenuation simulator is used to interfere with the communication signals. Based on communication quality parameters and threshold values, it is determined whether to switch communication protocols. If switching is determined, the communication protocol is switched. A multi-level data caching mechanism is used to cache communication data. Communication interruptions are detected; if an interruption occurs, a congestion control algorithm is used to resume the interrupted communication data. A missing data algorithm is used to identify if data is lost; if so, a completion algorithm is used to complete the data. A test report is generated based on data recovery rate, time efficiency indicators, resource consumption indicators, protocol adaptability indicators, protocol switching parameters, caching parameters, resumption parameters, and data completion parameters. This embodiment of the invention can simulate communication protocol switching, data caching, interruption identification, data resumption, data loss identification, and completion tests under various weak network environments. Especially under communication signal interruption conditions, it can perform data resumption and completion tests with high accuracy and good results, helping to ensure the accuracy and continuity of system monitoring.

[0038] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0039] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0040] Figure 1 A flowchart illustrating the distributed photovoltaic multi-protocol communication testing method provided in an embodiment of the present invention is shown.

[0041] Figure 2 A schematic diagram of the structure of the distributed photovoltaic multi-protocol communication test device provided in an embodiment of the present invention is shown;

[0042] Figure 3 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention is shown. Detailed Implementation

[0043] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0044] Figure 1 This diagram illustrates a flowchart of a distributed photovoltaic multi-protocol communication testing method provided by an embodiment of the present invention. This method is applied to a testing system, such as...Figure 1 As shown, the method includes the following steps:

[0045] Step 10: Interference is performed on the communication signals between photovoltaic devices based on a network signal attenuation simulator, wherein the photovoltaic devices communicate through a predetermined communication protocol.

[0046] The network signal attenuation simulator adopts a hardware-software integrated architecture. The hardware system includes core components such as a programmable RF attenuator, a signal interference generator, and a communication protocol adapter. The software system consists of modules such as a signal strength control algorithm, a packet loss generation engine, and a communication protocol simulator. The network signal attenuation simulator simultaneously supports multiple Low Power Wide Area Network (LPWAN) technologies and can interfere with communication signals under various communication protocols. The communication protocols in this embodiment include at least 4G LTE, LoRa (LoRa long-range wireless communication), and NB-IoT (Narrowband Internet of Things). Different communication protocols have significant differences in propagation characteristics, and their corresponding frequency bands, bandwidths, modulation methods, and signal attenuation models are all different. Photovoltaic devices can communicate using any of the above communication protocols and can switch between these protocols.

[0047] Interference can be achieved by using a network signal attenuation simulator to interfere with the communication signals between photovoltaic devices, including interference with signal strength, packet loss rate, and time delay. The packet loss rate can be controlled by using a combination of a binomial probability model and a Markov chain.

[0048] Furthermore, interference is applied to the communication signals between photovoltaic devices based on a network signal attenuation simulator, including:

[0049] The signal strength of the control communication signal is changed according to a predetermined first step value within a preset strength range; the packet loss rate of the control communication signal is changed according to a predetermined second step value within a preset packet loss rate range; and the delay of the control communication signal is changed according to a predetermined third step value within a preset delay range.

[0050] For the 4G LTE protocol: the strength range is -60dBm to -120dBm, with a first step value of 1dBm and an adjustable fluctuation frequency of 0.1Hz to 10Hz; the packet loss rate range is 0% to 100%, with a second step value of 0.1%, and it supports multiple packet loss modes such as Bernoulli distribution and Markov chain model; the latency range is 0ms to 5000ms, with a third step value of 10ms, and it supports fixed latency and fluctuating latency.

[0051] For the NB-IoT protocol: the signal strength range is -70dBm to -130dBm, with a first step value of 1dBm, supporting simulation of periodic signal strength fluctuations; the packet loss rate range is 0% to 100%, with a second step value of 0.1%, supporting simulation of packet loss probability distribution based on measured data; the latency range is 0ms to 10000ms, with a third step value of 10ms, supporting adaptive latency simulation based on network congestion.

[0052] For the LoRa protocol: the strength range is -80dBm to -140dBm, with a first step value of 1dBm, supporting signal attenuation simulation under different spreading factors; the packet loss rate range is 0% to 100%, with a second step value of 0.1%, supporting spatial packet loss simulation based on distance and obstacle distribution; the latency range is 0ms to 30000ms, with a third step value of 10ms, supporting latency characteristic simulation based on time slot allocation mechanism.

[0053] Furthermore, the network signal attenuation simulator of this embodiment can interfere with multiple communication protocols in parallel, and can programmable interference sequences. Different interference parameters can be set according to the time axis to simulate dynamically changing communication environments. Even further, this embodiment also provides a library of typical interference patterns based on measured data from real-world scenarios, including various geographical environments such as mountainous areas, islands, and suburbs. The network signal attenuation simulator can interfere with communication signals based on this measured data.

[0054] Step 20: Obtain the communication quality parameters and corresponding parameter thresholds of the communication signal; determine whether to switch the communication protocol based on the communication quality parameters and the parameter thresholds; if it is determined to switch the communication protocol, switch the communication protocol and obtain the protocol switching parameters.

[0055] The communication quality parameters of the communication signal include signal strength, packet loss rate, and latency. The decision to switch the current communication protocol is determined by comparing the signal strength, packet loss rate, or latency with corresponding parameter thresholds. In this embodiment, a communication protocol switch is triggered when the signal strength is below a preset strength threshold, when the packet loss rate is above a preset packet loss rate threshold, or when the latency exceeds a preset latency threshold. Furthermore, this embodiment also allows for manual switching of the communication protocol as needed.

[0056] Furthermore, in other embodiments, the communication quality of the communication signal can be comprehensively evaluated based on two or three parameters among signal strength, packet loss rate, and time delay. Based on the comprehensive evaluation, it can be determined whether to switch the communication protocol. For example, the communication protocol can also be switched when the signal strength is low but not lower than a preset strength threshold, the packet loss rate is high but not higher than a preset packet loss rate threshold, and the time delay is large but not higher than a preset time delay threshold.

[0057] In this embodiment, once the communication protocol switching is determined, the communication protocol is switched to another communication protocol. For example, if the current protocol is 4G LTE, and the switching conditions are met, it will be automatically switched to NB-IoT or LoRa. Furthermore, the priority of the communication protocol can be set, and the switching will be performed according to the priority of the communication protocol during the switching process.

[0058] After switching communication protocols, the protocol switching parameters are obtained, including switching accuracy and protocol switching efficiency. The accuracy of protocol switching refers to whether the switching conditions are met and whether the optimal switching is made under given conditions. Protocol switching efficiency includes switching time and resource consumption. Furthermore, the data transmission status during the switching process can be analyzed, including data loss and transmission interruption duration.

[0059] Furthermore, before switching the communication protocol, the method further includes: obtaining the transmission parameters of the communication protocol, and determining the target communication protocol based on the transmission parameters and a preset communication protocol switching decision algorithm;

[0060] Switching the communication protocol includes: switching the communication protocol to the target communication protocol.

[0061] In this embodiment, the transmission parameters of the communication protocol include the received signal strength, the signal-to-noise ratio plus interference ratio, transmission energy consumption assessment, and transmission priority. The communication protocol switching decision algorithm is as follows:

[0062] ;

[0063] in, For decision value, For the corresponding weighting coefficients, These are the received signal strength, signal-to-noise ratio plus interference ratio, transmission power consumption, and transmission priority, respectively. f, g, h, and j are the utility functions corresponding to each transmission parameter. Optimal target communication protocol selection is achieved through the evaluation of multiple transmission parameters. A communication protocol switching decision algorithm is used to score candidate communication protocols to obtain decision values. Finally, the target communication protocol is determined based on the decision values. Generally, the larger the decision value, the better the communication performance of the corresponding communication protocol, thus achieving optimal target communication protocol selection.

[0064] Once the target communication protocol is determined, the current communication protocol is switched to the target communication protocol to conduct communication.

[0065] Furthermore, during the switch to the target communication protocol, the communication protocol conversion mechanism is implemented based on the SDN (Software-Defined Networking) architecture to achieve a protocol conversion layer. This includes protocol conversion through a protocol conversion mapping matrix, packet reconstruction through a packet reconstruction algorithm, and calculation of the handover delay through a handover delay algorithm, thereby achieving seamless communication protocol switching.

[0066] The protocol conversion mapping matrix M = [m_ij], where m_ij represents the conversion overhead from communication protocol i to communication protocol j;

[0067] Packet reconstruction algorithm: NewPacket=T(OriginalPacket,Protocol1,Protocol2), where T is a conversion function that defines the mapping relationship between message headers and payloads between different communication protocols, NewPacket is the reconstructed data packet, OriginalPacket is the original data packet, Protocol1 is the current communication protocol, and Protocol2 is the target communication protocol.

[0068] The handover latency algorithm is: T_switch = T_detect + T_decision + T_handover + T_reconnect, where T_switch is the handover latency, and T_detect, T_decision, T_handover, and T_reconnect are the detection time, decision time, handover time, and reconnection time, respectively.

[0069] Step 30: Pre-build a multi-level data caching mechanism, cache the communication data generated during the communication process to a predetermined storage medium based on the multi-level data caching mechanism, and obtain the caching parameters of the storage medium.

[0070] This embodiment constructs a multi-layered data caching mechanism, which includes storing communication data through a layered caching architecture. The layered caching architecture includes a device-side caching layer, an edge caching layer, and a cloud caching layer, wherein:

[0071] Device-side caching layer: Implemented based on a ring buffer to cache frequently used real-time communication data;

[0072] Edge caching layer: Employs the LRU-K algorithm to manage cached data, thereby caching near real-time communication data to reduce the burden on the cloud;

[0073] Cloud caching layer: Implements a time-decay-based priority queue cache to cache historical communication data accessed infrequently.

[0074] In this embodiment, the caching parameters of the storage medium are obtained through testing or analysis, including the storage medium performance parameters obtained by testing the caching performance of data at each layer on different storage media, implementing progressive load testing to test the cache boundary values ​​of the test system under data volume conditions of 10MB, 100MB, 1GB, and 10GB, quantitatively analyzing the nonlinear relationship between cache data retention time and system resource consumption according to a preset cache data lifecycle management algorithm, and establishing a cache data integrity verification mechanism based on SHA-256 hash verification to analyze data consistency.

[0075] Furthermore, after caching the communication data generated during the communication process into a predetermined storage medium based on a multi-level data caching mechanism, the method further includes optimizing the capacity of the storage medium's cache according to a preset optimization algorithm, wherein the optimization algorithm includes:

[0076] ;

[0077] Where P_miss is the cache miss rate, C is the cache size, and C_max is the maximum cache capacity. This embodiment aims to minimize the cache miss rate P_miss and solves for the optimal cache capacity C_opt under the constraint of not exceeding the maximum capacity C_max. By quantitatively evaluating the balance between cache efficiency and resource consumption, it provides the optimal configuration for the storage medium.

[0078] Step 40: Detect whether a communication interruption has occurred between the photovoltaic devices using a preset communication detection method. If a communication interruption occurs, dynamically adjust the congestion window value and slow start threshold based on a preset congestion control algorithm to resume the interrupted communication data and obtain the resume parameters.

[0079] In this embodiment, the communication detection method can be based on the detection of handshake signals at the protocol layer, or it can be based on the detection of communication data streams. Preferably, this embodiment uses a clock model to detect whether a communication interruption has occurred. The clock model uses an improved Lamport clock. The Lamport clock is a logical clock model used in distributed systems to solve event timing problems. It establishes a partial order of causality by assigning an incremental timestamp to each event. The improved Lamport clock is as follows:

[0080] L(e) = max(L(prev_event) + 1, timestamp + Δt), where L(e) represents the logical timestamp of event e, determined by the max function combining the local counter and physical time reference. L(prev_event) represents the logical timestamp of the event preceding the current event. Timestamp represents the original timestamp provided by the physical clock, typically from time synchronization protocols such as NTP or PTP. Δt represents the timestamp increment parameter. When a communication interruption occurs, a logical timestamp is assigned to each interruption event, and a unique identifier is generated using an improved Lamport clock. By comparing the logical timestamps of the interruption event with those of the preceding and following communication events, a causal order is established. When a gap is detected between L(prev_event) and the current event timestamp, an abnormal communication interruption can be identified. The improved Lamport clock in this embodiment introduces a physical time reference by introducing a timestamp increment Δt, thus solving the window problem of pure logical clocks. Furthermore, when the test system recovers, the event timing relationship can be quickly reconstructed using the Δt value, enhancing its ability to detect interruption points in distributed systems.

[0081] In this embodiment, the congestion control algorithm can be an adaptive congestion control algorithm based on the TCP-Westwood+ protocol. The sender uses the detected ACK arrival rate to estimate the available bandwidth. When packet loss occurs, the estimated bandwidth is used to set the congestion window value and slow start threshold to achieve rapid recovery and resumption of interrupted communication data. The adaptive congestion control algorithm based on the TCP-Westwood+ protocol is as follows:

[0082] ,

[0083] Where cwnd is the congestion window size, cwnd_new is the new congestion window size, ssthresh is the slow start threshold, RTT_min is the minimum round-trip time, RTT_current is the current round-trip time, and α is the gain factor, which is dynamically adjusted as follows:

[0084] ,in, The baseline gain is set to 2.0 based on empirical values, and packet_loss_rate is the packet loss rate. The dynamic adjustment of the gain factor α causes α to decrease as the packet loss rate increases. In this embodiment, data congestion recovery is achieved through an adaptive congestion control algorithm based on the TCP-Westwood+ protocol. When communication conditions are good and the packet loss rate is low, the gain factor α is larger, which can accelerate the growth of the congestion window value cwnd to make full use of idle bandwidth. When communication conditions are poor and the packet loss rate is high, the gain factor α is significantly reduced, which can suppress window expansion to avoid aggravating congestion. This enhances the sensitivity and adaptability to network congestion, reduces unnecessary retransmissions and timeout events, and enables rapid recovery and resumption of interrupted communication data.

[0085] Furthermore, this embodiment can also detect the resume transmission parameter data corresponding to the resume transmission capability, including the detection of communication recovery time and data resume transmission trigger time. It also constructs a multi-dimensional data priority matrix considering the timeliness, importance and integrity of communication data to detect the priority identification and processing mechanism of different types of data. Through a resource consumption real-time monitoring system, it collects indicators such as CPU utilization, memory usage, I / O operation frequency and network bandwidth utilization during the rapid recovery and resume transmission of communication data. It also quantifies the efficiency index of the resume transmission process through the throughput / resource consumption ratio.

[0086] Step 50: Identify whether data is lost during communication using a preset missing data algorithm. If data is lost, complete the data using a preset completion algorithm and obtain the data completion parameters.

[0087] This embodiment identifies whether data is lost during communication through a missing data algorithm. The missing data algorithm includes a sequence number difference detection algorithm and / or a time series anomaly detection algorithm, wherein:

[0088] The sequence number difference detection algorithm is as follows: Δseq = seq_expected - seq_received if Δseq > 0: packet_loss = true, where seq_expected is the expected sequence of communication data, seq_received is the actual received sequence, and Δseq is the difference between the expected sequence number and the actual received sequence number. The sequence number difference detection algorithm compares the difference Δseq, and when Δseq > 0, it determines that data loss has occurred. It is suitable for scenarios where communication data is transmitted in an ordered manner.

[0089] The time series anomaly detection algorithm uses the ARIMA model to determine missing data points by predicting intervals: if |X_actual - X_predicted| > k * σ: potential_missing = true, where k is typically 2 or 3. The standard deviation is the prediction. Missing data points are determined by calculating the deviation between the actual and predicted values ​​(|X_actual - X_predicted|). If the deviation exceeds k times the standard deviation (k*σ), it is considered that data may be missing. This method is suitable for missing data detection in periodic / trend communication data.

[0090] This embodiment employs a hierarchical data completion strategy and uses a corresponding completion algorithm to complete the missing data. The hierarchical data completion strategy is tailored to the characteristics of communication data, including spatial, temporal, and complexity levels, corresponding to spatially relevant communication data, temporally relevant communication data, and complex communication data, respectively. Among these, spatially relevant communication data primarily targets sensor data, and the completion algorithm is as follows:

[0091] Among them, weight , Let be the spatial distance between the missing point and the i-th known sensor. The closer the sensor is, the greater the impact of the data from the missing point. These are estimates of the missing data points to be filled in. Let be the observation value of the i-th known sensor. The algorithm for completing spatially correlated communication data uses weighted interpolation based on the spatial similarity of data from adjacent sensors.

[0092] The completion algorithm for time-related communication data is mainly based on the modified Kalman filter for data prediction and updating. The completion algorithm for complex communication data uses a deep learning model for completion, preferably a bidirectional LSTM network.

[0093] This embodiment also tests the data completion capability when data is lost to obtain data completion parameters, including tests on data loss identification capability, completion algorithm, and data completion recovery. Data loss identification capability includes the accuracy and timeliness of data loss identification; completion algorithm includes the data completion effect for different loss modes, the completion capability under extreme packet loss conditions (such as continuous data loss), and the computational complexity and execution efficiency of the algorithm; data completion recovery includes the deviation between the completed and recovered data and the impact of the completed and recovered data on system decision-making.

[0094] Step 60: Obtain the data recovery rate, time performance index, resource consumption index, and protocol adaptability index when communication is interrupted; generate a test report based on the data recovery rate, time performance index, resource consumption index, protocol adaptability index, protocol switching parameters, cache parameters, resume transmission parameters, and data completion parameters.

[0095] This embodiment establishes multi-dimensional evaluation metrics to comprehensively assess the test system. These metrics include data recovery rate, time performance, resource consumption, and protocol adaptability.

[0096] Data recovery rate (DI) = (N_recovered / N_total) × 100%, calculated as a percentage of recovered data (N_recovered) to total data (N_total). A higher DI indicates better data integrity.

[0097] Time performance indicators This includes response time, recovery time, processing latency, etc., where k_i represents the weight of each type of time.

[0098] The resource consumption index RC = α*CPU + β*MEM + γ*BW + δ*E, where CPU is the processor utilization rate, MEM is the memory utilization rate, BW is the bandwidth utilization rate, E is the energy consumption rate, and α, β, γ and δ are the corresponding weights.

[0099] Protocol adaptability can be measured by end-to-end registration success rate (RSR) = (A / B) × 100%, where A is the number of successful registration processes and B is the number of attempted registration processes. The higher the RSR, the stronger the protocol adaptability.

[0100] This embodiment can also adaptively adjust the weights of each indicator according to the scenario, and dynamically optimize the allocation of indicator weights according to different application scenarios (such as suburbs, mountains, islands, etc.).

[0101] A test report is generated based on the above data recovery rate, time efficiency indicators, resource consumption indicators, protocol adaptability indicators, protocol switching parameters, caching parameters, resume transmission parameters, and data completion parameters.

[0102] Furthermore, based on the test scenario or test environment configuration parameters, a test report is generated that includes configuration parameters, process detection data (protocol switching parameters, caching parameters, resume transmission parameters, and data completion parameters) and result indicators (data recovery rate, time efficiency indicators, resource consumption indicators, and protocol adaptability indicators).

[0103] This embodiment can further include an expert system inference engine, which provides specific optimization suggestions and improvement measures based on the test report.

[0104] The test report generated in this embodiment can also be visualized in multiple dimensions, including performance radar charts, time-series trend charts, and heatmaps of key indicators.

[0105] This embodiment can also integrate anomaly detection algorithms to automatically identify and mark anomalies and potential performance bottlenecks during the testing process.

[0106] Furthermore, the data recovery rate, time performance index, resource consumption index, and protocol adaptability index during communication interruption are obtained. A test report is generated based on the data recovery rate, time performance index, resource consumption index, protocol adaptability index, protocol switching parameters, caching parameters, resuming transmission parameters, and data completion parameters, including:

[0107] The system acquires data recovery rate, time efficiency index, resource consumption index, and protocol adaptability index during communication interruption. It then assigns weights to these indicators using a pre-defined analytic hierarchy process (AHP) weight allocation model. Based on these indicators and their respective weights, it calculates the performance score of the test system. Finally, it generates a test report based on the data recovery rate, time efficiency index, resource consumption index, protocol adaptability index, performance score, protocol switching parameters, caching parameters, resuming transmission parameters, and data completion parameters.

[0108] A pre-established Analytic Hierarchy Process (AHP) weight allocation model assigns weights to data recovery rate, time efficiency, resource consumption, and protocol adaptability, with preferred weights of 0.4, 0.25, 0.2, and 0.15, respectively. The performance score is calculated as: 0.4d + 0.25f + 0.2g + 0.15h, where d, f, g, and h correspond to the data recovery rate, time efficiency, resource consumption, and protocol adaptability, respectively. The generated test report also includes the performance score, which provides an overall evaluation of the test system.

[0109] In this embodiment of the invention, photovoltaic devices communicate using multiple communication protocols. A network signal attenuation simulator is used to interfere with the communication signals. Based on communication quality parameters and threshold values, it is determined whether to switch communication protocols. If switching is determined, the communication protocol is switched. A multi-level data caching mechanism is used to cache communication data. Communication interruptions are detected; if an interruption occurs, a congestion control algorithm is used to resume the interrupted communication data. A missing data algorithm is used to identify if data is lost; if so, a completion algorithm is used to complete the data. A test report is generated based on data recovery rate, time efficiency indicators, resource consumption indicators, protocol adaptability indicators, protocol switching parameters, caching parameters, resumption parameters, and data completion parameters. This embodiment of the invention can simulate communication protocol switching, data caching, interruption identification, data resumption, data loss identification, and completion tests under various weak network environments. Especially under communication signal interruption conditions, it can perform data resumption and completion tests with high accuracy and good results, helping to ensure the accuracy and continuity of system monitoring.

[0110] In one embodiment, after acquiring the data recovery rate, time performance index, resource consumption index, and protocol adaptability index during communication interruption, and generating a test report based on the data recovery rate, time performance index, resource consumption index, protocol adaptability index, protocol switching parameters, caching parameters, resuming transmission parameters, and data completion parameters, the method further includes:

[0111] Establish a system performance evolution model and a long-term performance prediction model based on time series, and analyze the long-term system performance of the test system based on the system performance evolution model and the long-term performance prediction model.

[0112] In this embodiment, the time-series-based system performance evolution model uses a state-space model to describe the evolution of the test system's performance over time, obtaining evolution data including state equations and observation equations:

[0113] Equations of state: ,

[0114] Observation equation: ,

[0115] Where x_t is the current system state vector, y_t is the observation vector, x_(t-1) is the system state vector at the previous time step, wt and vt are the system noise and observation noise, respectively, At is the state transition matrix, Bt is the input influence matrix, ut is the input vector, and Ct is the output mapping matrix.

[0116] Long-term performance prediction models based on time series data can employ a hybrid ARIMA-GARCH model, comprising an ARIMA component (autoregressive composite moving average) and a GARCH component (generalized autoregressive conditional heteroscedasticity).

[0117] ARIMA section:

[0118] ,

[0119] GARCH section:

[0120] ,

[0121] in, d is the d-th difference of the time series Xt, used to eliminate trends and seasonality (to make the series stationary); c is a constant term; The autoregressive coefficient represents the impact of historical differences on the current value; The moving average coefficient represents historical noise. Impact on the current value; Let $\frac{ ... The distribution of ARIMA. The ARIMA component can capture the long-term trend and linear dependence of a sequence.

[0122] ω represents the conditional variance (volatility) over time t, reflecting the time-varying volatility of the series; ω is a constant term (basic volatility level); α i ε represents the ARCH term coefficient, indicating the past squared residuals; t-i To account for the impact of current fluctuations (short-term shock effect); β j The coefficients of the GARCH term represent the past conditional variance σ. t-j The persistence of ² (long-term fluctuation memory). The GARCH part can model the fluctuation clustering of residuals.

[0123] In this embodiment of the invention, communication interruption includes various types. Based on the duration of the interruption, the communication interruption types include the following:

[0124] Interruptions during short dramas: 0.5 to 2 hours;

[0125] Medium-duration interruption: 2 to 12 hours;

[0126] Long-term interruption: 12 to 72 hours;

[0127] Extreme interruption: 72 hours or more.

[0128] For example, for communication interruption scenarios of different communication interruption types, the following aspects are tested, including:

[0129] Hierarchical data cache capacity test: Verify the local data caching capability under different interruption durations and obtain the corresponding cache performance parameters;

[0130] Incremental data recovery strategy test: First, restore key parameter data (such as power generation and fault information), then restore regular monitoring data, and obtain the recovery rate;

[0131] Multi-protocol collaborative recovery mechanism test: a priority rotation mechanism for communication methods such as 4G, NB-IoT, and LoRa is preset to maximize recovery efficiency;

[0132] Bandwidth adaptive transmission algorithm test: Based on the network bandwidth conditions at the time of recovery, the data transmission batches and priorities are dynamically adjusted to obtain the recovery rate.

[0133] The quantitative evaluation indicators for the above test results also include the following indicators: data recovery rate under different interruption durations; resource consumption indicators during the recovery process: CPU utilization, memory utilization, and bandwidth utilization; recovery time efficiency evaluation: the amount of data recovered per unit time; and transmission protocol adaptability score: a comprehensive score based on the timeliness of protocol switching and transmission efficiency.

[0134] When generating the test report, the data or metrics obtained from the above tests should be written into the test report.

[0135] In the scenario of data recovery from frequent short-term interruptions, the following test plan and evaluation system are implemented to address the problem of short-term, high-frequency communication interruptions faced by the distributed photovoltaic test system in areas with unstable communication networks, and the corresponding test results data are obtained:

[0136] 1. Interrupt mode parameterization:

[0137] Interruption frequency index: defined as the number of interruptions per unit time (1 hour), with a test range of 5-120 times / hour;

[0138] Duration of a single interruption: ranging from 10 seconds to 5 minutes, following a log-normal distribution;

[0139] Interruption interval characteristics: Two typical modes are set: random interval mode (Poisson distribution) and periodic interval mode (fixed interval ±20% fluctuation).

[0140] 2. Testing Plan and Technical Approach:

[0141] Micro-caching technology testing: Testing a microsecond-level response data caching mechanism based on embedded storage, and analyzing data integrity under high-frequency interrupts;

[0142] Communication handshake test: Evaluate the performance of the improved fast reconnection protocol in a frequent interruption environment, measure the average reconnection time, and compare it with the standard TCP / IP protocol;

[0143] Dynamic data packetization mechanism: The ability to adaptively adjust the data packet size based on the interrupt frequency, quantifying the functional relationship between the optimal data packet size and the interrupt frequency;

[0144] Redundant transmission strategy testing: Analyze the effectiveness of selective data redundancy transmission strategies implemented under predictive outage mode, and test the balance between improved data recovery rate and bandwidth cost.

[0145] 3. Multi-dimensional performance quantification indicators:

[0146] Cumulative data recovery rate: Measures the cumulative integrity of data after experiencing frequent interruptions within a predetermined time period (e.g., one day);

[0147] System overhead efficiency ratio a: a = percentage point improvement in data recovery rate / percentage point increase in additional resource consumption;

[0148] Real-time performance metrics: Transmission latency of critical data (such as overcurrent and overvoltage alarms) in environments with frequent interruptions;

[0149] Availability index b: b = System normal response time / (System normal response time + Interruption recovery time).

[0150] When generating the test report, the test results data and multi-dimensional performance quantification indicators obtained from the above tests should be written into the test report.

[0151] Furthermore, Monte Carlo simulation technology can be used to simulate tens of thousands of different combinations of interruption frequency and duration scenarios to construct system performance surface plots; the cumulative impact of continuous interruption events can be analyzed through Markov chain models to predict the system reliability under long-term operation; the uncertainty of communication interruption modes can be quantified using information entropy theory to evaluate the system's adaptability to random interruptions, and the surface plots and other data can be written into the test report.

[0152] Figure 2 A schematic diagram of the structure of a distributed photovoltaic multi-protocol communication test device according to an embodiment of the present invention is shown. Figure 2 As shown, the device includes:

[0153] A network signal attenuation simulator 201 is used to interfere with the communication signals between photovoltaic devices that communicate through a predetermined communication protocol.

[0154] The protocol switching test module 202 is used to obtain the communication quality parameters and corresponding parameter thresholds of the communication signal, determine whether to switch the communication protocol based on the communication quality parameters and the parameter thresholds, and if it is determined to switch the communication protocol, then switch the communication protocol and obtain the protocol switching parameters.

[0155] The cache testing module 203 is used to pre-build a multi-level data caching mechanism, cache the communication data generated during the communication process to a predetermined storage medium based on the multi-level data caching mechanism, and obtain the cache parameters of the storage medium.

[0156] The interruption resumption test module 204 is used to detect whether a communication interruption has occurred between the photovoltaic devices through a preset communication detection method. If a communication interruption occurs, the congestion window value and slow start threshold are dynamically adjusted based on a preset congestion control algorithm to enable the interrupted communication data to resume transmission and to obtain the resumption parameters.

[0157] The data completion test module 205 is used to identify whether data is lost during communication through a preset missing data algorithm. If data is lost, the data is completed through a preset completion algorithm, and the data completion parameters are obtained.

[0158] The generation module 206 is used to obtain the data recovery rate, time performance index, resource consumption index and protocol adaptability index when communication is interrupted, and generate a test report based on the data recovery rate, the time performance index, the resource consumption index, the protocol adaptability index, the protocol switching parameters, the cache parameters, the resume transmission parameters and the data completion parameters.

[0159] Figure 3 The diagram shows a structural schematic of an embodiment of the computer device of the present invention. The specific embodiments of the present invention do not limit the specific implementation of the computer device.

[0160] like Figure 3 As shown, the computer device may include: a processor 402, a communications interface 404, a memory 406, and a communications bus 408.

[0161] The processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408. Communication interface 404 is used to communicate with other computer devices, such as clients or other server network elements. The processor 402 executes program 410, specifically performing the relevant steps described above in the computer device embodiment.

[0162] Specifically, program 410 may include program code, which includes computer-executable instructions.

[0163] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The computer device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0164] Memory 406 is used to store program 410. Memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0165] Specifically, program 410 can be called by processor 402 to cause the computer device to perform the following operations:

[0166] Interference is achieved by using a network signal attenuation simulator to interfere with the communication signals between photovoltaic devices, which communicate through a predetermined communication protocol.

[0167] Obtain the communication quality parameters and corresponding parameter thresholds of the communication signal; determine whether to switch the communication protocol based on the communication quality parameters and the parameter thresholds; if it is determined to switch the communication protocol, switch the communication protocol and obtain the protocol switching parameters.

[0168] A multi-level data caching mechanism is pre-built, and the communication data generated during the communication process is cached in a predetermined storage medium based on the multi-level data caching mechanism, and the caching parameters of the storage medium are obtained.

[0169] The system detects whether a communication interruption has occurred between the photovoltaic devices using a preset communication detection method. If a communication interruption occurs, it dynamically adjusts the congestion window value and slow start threshold based on a preset congestion control algorithm to enable the interrupted communication data to be transmitted again and obtain the transmission parameters.

[0170] The algorithm identifies whether data is lost during communication using a pre-defined missing data algorithm. If data is lost, it completes the data using a pre-defined completion algorithm and obtains the data completion parameters.

[0171] The system acquires data recovery rate, time performance index, resource consumption index, and protocol adaptability index during communication interruption, and generates a test report based on the data recovery rate, time performance index, resource consumption index, protocol adaptability index, protocol switching parameters, cache parameters, resume transmission parameters, and data completion parameters.

[0172] In one alternative approach, the communication protocol includes at least 4G LTE protocol, long-range wireless communication protocol, and narrowband IoT protocol, and the interference of communication signals between photovoltaic devices based on the network signal attenuation simulator includes:

[0173] The signal strength of the communication signal is controlled to change according to a predetermined first step value within a preset strength range; the packet loss rate of the communication signal is controlled to change according to a predetermined second step value within a preset packet loss rate range; and the delay of the communication signal is controlled to change according to a predetermined third step value within a preset delay range.

[0174] In one alternative approach, the interference of communication signals between photovoltaic devices based on the network signal attenuation simulator includes:

[0175] A library of typical interference patterns based on measured data from real-world scenarios is obtained. These scenarios include various geographical environments. The communication signals are then interfered with using a network signal attenuation simulator and the measured data.

[0176] In one optional approach, before switching the communication protocol, the method further includes: obtaining the transmission parameters of the communication protocol, and determining the target communication protocol based on the transmission parameters and a preset communication protocol switching decision algorithm.

[0177] The switching of the communication protocol includes: switching the communication protocol to the target communication protocol.

[0178] In one alternative approach, after pre-building a multi-level data caching mechanism, caching communication data generated during communication to a predetermined storage medium based on the multi-level data caching mechanism, and obtaining the caching parameters of the storage medium, the method further includes:

[0179] The capacity of the cache of the storage medium is optimized according to a preset optimization algorithm.

[0180] In one optional approach, after obtaining the data recovery rate, time performance index, resource consumption index, and protocol adaptability index during communication interruption, and generating a test report based on the data recovery rate, time performance index, resource consumption index, protocol adaptability index, protocol switching parameters, caching parameters, resuming transmission parameters, and data completion parameters, the method further includes:

[0181] Establish a system performance evolution model and a long-term performance prediction model based on time series, and analyze the long-term system performance of the test system based on the system performance evolution model and the long-term performance prediction model.

[0182] In one optional approach, the step of acquiring the data recovery rate, time performance index, resource consumption index, and protocol adaptability index during communication interruption, and generating a test report based on the data recovery rate, time performance index, resource consumption index, protocol adaptability index, protocol switching parameters, caching parameters, resuming transmission parameters, and data completion parameters, includes:

[0183] The system acquires data recovery rate, time efficiency index, resource consumption index, and protocol adaptability index during communication interruption. It then assigns weights to these indicators using a pre-defined analytic hierarchy process (AHP) weight allocation model. Based on these indicators and their respective weights, it calculates the performance score of the test system. Finally, it generates a test report based on the data recovery rate, time efficiency index, resource consumption index, protocol adaptability index, performance score, protocol switching parameters, caching parameters, resuming transmission parameters, and data completion parameters.

[0184] This invention provides a computer-readable storage medium storing at least one executable instruction that, when executed on a computer device, causes the computer device to perform any of the above-described method embodiments.

[0185] This invention provides a computer program that can be invoked by a processor to cause a computer device to execute any of the above-described method embodiments.

[0186] This invention provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions that, when executed on a computer, cause the computer to perform any of the above-described method embodiments.

[0187] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, the embodiments of the present invention are not directed to any particular programming language. It should be understood that the content of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0188] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0189] Similarly, it should be understood that, in order to streamline the invention and aid in understanding one or more of the various aspects of the invention, features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the above description of exemplary embodiments of the invention. However, this disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim.

[0190] Those skilled in the art will understand that modules in the computer device of the embodiments can be adaptively modified and placed in one or more computer devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or computer device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0191] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A distributed photovoltaic multi-protocol communication testing method, applied to a testing system, characterized in that, The method includes: Interference is achieved by using a network signal attenuation simulator to interfere with the communication signals between photovoltaic devices, which communicate through a predetermined communication protocol. Obtain the communication quality parameters and corresponding parameter thresholds of the communication signal; determine whether to switch the communication protocol based on the communication quality parameters and the parameter thresholds; if it is determined to switch the communication protocol, switch the communication protocol and obtain the protocol switching parameters. A multi-level data caching mechanism is pre-built, and the communication data generated during the communication process is cached in a predetermined storage medium based on the multi-level data caching mechanism, and the caching parameters of the storage medium are obtained. The system detects whether a communication interruption has occurred between the photovoltaic devices using a preset communication detection method. If a communication interruption occurs, it dynamically adjusts the congestion window value and slow start threshold based on a preset congestion control algorithm to enable the interrupted communication data to be transmitted again and obtain the transmission parameters. The algorithm identifies whether data is lost during communication using a pre-defined missing data algorithm. If data is lost, it completes the data using a pre-defined completion algorithm and obtains the data completion parameters. The system acquires data recovery rate, time performance index, resource consumption index, and protocol adaptability index during communication interruption, and generates a test report based on the data recovery rate, time performance index, resource consumption index, protocol adaptability index, protocol switching parameters, cache parameters, resume transmission parameters, and data completion parameters.

2. The method according to claim 1, characterized in that, The communication protocol includes at least 4G LTE protocol, long-range wireless communication protocol, and narrowband IoT protocol. The interference of communication signals between photovoltaic devices based on the network signal attenuation simulator includes: The signal strength of the communication signal is controlled to change according to a predetermined first step value within a preset strength range; the packet loss rate of the communication signal is controlled to change according to a predetermined second step value within a preset packet loss rate range; and the delay of the communication signal is controlled to change according to a predetermined third step value within a preset delay range.

3. The method according to claim 1, characterized in that, The interference of communication signals between photovoltaic devices based on the network signal attenuation simulator includes: A library of typical interference patterns based on measured data from real-world scenarios is obtained. These scenarios include various geographical environments. The communication signals are then interfered with using a network signal attenuation simulator and the measured data.

4. The method according to claim 1, characterized in that, Before switching the communication protocol, the method further includes: obtaining the transmission parameters of the communication protocol, and determining the target communication protocol based on the transmission parameters and a preset communication protocol switching decision algorithm; The switching of the communication protocol includes: switching the communication protocol to the target communication protocol.

5. The method according to claim 1, characterized in that, The pre-built multi-level data caching mechanism, after caching communication data generated during communication to a predetermined storage medium based on the multi-level data caching mechanism and obtaining the caching parameters of the storage medium, further includes: The capacity of the cache of the storage medium is optimized according to a preset optimization algorithm.

6. The method according to claim 1, characterized in that, After acquiring the data recovery rate, time performance index, resource consumption index, and protocol adaptability index during communication interruption, and generating a test report based on the data recovery rate, time performance index, resource consumption index, protocol adaptability index, protocol switching parameters, caching parameters, resuming transmission parameters, and data completion parameters, the method further includes: Establish a system performance evolution model and a long-term performance prediction model based on time series, and analyze the long-term system performance of the test system based on the system performance evolution model and the long-term performance prediction model.

7. The method according to claim 1, characterized in that, The process involves acquiring data recovery rate, time performance metrics, resource consumption metrics, and protocol adaptability metrics during communication interruptions. A test report is generated based on these metrics, including the data recovery rate, time performance metrics, resource consumption metrics, protocol adaptability metrics, protocol switching parameters, caching parameters, resuming transmission parameters, and data completion parameters. The report includes: The system acquires data recovery rate, time efficiency index, resource consumption index, and protocol adaptability index during communication interruption. It then assigns weights to these indicators using a pre-defined analytic hierarchy process (AHP) weight allocation model. Based on these indicators and their respective weights, it calculates the performance score of the test system. Finally, it generates a test report based on the data recovery rate, time efficiency index, resource consumption index, protocol adaptability index, performance score, protocol switching parameters, caching parameters, resuming transmission parameters, and data completion parameters.

8. A distributed photovoltaic multi-protocol communication testing device, characterized in that, The device includes: A network signal attenuation simulator is used to interfere with the communication signals between photovoltaic devices that communicate through a predetermined communication protocol. The protocol switching test module is used to obtain the communication quality parameters and corresponding parameter thresholds of the communication signal, determine whether to switch the communication protocol based on the communication quality parameters and the parameter thresholds, and if it is determined to switch the communication protocol, then switch the communication protocol and obtain the protocol switching parameters. The cache testing module is used to pre-build a multi-level data caching mechanism, cache the communication data generated during the communication process to a predetermined storage medium based on the multi-level data caching mechanism, and obtain the cache parameters of the storage medium. The interruption resumption test module is used to detect whether a communication interruption has occurred between the photovoltaic devices through a preset communication detection method. If a communication interruption occurs, the congestion window value and slow start threshold are dynamically adjusted based on a preset congestion control algorithm to enable the interrupted communication data to resume transmission and to obtain the resumption parameters. The data completion test module is used to identify whether data is lost during communication using a preset missing data algorithm. If data is lost, it completes the data using a preset completion algorithm and obtains the data completion parameters. The generation module is used to obtain the data recovery rate, time performance index, resource consumption index and protocol adaptability index when communication is interrupted, and generate a test report based on the data recovery rate, the time performance index, the resource consumption index, the protocol adaptability index, the protocol switching parameters, the cache parameters, the resume transmission parameters and the data completion parameters.

9. A computer device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores at least one executable instruction, which, when executed on a computer device, causes the computer device to perform the method as described in any one of claims 1-7.

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