Distributed photovoltaic power station intelligent regulation and control system based on 5G multi-protocol fusion

Abstract

The invention relates to the technical field of photovoltaic power station regulation and control, in particular to a distributed photovoltaic power station intelligent regulation and control system based on 5G multi-protocol fusion, which deeply fuses 5G network capability and distributed photovoltaic service requirements, intelligently analyzes a regulation and control intention and customizes a multi-dimensional special slice. Uniform access of multiple protocols such as OPCUA and MQTT and intelligent scheduling of a network side protocol are achieved, protocol interaction and resource scheduling full-process simulation is carried out by means of a two-dimensional twinborn body, heterogeneous adaptation and scene conflict risks are resolved in advance, and accurate cooperation of service requirements and network capacity is promoted. Meanwhile, a scientific decision-making system is constructed through quantitative evaluation, resource utilization and elastic response are dynamically optimized, safety is guaranteed through physical and logic double isolation and a protocol white list mechanism, and a'demand analysis-simulation verification-decision optimization-safety protection 'closed loop is formed; and an intelligent regulation and control mode which is accurate in adaptation, efficient in cooperation, safe and reliable is created for the distributed photovoltaic power station.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of photovoltaic power station regulation, more particularly, it relates to a distributed photovoltaic power station intelligent regulation system based on 5G multi-protocol fusion. BACKGROUND

[0002] In the field of intelligent regulation of distributed photovoltaic power stations, multi-protocol heterogeneity and business demand diversity constitute the core technical bottleneck. Photovoltaic equipment often uses different industrial protocols such as OPCUA, MQTT, Modbus to transmit data, and the characteristics of various protocols in terms of reliability, transmission efficiency, etc. are significantly different. Traditional regulation systems lack unified adaptation capability for heterogeneous protocols, making it difficult to achieve efficient access and collaborative scheduling of multi-protocol data, resulting in frequent problems such as inaccurate transmission of real-time control instructions and congestion of periodic data upload, which restricts the accuracy and timeliness of photovoltaic power station regulation.

[0003] From the network support level, the existing technology has obvious shortcomings in the design and verification of slices. Although network slicing technology provides the possibility of customized transmission for differentiated business needs, traditional slicing schemes rely on manual experience configuration and lack effective pre-verification of slicing scheduling logic and resource conflict risks in multi-protocol fusion scenarios. After actual deployment, problems such as protocol parsing failure and uncontrollable resource preemption may occur. At the same time, in the scenario of coexistence of heterogeneous protocols, the imperfect physical or logical isolation mechanism between slices not only causes interference from low-priority business to high-priority business, but also may lead to the risk of penetration of external network attacks, seriously threatening the stable operation of photovoltaic power station regulation systems. It is urgent to build a full-process intelligent regulation scheme that takes into account protocol adaptation, resource scheduling, pre-verification, and security protection. SUMMARY

[0004] In view of the deficiencies of the existing technology, the purpose of the present application is to provide a distributed photovoltaic power station intelligent regulation system based on 5G multi-protocol fusion.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0006] The distributed photovoltaic power station intelligent regulation system based on 5G multi-protocol fusion comprises

[0007] A regulation intention analysis module analyzes structured regulation intentions in real time according to the original regulation needs of the distributed photovoltaic power station.

[0008] An intention slice creation module determines a plurality of special slice schemes according to different dimensions and determines the special slices included in each special slice scheme.

[0009] A dual-dimensional twin body building module builds a dual-dimensional twin body based on the distributed photovoltaic power station and the 5G network infrastructure.

[0010] The regulation slice scheme determination module selects a regulation slice scheme from the special slice schemes based on the dual-dimensional twin, and slices the original regulation demand of the distributed photovoltaic power station according to the regulation slice scheme and transmits the original regulation demand.

[0011] Further, the construction steps of the dual-dimensional twin are as follows: S1: collecting multi-protocol data of the photovoltaic power station side and the 5G network side;

[0012] S2: constructing a photovoltaic power station twin and a 5G network twin respectively;

[0013] S3: establishing real-time interaction and correlation mapping across dimensions to build a dual-dimensional twin.

[0014] Further, the multi-protocol data collection of the photovoltaic power station side: the photovoltaic equipment transmits data using diversified industrial protocols, and needs to realize unified access through the protocol conversion gateway of the edge computing node: group string inverter and energy storage system transmit high-precision control instructions through OPCUA protocol; the busbar box and environmental sensor transmit periodic state data through MQTT protocol; the old equipment transmits data through ModbusRTU protocol, and is connected to the system after being converted by ECU to MQTT / OPCUA, the collection frequency remains the original standard, and is uniformly packaged into Protobuf format through the protocol gateway, with the addition of device identification and protocol type label.

[0015] Further, the multi-protocol data collection of the 5G network side: 5G network involves control plane, user plane and multi-protocol, which needs to extract key data through the protocol analysis module of the core network and edge node: control plane: the connection state of the base station gNB and the core network is collected through S1AP protocol, and the policy interaction information of PCF and SMF is obtained through N11 protocol; user plane: the forwarding path and traffic characteristics of the slice service are collected through GTP-U protocol, and the AI inference result of the edge node is received through HTTP / 2 protocol; management plane: the base station resources are configured through NetConf protocol, and the device alarm is collected through SNMP protocol.

[0016] Further, the regulation slice scheme is selected from the special slice schemes based on the dual-dimensional twin: the slice regulation evaluation value of each special slice scheme is determined based on the dual-dimensional twin, and the special slice scheme with the maximum slice regulation evaluation value is marked as the regulation slice scheme.

[0017] Further, the step of determining the slice regulation evaluation value of the special slice solution: selecting a special slice solution, importing the special slice contained in the special slice solution into the double-dimensional twin for simulation, simulating the transmission process of the special slice by the double-dimensional twin, obtaining the service compliance value, the network protocol layer adaptation value and the resource efficiency value after the transmission is completed, and calculating the slice regulation evaluation value of the special slice solution by weighted sum calculation of the service compliance value, the network protocol layer adaptation value and the resource efficiency value.

[0018] Further, the step of obtaining the service compliance value: after the transmission is completed, collecting the time delay of each data packet in the transmission process, calculating the average time delay by summing and averaging the time delay of each data packet, and obtaining the broadband fluctuation rate of the entire transmission process, and calculating the service compliance value based on the average time delay and the broadband fluctuation rate.

[0019] Further, the step of obtaining the network protocol layer adaptation value: after the transmission is completed, determining the data packet parsing failure rate Rate fail , measuring the total time consumption TP 5G of OPCUA protocol conversion to 5G protocol, and calculating the network protocol layer adaptation value based on the parsing failure rate and the total time consumption.

[0020] Further, the step of obtaining the resource efficiency value: after the transmission is completed, determining the average PRB occupation rate and the elastic broadband response time , determining the average PRB occupation rate , , , determining the elastic broadband response time , , , calculating the resource efficiency value by , wherein, is the PRB occupation coefficient, is the elastic broadband response coefficient.

[0021] Compared with the prior art, the present application has the following advantages:

[0022] The system of the application deeply integrates the 5G network capability and the distributed photovoltaic business demand, realizes the unified access of multiple protocols such as OPCUA and MQTT and the intelligent scheduling of network side protocols by intelligently analyzing and regulating the intention and customizing multi-dimensional special slices, resolves the heterogeneous adaptation and scene conflict risk in advance by means of the double-dimensional twin body to simulate the whole process of protocol interaction and resource scheduling, and promotes the accurate cooperation between business demand and network capability. Based on the quantitative evaluation mechanism of the double-dimensional twin body, the system constructs a scientific decision-making system, realizes the optimal selection of the special slice scheme through the weighted analysis of multi-dimensional indexes such as business compliance, protocol adaptability and resource efficiency. This not only improves the utilization efficiency and flexible response capability of network resources, but also relies on physical isolation and logical isolation technology to strengthen the security protection level of the system, and finally forms a complete closed loop of "demand analysis-simulation verification-decision optimization-security protection", which provides an intelligent regulation mode of accurate adaptation, efficient cooperation and safe and reliable for the distributed photovoltaic power station. BRIEF DESCRIPTION OF DRAWINGS

[0023] Fig. 1 It is a system principle diagram of the distributed photovoltaic power station intelligent regulation system based on 5G multi-protocol fusion.

[0024] Fig. 2 It is a principle diagram of the regulation intention analysis module.

[0025] Fig. 3 It is a principle diagram of the double-dimensional twin body building. DETAILED DESCRIPTION

[0026] Referring to Figs. 1 to 3 The distributed photovoltaic power station intelligent regulation system based on 5G multi-protocol fusion includes a regulation intention analysis module, an intention slice creation module, a double-dimensional twin body building module and a regulation slice scheme determination module.

[0027] The regulation intention analysis module analyzes the structured regulation intention in real time according to the original regulation requirement of the distributed photovoltaic power station (the original regulation requirement of the distributed photovoltaic power station can be input by a business personnel or automatically generated by the system; if the original regulation requirement of the distributed photovoltaic power station is "preferentially upload the alarm information of the inverter in region A, and the time delay is less than or equal to 50 ms" (temporary original regulation requirement), the business personnel needs to input the original regulation requirement; if the original regulation requirement of the distributed photovoltaic power station is "automatically trigger the upload of daily power generation data of inverters in each region at 00:00 every day, and the bandwidth is greater than or equal to 1 Mbps" (periodic), the system automatically generates the original regulation requirement; for example, "preferentially upload the alarm information of the inverter in region A, and the time delay is less than or equal to 50 ms" is analyzed by natural language processing technology to obtain the intention classification: "ALARM_UPLOAD" (alarm upload); entity recognition: extract the region "region A", the equipment "inverter", and the parameter "time delay less than or equal to 50 ms"; relationship extraction: determine that "time delay less than or equal to 50 ms" is the parameter of "alarm upload"); and the analyzed original regulation requirement is converted into a structured format that can be recognized by the 5G network. The distributed photovoltaic power station may need to analyze multiple original regulation requirements such as "preferentially upload the alarm information of the inverter in region A, and the time delay is less than or equal to 50 ms" and "automatically trigger the upload of daily power generation data of inverters in each region at 00:00 every day, and the bandwidth is greater than or equal to 1 Mbps".

[0028] An intent slice creation module determines a plurality of dedicated slice schemes according to different dimensions (each dimension corresponds to a dedicated slice scheme, and the dimensions include but are not limited to the following: a service type dimension, a priority dimension, an isolation requirement dimension (highest isolation), an isolation requirement dimension (compromise isolation), etc. The service type dimension divides slices according to the 5G technology type (URLLC / eMBB / mMTC) of the service to ensure that the slice characteristics match the technical requirements of the service. The priority dimension divides slices according to the emergency level (high / medium / low priority) of the service, rather than strictly according to the service type, allowing high-priority services across types to share slice resources. The isolation requirement dimension (highest isolation) requires complete physical or logical isolation between slices (no resource sharing, no signaling interaction) to avoid any form of interference or risk transmission. The isolation requirement dimension (compromise isolation) allows slices to share some redundant resources (such as idle resources of low-priority slices) under the premise of ensuring basic isolation (such as "high-priority services are not disturbed by low-priority services"). Determine the dedicated slices included in each dedicated slice scheme (such as the structured control intent composed of "upload daily power generation data of each regional inverter at 00:00 every day, bandwidth ≥ 1 Mbps" and "upload alarm information of inverter in area A first, require latency ≤ 50 ms" are parsed as "ALARM_UPLOAD" two original control requirements, in the dedicated slice scheme corresponding to the service type dimension, can be divided into two dedicated slices, slice 1: ALARM_UPLOAD (alarm upload in area A), S-NSSAI = "ALARM-A", QCI = 2 (high reliability and low latency priority defined by 3GPP), latency ≤ 50 ms, bind dedicated PRB resource of gNB1 (independent physical resource block, not shared with other services), slice 2: DATA_UPLOAD (daily power generation upload), S-NSSAI = "DATA-ALL", QCI = 5 (non-real-time high-throughput priority defined by 3GPP), bandwidth ≥ 1 Mbps, bind shared PRB resource of gNB1 (dynamically allocated with other eMBB services, automatically increase bandwidth weight at 00:00 every day); in the dedicated slice scheme corresponding to the priority dimension, can be divided into two dedicated slices, slice 1: high-priority slice (only contains alarm upload in area A), S-NSSAI = "HIGH-PRIORITY", QCI = 1 (3GPP highest priority, cannot be preempted), latency ≤ 30 ms, reserve 20% dedicated bandwidth (bind independent PRB of gNB1); slice 2: low-priority slice (only contains daily power generation upload), S-NSSAI = "LOW-PRIORITY", QCI = 6 (3GPP low priority, can be preempted), bandwidth baseline ≥ 1 Mbps, elastic bandwidth (can be expanded to 2 Mbps when idle, can be temporarily reduced to 0 when high-priority slice resources are insufficient).8 Mbps); under the special slice scheme corresponding to the isolation requirement dimension (highest isolation), it can be divided into two special slices, Slice 1: ALARM_UPLOAD (A area alarm upload), S-NSSAI = "ALARM-ISOLATED", binding the special PRB resource of independent base station gNB1, independent core network UPF1 instance, the physical link (optical fiber) is completely isolated from other slices, and the time delay is ≤50 ms; Slice 2: DATA_UPLOAD (daily power generation upload), S-NSSAI = "DATA-ISOLATED", binding the special PRB resource of independent base station gNB2, independent core network UPF2 instance, and there is no resource overlap (no sharing of the remaining bandwidth of gNB1 / gNB2) with Slice 1, and the bandwidth is ≥1 Mbps).

[0029] The dual-dimensional twin body building module builds a dual-dimensional twin body based on the distributed photovoltaic power station and the 5G network infrastructure. The specific steps are as follows:

[0030] S1: Collecting multi-protocol data on the photovoltaic power station side and the 5G network side (multi-protocol data collection on the photovoltaic power station side: photovoltaic equipment transmits data using diversified industrial protocols, and needs to access uniformly through the protocol conversion gateway of the edge computing node (ECU): group string inverter and energy storage system transmit high-precision control instructions (such as reactive power compensation instructions, supporting millisecond-level response and data encryption) through OPCUA protocol; junction box and environmental sensors transmit periodic state data (such as group string current and light intensity, lightweight and low bandwidth consumption) through MQTT protocol; old equipment (such as traditional inverters) transmits data through ModbusRTU protocol, which is converted to MQTT / OPCUA after ECU and then accessed to the system. The collection frequency remains the original standard (100 ms / second for key equipment and 1 s / second for ordinary equipment), and is uniformly packaged into Protobuf format through the protocol gateway, with additional equipment identification and protocol type label (such as "INV-A-001_OPCUA"); multi-protocol data collection on the 5G network side: 5G network involves control plane, user plane and multi-protocol, which needs to extract key data through the protocol analysis module of the core network and the edge node: control plane: collect the connection state of base station gNB and core network (such as S1 connection establishment / release event of gNB1 and AMF) through S1AP protocol, and obtain policy interaction information (such as slice priority adjustment instruction) of PCF and SMF through N11 protocol; user plane: collect the forwarding path and traffic characteristics of slice service (such as GTP tunnel identifier and data packet delay of URLLC slice) through GTP-U protocol, and receive AI inference results (such as anomaly detection report) of edge node (MEC) through HTTP / 2 protocol; management plane: configure base station resources (such as PRB allocation ratio) through NetConf protocol, and collect device alarms (such as fan failure alarm of gNB1) through SNMP protocol.

[0031] S2: Construct photovoltaic power station twin and 5G network twin respectively (construct photovoltaic power station twin: device protocol simulation: inverter: simulate the "publish-subscribe" mechanism of OPCUA protocol (such as publishing voltage data to edge node once every 100 ms, and timeout retransmission mechanism ensures reliability), and protocol stack processing delay (about 5 ms); sensor: simulate the "lightweight transmission" feature of MQTT protocol (such as using QoS=1 level to ensure that messages are delivered at least once, and packet header overhead ≤20 bytes), and the influence of network jitter on transmission interval (such as ±10 ms fluctuation). Business protocol adaptation: control type business: preferentially bind OPCUA protocol, simulate its performance in high reliability scenario (such as instruction transmission success rate ≥99.99%, but protocol overhead is 30% higher than MQTT); data type business: bind MQTT protocol, simulate its lightweight advantage in large flow scenario (such as uploading 1MB power generation data every 5 minutes, and the total transmission delay is 20% lower than OPCUA). Construct 5G network twin: base station protocol processing: simulate the scheduling logic of gNB for different protocol data packets: OPCUA control instruction (URLLC slice) uses "preemptive scheduling" (preferentially allocates time slots), and MQTT data (eMBB slice) uses "non-preemptive scheduling" (processes according to queue order), and simulates protocol parsing delay (such as GTP-U packet header parsing time-consuming 0.5 ms). Core network protocol interaction: simulate SMF issuing "protocol-aware forwarding rules" to UPF through N4 protocol (such as "OPCUA data packet marked DSCP=EF, go to low latency path; MQTT data packet marked DSCP=AF41, go to high throughput path"); simulate PCF pushing "protocol adapted QoS policy" to SMF through N7 protocol (such as "maximum allowed delay of OPCUA business =10 ms, maximum allowed delay of MQTT business =100 ms"). Slice protocol isolation: add "protocol whitelist" to each slice model: URLLC control slice only allows OPCUA protocol access, eMBB data slice allows MQTT / HTTP protocol access, simulate the isolation ability of slice to heterogeneous protocol (such as rejecting data packets of non-whitelist protocols, interception rate 100%).

[0032] S3: Establish real-time interaction and correlation mapping across dimensions, and build a two-dimensional twin (protocol correlation in spatial mapping: In the "device IP-slice identifier-base station ID" binding table, add a protocol type field to clearly define the protocol adaptation relationship between the device and the slice: For example, the inverter group (IP: 192.168.1.1~10) of photovoltaic power station A binds the slice "INV-CTRL-001" (URLLC type), and the protocol type is limited to "OPCUA". The base station gNB1 needs to enable the "OPCUA data packet priority scheduling" function; In the twin, the "OPCUA instruction sending" action of the inverter model automatically triggers the "GTP-U tunnel establishment + OPCUA packet header analysis" simulation of the slice model, reproducing the complete protocol chain. Protocol adaptation rules in parameter mapping: Define the correlation logic of photovoltaic business requirements, protocol types, and 5G slice parameters: inverter control instructions (need millisecond-level response + high reliability) → bind OPCUA protocol → map to slice parameters "QCI=1 + OPCUA data packet scheduling priority = highest + GTP-U tunnel redundancy backup"; power generation data upload (large flow + low latency sensitive) → bind MQTT protocol → map to slice parameters "QCI=7 + MQTT data packet aggregation transmission (every 10 packets are combined and forwarded) + dynamic bandwidth 2-10 Mbps". Protocol adaptation for time synchronization and state synchronization: Time synchronization: For the clock characteristics of different protocols, adopt differentiated synchronization strategies: OPCUA protocol relies on the Precision Time Protocol (PTP, deviation ≤1ms), and MQTT protocol uses NTP synchronization (deviation ≤10ms), to ensure the timestamp consistency of protocol interaction in the twin. State synchronization: Every 500ms, synchronize the "protocol performance data" across the twin: the photovoltaic twin synchronizes "OPCUA instruction retransmission rate" and "MQTT connection disconnection times"; the 5G twin synchronizes "GTP-U protocol tunnel packet loss rate" and "S1AP protocol signaling delay", to realize virtual-real mapping of protocol layer state. Interface development and scenario testing for multi-protocol integration: Add a protocol conversion gateway at the interface layer: the northbound interface supports the transmission of OPCUA / MQTT protocol data of the photovoltaic twin to the 5G twin through the HTTP / 2 protocol, and the southbound interface converts the GTP-U protocol data of the 5G twin into Modbus protocol instructions recognizable by photovoltaic devices; Scene testing strengthens multi-protocol collaboration verification: Simulate "OPCUA control instructions and MQTT data concurrent transmission in the same base station", verify the protocol isolation of the slice (control instruction delay ≤10ms, data delay ≤50ms, no mutual interference); simulate "protocol switching scenarios" (such as inverter switching from OPCUA to backup MQTT protocol), verify the dynamic adaptation capability of the 5G twin (switching delay ≤50ms, business uninterrupted).Protocol optimization in physical linkage iteration: based on the simulation results of the two-dimensional twin, the protocol adaptation strategy is issued to the physical system: for photovoltaic equipment: when the network is congested, automatically switch the transmission protocol of non-critical data from OPCUA to MQTT (reduce bandwidth occupancy by 30%); for 5G network: configure "OPCUA protocol dedicated time slot" for URLLC slice to reduce protocol parsing delay (from 5ms to 3ms).

[0033] The regulation slice scheme determination module determines the slice regulation evaluation value of each dedicated slice scheme based on the two-dimensional twin, and marks the dedicated slice scheme with the maximum slice regulation evaluation value as the regulation slice scheme. The original regulation demand of the distributed photovoltaic power station is sliced and transmitted according to the regulation slice scheme.

[0034] The determination step of the slice regulation evaluation value of the dedicated slice scheme: select a dedicated slice scheme, import the dedicated slice contained in the dedicated slice scheme into the two-dimensional twin for simulation, the two-dimensional twin simulates the transmission process of the dedicated slice, after the transmission is completed, the business compliance value, the network protocol layer adaptation value and the resource efficiency value are obtained, and the business compliance value, the network protocol layer adaptation value and the resource efficiency value are weighted and summed to calculate the slice regulation evaluation value of the dedicated slice scheme.

[0035] The acquisition step of the business compliance value: after the transmission is completed, the time delay of each data packet in the transmission process is collected, the time delay of each data packet is averaged, the average time delay ave T，delay is calculated, and the broadband fluctuation rate vol broad of the entire transmission process is obtained, and the business compliance value Busnco (dimensionless calculation) is calculated through , wherein yg1 is the time delay compensation coefficient, yg2 is the broadband fluctuation coefficient, the time delay compensation coefficient can be 0.6, the broadband fluctuation coefficient can be 0.4, T0 is the preset maximum allowed average time delay, such as 30ms, and V0 is the preset maximum allowed bandwidth fluctuation rate, such as 15%.

[0036] The acquisition step of the network protocol layer adaptation value: after the transmission is completed, the parsing failure rate of the data packet in the transmission process is determined (such as 10000 data packets in the two-dimensional twin, of which 5 times are parsed, then the parsing failure rate = 0.05%), the total time consumption of OPCUA protocol conversion to 5G protocol is measured , and the network protocol layer adaptation value is calculated through , wherein yg3 is the parsing failure coefficient, yg4 is the protocol conversion time consumption coefficient, the parsing failure coefficient can be 0.7, the protocol conversion time consumption coefficient can be 0.3, , and the maximum allowed parsing failure rate is 1% (such as 0.01, and if it exceeds, it is taken as 1). The maximum conversion time allowed (e.g. 200us, 1 if exceeded).

[0037] Resource efficiency value acquisition step: after transmission, determine the average PRB occupancy Data collection: real-time monitoring of gNB1 PRB occupancy (sampled every 10ms) by base station simulation module, average PRB occupancy is the ratio of allocated PRB number to total PRB number) and elastic broadband response time (time difference from service bandwidth demand change event trigger to network slice actual completion of bandwidth adjustment and stabilization, including three key stages: demand trigger stage: traffic surge / drop or SLA threshold reached; resource scheduling stage: slice management system starts bandwidth adjustment strategy (such as expansion / contraction); adjustment completion stage: new bandwidth configuration takes effect and transmission performance is stable), according to the average PRB occupancy determine ; , according to the elastic broadband response time determine , , through calculate the resource efficiency value, wherein PRB occupancy coefficient, elastic broadband response coefficient, PRB occupancy coefficient can be 0.6, and elastic broadband response coefficient can be 0.4.

[0039] The above system deeply integrates 5G network capabilities and distributed photovoltaic business demand, realizes unified access of multiple protocols such as OPCUA and MQTT and intelligent scheduling of network side protocols through intelligent analysis and regulation of control intent and customization of multi-dimensional special slices, resolves heterogeneous adaptation and scene conflict risks in advance through double-dimensional twin simulation of protocol interaction and resource scheduling whole process, and promotes precise cooperation between business demand and network capability. Based on the quantitative evaluation mechanism of double-dimensional twin, the system constructs a scientific decision-making system, realizes the optimal selection of special slice scheme through the weighted analysis of business compliance, protocol adaptability, resource efficiency and other multi-dimensional indicators. This not only improves the utilization efficiency and elastic response capability of network resources, but also relies on physical isolation and logical isolation technology to strengthen the security protection level of the system, and finally forms a complete closed loop of "demand analysis-simulation verification-decision optimization-security protection", providing an intelligent regulation mode of precise adaptation, efficient cooperation and safe and reliable for distributed photovoltaic power stations.

[0040] The above formulas are dimensionless to calculate their numerical values, and the preset parameters in the formulas are set by those skilled in the art according to actual conditions.

[0041] The above-described embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, the above-described embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center through a wired or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. containing one or more available medium collections. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0042] It should be understood that the size of the sequence number of each process described above in various embodiments of the present application does not mean the order of execution, and the execution order of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0043] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be realized in electronic hardware, or a combination of computer software and electronic hardware. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0044] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0045] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. For example, the division of the above-described device embodiments is only a logical function division, and there can be another division manner for actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, or the among different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0046] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, and various other media that can store program codes.

[0047] The above describes only the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A distributed photovoltaic power station intelligent regulation and control system based on 5G multi-protocol fusion, characterized in that, Comprising The regulation intention analysis module analyzes the structured regulation intention in real time according to the original regulation demand of the distributed photovoltaic power station; The intention slice creation module determines a plurality of special slice schemes according to different dimensions, and determines the special slices contained in each special slice scheme; The dual-dimension twin body building module builds a dual-dimension twin body based on the distributed photovoltaic power station and the 5G network infrastructure; The regulation slice scheme determination module selects a regulation slice scheme from the special slice schemes based on the dual-dimension twin body, slices the original regulation demand of the distributed photovoltaic power station according to the regulation slice scheme, and transmits the original regulation demand. 2.The 5G multi-protocol fusion-based distributed photovoltaic power station intelligent regulation and control system according to claim 1, characterized in that, The building steps of the dual-dimension twin body are as follows: S1: collecting multi-protocol data on the photovoltaic power station side and the 5G network side; S2: respectively constructing photovoltaic power station twin body and 5G network twin body; S3: establishing cross-dimension real-time interaction and correlation mapping to build a dual-dimension twin body. 3.The 5G multi-protocol fusion-based distributed photovoltaic power station intelligent regulation and control system according to claim 2, characterized in that, Multi-protocol data acquisition on the photovoltaic power station side: photovoltaic equipment transmits data using diversified industrial protocols, and needs to realize unified access through the protocol conversion gateway of the edge computing node: group string inverter and energy storage system transmit high-precision control instructions through OPCUA protocol; The current box and the environmental sensor transmit periodic state data through the MQTT protocol; the old equipment transmits data through the ModbusRTU protocol, and is connected to the system after being converted by the ECU into MQTT / OPCUA, the collection frequency remains the original standard, and is uniformly packaged into Protobuf format through the protocol gateway, with the addition of device identification and protocol type tags.

4. The 5G multi-protocol fusion-based distributed photovoltaic power station intelligent regulation and control system according to claim 2, characterized in that, Multi-protocol data acquisition on the 5G network side: 5G network involves control plane, user plane and multi-protocol, which needs to extract key data through the protocol analysis module of the core network and the edge node: control plane: through S1AP protocol, the connection state of base station gNB and core network is collected, and through N11 protocol, the policy interaction information of PCF and SMF is obtained; User plane: through GTP-U protocol, the forwarding path and traffic characteristics of the slice service are collected, and through HTTP / 2 protocol, the AI inference result of the edge node is received; Management plane: through NetConf protocol, the base station resources are configured, and through SNMP protocol, the device alarm is collected. 5.The 5G multi-protocol fusion-based distributed photovoltaic power station intelligent regulation and control system of claim 1, wherein, Selection of the regulation slice scheme from the special slice schemes based on the dual-dimension twin body: based on the dual-dimension twin body, the slice regulation evaluation value of each special slice scheme is determined, and the special slice scheme with the maximum slice regulation evaluation value is marked as the regulation slice scheme. 6.The 5G multi-protocol fusion-based distributed photovoltaic power station intelligent regulation and control system of claim 5, characterized in that, The determination steps of the slice regulation evaluation value of the special slice scheme: select a special slice scheme, import the special slices contained in the special slice scheme into the dual-dimension twin body for simulation, the dual-dimension twin body simulates the transmission process of the special slice, after the transmission is completed, the business compliance value, the network protocol layer adaptation value and the resource efficiency value are obtained, the business compliance value, the network protocol layer adaptation value and the resource efficiency value are weighted and summed, and the slice regulation evaluation value of the special slice scheme is calculated. 7.The 5G multi-protocol converged-based distributed photovoltaic power station intelligent regulation and control system according to claim 6, characterized in that, The service target value obtaining step: after the transmission, the time delay of each data packet in the transmission process is collected, the time delay of each data packet is summed and averaged, the average time delay is calculated, the broadband fluctuation rate of the whole transmission process is obtained, and the service target value is calculated based on the average time delay and the broadband fluctuation rate. 8.The 5G multi-protocol fusion-based distributed photovoltaic power station intelligent regulation and control system according to claim 6, characterized in that, The network protocol layer adaptation value obtaining step: after the transmission, determining the parsing failure rate Rate of the data packet in the transmission process fail , measuring the total time TP of converting the OPCUA protocol into the 5G protocol 5G , calculating the network protocol layer adaptation value based on the parsing failure rate and the total time. 9.The 5G multi-protocol converged based distributed photovoltaic power station intelligent regulation and control system of claim 6, wherein, Resource efficiency value obtaining step: after the transmission, determining the average PRB occupancy Elastic wideband response time , according to the average PRB occupancy Determination , , according to the elastic wideband response time Determination , , by Calculate the resource efficiency value, wherein, PRB occupancy coefficient, Elastic wideband response coefficient.

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