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CN-121440679-B - Cluster type ordered charge and discharge management system based on LoRa (loRa) Internet of things

CN121440679BCN 121440679 BCN121440679 BCN 121440679BCN-121440679-B

Abstract

The invention discloses a clustered ordered charge and discharge management system based on the LoRa Internet of things, which relates to the technical field of power system management and is used for solving the problems of realizing accurate state sensing and optimal scheduling of a clustered charge and discharge system under the condition that communication of the LoRa Internet of things is limited, keeping key states under the conditions of failure report and time delay continuously available by establishing a belief state of consistency check and time sequence tracking, forming a power instruction sequence in a rolling time domain based on the state, obtaining information value density through objective function sensitivity, organizing reporting collection and time stamp arrangement according to priority, leading key information in a limited air port to reach and be aligned with an instruction in a period, triggering local deviation correction to limit an adjustment range and quickly converge errors when the difference between observation and prediction is increased, and writing back a record and an index to the next period, so that estimation and instruction can be tracked and executed in a cross period.

Inventors

  • SUN YUEFENG
  • ZHANG MENG
  • LIU KANGKANG

Assignees

  • 特易充新能源(上海)有限公司

Dates

Publication Date
20260508
Application Date
20251103

Claims (10)

  1. 1. Clustered ordered charge and discharge management system based on LoRa thing networking, characterized by comprising: The belief state representation and update module 102 is configured to obtain a record of reporting and not reporting of a node, a period instruction and a time stamp, calculate a state mean value, a covariance and a period, advance a boundary according to a failure report, maintain a time sequence index and a failure report count, form the belief state set, and output the belief state set; The robust group optimization module 103 is used for acquiring the belief state set, the station-level power targets and the operation constraint, constructing rolling time domain optimization, solving the power instruction sequence of each node, extracting the sensitivity abstract of the objective function to the state and the instruction disturbance, and generating the power instruction in the current period; The information value evaluation module 104 is configured to obtain the sensitivity abstract, the communication quality index and the link parameter, calculate the information value density of each node, form a priority ordering and reporting set definition, and generate a reporting timestamp requirement and a node selection list for use in communication scheduling; And the communication compliance scheduling module 105 is used for acquiring the sequence, the reporting set and the air interface time budget, distributing node reporting time stamps according to a duty ratio and a time division access rule, generating a time stamp table, and packaging the time stamp table and a power instruction into a downlink message and sending the downlink message to the gateway.
  2. 2. The clustered ordered charge and discharge management system based on the LoRa internet of things of claim 1, wherein: the belief state representation and update module 102 updates the state mean and covariance by unscented kalman filtering for successfully reported nodes, advances the upper and lower boundaries by interval observation for unreported nodes and increments the reporting-missing count, maintains the timestamp index and writes back the belief state set, and establishes the measurement source label and quality label and data source description for subsequent referencing.
  3. 3. The clustered ordered charge and discharge management system based on LoRa Internet of things of claim 2 wherein said belief state representation and update module 102 performs sliding window trending and robust filtering and retracts out-of-range interval boundaries according to historical boundaries when processing voltage, current and temperature samples, performs proportional expansion on covariance main diagonal elements and synchronously updates said ischemia counts while setting anomaly observation suppression markers and alternate observation source entries and maintaining consistency with said timing index.
  4. 4. The clustered ordered charge and discharge management system based on the LoRa internet of things of claim 1, wherein the system is characterized in that; The robust population optimization module 103 builds rolling time domain optimization in a control period and a prediction time domain, applies node power upper and lower bounds and change rate constraint, obtains a power instruction sequence and only issues a current period instruction, uses the rest sequence for the next period initialization, records a constraint active set, a solving state code and an operation constraint list for subsequent reference, and builds a corresponding relation with the time sequence index.
  5. 5. The clustered ordered charge and discharge management system based on the LoRa internet of things of claim 4, wherein: The robust population optimization module 103 calculates the increment of the objective function to form a sensitivity vector arranged according to node indexes by reading dual variables or applying micro disturbance to states and instructions, compresses and generates the sensitivity abstract containing node identifiers and period sequence number fields for the information value evaluation module to use, encapsulates the sensitivity abstract into a structural description according to the module interface convention, and adds a version tag to support cross-period calling.
  6. 6. The clustered ordered charge and discharge management system based on the LoRa internet of things of claim 1, wherein the information value evaluation module 104 calculates an information value density according to the sensitivity abstract and the link parameter, wherein the information value density is a normalized quantity of an objective function increment relative to a single packet air interface time, generates a priority ordering and reporting set, outputs a timestamp requirement and a packet number requirement corresponding to a node, generates a reporting subset of channel resource groups, and persists the priority ordering and reporting set snapshot for a communication compliance scheduling module to read.
  7. 7. The clustered ordered charge and discharge management system based on the LoRa internet of things according to claim 6, wherein the communication compliance scheduling module 105 distributes non-overlapping reporting time stamps for the reporting set under the limitation of duty cycle and regional parameters to form a time stamp table containing node identifiers, time stamps, sequence numbers and validity periods, packages the time stamp table and power instructions into a downlink message, sends the downlink message to a gateway, and generates synchronization offset and check values of a gateway clock, writes a message header according to interface convention, and ensures that the time stamps are consistent with the node address mapping relationship.
  8. 8. The clustered ordered charge and discharge management system based on the LoRa internet of things according to claim 1, further comprising a fast local deviation rectifying module 106, wherein the fast local deviation rectifying module 106 is started when the residual error exceeds a threshold value, a small-scale quadratic programming is constructed in a current period and a subsequent limited period, a single node power adjustment amplitude and an adjacent period change rate are constrained, a small number of nodes are selected according to a preset upper limit to generate a correction instruction, the gateway is submitted, and a correction version label and a target set selection basis are recorded for reading of a next period audit record and the belief state representation and updating module.
  9. 9. The clustered ordered charge and discharge management system based on the LoRa Internet of things according to claim 4, wherein the power instruction issuing message comprises a node address field, a power instruction field, a time stamp field and a check field, the uplink reporting message comprises a measured value, a missing report count and a version number field, the message field sequence is analyzed uniformly by the gateway and corresponds to the link parameter, and a message header carries an area parameter and a spread spectrum factor indication for joint analysis and use of the communication compliance scheduling module and the information value evaluation module.
  10. 10. The clustered ordered charge and discharge management system based on the LoRa internet of things of claim 7, wherein the communication compliance scheduling module 105 maintains a transmission and retransmission queue, a retransmission interval is determined by a gateway policy, a transmission item which is not confirmed by a timeout is transferred to the retransmission queue, an expiration time stamp is cleared at the end of a control period, a retransmission sequence number and a confirmation state are recorded for the next period scheduling, and a snapshot and a selection result of a time stamp table are updated and output to the belief state representation and update module.

Description

Cluster type ordered charge and discharge management system based on LoRa (loRa) Internet of things Technical Field The invention relates to the technical field of power system management, in particular to a clustered ordered charge and discharge management system based on LoRa (loRa) internet of things. Background With the popularization of electric vehicles and distributed energy storage devices, the scale of a clustered charge and discharge system in a power distribution network is continuously expanded. Such systems typically contain tens to hundreds of charge and discharge nodes, requiring coordinated control over a communication network. However, three main technical problems are faced in actual operation, namely firstly, unavoidable data packet loss and transmission delay exist in a wireless communication network, particularly in the low-power-consumption wide-area internet of things such as LoRa, uncertainty of a node reporting state can cause deviation of a scheduling system on cognition of an actual state of the cluster, secondly, response delay exists in an executing mechanism of charging and discharging equipment, equipment parameters (such as internal resistance and efficiency) can change along with temperature and aging degree, difficulty of state observation is further increased, finally, a traditional scheduling method is either assumed to be perfect communication and optimistic, or extremely conservative strategies are adopted to sacrifice economy, and safety and economy balance is difficult to realize under the condition of limited communication. In the prior art, some schemes reduce uncertainty by increasing reporting frequency, but the method can obviously increase communication burden and node energy consumption and even violate duty ratio limit of the LoRa network, some schemes process missing data by adopting a simple weighted average or filtering method, but the state estimation is possibly deviated from a practical feasible domain due to insufficient utilization of a conservation relation of a physical side, and other schemes adopt fully-conservative robust optimization, but often a scheduling strategy which is too conservative and poor in economy is obtained because an uncertainty set is too loose. The present invention proposes a solution to the above-mentioned problems. Disclosure of Invention In order to overcome the defects in the prior art, the embodiment of the invention provides a clustered ordered charge and discharge management system based on the LoRa Internet of things, which aims to solve the problems in the background art. In order to achieve the above purpose, the present invention provides the following technical solutions: clustered ordered charge and discharge management system based on LoRa thing networking includes: The belief state representation and update module 102 is configured to obtain a record of reporting and not reporting of a node, a period instruction and a time stamp, calculate a state mean value, a covariance and a period, advance a boundary according to a failure report, maintain a time sequence index and a failure report count, form the belief state set, and output the belief state set; The robust group optimization module 103 is used for acquiring the belief state set, the station-level power targets and the operation constraint, constructing rolling time domain optimization, solving the power instruction sequence of each node, extracting the sensitivity abstract of the objective function to the state and the instruction disturbance, and generating the power instruction in the current period; The information value evaluation module 104 is configured to obtain the sensitivity abstract, the communication quality index and the link parameter, calculate the information value density of each node, form a priority ordering and reporting set definition, and generate a reporting timestamp requirement and a node selection list for use in communication scheduling; And the communication compliance scheduling module 105 is used for acquiring the sequence, the reporting set and the air interface time budget, distributing node reporting time stamps according to a duty ratio and a time division access rule, generating a time stamp table, and packaging the time stamp table and a power instruction into a downlink message and sending the downlink message to the gateway. In a preferred embodiment, the belief state representation and update module 102 updates the state mean and covariance using unscented Kalman filtering for successfully reported nodes, advances the upper and lower boundaries using interval observations for unreported nodes and increments the reporting missing count, maintains a timestamp index and writes back to the belief state set, and builds measurement source tags and quality labels and data source descriptions for subsequent referencing. In a preferred embodiment, the belief state representation and update module 102 performs sliding window tr