Energy storage cabinet energy scheduling method and system for multi-scene grid connection

Abstract

The application discloses an energy scheduling method and system for energy storage cabinets in multi-scene grid connection, relates to the technical field of energy storage cabinet energy scheduling, and aims to improve the safety and operation efficiency of the energy storage cabinet in a complex network environment, establishes a trusted communication foundation through a hardware trust root holding mechanism, ensures the authenticity of the equipment identity, adopts safe channel transmission and a distributed log account book to guarantee the traceability of instructions, introduces an instruction credibility evaluation mechanism to judge the reliability of the instructions in real time, effectively suppresses the risks on the network side and the physical side, dynamically optimizes power output through a fine scheduling strategy, balances power grid demand and equipment safety, and in the case of abnormal conditions, implements capacity reduction operation and abnormal record to improve the fault tolerance and traceability of the system. Through the synergistic effect of the multi-level technical features, the safety and stability of the energy storage cabinet in multi-scene grid connection are improved, and a solid guarantee is provided for the reliable operation of the power grid.

Description

Technical Field

[0001] This invention relates to the field of energy dispatching technology for energy storage cabinets, specifically to energy dispatching methods and systems for energy storage cabinets in multiple grid-connected scenarios. Background Technology

[0002] In multi-scenario grid-connected applications, energy storage cabinets maintain real-time interconnection with the dispatch center through public cellular networks and virtual private networks. They must respond quickly to fluctuations in photovoltaic and wind power, and undertake multiple functions such as peak shaving, reactive power support, and black start. However, existing power distribution systems generally use traditional power dispatch communication architectures, lacking dedicated protection layers and end-to-end identity verification mechanisms for energy storage scenarios. Manufacturers and system integrators are beginning to include sections on network security and collaborative design of dispatch algorithms in their product roadmaps, responding to the industry's growing concern about the rapidly increasing risks associated with energy storage communication. Meanwhile, recent reports from Reuters and other media outlets have revealed that some inverters and energy storage devices have built-in, undisclosed communication modules that can bypass firewalls and directly take over power interfaces, prompting joint investigations by regulatory authorities in various countries into the trustworthiness of the supply chain.

[0003] The technical problem exposed in the above context is that the protection of the remote energy dispatch link is insufficient, which makes the dispatch instructions easy to be intercepted, forged or delayed during transmission, resulting in the energy storage cabinet being unable to accurately execute the multi-scenario grid-connected dispatch strategy.

[0004] The cause lies in the fact that current communication paths mostly rely on open networks and lack end-to-end authentication and integrity verification. Attackers can inject malicious gateways, modify firmware, or use hidden communication channels to insert illegal commands, thereby causing deviations in power curves, reactive power support, or status reporting. Once the commands are distorted, the energy storage cabinet will experience disordered charging and discharging rhythms, state estimation drift, and concentrated heat load, thus undermining peak shaving and frequency support effects. If the dispatch center loses control due to denial of service, it may trigger the energy storage cabinet to enter islanding protection or be forced to disconnect from the grid, resulting in decreased grid connection stability and economic losses.

[0005] Therefore, this invention provides an energy scheduling method and system for energy storage cabinets oriented towards multi-scenario grid connection. Summary of the Invention

[0006] (a) Technical problems to be solved

[0007] To address the shortcomings of existing technologies, this invention provides an energy scheduling method and system for energy storage cabinets in multiple grid-connected scenarios. It deeply integrates communication security with scheduling optimization, and through trusted identity authentication, chain event logging, and local fault tolerance strategies, it ensures that scheduling commands remain accurate, timely, and traceable in complex network environments. This fundamentally eliminates the scheduling distortion and coordination instability risks caused by remote links, and solves the technical problems described in the background section.

[0008] (II) Technical Solution

[0009] To achieve the above objectives, the present invention provides the following technical solution:

[0010] Energy dispatching methods for energy storage cabinets in multiple grid-connected scenarios include,

[0011] A handshake is completed between the energy storage cabinet, dispatch center and power converter through hardware trust root, a unique trust root identifier is generated and the chain instruction index is initialized synchronously, and the session key is derived based on the trust root identifier.

[0012] The dispatch center packages the power requirements of multiple scenarios into encrypted messages carrying scenario tags based on the chained instruction index, sends them through a secure channel, and synchronously writes them into the distributed log ledger.

[0013] The command credibility coefficient is generated by combining the overall envelope difference between the actual power output and the predicted curve and the characteristics of the cell temperature rise rate. The command is then released or derating is initiated based on the credibility coefficient.

[0014] For released instructions, the scenario weight is calculated based on real-time state of charge, temperature information and chain instruction index, the final power scheduling vector is output, and the execution receipt hash is appended to the distributed log ledger.

[0015] When the instruction reliability coefficient is lower than the threshold or communication times out, the system will implement step-by-step de-capacity operation according to the most recent effective power scheduling vector and in combination with the charge prediction curve.

[0016] Furthermore, the energy storage cabinet, dispatch center, and power converter each execute a handshake protocol through the hardware trust root module to mutually verify the device identity credentials;

[0017] A temporary session key is generated through negotiation using asymmetric encryption technology. After the handshake protocol is completed, the public key of the energy storage cabinet, the public key of the dispatch center, and the public key of the power converter are concatenated and a root trust identifier is generated through a secure hash algorithm.

[0018] Furthermore, the scheduling center generates and maintains a chained instruction index, with the initial value being the current timestamp, which increments with each instruction; based on the root trust identifier and the chained instruction index, a session key is generated through a key derivation function;

[0019] The communication messages are symmetrically encrypted using a session key to ensure confidentiality, and a digital signature is generated to verify integrity and sender identity.

[0020] Furthermore, the dispatch center packages the power requirements of multiple scenarios into instruction content, which is organized using JSON object format. The instruction content includes scenario tags, power requirement values, timestamps, and chained instruction indexes.

[0021] The dispatch center uses the session key to perform symmetric encryption on the instruction content, generating encrypted instruction content and a digital signature.

[0022] Furthermore, the dispatch center combines the encrypted instruction content, initialization vector, and digital signature into an encrypted message, which is then transmitted to the energy storage cabinet.

[0023] Encrypted messages, chained instruction indexes, and timestamps are written to a distributed log ledger to ensure the non-repudiation and temporal consistency of instructions.

[0024] Furthermore, the energy storage cabinet uses the session key to decrypt the received message and verify the validity of the digital signature, extracts the instruction content contained in the message, and checks the timeliness of the instruction.

[0025] Calculate the envelope difference between the actual generated power and the predicted power curve, and monitor the temperature rise rate of the cells in the energy storage cabinet;

[0026] The command reliability coefficient is calculated by combining the envelope difference and the temperature rise rate. Based on the command reliability coefficient, it is determined whether the command should be released or a derating operation should be triggered.

[0027] Furthermore, the energy storage cabinet acquires real-time state of charge, cell temperature, scenario tags, and chain command index; and calculates scenario weights based on the real-time state of charge, cell temperature, and chain command index.

[0028] Furthermore, a final power scheduling vector is generated based on the scenario weights and the power demand values ​​in the instructions;

[0029] The final power scheduling vector is executed to adjust the output power and generate an execution receipt. The execution receipt is then hashed and the hash value is written to the distributed log ledger.

[0030] Furthermore, the energy storage cabinet monitors the command reliability coefficient and communication status in real time, and detects abnormal situations, including retrieving the most recent effective power scheduling vector from the distributed log ledger;

[0031] A charge prediction curve is generated based on historical state of charge data and a pre-set charge prediction model, and derating is implemented based on the duration of the anomaly and the charge prediction curve.

[0032] Perform de-capacity operation and record abnormal events to a distributed log ledger, continuously monitor communication status and command reliability, and wait for recovery from abnormal situations.

[0033] An energy dispatching system for energy storage cabinets designed for multi-scenario grid connection includes,

[0034] The identity authentication module completes a handshake between the energy storage cabinet, dispatch center and power converter through hardware trust root, generates a unique trust root identifier and synchronously initializes the chain instruction index, and derives the session key based on the trust root identifier.

[0035] In the instruction generation module, the scheduling center packages the power requirements of multiple scenarios into encrypted messages carrying scenario tags based on the chained instruction index, sends them through a secure channel, and synchronously writes them into the distributed log ledger.

[0036] The instruction evaluation module combines the overall envelope difference between the actual power output and the predicted curve, as well as the characteristics of the cell temperature rise rate, to generate an instruction credibility coefficient. Based on the credibility coefficient, it determines whether to release the instruction or initiate derating.

[0037] The scheduling and execution module calculates the scenario weights for released instructions based on real-time state of charge, temperature information, and chained instruction indexes, outputs the final power scheduling vector, and appends the execution receipt hash to the distributed log ledger.

[0038] The exception handling module implements step-by-step de-capacity operation according to the most recent effective power scheduling vector and in combination with the charge prediction curve when the instruction credibility coefficient is lower than the threshold or the communication times out.

[0039] (III) Beneficial Effects

[0040] This invention provides an energy dispatching method and system for energy storage cabinets oriented towards multi-scenario grid connection, which has the following beneficial effects:

[0041] The introduced hardware root of trust handshake mechanism ensures the authenticity of device identities and the security of communication data. Through the hardware root of trust module, the energy storage cabinet, dispatch center, and power converter complete identity verification and session key derivation during the communication initialization phase, eliminating the risk of device forgery and communication tampering from the source.

[0042] The coordinated application of secure channels and a distributed ledger ensures the security and traceability of command transmission. The dispatch center packages power requirements from multiple scenarios into encrypted messages and transmits them through secure channels, effectively preventing interception and tampering of commands during transmission. Simultaneously, the distributed ledger records commands and execution results, ensuring data immutability and temporal consistency.

[0043] The energy storage cabinet generates a command credibility coefficient by integrating abnormal indicators from both the network and physical sides, enabling real-time assessment of command reliability. This effectively identifies and suppresses abnormal commands from the network side, provides timely warnings of potential risks on the physical side, and ensures the safety and reliability of command execution.

[0044] The energy storage cabinet integrates real-time operating status and scenario characteristics to generate a final power dispatch vector, achieving a dynamic balance between grid demand and equipment safety. Relying on the command credibility assessment in step three, the accuracy and security of command execution are ensured. Recording the execution results provides data support for subsequent anomaly handling, improving the operational efficiency of the energy storage cabinet in multi-scenario grid connection.

[0045] When an anomaly is detected, the energy storage cabinet reduces its capacity based on the real-time status to avoid the risk of equipment malfunction and grid interruption. Anomalies are recorded through a distributed ledger, providing a reliable basis for post-event analysis and rapid recovery. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the energy dispatching method for energy storage cabinets in multiple grid-connected scenarios according to the present invention;

[0047] Figure 2 This is a schematic diagram of the energy dispatching system structure of the energy storage cabinet for multi-scenario grid connection according to the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] Please see Figure 1 This invention provides an energy scheduling method for energy storage cabinets oriented towards multi-scenario grid connection, including:

[0050] Step 1: The energy storage cabinet, dispatch center, and power converter execute a handshake protocol through the hardware root of trust module to mutually verify device identity credentials and negotiate and generate a temporary session key using asymmetric encryption technology. After the handshake protocol is completed, the public keys of the energy storage cabinet, dispatch center, and power converter are concatenated and generated into a root of trust identifier using a secure hash algorithm. The dispatch center generates and maintains a chained instruction index, with the initial value being the current timestamp, represented by a Unix timestamp in milliseconds, and incrementing with each instruction. Based on the root of trust identifier and the chained instruction index, a session key is generated through a key derivation function for encrypting and signing communication messages. The communication messages are symmetrically encrypted using the session key to ensure confidentiality, and a digital signature is generated to verify integrity and sender identity.

[0051] Step one includes the following:

[0052] Step 101: Verify device identity through the hardware root trust handshake mechanism.

[0053] First, a hardware root-of-trust handshake mechanism ensures the authenticity of the identities of the energy storage cabinet, dispatch center, and power converter. Each of these three devices is equipped with a hardware root-of-trust module, such as a Trusted Platform Module (TPM), to generate a unique public key and digital certificate for each device. During the communication initialization phase, the three devices use their hardware root-of-trust modules to execute a handshake protocol, mutually verifying each other's credentials. During the handshake, asymmetric encryption technology is used to negotiate and generate a temporary session key. Specifically, the energy storage cabinet generates a pair of temporary public and private keys and sends the public key to the dispatch center; after verifying the energy storage cabinet's public key and digital certificate, the dispatch center generates its own temporary public and private keys, encrypts its temporary public key using the energy storage cabinet's public key, and sends it back; the energy storage cabinet decrypts the temporary public key using its private key to obtain the dispatch center's temporary public key, and then both parties negotiate and generate a temporary session key based on their respective temporary public keys. The power converter performs the same process with both the dispatch center and the energy storage cabinet, ultimately sharing a single temporary session key.

[0054] The public key and digital certificate provided by the hardware root trust module can verify the authenticity of the device and prevent counterfeit devices from accessing the communication network. Asymmetric encryption technology is used to negotiate temporary session keys, avoiding direct key transmission and ensuring the security of the negotiation process, thus effectively resisting man-in-the-middle attacks.

[0055] Step 102: Generate the root trust identifier

[0056] After the handshake is completed, step one generates a root trust identifier (TRID). The root trust identifier is obtained by concatenating the public keys of the energy storage cabinet, dispatch center, and power converter in a predetermined order and then applying a secure hash algorithm (such as SHA-256) to calculate the hash value. This root trust identifier serves as a trusted foundational identifier for the communication link between the three parties, ensuring the uniqueness and consistency of device identities.

[0057] The public key serves as a unique credential for each device's identity. By concatenating the public keys from three parties and calculating their hash values, a unique identifier can be generated that is bound to a specific combination of devices. The root trust identifier reflects the trust relationship between the three parties, providing a reliable basis for authentication and key generation in subsequent communications.

[0058] Step 103: Initialize the chained instruction index

[0059] Step 1 initializes the Chained Instruction Index (CII). The CII is generated and maintained by the scheduling center, and its initial value is set to the current timestamp, represented by a Unix timestamp in milliseconds. The scheduling center increments the CII value each time an instruction is issued to ensure the timing and uniqueness of the instructions.

[0060] The timestamp is used as the initial value for the chained instruction index and updated incrementally to ensure that each instruction has a unique identifier while preserving the order in which instructions are issued. This design prevents instructions from being reused (i.e., replay attacks) and guarantees the timing consistency of scheduling instructions across multiple devices.

[0061] Step 104: Derive Session Key

[0062] Next, step one derives the session key (SK) based on the root of trust identifier and the chained instruction index. The session key is generated using a key derivation function (e.g., HKDF), with input parameters including the root of trust identifier and the chained instruction index. The session key is used for encryption and signing of subsequent communication messages. Each time the chained instruction index is updated, the session key is re-derived based on the new index to maintain key dynamism. Using the root of trust identifier and the chained instruction index as input ensures that the session key is associated with a specific device combination and instruction sequence, improving key exclusivity and security. Using a standard key derivation function to generate a high-strength key guarantees the reliability of encryption. Dynamic updates to the session key avoid security risks that may result from long-term key use, enhancing the communication's resistance to attacks.

[0063] Step 105: Encrypt and sign the communication message.

[0064] Finally, subsequent communication messages are encrypted and signed using the session key. The messages are encrypted using a symmetric encryption algorithm (e.g., AES-GCM) with the session key to ensure the confidentiality of the content. At the same time, a digital signature (e.g., HMAC-SHA256) is generated using the session key to verify the integrity of the messages and the legitimacy of the sender.

[0065] Symmetric encryption algorithms protect message content, preventing unauthorized parties from reading the data and thus ensuring the confidentiality of instructions. Digital signatures verify that messages have not been tampered with and confirm the sender's identity, preventing messages from being forged or modified during transmission and ensuring that scheduling instructions can be executed accurately and securely.

[0066] In practice, step one establishes a trusted communication link based on a hardware root of trust between the energy storage cabinet, the dispatch center, and the power converter, ensuring the trustworthiness of the device identities and the security of communication data. This design provides a solid guarantee for the reliable operation of the entire energy dispatch system, while effectively addressing potential security threats.

[0067] Step 2: The dispatch center packages the power demands from multiple scenarios into instruction content, organized using JSON object format. The instruction content includes scenario tags, power demand values, timestamps, and chained instruction indexes. The dispatch center uses a session key to perform symmetric encryption on the instruction content, generating encrypted instruction content and a digital signature. The dispatch center combines the encrypted instruction content, initialization vector, and digital signature into an encrypted message. The dispatch center transmits the encrypted message to the energy storage cabinet through a secure channel conforming to the IEC61850-TLS standard. The dispatch center writes the encrypted message, chained instruction index, and timestamp into a distributed log ledger to ensure the non-repudiation and timing consistency of the instructions.

[0068] Step two includes the following:

[0069] Step 201: The dispatch center packages the power requirements for multiple scenarios and formats them into JSON objects.

[0070] The dispatch center integrates power demands from multiple scenarios into a unified data packet, called the instruction content. The instruction content is organized using a JSON object format and specifically includes the following fields:

[0071] Scenario tags identify the specific scenario to which the power demand belongs; power demand value represents the amount of electrical energy required in that scenario; timestamp records the generation time of the instruction content; and chained instruction index serves as a unique identifier for the instruction content. The dispatch center obtains power demand information from multiple scenarios through the data collection system, and then fills in the corresponding fields one by one according to a predefined JSON object structure to form the complete instruction content.

[0072] Using JSON object format allows for structured organization of instruction content, facilitating subsequent parsing and processing and improving data processing efficiency. Scenario tags clearly distinguish power requirements under different scenarios, ensuring that the energy storage cabinet can accurately execute corresponding energy dispatch operations based on specific scenarios. Timestamps record the generation time of the instruction content, facilitating system timing management and anomaly detection, such as identifying expired instructions. A chained instruction index, serving as a unique identifier, ensures the traceability of each instruction within the system and maintains the temporal order of instructions, preventing confusion or duplicate execution.

[0073] Step 202: The dispatch center encrypts the instruction content using the session key.

[0074] The dispatch center uses a session key to encrypt the instruction content. The session key is a temporary key negotiated in step one, possessing uniqueness and time expiration. The encryption process employs a symmetric encryption algorithm, such as the Galois counter mode in the Advanced Encryption Standard (AES). The dispatch center takes the plaintext data of the instruction content as input, and calculates using the session key and the symmetric encryption algorithm to generate the encrypted instruction content, i.e., the ciphertext data. An initialization vector is also generated during the encryption process as random input to enhance encryption security.

[0075] Encrypting the instruction content using a symmetric encryption algorithm effectively protects its confidentiality, preventing unauthorized third parties from reading or stealing data during transmission. The session key, generated in step one and updated periodically, offers high security and ensures the reliability of the encryption process. Only the recipient holding the same session key can decrypt the encrypted instruction content, thus guaranteeing its confidentiality during transmission and providing a safeguard for subsequent secure communication.

[0076] Step 203: The dispatch center generates a digital signature to verify the instruction content.

[0077] The scheduling center generates a digital signature for the unencrypted instruction content. The generation process uses a hash message authentication code algorithm, such as SHA256-based hash message authentication code. The scheduling center first hashes the plaintext data of the instruction content to generate a fixed-length hash value. Then, it further processes this hash value using the session key to generate the digital signature. The digital signature is bound to the instruction content and used by the subsequent recipient to verify the integrity and authenticity of the instruction content.

[0078] The generation of digital signatures verifies whether the instruction content has been tampered with during transmission and confirms that the instruction content originates from a legitimate dispatch center. The hash message authentication code algorithm, through hash calculation and key processing, ensures that even minor changes to the instruction content will result in a significantly different digital signature, thus guaranteeing integrity. Using session keys to generate digital signatures further enhances signature security, making signature forgery extremely difficult. This mechanism improves the reliability of the instruction content, ensuring that the instructions received by the energy storage cabinet are authentic and trustworthy.

[0079] Step 204: The dispatch center combines the encrypted instruction content with relevant data to form an encrypted message.

[0080] The dispatch center integrates the encrypted instruction content, initialization vector, and digital signature into a complete data packet, called an encrypted message. The process of assembling an encrypted message includes: first, obtaining the encrypted instruction content, i.e., the ciphertext data generated using a symmetric encryption algorithm; then, adding the initialization vector, which is a random value generated during the encryption process; and finally, attaching the digital signature as a verification basis. The dispatch center arranges these three parts of data sequentially according to a predefined message structure to form the encrypted message.

[0081] The structured design of the encrypted message ensures that the receiver can correctly extract the ciphertext data, initialization vector, and digital signature, thus successfully completing the decryption and verification process. The inclusion of the initialization vector provides randomness to the encryption process, effectively preventing replay attacks—that is, preventing malicious parties from reusing old messages to interfere with system operation. The inclusion of the digital signature allows the receiver to verify the validity of the message before decryption, ensuring that the instruction content has not been tampered with. This combination improves the overall security of the message and provides complete data support for subsequent transmissions.

[0082] Step 205: The dispatch center transmits encrypted messages through a secure channel.

[0083] The dispatch center transmits encrypted messages to the energy storage cabinet through a secure channel conforming to the IEC 61850-TLS standard. This secure channel is established based on a transport layer security protocol. Before transmission begins, the dispatch center and the energy storage cabinet conduct a handshake negotiation to confirm their identities and establish an encrypted communication channel. The encrypted messages are sent through this channel, and the transport layer security protocol encrypts and protects the integrity of the message data, ensuring that the data is not intercepted or modified during network transmission.

[0084] The secure channel, compliant with the IEC 61850-TLS standard, utilizes the encryption mechanisms of transport layer security protocols to ensure the confidentiality and integrity of encrypted messages during transmission, preventing eavesdropping or tampering by third parties. The handshake negotiation process verifies the identities of both communicating parties, effectively preventing man-in-the-middle attacks. The adoption of standardized protocols improves system compatibility and security, ensuring that instructions are delivered securely and reliably to the energy storage cabinet, providing communication assurance for the correct execution of energy dispatch.

[0085] The scheduling center synchronously records encrypted messages, chained instruction indexes, and timestamps into a distributed log ledger.

[0086] The distributed log ledger is implemented based on blockchain technology. The specific process is as follows: The scheduling center assembles an encrypted message, a chained instruction index, and a timestamp into a record. A hash value for this record is generated through hash calculation and linked with the hash values ​​of the previous record to form a hash chain. The record is then broadcast to multiple nodes in the distributed network, verified by the consensus mechanism, and written into the ledger to ensure the data is immutable.

[0087] Distributed log ledgers, through hash chains and blockchain technology, ensure the immutability and temporal consistency of records. Any modification to an existing record will disrupt the continuity of the hash chain and thus be detected. This mechanism enhances the credibility of instruction content, facilitating post-event auditing and anomaly tracing, such as backtracking specific instructions in the event of a scheduling error. The chained instruction index and timestamp recording further ensure the uniqueness and temporal order of instructions, enhancing the system's transparency and verifiability, and providing reliable data support for energy scheduling management across multiple scenarios.

[0088] When in use, the dispatch center enables the secure generation, transmission, and storage of power requirements across multiple scenarios.

[0089] Step 3: The energy storage cabinet uses the session key to decrypt the received message and verify the validity of the digital signature. It extracts the instruction content contained in the message and checks the timeliness of the instruction. It calculates the envelope difference between the actual power output and the predicted power curve, monitors the temperature rise rate of the cells in the energy storage cabinet, calculates the instruction credibility coefficient by combining the envelope difference and the temperature rise rate, and determines whether to allow the instruction or trigger a derating operation based on the instruction credibility coefficient.

[0090] Step three includes the following:

[0091] Step 301: Decrypt the message and verify the digital signature in the energy storage cabinet.

[0092] After receiving an encrypted message, the energy storage cabinet decrypts the message using a pre-negotiated session key.

[0093] The session key is jointly determined by the energy storage cabinet and the dispatch center when the communication connection is established, and is used to ensure the confidentiality of communication data. The decryption process uses a symmetric encryption algorithm to restore the encrypted message to readable plaintext. After decryption, the energy storage cabinet extracts the digital signature from the plaintext message and performs a hash calculation on the plaintext message content to generate a new digital signature value. Next, the energy storage cabinet compares the newly generated digital signature value with the digital signature value extracted from the message. If they match, it indicates that the message has not been tampered with during transmission and originates from a legitimate dispatch center; if they do not match, it indicates that the message may have been tampered with or forged, and the energy storage cabinet will refuse to execute the instructions in the message.

[0094] By decrypting and verifying with digital signatures, the confidentiality, integrity, and authenticity of the message content are ensured. This process effectively prevents unauthorized access or data tampering, thereby enhancing the security of communication between the energy storage cabinet and the dispatch center.

[0095] Step 302: Extract the instruction content from the energy storage cabinet and check its timeliness.

[0096] After decrypting the message, the energy storage cabinet extracts the instruction content from the plaintext message, including scenario tags, power demand values, timestamps, and chained instruction indexes. The cabinet records the current system time and calculates the time difference between the current system time and the message timestamp. Next, the cabinet compares this time difference with a pre-set timeliness threshold, for example, 5 seconds. If the time difference exceeds the threshold, the instruction is considered potentially time-sensitive due to transmission delays or replay attack risks, and the cabinet lowers its trust rating for the instruction. If the time difference is less than or equal to the threshold, the instruction is considered timely, and the cabinet continues with subsequent processing steps.

[0097] By checking timestamps and calculating time differences, the energy storage cabinet can identify and reject outdated or delayed commands. This method effectively prevents commands from being executed repeatedly due to replay attacks, ensuring the real-time nature and validity of commands, thereby enhancing system security and operational reliability.

[0098] Step 303: Calculate the envelope difference between the actual generated power and the predicted power curve of the energy storage cabinet.

[0099] Based on historical operating data and a pre-set prediction model, the energy storage unit generates a predicted power output curve for the current time period. This curve reflects the expected power output of the energy storage unit under normal operating conditions. The energy storage unit then calculates the difference between the actual output power and the predicted power curve by collecting real-time data on the current actual output power.

[0100] The specific calculation method is as follows: within a predetermined time window, the absolute differences between the actual output power and the predicted power are accumulated and summed to obtain an envelope difference value that characterizes the degree of deviation between the two. The larger the envelope difference value, the greater the degree of deviation between the actual output power and the predicted power curve, which may reflect anomalies on the network side, such as command errors or system malfunctions.

[0101] By calculating the envelope difference between the actual output power and the predicted power curve, the energy storage cabinet can quantitatively analyze the operating status on the network side. This method provides an objective basis for identifying command anomalies or system deviations, helping to improve the adaptability and operational safety of the energy storage cabinet in complex grid connection scenarios.

[0102] Step 304: Monitor the temperature rise rate of the battery cells in the energy storage cabinet.

[0103] The energy storage cabinet monitors the cell temperature in real time using temperature sensors and calculates the rate of temperature change over time, i.e., the temperature rise rate. The specific calculation method is as follows: take the cell temperature values ​​at two adjacent time points, calculate the difference between them, and then divide it by the corresponding time interval to obtain the temperature rise rate. If the temperature rise rate exceeds the normal range, it indicates that the cell may be experiencing abnormal heating, potentially leading to thermal runaway. The energy storage cabinet will assess the cell's operating status based on the magnitude of the temperature rise rate and record relevant data for subsequent analysis.

[0104] By monitoring the temperature rise rate of the battery cells in real time, the energy storage cabinet can promptly detect abnormal heating trends in the cells. This method helps to provide early warning of thermal runaway risks, ensuring the physical safety of the energy storage system and thus improving the overall operational stability and reliability.

[0105] Step 305: Calculate the reliability coefficient of the energy storage cabinet command.

[0106] The energy storage cabinet calculates the command reliability coefficient by combining the aforementioned envelope difference and temperature rise rate. The specific calculation method is as follows: First, the envelope difference is compared with a pre-set maximum allowable envelope difference value to obtain a normalized envelope difference anomaly index; similarly, the temperature rise rate is compared with a pre-set maximum allowable temperature rise rate value to obtain a normalized temperature rise rate anomaly index. Then, the average of these two normalized anomaly indices is taken, and this average is subtracted from a fixed value of 1 to obtain the command reliability coefficient. The command reliability coefficient ranges from 0 to 1; the closer the value is to 1, the higher the reliability of the command; the closer the value is to 0, the lower the reliability of the command.

[0107] By calculating the command reliability coefficient by combining the envelope differences on the network side and the temperature rise rate on the physical side, the energy storage cabinet can comprehensively assess the reliability of commands. This method transforms multi-dimensional anomaly data into a single reliability index, providing a scientific basis for command execution decisions and improving the system's intelligence and security.

[0108] The energy storage cabinet compares the calculated command reliability coefficient with a pre-set threshold. If the command reliability coefficient is greater than or equal to the threshold, the command is considered to have sufficient reliability, and the energy storage cabinet will allow the execution of the power scheduling command in the message. If the command reliability coefficient is less than the threshold, the command is considered to have a high risk, and the energy storage cabinet will initiate a derating operation to reduce the output power, while recording abnormal event information, awaiting further manual intervention or system self-check processing.

[0109] By comparing the command credibility coefficient with a threshold, the energy storage cabinet can make flexible decisions while ensuring safety. This approach balances the effectiveness of command execution with the needs of system protection, effectively reducing the risks caused by abnormal commands and improving the stability and security of the energy storage cabinet in multi-scenario grid connection.

[0110] In use, the energy storage cabinet implements a complete process of command decryption and verification, timeliness checks, anomaly assessment, and credibility decisions. This method ensures the security and reliability of commands while improving the adaptability and operational stability of the energy storage cabinet in multi-scenario grid-connected applications.

[0111] Step 4: The energy storage cabinet acquires real-time state of charge, cell temperature, scenario tags, and chained instruction index; calculates scenario weights based on the real-time state of charge, cell temperature, and chained instruction index; generates a final power scheduling vector based on the scenario weights and power demand values ​​in the instructions; executes the final power scheduling vector to adjust the output power and generates an execution receipt; hashes the execution receipt and writes the hash value to the distributed log ledger.

[0112] Step four includes the following:

[0113] Step 401: The energy storage cabinet acquires real-time operating status data.

[0114] The energy storage cabinet collects real-time operational status data through internal sensors and monitoring equipment. The collected data includes the cabinet's real-time state of charge (SOC) and the battery cell temperature. SOC indicates the percentage of the cabinet's current charge relative to its total capacity, used to assess the cabinet's available capacity and discharge capability. The battery cell temperature reflects the cabinet's thermal state, used to monitor for potential equipment damage or safety hazards due to overheating. Furthermore, the cabinet extracts scenario tags and chained instruction indexes from released commands. Scenario tags identify the scenario type of the current power demand, while the chained instruction index tracks the timing and uniqueness of commands.

[0115] The collection of real-time operating status data provides the necessary data support for the subsequent calculation of scenario weights. The monitoring of real-time state of charge and cell temperature ensures that the energy storage cabinet takes into account both the safety and operating efficiency of the equipment when performing power scheduling. The extraction of scenario tags and chained instruction indexes enables the energy storage cabinet to perform differentiated processing according to scenario characteristics and instruction timing, thereby improving the pertinence and accuracy of scheduling strategies.

[0116] Step 402: Calculate the scenario weights for the energy storage cabinet.

[0117] The energy storage cabinet calculates scenario weights based on real-time state of charge (SOC), cell temperature, and chain command index. Scenario weights quantify the priority of power dispatch under different scenarios, enabling the energy storage cabinet to rationally allocate power output in multi-scenario grid connection. The specific calculation process is as follows: First, the real-time SOC is divided by its maximum value (i.e., the proportion of total capacity when fully charged) to obtain a normalized SOC factor. Then, the cell temperature is compared with a pre-set safe temperature threshold (e.g., 60 degrees Celsius) to calculate a temperature influence factor, where the closer the temperature is to or exceeds the threshold, the smaller the influence factor. Finally, the chain command index is compared with the total number of currently received commands to obtain a command timing factor, representing the command's timing priority. Scenario weights are obtained by multiplying the SOC factor, temperature influence factor, and command timing factor, with values ​​controlled between 0 and 1.

[0118] The calculation of scenario weights comprehensively considers the real-time status of the energy storage cabinet and the timing characteristics of commands, enabling dynamic adjustment of power output priority. The state of charge factor reflects the available capacity of the energy storage cabinet, the temperature influence factor ensures equipment safety, and the command timing factor improves the orderliness of command processing. This allows the energy storage cabinet to prioritize responding to high-priority scenario demands while ensuring equipment safety, thereby enhancing the system's flexibility and responsiveness.

[0119] Step 403: The energy storage cabinet generates the final power dispatch vector.

[0120] The energy storage unit generates a final power dispatch vector based on the scenario weights and the power demand value in the command. The final power dispatch vector represents the actual power value that the energy storage unit should output at the current time. The specific generation process is as follows: the power demand value in the command is multiplied by the scenario weight to obtain the adjusted power output value. When the scenario weight is less than 1, the value of the final power dispatch vector is less than the power demand value in the command, reflecting the dynamic adjustment of the energy storage unit's power output according to the current state.

[0121] By applying scenario weights to power demand values, the energy storage unit can optimize power output based on real-time conditions and scenario characteristics. This generation method ensures that the energy storage unit balances grid demand and equipment safety when executing dispatch commands, avoiding overload or overheating risks caused by directly executing commands, thereby improving system stability and security.

[0122] Step 404: The energy storage cabinet performs power scheduling and generates an execution receipt.

[0123] The energy storage cabinet adjusts its actual output power according to the final power dispatch vector to ensure operation within a safe range. Simultaneously, the cabinet generates an execution receipt to record key information during the execution process. The execution receipt includes an execution timestamp, actual output power, a chained instruction index, and a scenario tag. The execution timestamp records the precise time of the power adjustment, the actual output power records the actual power value executed by the cabinet, and the chained instruction index and scenario tag are used to link instructions with the execution result. The generation and recording of the execution receipt provides a traceable basis for the instruction execution process. The recording of the execution timestamp and actual output power provides detailed data support for subsequent auditing and anomaly analysis, ensuring the transparency and verifiability of instruction execution. The recording of the chained instruction index and scenario tag enhances the correlation between the execution receipt and the instructions, improving the system's manageability.

[0124] Step 405: The energy storage cabinet writes the execution receipt hash into the distributed log ledger.

[0125] The energy storage cabinet processes execution receipts using a hash algorithm (such as SHA-256) to generate an execution receipt hash. This hash, along with the chained instruction index and execution timestamp, is written as a record item to the distributed log ledger. The distributed log ledger connects these records using hash chaining technology, ensuring data immutability and temporal consistency. Writing the execution receipt hash to the distributed log ledger ensures the immutability and traceability of the execution results. This recording method provides a reliable audit basis for the instruction execution process, facilitating rapid location and analysis in case of anomalies. The application of hash chaining technology enhances the security and data integrity of the ledger, improving the system's transparency and credibility.

[0126] In use, the energy storage cabinet enables fine-grained processing and dynamic adjustment of released commands, ensuring the safety and effectiveness of power dispatch. This approach not only improves the operational efficiency of the energy storage cabinet in multi-scenario grid connection but also enhances the traceability and reliability of the system through execution receipts and a distributed log ledger.

[0127] Step 5: The energy storage cabinet monitors the command reliability coefficient and communication status in real time to detect abnormal situations; retrieves the most recent effective power scheduling vector from the distributed log ledger; generates a charge prediction curve based on historical charge state data and a preset charge prediction model, and implements capacity reduction based on the duration of the abnormality and the charge prediction curve; executes capacity reduction operation and records the abnormal event to the distributed log ledger; continuously monitors the communication status and command reliability, and waits for the abnormal situation to recover.

[0128] Step five includes the following:

[0129] Step 501: Detect abnormalities in the energy storage cabinet.

[0130] The energy storage cabinet monitors the command credibility coefficient and communication status in real time. The command credibility coefficient is generated by the aforementioned steps and is used to evaluate the reliability and authenticity of the command.

[0131] The energy storage cabinet compares the command reliability coefficient with a pre-set threshold, for example, a value between 0 and 1. If the command reliability coefficient is less than this threshold, the command is considered risky. Simultaneously, the energy storage cabinet records the time of the most recent successful command reception and calculates the time difference between the current time and the time of the most recent successful command reception. If this time difference exceeds a preset communication timeout threshold, for example, a fixed number of seconds, a communication timeout is considered to have occurred. When either the command reliability coefficient is less than the preset threshold or the communication time difference exceeds the communication timeout threshold, the energy storage cabinet triggers an abnormal situation handling mechanism.

[0132] Real-time monitoring of command reliability coefficients and communication status enables energy storage cabinets to quickly identify risks of command anomalies or communication interruptions. This detection method provides energy storage cabinets with timely early warning capabilities for anomalies, ensuring rapid response measures are taken when potential risks occur, thereby guaranteeing the safe operation of energy storage cabinets and the stability of the power grid.

[0133] Step 502: The energy storage cabinet obtains the most recent effective power dispatch vector.

[0134] Upon detecting an anomaly, the energy storage unit retrieves the most recently executed effective power scheduling vector from the distributed ledger. This vector records the last output power value of the energy storage unit under normal communication and command reliability conditions, in kilowatts. The distributed ledger is maintained by the aforementioned steps, ensuring the immutability and traceability of the data. The energy storage unit obtains the most recently executed effective power scheduling vector by querying the distributed ledger, which serves as the baseline power value in case of anomalies.

[0135] Retrieving the most recent valid power dispatch vector provides a reliable operational reference for the energy storage cabinet under abnormal conditions. This method ensures that the energy storage cabinet can still adjust its power based on historical valid data when new instructions are lost, avoiding operational loss of control due to missing or abnormal instructions, thereby maintaining the basic functions and safety of the system.

[0136] The energy storage unit generates a charge prediction curve for the current time period based on historical state of charge (SOC) data and a pre-set charge prediction model. This curve is used to predict SOC changes over a future period. The SOC is provided by the real-time SOC obtained in the preceding steps, expressed as a percentage. The energy storage unit is configured with a derating factor, initially set to a value indicating no derating, which decreases progressively based on the duration of the anomaly. The anomaly duration is the time elapsed from the start of anomaly detection to the current time, expressed in seconds.

[0137] The derating factor is updated as follows: the duration of the abnormal event is compared with a preset derating time constant, such as a fixed number of seconds. If the duration of the abnormal event exceeds this constant, the derating factor is reduced proportionally. If the calculated proportional result is less than zero, the derating factor is set to zero, indicating a complete stop in output. The energy storage unit calculates the derating power dispatch vector based on the derating factor and the most recent effective power dispatch vector. Furthermore, if the charge prediction curve indicates that the state of charge is about to fall below a safe threshold, such as a percentage value, the energy storage unit further reduces the derating factor to ensure no discharge.

[0138] By implementing derating based on the charge prediction curve, the output power of the energy storage cabinet can be dynamically adjusted to avoid overload or over-discharge caused by abnormal conditions. This approach, through a comprehensive consideration of the derating factor and charge prediction, ensures that the energy storage cabinet maintains safe operation under abnormal conditions, while providing appropriate support to the power grid and enhancing the system's fault tolerance and stability.

[0139] Step 503: The energy storage cabinet performs derating operation and records abnormal events.

[0140] The energy storage unit adjusts its actual output power based on the degraded power dispatch vector to ensure adequate grid support even under abnormal conditions. Simultaneously, the unit generates anomaly event logs, including the anomaly start time, anomaly type (e.g., low command reliability or communication timeout), degradation factor, and state of charge. The unit applies a hash algorithm to these anomaly event logs, such as a general-purpose cryptographic hash algorithm, to generate anomaly event hashes, ensuring the logs' immutability. The unit then writes the anomaly event hash, start time, and type to a distributed ledger.

[0141] Performing derating operations and logging abnormal events ensures that the energy storage cabinet's operational status is controllable and traceable under abnormal conditions. The generation and writing of abnormal event records to a distributed ledger provides reliable data support for post-event analysis and rapid recovery, enhancing system transparency and manageability. The application of hash algorithms ensures the integrity and immutability of records, improving data security and reliability.

[0142] Step 504: Continuously monitor the energy storage cabinet and wait for recovery.

[0143] In abnormal situations, the energy storage cabinet continuously monitors communication status and command reliability. Once communication is restored or a reliable command is received (i.e., the command reliability coefficient is greater than or equal to a preset threshold), the energy storage cabinet stops de-capacity operation and resumes normal scheduling mode. After resuming normal operation, the energy storage cabinet generates a recovery event record, including the recovery time and the power scheduling vector after recovery, and writes the recovery event record to a distributed log ledger.

[0144] A mechanism for continuous monitoring and awaiting recovery ensures that the energy storage cabinet quickly resumes normal operation after the abnormal situation is eliminated. By generating and storing recovery event logs, a complete record of the system's operating status is provided, facilitating subsequent auditing and analysis, while also enhancing the energy storage cabinet's adaptability and stability in multi-scenario grid connection.

[0145] In use, the energy storage cabinet achieves autonomous fault tolerance and safe operation under abnormal conditions, ensuring continuous support for the power grid and the safety of the energy storage cabinet. This method, through de-capacity operation and anomaly recording, enhances the system's fault tolerance and traceability, providing a solid guarantee for the safe and reliable operation of grid-connected energy storage cabinets in multiple scenarios.

[0146] Please see Figure 2 This invention provides an energy dispatching system for energy storage cabinets oriented towards multi-scenario grid connection, comprising:

[0147] The identity authentication module completes a handshake between the energy storage cabinet, dispatch center and power converter through hardware trust root, generates a unique trust root identifier and synchronously initializes the chain instruction index, and derives the session key based on the trust root identifier.

[0148] The instruction generation module, based on the chained instruction index, packages the power requirements of multiple scenarios into encrypted messages carrying scenario tags, sends them through a secure channel, and synchronously writes them into the distributed log ledger;

[0149] The instruction evaluation module combines the overall envelope difference between the actual power output and the predicted curve, as well as the characteristics of the cell temperature rise rate, to generate an instruction credibility coefficient. Based on the credibility coefficient, it determines whether to release the instruction or initiate derating.

[0150] The scheduling and execution module calculates the scenario weight based on the real-time state of charge, temperature information and chain instruction index for released instructions, outputs the final power scheduling vector, and appends the execution receipt hash to the distributed log ledger.

[0151] The exception handling module implements step-by-step de-capacity operation according to the most recent effective power scheduling vector and in combination with the charge prediction curve when the instruction credibility coefficient is lower than the threshold or the communication times out.

[0152] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented 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 this application.

[0153] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0154] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0155] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0156] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An energy dispatching method for energy storage cabinets oriented towards multi-scenario grid connection, characterized in that: include, A handshake is completed between the energy storage cabinet, dispatch center and power converter through hardware trust root, a unique trust root identifier is generated and the chain instruction index is initialized synchronously, and the session key is derived based on the trust root identifier. The dispatch center packages the power requirements of multiple scenarios into encrypted messages carrying scenario tags based on the chained instruction index, sends them through a secure channel, and synchronously writes them into the distributed log ledger. The command credibility coefficient is generated by combining the overall envelope difference between the actual power output and the predicted curve and the characteristics of the cell temperature rise rate. The command is then released or derating is initiated based on the credibility coefficient. For released instructions, the scenario weight is calculated based on real-time state of charge, temperature information and chain instruction index, the final power scheduling vector is output, and the execution receipt hash is appended to the distributed log ledger. When the instruction reliability coefficient is lower than the threshold or communication times out, the system will implement step-by-step de-capacity operation according to the most recent effective power scheduling vector and in combination with the charge prediction curve.

2. The energy dispatching method for energy storage cabinets oriented towards multi-scenario grid connection according to claim 1, characterized in that: The energy storage cabinet, dispatch center and power converter each execute a handshake protocol through the hardware trust root module to verify each other's device identity credentials; A temporary session key is generated through negotiation using asymmetric encryption technology. After the handshake protocol is completed, the public key of the energy storage cabinet, the public key of the dispatch center, and the public key of the power converter are concatenated and a root trust identifier is generated through a secure hash algorithm.

3. The energy dispatching method for energy storage cabinets oriented towards multi-scenario grid connection according to claim 2, characterized in that: The scheduling center generates and maintains a chained instruction index, which is initially set to the current timestamp and increments with each instruction. Based on the root trust identifier and the chained instruction index, a session key is generated through a key derivation function. The communication messages are symmetrically encrypted using a session key to ensure confidentiality, and a digital signature is generated to verify integrity and sender identity.

4. The energy dispatching method for energy storage cabinets oriented towards multi-scenario grid connection according to claim 3, characterized in that: The dispatch center packages the power requirements of multiple scenarios into instruction content, which is organized using JSON object format. The instruction content includes scenario tags, power requirement values, timestamps, and chained instruction indexes. The dispatch center uses the session key to perform symmetric encryption on the instruction content, generating encrypted instruction content and a digital signature.

5. The energy dispatching method for energy storage cabinets oriented towards multi-scenario grid connection according to claim 4, characterized in that: The dispatch center combines the encrypted instruction content, initialization vector, and digital signature into an encrypted message, which is then transmitted to the energy storage cabinet. Encrypted messages, chained instruction indexes, and timestamps are written to a distributed log ledger to ensure the non-repudiation and temporal consistency of instructions.

6. The energy dispatching method for energy storage cabinets oriented towards multi-scenario grid connection according to claim 5, characterized in that: The energy storage cabinet uses the session key to decrypt the received message and verify the validity of the digital signature, extract the instruction content contained in the message and check the timeliness of the instruction; Calculate the envelope difference between the actual generated power and the predicted power curve, and monitor the temperature rise rate of the cells in the energy storage cabinet; The command reliability coefficient is calculated by combining the envelope difference and the temperature rise rate. Based on the command reliability coefficient, it is determined whether the command should be released or a derating operation should be triggered.

7. The energy dispatching method for energy storage cabinets oriented towards multi-scenario grid connection according to claim 6, characterized in that: The energy storage cabinet acquires real-time state of charge, cell temperature, scenario tags, and chain command index; and calculates scenario weights based on the real-time state of charge, cell temperature, and chain command index.

8. The energy dispatching method for energy storage cabinets oriented towards multi-scenario grid connection according to claim 7, characterized in that: The final power scheduling vector is generated based on the scenario weights and the power demand values ​​in the instructions. The final power scheduling vector is executed to adjust the output power and generate an execution receipt. The execution receipt is then hashed and the hash value is written to the distributed log ledger.

9. The energy dispatching method for energy storage cabinets oriented towards multi-scenario grid connection according to claim 8, characterized in that: The energy storage cabinet monitors the command reliability coefficient and communication status in real time and detects abnormal situations. Among them, it retrieves the most recent effective power scheduling vector from the distributed log ledger. A charge prediction curve is generated based on historical state of charge data and a pre-set charge prediction model, and derating is implemented based on the duration of the anomaly and the charge prediction curve. Perform de-capacity operation and record abnormal events to a distributed log ledger, continuously monitor communication status and command reliability, and wait for recovery from abnormal situations.

10. An energy dispatching system for energy storage cabinets oriented towards multi-scenario grid connection, characterized in that: include, The identity authentication module completes a handshake between the energy storage cabinet, dispatch center and power converter through hardware trust root, generates a unique trust root identifier and synchronously initializes the chain instruction index, and derives the session key based on the trust root identifier. The instruction generation module, based on the chained instruction index, packages the power requirements of multiple scenarios into encrypted messages carrying scenario tags, sends them through a secure channel, and synchronously writes them into the distributed log ledger; The instruction evaluation module combines the overall envelope difference between the actual power output and the predicted curve, as well as the characteristics of the cell temperature rise rate, to generate an instruction credibility coefficient. Based on the credibility coefficient, it determines whether to release the instruction or initiate derating. The scheduling and execution module calculates the scenario weight based on the real-time state of charge, temperature information and chain instruction index for released instructions, outputs the final power scheduling vector, and appends the execution receipt hash to the distributed log ledger. The exception handling module implements step-by-step de-capacity operation according to the most recent effective power scheduling vector and in combination with the charge prediction curve when the instruction credibility coefficient is lower than the threshold or the communication times out.

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