Energy storage power supply charging type identification, authentication and consumption metering system and method

Abstract

The invention provides an energy storage power supply charging type identification, authentication and consumption metering system and method, and relates to the technical field of new energy storage, and the method comprises the steps: collecting a charging signal, analyzing the statistical characteristics of the signal through power spectral density and an autocorrelation function, and distinguishing green electricity from pseudo green electricity; generating a block chain Token for the green electricity passing the verification, binding the block chain Token with a BMS unique identifier, and then performing uplink; the energy storage equipment executes green electricity storage and consumption operation based on the legality of the Token; and the carbon integral platform automatically distributes the integral according to the on-chain data. According to the method, green electricity and pseudo green electricity are distinguished through a signal feature analysis technology, a unique Token is generated for a BMS in combination with a block chain to realize data tamper-proofing, a power generation, storage and consumption full-process metering system is constructed, and finally automatic distribution of carbon points is supported. The system can be widely applied to the scenes of photovoltaic energy storage, electric automobile battery swap stations and the like, and assists the realization of the dual-carbon target.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy energy storage, and particularly to a system and method for identifying, authenticating, and consuming and measuring the charging type of an energy storage power supply based on signal feature analysis, blockchain authentication, and green power closed-loop management. Background Art

[0002] With the increasingly severe global climate change problem, new energy and energy storage technologies have been vigorously developed. In this context, the accurate identification, secure authentication, metering and statistics, and consumption management of green energy (such as photovoltaic power, wind power, etc.) have become particularly important. However, in the combination of current new energy power generation equipment and energy storage systems, there are still problems such as difficult green power identification, lack of metering and authentication, and insufficient closed-loop management.

[0003] Existing technologies are difficult to effectively distinguish whether the input charging signal is naturally generated green power (such as photovoltaic power, wind power) or artificially forged pseudo-green power (such as periodic DC signals superimposed with noise). This difficulty in identification leads to inaccuracies in green power authentication, affecting subsequent metering and carbon credit allocation. Moreover, there is a lack of a credible authentication mechanism for the power generation, storage, and consumption amounts of green power. Traditional metering methods often rely on simple electricity meter readings, which cannot ensure the authenticity and reliability of data. This results in a lack of a solid basis for carbon credit allocation, affecting the fairness and credibility of the entire green energy trading system. There is also a lack of an integrated tracking mechanism for the entire process of green power from generation, storage to consumption. The data at each link is often fragmented, making it difficult to form a complete carbon emission reduction evidence chain. This management defect hinders the optimization of the entire life cycle of green energy and the accurate calculation of carbon footprints.

[0004] In view of the above problems, there is an urgent need for a new system and method for identifying, authenticating, consuming and measuring the charging type of an energy storage power supply that can accurately identify green power, ensure data security, achieve full-process closed-loop management, and support fair and transparent carbon credit allocation to improve the utilization efficiency of new energy. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to propose a system and method for identifying, authenticating, consuming and measuring the charging type of an energy storage power supply. By using signal feature analysis technology to distinguish green power from pseudo-green power, combined with blockchain to generate a unique Token for the BMS to achieve data anti-tampering, and constructing a metering system for the entire process of power generation, storage, and consumption, ultimately supporting the automated allocation of carbon credits, for realizing the accurate identification, secure authentication, metering and statistics, and consumption closed-loop management of green energy (such as photovoltaic power, wind power), achieving the full-process trusted management of green power, and supporting the application of the carbon credit system.

[0006] To achieve the above purpose, the present invention provides the following technical solutions: For the above purposes, in a first aspect, the present invention provides a system for identifying, authenticating, and consuming and measuring the charging type of an energy storage power supply, including the following components: A green energy identification and measurement module for power generation equipment, which is used to identify green electricity through power spectral density (PSD) and autocorrelation function analysis; A blockchain integrated battery management module (BMS) for energy storage equipment, which generates a unique Token and verifies the identity of green electricity; A communication module, which is used to encrypt and transmit power generation, storage, and consumption data to blockchain nodes and the carbon credit management platform; A carbon credit management platform, which generates carbon credits based on blockchain green electricity data according to preset rules and feeds them back to the user side.

[0007] As a further solution of the present invention, the power generation equipment is a green electricity generation device including a photovoltaic panel and a wind turbine; the green energy identification and measurement module of the power generation equipment includes: A signal acquisition unit, which is used to perform real-time sampling on the green electricity input signal; A feature analysis unit, which is used to calculate the signal power spectral density (PSD) by using the Welch method and combine autocorrelation function analysis to determine whether the signal is green electricity. Among them, green electricity is a stationary random signal, and pseudo-green electricity is a periodic signal; A blockchain writing unit, which is used to generate a unique Token for the green electricity generation data and write it into the blockchain through a smart contract.

[0008] As a further solution of the present invention, the signal analysis method of the green energy identification and measurement module includes: Calculate the power spectral density (PSD) of the input signal by using the Welch method. If there is no obvious periodic peak in the frequency domain of the PSD, it is determined as green electricity; Calculate the autocorrelation function. If the autocorrelation value decays to zero as the delay increases, the identity of green electricity is further confirmed.

[0009] As a further solution of the present invention, the blockchain integrated battery management module (BMS) includes: A green electricity verification unit: communicates with the power generation equipment to verify the identity of green electricity and the legitimacy of the blockchain Token; A metering unit: statistics the green electricity storage and charge-discharge data; A battery management unit: generates an immutable Token based on the hardware serial number and integrates the blockchain unique identifier to ensure the uniqueness of the BMS identity.

[0010] As a further solution of the present invention, the method for generating the blockchain unique identifier of the BMS is: Extract the BMS hardware serial number and generate an initial identifier through a hash algorithm; Use an asymmetric encryption algorithm to sign the identifier and generate an immutable Token; After binding the Token to the green electricity data, write it into the blockchain through a smart contract.

[0011] As a further solution of the present invention, the verification method of the Token includes: When the energy storage device receives green electricity, call the smart contract to verify the matching of the Token with the blockchain record; If the verification fails, trigger an alarm and prohibit the access of green electricity to the energy storage device.

[0012] As a further solution of the present invention, the communication module includes: 4G / 5G transmission unit: Upload the power generation, storage, and consumption data to the cloud server; Blockchain node: Deploy a smart contract to realize data on-chain and Token verification.

[0013] As a further solution of the present invention, the 4G / 5G transmission unit of the communication module satisfies: Adopt the AES-256 encryption algorithm to protect the transmission data; Support dynamic adjustment of the data transmission frequency to adapt to battery pack clusters of different scales.

[0014] As a further solution of the present invention, the carbon credit management platform's credit generation rule is: The green electricity generation is converted into carbon credits at a ratio of 1:1, and the consumption is superimposed on the credits with a weight of 0.5 times; The credit allocation record is written into the blockchain through a smart contract, and users can publicly query it.

[0015] As a further solution of the present invention, the energy storage device is also provided with a green energy consumption and metering module, and the green energy consumption and metering module includes: Energy storage main control module, used to control the green electricity consumption strategy; Bidirectional inverter module, used for the storage and release control of green electricity; Load module, which is the final consumption end of green electricity, used to real-time statistically measure the consumed electricity and synchronize it to the blockchain.

[0016] In a second aspect, the present invention provides a method for identifying, authenticating, and consuming and metering the charging type of an energy storage power supply, including the following steps: Collect the charging signal, analyze the signal statistical characteristics through the power spectral density (PSD) and autocorrelation function to distinguish green electricity from pseudo-green electricity; Generate a blockchain Token for the verified green electricity, bind it to the BMS unique identifier and then upload it to the chain; The energy storage device performs green power storage and consumption operations based on the Token's legality; The carbon credit platform automatically allocates credits according to the on-chain data.

[0017] As a further aspect of the present invention, when differentiating green power from pseudo-green power, the autocorrelation function of green power decays to zero with delay, while the autocorrelation function of pseudo-green power exhibits periodic characteristics.

[0018] As a further aspect of the present invention, the steps for generating the blockchain Token include: Generate a unique hardware identifier for each BMS, and generate a hash value based on the BMS hardware serial number as the initial identifier; Use the Elliptic Curve Digital Signature Algorithm (ECDSA) to sign the hash value to generate a non-replicable Token; Bind the Token to the power generation amount, timestamp, and geographical location of the green power data through a smart contract and write it into the blockchain.

[0019] As a further aspect of the present invention, when the carbon credit platform automatically allocates credits according to the on-chain data, the carbon credit allocation rule is: For every 1 kWh of green power generation, 1 credit is corresponding, and for every 1 kWh of consumption, 0.5 credits are added; The credit data is updated in real time through a smart contract and supports visual query on the user side.

[0020] In another aspect of the present invention, there is also provided a computer device, including a memory and a processor. A computer program is stored in the memory, and when the computer program is executed by the processor, it executes any one of the above-mentioned methods for identifying, authenticating, and consuming and measuring the charging type of the energy storage power supply according to the present invention.

[0021] In still another aspect of the present invention, there is also provided a computer-readable storage medium storing computer program instructions, and when the computer program instructions are executed, they implement any one of the above-mentioned methods for identifying, authenticating, and consuming and measuring the charging type of the energy storage power supply according to the present invention.

[0022] Compared with the prior art, a system and method for identifying, authenticating, and consuming and measuring the charging type of an energy storage power supply proposed by the present invention have the following beneficial effects: The present invention effectively distinguishes green electricity from pseudo-green electricity through signal feature analysis, achieving precise identification of green electricity and pseudo-green electricity. By combining blockchain Token with the unique identifier of the BMS hardware, it ensures that data cannot be tampered with throughout the entire life cycle, realizes trustworthy metering for the entire chain of "generation - storage - utilization" of green electricity, supports carbon footprint tracking, and achieves a full-process closed-loop. By adopting the Welch method and an open-source blockchain framework, the deployment cost and system implementation cost are reduced. The present invention distinguishes green electricity from pseudo-green electricity through signal feature analysis technology, combines blockchain to generate a unique Token for the BMS to prevent data tampering, and constructs a metering system for the entire process of power generation, storage, and consumption, ultimately supporting the automated allocation of carbon credits. This system can be widely applied to scenarios such as photovoltaic energy storage and electric vehicle swapping stations.

[0023] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. Brief Description of the Drawings

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the following will briefly introduce the drawings required for the description of the exemplary embodiments or related technologies. The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings: Figure 1 It is a structural block diagram of a system for identifying, authenticating, and consuming and metering the charging type of an energy storage power supply according to an embodiment of the present invention.

[0025] Figure 2 It is a structural block diagram of a green energy consumption and metering module in a system for identifying, authenticating, and consuming and metering the charging type of an energy storage power supply according to an embodiment of the present invention.

[0026] Figure 3 It is a flowchart of a method for identifying, authenticating, and consuming and metering the charging type of an energy storage power supply according to an embodiment of the present invention.

[0027] Figure 4 It is a flowchart of generating blockchain Token in a method for identifying, authenticating, and consuming and metering the charging type of an energy storage power supply according to an embodiment of the present invention. Detailed Embodiments

[0028] Next, in combination with the drawings and specific embodiments, the present application will be further described. It should be noted that, on the premise of non-conflict, the following-described embodiments or technical features can be arbitrarily combined to form new embodiments.

[0029] To make the objectives, technical solutions and advantages of the present invention more clear and understandable, the following further elaborates on the embodiments of the present invention in detail with reference to specific embodiments and the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0030] It should be noted that all the expressions using "first" and "second" in the embodiments of the present invention are for distinguishing two non-identical entities or non-identical parameters with the same name. It can be seen that "first" and "second" are only for the convenience of expression and should not be construed as a limitation on the embodiments of the present invention. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units inherently includes other steps or units.

[0031] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0032] The flowcharts shown in the accompanying drawings are only illustrative examples, and do not necessarily include all the contents and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can also be decomposed, combined or partially merged. Therefore, the actual execution order may change according to the actual situation.

[0033] Next, some embodiments of the present application will be described in detail in conjunction with the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0034] In view of the problems of difficult green power identification, lack of metering and certification, and insufficient closed-loop management in the current combination of new energy power generation equipment and energy storage systems, the present invention proposes a system and method for identifying, certifying, and consuming and metering the charging type of an energy storage power supply. By signal feature analysis technology, green power is distinguished from pseudo-green power. Combining blockchain to generate a unique Token for the BMS to achieve data anti-tampering, and constructing a metering system for the entire process of power generation, storage, and consumption. Finally, it supports the automatic allocation of carbon credits, which is used to achieve accurate identification, secure certification, metering statistics, and consumption closed-loop management of green energy (such as photovoltaic and wind power), realize the trusted management of the entire process of green power, and support the application of the carbon credit system.

[0035] See Figure 1 As shown, the embodiments of the present invention provide a system for identifying, certifying, and consuming and metering the charging type of an energy storage power supply, and the system includes the following components: The green energy identification and metering module 100 of the power generation device 10 is used to identify green electricity through power spectral density (PSD) and autocorrelation function analysis; The blockchain integrated battery management module 200 (BMS) of the energy storage device 20 generates a unique Token and verifies the identity of green electricity; The communication module 30 is used to encrypt and transmit the power generation amount, storage amount and consumption amount data to the blockchain node and the carbon credit management platform 40; The carbon credit management platform 40 generates carbon credits according to preset rules based on the blockchain-based green electricity data and feeds them back to the user side.

[0036] In this embodiment, the power generation device 10 is a green electricity generation device including a photovoltaic panel, a wind turbine, etc. Among them, the green energy identification and metering module 100 of the power generation device 10 includes: The signal acquisition unit 101 is used to perform real-time sampling on the green electricity input signal; The feature analysis unit 102 is used to calculate the signal power spectral density (PSD) by the Welch method, and combine the autocorrelation function analysis to judge whether the signal is green electricity. Among them, green electricity is a stationary random signal, and pseudo-green electricity is a periodic signal; The blockchain writing unit 103 is used to generate a unique Token for the green electricity generation amount data and write it into the blockchain through a smart contract.

[0037] Among them, the signal analysis method of the green energy identification and metering module 100 includes: Calculate the power spectral density (PSD) of the input signal by the Welch method. If there is no obvious periodic peak in the frequency domain of the PSD, it is determined as green electricity; Calculate the autocorrelation function. If the autocorrelation value decays to zero as the delay increases, the identity of green electricity is further confirmed.

[0038] In this embodiment, when calculating the autocorrelation function, the autocorrelation function is used to describe the similarity of a single signal at different time delays. The autocorrelation function The calculation formula is:

[0039] In the formula, is the time delay, indicating the time difference between different time points of the signal; is the signal value of the signal at time , representing the time function to be analyzed; is the signal value of the delay ; is the length of the integration interval, indicating the time interval. The autocorrelation function is used to determine the similarity of signals at different time points. If a signal is a stationary random signal, the autocorrelation function will be If it is a periodic signal, the autocorrelation function will show periodicity.

[0040] In this embodiment, the power spectral density (PSD) represents the distribution characteristics of the signal in the frequency domain. The calculation formula is:

[0041] make:

[0042] In the formula, For power limited signals; Take a section, then:

[0043] In the formula, Indicates Fourier transform; is the expression of Fourier transform result; is the complex frequency; According to Parseval's theorem, we can get:

[0044]

[0045] In the formula, is the instantaneous energy; and exist same; is the power expression in the time domain, And the frequency domain power spectrum representation From the energy point of view, the representation of the signal is equivalent.

[0046] is the power spectrum; then:

[0047] The relationship between the related functions is:

[0048] In the formula, for Inverse Fourier transform; Power spectral density is used to describe the energy distribution of a signal in the frequency domain and identify the intensity of the signal at different frequencies. If there are no obvious periodic peaks in the spectrum, it indicates that the signal is random (i.e., green electricity); if there are periodic peaks, the signal exhibits periodicity (pseudo-green electricity).

[0049] In practical applications, the power spectral density (PSD) can be calculated using the Fourier transform of the signal. According to the properties of the Fourier transform, the frequency domain of a periodic signal in the time domain exhibits discreteness, harmonicity, and convergence, while the power spectrum of white noise is a constant, and its , is the Dirac function, that is, when there is no correlation, are all 0. For the detection of a periodic signal mixed with noise, when the delay is long enough, the autocorrelation function of the noise should approach zero, and the autocorrelation function of the useful signal is detected. This is used as the basis for whether the signal has periodicity.

[0050] Exemplarily, if a green energy identification and metering module 100 of a power generation device 10 is installed in a photovoltaic power station, when sunlight irradiates the photovoltaic panel to generate current, the signal acquisition unit 101 samples the output voltage at a frequency of 1 kHz; the feature analysis unit 102 uses the Welch method to calculate the PSD of the sampled signal and finds that the spectrum shows a continuous distribution in the range of 0 - 100 Hz without obvious peaks. At the same time, the autocorrelation function analysis shows that the correlation value rapidly decays to 0 as the delay increases. Based on these two features, the system determines that the signal is green electricity. Subsequently, the blockchain writing unit 103 generates a Token containing the power generation amount, timestamp, and geographical location, and writes it into the blockchain through a smart contract.

[0051] In this embodiment, the blockchain integrated battery management module 200 (BMS) includes: Green electricity verification unit 201: Communicates with the power generation device 10 to verify the identity of green electricity and the legality of the blockchain Token; Metering unit 202: Counts the green electricity storage amount and charge / discharge data; Battery management unit 203: Generates an immutable Token based on the hardware serial number, integrates the blockchain unique identifier, and ensures the uniqueness of the BMS identity.

[0052] Among them, the method for generating the blockchain unique identifier of the blockchain integrated battery management module 200 (BMS) is as follows: Extract the hardware serial number of the blockchain integrated battery management module 200 (BMS), and generate an initial identifier through a hash algorithm; Use an asymmetric encryption algorithm to sign the identifier to generate an immutable Token; After binding the Token to the green power data, it is written into the blockchain through a smart contract.

[0053] Among them, the verification method of the Token includes: When the energy storage device 20 receives green power, it calls the smart contract to verify the matching of the Token with the blockchain record; If the verification fails, an alarm is triggered and the access of green power to the energy storage device 20 is prohibited.

[0054] Exemplarily, the energy storage system of an electric vehicle charging station is equipped with this blockchain integrated battery management module 200 (BMS). When an electric vehicle is connected for charging, the green power verification unit 201 first communicates with the power generation device 10 to verify the Token of the input current. After the verification passes, the metering unit 202 starts to record the charging amount. At the same time, the battery management unit 203 generates a hash value based on its hardware serial number "BMS20230601001", and then signs it using the ECDSA algorithm to form a unique blockchain identifier. This identifier is written into the blockchain together with the charging data, ensuring the immutability of the data.

[0055] In this embodiment, the communication module 30 includes: 4G / 5G transmission unit 301: Uploads the power generation amount, storage amount, and consumption amount data to the cloud server; Blockchain node 302: Deploys a smart contract to realize data uploading to the chain and Token verification.

[0056] Among them, the 4G / 5G transmission unit 301 of the communication module 30 satisfies: Protects the transmission data using the AES-256 encryption algorithm; Supports dynamically adjusting the data transmission frequency to adapt to battery pack clusters of different scales.

[0057] Exemplarily, in a large-scale photovoltaic power plant, each photovoltaic array is equipped with a 4G transmission unit. These units send encrypted power generation data packets to the cloud server every 5 minutes. At the same time, the blockchain nodes set up in the field run smart contracts, which are responsible for data uploading to the chain and Token verification. When abnormal data is detected (such as a sudden abnormal increase in the power generation amount of a certain array), the smart contract will automatically trigger an alarm.

[0058] In this embodiment, the carbon credit management platform 40 has the following carbon credit generation rules: The green power generation amount is converted into carbon credits at a ratio of 1:1, and the consumption amount is superimposed on the credits with a weight of 0.5 times; The credit allocation record is written into the blockchain through a smart contract, and users can publicly query it.

[0059] Exemplarily, if an enterprise participates in a green power trading program, the carbon credit management platform 40 records that the enterprise's photovoltaic system generates 1000 kWh of electricity in a day and consumes 800 kWh. According to the rules, the platform automatically calculates the carbon credits: 1000 + 800 * 0.5 = 1400 points. This credit record is written into the blockchain through a smart contract, and the enterprise can query its credit details at any time.

[0060] In this embodiment, as shown in Figure 2 Figure, the energy storage device 20 is also provided with a green energy consumption and metering module, and the green energy consumption and metering module includes: An energy storage main control module for controlling the green power consumption strategy; A bidirectional inverter module for controlling the storage and release of green power; A load module, which is the final consumption end of green power, for real-time statistics and metering of the consumed electricity and synchronizing it to the blockchain.

[0061] The energy storage power charging type identification, authentication, and consumption metering system of the present invention realizes the accurate identification of green power through innovative signal analysis technology, and uses blockchain technology to ensure the immutability and traceability of data. The unique identification mechanism of the BMS enhances the system security, while the carbon credit management platform 40 provides a fair and transparent incentive mechanism for green energy trading. The entire system forms a closed-loop green power management ecosystem, and each link from power generation, storage to consumption is effectively monitored and managed.

[0062] As shown in Figure 3 Figure, the embodiment of the present invention provides an energy storage power charging type identification, authentication, and consumption metering method, and the method includes the following steps: Step S10: Collect charging signals, analyze the signal statistical characteristics through the power spectral density (PSD) and autocorrelation function, and distinguish green power from pseudo-green power.

[0063] Among them, when distinguishing green power from pseudo-green power, the autocorrelation function of green power decays to zero with delay, and the autocorrelation function of pseudo-green power shows periodic characteristics.

[0064] Step S20: Generate a blockchain Token for the verified green power, and bind it with the BMS unique identifier and then upload it to the chain.

[0065] Among them, as shown in Figure 4 Figure, the generation steps of the blockchain Token include: Step S201: Generate a unique hardware identifier for each BMS, generate a hash value based on the BMS hardware serial number as the initial identifier; Step S202: Sign the hash value using the Elliptic Curve Digital Signature Algorithm (ECDSA) to generate a non-replicable Token; Step S203: Bind the Token with the generated electricity quantity, timestamp, and geographical location of the green electricity data through a smart contract and write them into the blockchain.

[0066] Step S30: The energy storage device 20 performs green electricity storage and consumption operations based on the Token's legitimacy.

[0067] Step S40: The carbon credit platform automatically allocates credits according to the data on the chain.

[0068] In this embodiment, when the carbon credit platform automatically allocates credits according to the data on the chain, the carbon credit allocation rule is as follows: For every 1 kWh of green electricity generated, 1 credit is allocated, and for every 1 kWh of consumption, an additional 0.5 credit is added; The credit data is updated in real time through a smart contract and supports visual query on the user side.

[0069] Exemplarily, when the energy storage power supply charging type identification, authentication, and consumption metering method of the present invention is applied to a wind farm, if the output voltage signal of the turbine-1 fan in the wind farm is collected by a sampler at a frequency of 10 kHz, the energy storage power supply charging type identification, authentication, and consumption metering system calculates the power spectral density and finds that the spectrum shows a continuous distribution within the range of 0 - 500 Hz without obvious peaks. The autocorrelation function analysis shows that the correlation value decays to nearly zero within 0.1 second. The system determines that the signal is green electricity. In contrast, when a forged "green electricity" signal is detected, its PSD shows obvious peaks at 50 Hz and 100 Hz, and the autocorrelation function shows fluctuations with a period of 0.02 seconds. The system identifies it as fake green electricity and triggers an alarm.

[0070] For the green electricity generated by the turbine-1 fan, the process of generating a Token by the system is as follows: S201: The BMS hardware serial number of the fan is "WT20230701001", and the hash value is generated using the SHA-256 algorithm: "7f83b1657ff1fc53b92dc18148a1d65dfc2d4b1fa3d677284addd200126d9069" is used as the initial identifier.

[0071] S202: Sign the hash value using the ECDSA algorithm to generate a non-replicable Token "0x1c2a7f...".

[0072] S203: The smart contract binds this Token with the green electricity data (generated electricity quantity: 500 kWh, timestamp: 2023-07-01 14:30:00 UTC, geographical location: N40°42'46", E74°0'21") and writes it into the blockchain.

[0073] When the energy storage device 20 performs green power storage and consumption operations based on the Token legality, if the electric vehicle charging station receives green power from turbine-1. The energy storage system of the charging station first verifies the legality of the Token "0x1c2a7f...". After passing the verification, the system starts to perform the green power storage operation and deposits 500 kWh of electricity into the large-capacity battery pack.

[0074] When the carbon credit platform automatically allocates credits based on the on-chain data, the carbon credit platform detects the on-chain data of turbine-1 and automatically calculates the credits: Generation credit: 500 kWh * 1 = 500 credits. Assuming that this batch of electricity is completely consumed within 24 hours, then: Consumption credit: 500 kWh * 0.5 = 250 credits; Total credits: 500 + 250 = 750 credits. The platform records 750 credits into the account of the company to which turbine-1 belongs through a smart contract, and users can view the credit changes in real time through the mobile APP.

[0075] The energy storage power supply charging type identification, authentication, and consumption metering method of the present invention realizes the accurate identification of green power through advanced signal processing technology, effectively preventing the mixing of pseudo-green power; the application of blockchain technology ensures the immutability and traceability of data, and the introduction of the unique BMS identifier further enhances the system security; the automated operation of the carbon credit platform provides a fair and transparent incentive mechanism for green energy trading. The whole process forms a complete closed loop, covering the entire life cycle of green power from generation, storage to consumption.

[0076] In summary, for the energy storage power supply charging type identification, authentication, and consumption metering system and method of the present invention, through PSD and autocorrelation function analysis, the system can accurately distinguish green power and pseudo-green power, greatly reducing the fraud risk and significantly improving the accuracy of green power identification; the application of blockchain technology and ECDSA algorithm ensures the immutability and authenticity of data, providing a reliable technical guarantee for green power trading and enhancing the data security and credibility. Among them, the unique BMS identifier mechanism effectively prevents device counterfeiting and improves the security of the entire system. Every link from green power generation to final consumption is recorded on the blockchain, realizing complete carbon footprint tracking. The automatic calculation and real-time update of carbon credits improve the efficiency and fairness of green power trading, encouraging more participants to join the green energy ecosystem. The system's modular design enables the system to adapt to different scales and types of green power projects, with good scalability, and can provide strong technical support for the efficient utilization of new energy and the achievement of carbon neutrality goals, and is expected to play an important role in promoting the development of the green energy industry and addressing climate change.

[0077] It should be noted that the above-mentioned drawings are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present invention, rather than for limiting purposes. It is easy to understand that the processes shown in the above-mentioned drawings do not indicate or limit the chronological order of these processes. Additionally, it is also easy to understand that these processes can be executed synchronously or asynchronously, for example, in multiple modules.

[0078] It should be understood that although the above is described in a certain order, these steps are not necessarily executed in the above order sequentially. Unless there is a clear indication in this article, the execution of these steps has no strict order limitation, and these steps can be executed in other orders. Moreover, a part of the steps in this embodiment may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same moment, but can be executed at different moments, and the execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0079] In the third aspect of the embodiments of the present invention, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory, and when the computer program is executed by the processor, the method of any one of the above embodiments is implemented.

[0080] In this computer device, there is a processor and a memory, and may further include: an input system and an output system. The processor, the memory, the input system, and the output system can be connected through a bus or other means. The input system can receive input digital or character information, and generate signal inputs related to the identification, authentication, and consumption metering migration of the energy storage power supply charging type. The output system may include a display device such as a display screen.

[0081] As a non-volatile computer-readable storage medium, the memory can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the energy storage power supply charging type identification, authentication, and consumption metering methods in the embodiments of the present application. The memory can include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created by the use of the energy storage power supply charging type identification, authentication, and consumption metering methods, etc. In addition, the memory can include high-speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory may optionally include a memory remotely set relative to the processor, and these remote memories can be connected to the local module through a network. Examples of the above network include but are not limited to the Internet, an enterprise internal network, a local area network, a mobile communication network, and combinations thereof.

[0082] In some embodiments, the processor may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips. The processor is generally used to control the overall operation of the computer device. In this embodiment, the processor is used to run the program code stored in the memory or process data. In this embodiment, the processors of multiple computer devices of the computer device execute various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory, that is, implement the steps of the energy storage power charging type identification, authentication, and consumption metering methods in the above method embodiments.

[0083] It should be understood that, without conflict, all the embodiments, features, and advantages described above for the energy storage power charging type identification, authentication, and consumption metering methods according to the present invention equally apply to the energy storage power charging type identification, authentication, consumption metering, and storage medium according to the present invention.

[0084] Those skilled in the art will also understand that the various exemplary logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability of hardware and software, a general description has been given of the functions of the various illustrative components, blocks, modules, circuits, and steps. Whether this function is implemented as software or hardware depends on the particular application and the design constraints imposed on the overall system. The functions that can be implemented in various ways by those skilled in the art for each specific application, but such implementation decisions should not be construed as causing a departure from the scope of the disclosure of the embodiments of the present invention.

[0085] Finally, it should be noted that the computer-readable storage medium (e.g., memory) in this article can be a volatile memory or a non-volatile memory, or can include both volatile memory and non-volatile memory. By way of example and not limitation, non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM), which can serve as an external cache memory. By way of example and not limitation, RAM can be obtained in various forms, such as synchronous RAM (DRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct Rambus RAM (DRRAM). The storage devices of the disclosed aspects are intended to include, but are not limited to, these and other suitable types of memory.

[0086] The various exemplary logic blocks, modules, and circuits described in connection with the disclosure herein can be implemented or executed using the following components designed to perform the functions herein: a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination of these components. The general-purpose processor can be a microprocessor, but alternatively, the processor can be any conventional processor, controller, microcontroller, or state machine. The processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP and / or any other such configuration.

[0087] The above are the exemplary embodiments disclosed in the present invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments disclosed in the claims of the present invention. The functions, steps, and / or actions of the method claims according to the disclosed embodiments herein need not be performed in any particular order. In addition, although the elements disclosed in the embodiments of the present invention can be described or claimed in individual form, they can also be understood as plural unless explicitly limited to the singular.

[0088] It should be understood that, as used herein, unless the context clearly supports exceptions, the singular form "a" is also intended to include the plural form. It should also be understood that the "and / or" used herein refers to any and all possible combinations of one or more of the associated listed items. The serial numbers of the disclosed embodiments of the present invention above are only for description and do not represent the advantages or disadvantages of the embodiments.

[0089] Those of ordinary skill in the art should understand that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope (including the claims) disclosed by the embodiments of the present invention is limited to these examples; under the concept of the embodiments of the present invention, the technical features in the above embodiments or different embodiments can also be combined, and there are many other variations in different aspects of the embodiments of the present invention as above, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention shall be included in the protection scope of the embodiments of the present invention.

Claims

1. A system for identifying, authenticating, and measuring the charging type of an energy storage power source, characterized in that: It includes the following components: Green energy identification and metering module for power generation equipment, used to identify green electricity through power spectrum density and autocorrelation function analysis; The blockchain of energy storage equipment integrates the battery management module to generate a unique token and verify the identity of green electricity; Communication module, used to encrypt and transmit power generation, storage and consumption data to blockchain nodes and carbon credit management platform; The carbon credit management platform generates carbon credits based on green electricity data on the blockchain according to preset rules and feeds them back to the user end.

2. The energy storage power supply charging type identification, authentication, and consumption metering system according to claim 1, characterized in that: The power generation equipment is a green electricity generation device including a photovoltaic panel and a wind turbine; The green energy identification and metering module of the power generation equipment includes: A signal acquisition unit, used for real-time sampling of green power input signals; The characteristic analysis unit is used to calculate the signal power spectrum density using the Welch method and combine it with the autocorrelation function analysis to determine whether the signal is green electricity, where green electricity is a stationary random signal and pseudo green electricity is a periodic signal; The blockchain writing unit is used to generate a unique token from green electricity generation data and write it into the blockchain through a smart contract.

3. The energy storage power supply charging type identification, authentication, and consumption metering system according to claim 2, characterized in that: The signal analysis method of the green energy identification and metering module includes: The power spectrum density of the input signal is calculated using the Welch method. If the power spectrum density has no obvious periodic peak in the frequency domain, it is determined to be green electricity. The autocorrelation function is calculated. If the autocorrelation value decays to zero as the delay increases, the green electricity identity is further confirmed.

4. The energy storage power supply charging type identification, authentication, and consumption metering system according to any one of claims 1 to 3, characterized in that: The blockchain integrated battery management module includes: Green power verification unit: communicates with power generation equipment to verify the green power identity and the legitimacy of blockchain tokens; Metering unit: statistics on green power storage and charging and discharging data; Battery Management Unit: Generates a tamper-proof token based on the hardware serial number and integrates the blockchain unique identifier.

5. The energy storage power supply charging type identification, authentication, and consumption metering system according to claim 4, characterized in that: The method for generating a blockchain unique identifier of the blockchain integrated battery management module is as follows: Extract the hardware serial number of the blockchain integrated battery management module and generate the initial identification through the hash algorithm; Use an asymmetric encryption algorithm to sign the identity and generate a tamper-proof token; After binding the Token to the green electricity data, it is written into the blockchain through a smart contract.

6. The energy storage power supply charging type identification, authentication, and consumption metering system according to claim 5, characterized in that: Token verification methods include: When the energy storage device receives green electricity, the smart contract is called to verify the matching of the token and the blockchain record; If the verification fails, an alarm is triggered and green electricity is prohibited from accessing the energy storage device.

7. The energy storage power supply charging type identification, authentication, and consumption metering system according to claim 6, characterized in that: The communication module comprises: 4G / 5G transmission unit: upload power generation, storage and consumption data to the cloud server; Blockchain nodes: deploy smart contracts to achieve data on-chain and token verification; Among them, the 4G / 5G transmission unit of the communication module meets the following requirements: Use AES-256 encryption algorithm to protect transmission data; Supports dynamic adjustment of data transmission frequency to adapt to battery pack clusters of different sizes.

8. The energy storage power supply charging type identification, authentication, and consumption metering system according to claim 1, characterized in that: The points generation rules of the carbon points management platform are as follows: Green electricity generation is converted into carbon credits at a ratio of 1:1, and the consumption is weighted at 0.5 times the weight. The points allocation records are written into the blockchain through smart contracts and can be publicly queried by users.

9. The energy storage power supply charging type identification, authentication, and consumption metering system according to claim 8, characterized in that: The energy storage device is also provided with a green energy consumption and metering module, and the green energy consumption and metering module includes: Energy storage master control module, used to control green power consumption strategy; Bidirectional inverter module for storage and release control of green electricity; The load module is the final consumption terminal of green electricity. It is used to count and measure the consumed electricity in real time and synchronize it to the blockchain.

10. A method for identifying, authenticating, and measuring the charging type of an energy storage power source, characterized in that: The method is performed by the energy storage power supply charging type identification, authentication, and consumption metering system according to any one of claims 1 to 9, and the method comprises the following steps: Collect charging signals, analyze signal statistical characteristics through power spectrum density and autocorrelation function, and distinguish green power from pseudo green power; Generate a blockchain token for the green electricity that has passed the verification, and bind it to the unique identifier of the blockchain integrated battery management module before uploading it to the chain; Energy storage equipment performs green electricity storage and consumption operations based on the legitimacy of Token; The carbon credits platform automatically allocates credits based on on-chain data.

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