149 results about "Carbon credit" patented technology

The invention discloses an energy storage transaction and carbon credit management system and method based on a block chain, and relates to the technical field of block chains, and the system comprises four modules: a dynamic carbon factor accounting module obtains data in real time, calculates the carbon emission reduction amount, and generates a carbon credit value; the heterogeneous cross-chain interoperation transaction module is connected with an energy chain and a carbon chain, and binds carbon credit and transaction records; the multi-target reinforcement learning energy storage scheduling optimization module is combined with a multi-target deep network algorithm to generate a strategy and a proportion; the enhanced carbon account module stores data and generates a voucher. The system has the advantages that data are acquired in real time through the dynamic carbon factor accounting module, the equivalent carbon emission reduction amount is calculated, the dynamic carbon credit value is generated, the problem of carbon credit calculation lag is solved, and accurate calculation and timely issuing of the carbon credit are realized; and meanwhile, by utilizing a hash time lock and a zero-knowledge proof verification mechanism of the heterogeneous cross-chain interoperation transaction module, the carbon credit is bound with the transaction record, and the energy chain and the carbon chain are connected, so that the mobility of the transaction and the integration of carbon emission reduction are improved.

The invention relates to the technical field of carbon sink calculation, in particular to a forestry carbon sink calculation model, a forestry carbon credit calculation method and a storage medium. The model comprises an overground biological carbon sink amount estimation module used for calculating overground biological carbon sink data of a target area, an underground soil carbon sink amount estimation module used for calculating soil carbon sink data of the target area, and a litter carbon reserve estimation module used for calculating litter carbon sink data of the target area. The combined loss calculation module is used for calculating carbon loss data; and the final carbon sink total quantity fusion module is used for calculating the carbon sink quantity according to the aboveground biological carbon sink data, the soil carbon sink data, the litter carbon sink data and the carbon loss data. A forestry carbon sink calculation model based on multiple dimensions is established through multiple types of carbon sink estimation modules, and the problem that the requirement for rapid authentication of the global carbon market cannot be met due to high manual dependency is solved; the problems of low calculation precision, high cost and the like caused by insufficient model dynamics, single model calculation dimension and the like are solved.

The invention relates to a community demand response carbon emission reduction data monitoring method based on the Internet of Things technology, and the method comprises the following steps: S1, collecting multi-source heterogeneous data of community carbon emission data, and carrying out the preprocessing, and obtaining a basic data set; s2, performing feature engineering and depth representation according to the basic data set, and constructing a high-dimensional feature vector set; s3, constructing a new energy output prediction model, and predicting a new energy output confidence interval based on the high-dimensional feature vector set; s4, constructing a load demand elastic prediction model, and predicting a rigid load and flexible load adjustment boundary based on the high-dimensional feature vector set; s5, based on the predicted new energy output confidence interval and the rigid load and flexible load adjustment boundary, adopting multi-objective optimization control to obtain an optimal equipment control instruction set; and S6, performing control based on the optimal equipment control instruction set, obtaining the verification emission reduction amount and a user response log, and generating a carbon perbenefit integral. According to the invention, the community can flexibly adjust the energy supply strategy according to the new energy volatility and the user demand.

The invention provides a blue carbon market adaptive accounting method based on multi-source data and Bayesian updating, and belongs to the technical field of natural resource planning and ecological management. The method comprises the following steps: firstly, constructing a standardized multi-source fusion data set through a systematic process, and then preprocessing collected data to generate a standardized blue carbon multi-source fusion data set; then, through a Bayesian-based carbon reserve estimation model, outputting a monitoring point carbon reserve prior value, fusing a monitoring point carbon reserve mean value with a spatial prior value, and updating monitoring point carbon reserve distribution; and finally, constructing a carbon credit risk index system, calculating risk indexes of the plot layer and the region layer, updating a plot layer carbon reserve mean value by using the updated monitoring point carbon reserve distribution, and generating a blue carbon project reference transaction price according to the carbon reserve mean value and the risk indexes. According to the invention, a full-chain blue carbon intelligent accounting system is constructed, and interdisciplinary fusion of an ecological model, deep learning and a carbon market mechanism is realized.

The invention relates to a running integral incentive method based on zero-knowledge proof and cross-chain carbon credit mapping, which comprises the following steps of: modeling a running behavior into a semantic condition, and locally calculating and generating zero-knowledge proof in equipment; estimating individual energy output based on the physiological parameters and the motion type; comparing the carbon emission of the same traffic trip mode, and estimating an alternative emission reduction effect; a carbon reduction value is compared with intention and behavior, and energy and carbon are converted into a core model; introducing zero-knowledge proof to derive a carbon credit identity label on a chain, wherein the label is generated by two technologies of semantic proof and carbon estimation; after running is completed each time, the user obtains an anonymous carbon credit anchor point on the chain; the anchor point records a zero-knowledge proof abstract, a carbon reduction value, a timestamp and an intention label; a carbon credit atomic mapping protocol is adopted, and a carbon credit anchor point on a local chain is inseparably mapped to a mainstream carbon credit public chain at a time; the individual carbon emission reduction contribution is accurately quantified, and atomic cross-chain mapping and circulation of the carbon credit assets are realized.

The illustrative embodiments provide a data platform, system and method for utilizing carbon credits through blockchain-based tokenization. The platform receives carbon utilization data corresponding to at least one carbon credit and executes a smart contract on a blockchain network based on the received data. Execution of the smart contract generates one or more blockchain tokens that embed metadata including a hash of the carbon utilization data and a unique security identifier. The platform performs electronic transactions for the tokens by propagating transactions for distributed consensus, verifying token authenticity through comparisons with distributed-ledger records, or generating immutable electronic records indicating tracking information for the carbon credit. Records of the electronic transactions are stored in a distributed ledger as immutable entries linking token activity to corresponding carbon utilization data.

A system and method for an AI enhanced smart grid framework with optimized incentive capabilities. The present invention optimizes energy efficiency by generating personalized retrofit plans, optimal energy dispatch schedules, and customized financial incentives. Machine learning algorithms analyze homeowner profiles, energy consumption patterns, and market conditions to recommend tailored energy-saving solutions. The system integrates with funding institutions and aggregators to streamline retrofit financing and carbon credit management. By leveraging AI and ML techniques, this innovative approach aims to accelerate the adoption of energy-efficient technologies, reduce homeowner energy costs, and contribute to a more sustainable energy future.

The invention discloses a building energy scheduling method and platform based on regional energy carbon management, and relates to the technical field of building energy scheduling. The method comprises the steps of multi-dimensional data acquisition, energy-carbon collaborative optimization, dynamic scheduling execution, block chain energy transaction and community-based energy collaboration. The platform comprises a multi-dimensional data acquisition module, an energy-carbon collaborative optimization module, a dynamic scheduling execution module, a block chain energy transaction module and a community collaborative module, and adopts a cloud edge collaborative architecture and a digital twin system. According to the method, double optimization of economy and carbon targets is realized through a cooperation mechanism of a genetic whale algorithm and an NSGA-II algorithm, an energy and carbon credit closed-loop system is constructed by using a block chain, idle energy storage resources are activated in combination with community cooperation, dynamic mapping and early warning are realized by means of digital twinning, and the method is high in practicability. The problems that in the prior art, economy and carbon targets are difficult to balance, energy transaction trust is lost, the user participation degree is low, and carbon management and control lack perspectiveness are solved.

The invention relates to the technical field of carbon credit transaction, in particular to a carbon credit automatic transaction system based on an intelligent contract, which comprises an intelligent contract self-adaptive updating management module, a carbon credit evaluation module, an intelligent contract module, a transaction matching module and a user interface module, the intelligent contract self-adaptive updating management module is responsible for continuous monitoring, verification and updating of the intelligent contract; the carbon credit evaluation module evaluates the submitted emission reduction project; the intelligent contract module generates an intelligent contract required for executing a carbon credit transaction; the transaction matchmaking module optimizes the transaction process; and the transaction recording module records detailed information of each carbon credit transaction on the block chain. According to the invention, current business requirements can be met, and long-term foresight and adaptability are realized, so that the carbon credit trading platform can effectively cope with development and change of the future market.

The invention discloses an innovative carbon credit derivative transaction tool based on a block chain technology, relates to the field of carbon transaction and block chain application, and realizes efficient data processing, secure communication and cross-chain interaction by constructing a block chain architecture fusing cross-chain, quantum encryption and edge calculation. Building a dynamic self-adaptive carbon credit derivative digital model by using an artificial intelligence algorithm, and automatically adjusting parameters and evaluating values; a natural language processing technology and an intelligent matching and strategy transaction engine of various transaction strategy templates are integrated, so that intelligent transaction instruction processing and personalized strategy execution are realized; an intelligent risk management and control and compliance supervision system is constructed by means of a machine learning algorithm, risks are monitored in real time and automatically handled, and a distributed data sharing and privacy protection mechanism of technologies such as zero-knowledge proof and homomorphic encryption is adopted to guarantee data security and privacy.

The invention discloses a forest land restoration and carbon sink management system and method based on a three-dimensional cadastral model, and the method comprises the steps: integrating an earth surface forest right, an underground space right and a block chain information management right through the three-dimensional cadastral model, and collecting forest biomass and soil carbon library data in real time in combination with an Internet of Things sensor network; and data storage and carbon point transaction are realized based on a block chain multi-chain architecture. According to the scheme, the problems of unclear ownership and low data credibility in traditional forest land restoration are solved, the carbon sink value is converted into economic benefits, and the method is suitable for low-efficiency forest land ecological restoration and carbon asset management.

The invention discloses a carbon emission dynamic accounting method and system. The method comprises the following steps: collecting production equipment direct emission, logistics carbon emission, social media / satellite remote sensing and other abnormal event data; extracting unit yield carbon intensity and supply chain path sensitivity through principal component analysis; constructing a QUBO model and solving an optimal transportation path by using quantum annealing; training a prediction model in combination with the sudden emission risk index to output a carbon emission value; dynamically updating an emission factor library according to the cleanliness of the power grid, and accelerating generation of a confidence interval by adopting a quantum random number generator; and when the predicted value exceeds the threshold value and the lower limit of the confidence interval is higher than the threshold value, triggering carbon capture, carbon credit purchase or production regulation compensation according to the priority. The system correspondingly comprises a multi-mode acquisition module, a calculation optimization module, a dynamic accounting module and a carbon compensation module. Full-chain real-time carbon tracking and intelligent compensation are achieved, the problems of traditional accounting data isolation and compensation lag are solved, and the industrial carbon management accuracy is improved.

The illustrative embodiments provide a system, method, device, and platform for managing carbon credits. Information corresponding to carbon credits with carbon emissions are received. A smart contract is executed on a data platform of a blockchain network based at least on the received information. The smart contract specifies one or more parameters for transactions corresponding to the carbon credits. One or more tokens for performing transactions in accordance with the smart contract are generated utilizing the data platform. Transaction for the one or more tokens are performed in accordance with the smart contract. The transactions include at least verifying the authenticity of the one or more tokens. Records of the transactions for the tokens a stored in a distributed ledger associated with the blockchain network.

The invention discloses a zero-carbon park carbon accounting method and system based on Transform, and the method comprises the steps: collecting multi-source heterogeneous carbon data of a zero-carbon park, completing the preprocessing, and generating a fusion input tensor and a corresponding data quality identifier; inputting the fusion input tensor into a multi-scale time sequence fusion coding model, and generating a time sequence feature intermediate representation through multi-branch coding processing adaptive to different data sources and sampling granularities; emission source contribution degree decomposition information is obtained through a category-constrained carbon flow tracking attention module, uncertainty analysis is completed to obtain a target carbon accounting result and confidence interval data, and a compliant carbon integral scheme and an auditable evidence packet are generated through a carbon integral generation optimization module; therefore, the problems of difficulty in aligning multi-source heterogeneous data of the zero-carbon park, insufficient consideration of period and mutation features and poor traceability of accounting results are effectively solved, the precision and compliance of carbon accounting are greatly improved, and a complete closed loop from carbon accounting to incentive management is realized.

An example operation includes comparing a first set of driving styles for a vehicle to a second set of driving styles for one or more similar vehicles in a geographic area over a period, wherein the first set of driving styles affects a carbon footprint of the vehicle and the second set of driving styles affects another carbon footprint of the one or more similar vehicles; determining a carbon credit when the carbon footprint of the vehicle is lower than the another carbon footprint of the one or more similar vehicles, by a threshold, based on the comparing; and applying the carbon credit to the vehicle.

The invention relates to the technical field of carbon sink calculation, in particular to a grassland carbon sink calculation model, a grassland carbon credit calculation method and a storage medium. And calculating overground biological carbon reserve, underground root carbon reserve and soil organic carbon content by using a multi-task learning model based on a Transform architecture and a bidirectional long-short-term memory network. According to the method, multi-dimensional calculation of the carbon sink amount is achieved, the model generalization ability and the calculation precision are ensured, meanwhile, the manual dependency degree is reduced, and the calculation efficiency is further improved.

Intelligent methods, processes, and systems are disclosed for generating synthetic eco-crypto tokens for carbon credits and may include the steps of identifying the amount of carbon credits saved for a product or service purchased by a customer by using data centric artificial intelligence (AI) working with trained data sets. The trained data sets may be loaded to knowledge graphs and a unique green reward identification for a customer may be combined to then generate a new synthetic data which may be used to generate an eco-crypto token. Responsible AI may be used to generate the eco-crypto tokens in a safe, trustworthy, and ethical fashion for use in other transactions for products and services.

A system for measuring greenhouse gases and automatic generation of carbon credits in forest areas, based on real-time data, which allows online analysis, generating automatic certification of carbon credits. The system presents a microprocessor unit (UP) that receives signals from sensors measurement of gases (Sg) analyzed in a chromatography unit High Efficiency Liquid (HPLC) and rainfall sensors (Sp). The data is processed in the local processing unit (UP) and transmitted to a remote processing unit (UPr) through the communication module (MC), using transmission protocols of data. The processed data generates credit certificates for authenticated and authorized by the UNFCCC (Convention-United Nations Framework on Climate Change), ensuring its internationally recognized validity.

A process for segregating attributes of carbon credits including extracting pure CO2 equivalent from existing carbon credits, tokenizing the extracted pure CO2 equivalent and recording the tokenized pure CO2 equivalent on a distributed ledger. The process includes generating a quality certification mark with an embedded QR code when the tokenized pure CO2 equivalent is used for voluntary offsetting. The embedded QR code provides a link to the distributed ledger for independent verification of offsetting claims. The process includes segregating additional attributes from the existing carbon credits, wherein the additional attributes represent social or environmental benefits associated with carbon projects. The process includes tokenizing the segregated additional attributes and recording the tokenized additional attributes on the distributed ledger or a separate distributed ledger. The distributed ledger is a blockchain wherein the tokenized pure CO2 equivalent is represented as a smart contract on the blockchain.

The present invention is directed to a distributed ledger-based platform for generating and trading carbon NFTs representing carbon credit projects. The carbon NFTs each represent 1 ton of carbon emissions and are able to be traded in real-time. In one embodiment, the platform produces at least one non-fungible token (NFT) representing carbon credits, wherein the at least one NFT includes a carbon credit issuance serial number, a name of the associated project, a location (e.g., geospatial coordinates) of the project, a project start date, a project end date, a project duration, a company associated with the project, at least one image of the project, and / or an expiration date for the carbon credit.

The present invention relates to a household low-carbon energy optimization method and system that considers green electricity consumption and V2H. The method includes: collecting historical household electricity consumption statistics, establishing a carbon emission baseline scenario for household electricity consumption, and constructing a carbon credit emission reduction accounting model based on the emission reduction scenario; establishing a load flexibility optimization model based on the household's non-temperature-controlled flexible load; constructing an air conditioning load model; constructing an electric vehicle load model based on user commuting characteristics, electric vehicle operating parameters, and charging pile operating parameters; and constructing a household energy economic low-carbon optimization model based on the established model. The model is solved with the goal of minimizing electricity purchase costs and comfort losses and maximizing carbon emission reductions, thereby obtaining an optimized household economic low-carbon energy consumption plan. Compared with the existing technology, the present invention achieves quantification of the carbon reduction potential contained in household low-carbon energy consumption through multiple household green electricity consumption methods, scientifically guides household users to economical, low-carbon and comfortable electricity consumption, and facilitates the achievement of energy conservation and carbon reduction goals.

The illustrative embodiments provides a system, method, device, and platform for managing carbon credits utilizing tokens. Carbon credits associated with a unit of carbon emissions are received. The carbon credits are tokenized to create tokens associated with each of the carbon credits. The carbon credits are marketed to authorized parties. Transactions for the tokens associated with the carbon credits are performed. The transactions for the tokens are documented.

The objective is to provide a method for businesses to efficiently manage and calculate their greenhouse gas emissions. [Solution] A method for supporting the creation of carbon credits by a business operator according to one embodiment of the present invention, wherein the control unit of the management terminal receives answers to predetermined questions from the business operator terminal, receives information on assets held by the business operator from the business operator terminal, and calculates a score for the possibility of creating carbon credits based on the answers and the asset information.

The objective is to provide a method for businesses to efficiently manage and calculate their greenhouse gas emissions. [Solution] A method for recommending carbon credits for a business operator according to one embodiment of the present invention, wherein the control unit of a management terminal receives search conditions for carbon credits from the business operator terminal, refers to carbon credit information stored in the storage unit of the management terminal, extracts one or more carbon credits that match the search conditions, and transmits the extracted carbon credits to the business operator terminal.

To provide a carbon credit granting system, a method and a program which grant carbon credit to a CO2 discharger to promote a carbon offset system, while granting an incentive to an ordinary consumer.SOLUTION: In a carbon credit granting system 100, a server 10 includes: a purchase price grasp unit which grasps a purchase price of commodities or service purchased by a consumer (consumer side communication terminal 20) from an enterprise or an autonomous community (enterprises side communication terminal 30); an incentive granting unit which grants an incentive calculated on the basis of a predetermined incentive ratio with respect to the purchase price to the consumer; and a carbon credit granting unit which grants a carbon credit calculated on the basis of a predetermined granting ratio with respect to the purchase price to the enterprise or the autonomous community. The server performs purchase and sale of the carbon credit or application of the carbon credit, via a J-credit directory system etc. of a governmental carbon credit management computer 40.SELECTED DRAWING: Figure 1

Computer Device for Carbon Credit Accounting and Financial Reporting in Oil and Gas Enterprises

A method for scaling carbon related woody surface gas exchange (WSGE) from small-area measurements to a larger scale, comprising the steps of: providing a woody surface area allometry, providing a WAI map to estimate a current and a historical woody methane uptake, providing a WSGE model based on bark surface area across a region of interest; combining the WAI map with WSGE model to estimate total current and historical WSGE, and generating a verified carbon credit based upon the total current and historical WSGE.

An Internet of Things (IoT) digitization module featuring a compact dual hardware architecture designed for electrical appliances. The system is divided into two physically separate units: a cable-mounted external device (Device 1) and an appliance-internal device (Device 2). Device 1 enables real-time monitoring of power consumption, runtime, and calculation of carbon emissions, and features quad wireless communication (GSM, Wi-Fi, Bluetooth, and SMS). Device 2 contains a relay to enable or disable power delivery. The two devices communicate directly via a peer-to-peer connection, rendering the appliance tamper-proof; removal of the external cable disables the internal relay. The module integrates with cloud platforms to facilitate financing management, verifiable carbon credit generation, and secure remote control, thereby addressing high upfront costs and usage visibility in emerging markets.

This invention proposes a carbon credit mechanism and points allocation method for large-scale events based on blockchain technology, relating to the field of dynamic allocation of carbon credits based on blockchain. The method includes: integrating ambient temperature data to generate multi-dimensional carbon reduction data for individual emission reduction behaviors; extracting cluster centers for each type of emission reduction behavior and their corresponding ambient temperature data to construct an individual satisfaction function; dynamically calculating the weights of individual emission reductions and individual satisfaction based on real-time carbon prices published in the local carbon market, combined with the entropy weight method, to generate individual carbon credit allocation factors; and calculating the carbon credits for each individual within a time window based on these individual carbon credit allocation factors, and writing the carbon credits into their corresponding blockchain account. This invention enables dynamic correlation assessment between individual emission reduction behaviors and environmental factors in large-scale events, improving the fairness and incentive effectiveness of carbon credit allocation, while ensuring data privacy and blockchain traceability.