228 results about "Carbon credit" patented technology

Carbon usage is monitored and recorded from emissions of one or more sources associated with carbon consumers. Public and private metadata about sources are maintained. A block chain records carbon credit transactions representing savings in the carbon footprint.

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.

An enterprise system may include one or more devices that perform respective operations of an enterprise and a sustainability platform system. The sustainability platform system may obtain a sustainability model representative of a state of operations of the enterprise and a current sustainability action plan associated with improving one or more sustainability parameters of the enterprise. The sustainability platform system may also receive updated carbon credit data, simulate an effect of the current sustainability action plan on the sustainability parameters based on the updated carbon credit data (generating simulated sustainability parameters), and determine whether the current sustainability action plan is effective based on a comparison of the simulated sustainability parameters to sustainability target data. In response to determining that the current sustainability action plan is effective, the sustainability platform system may send commands to the devices to maintain their operations according to the current sustainability action plan.

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 discloses a carbon emission accurate accounting system based on big data analysis, and relates to the technical field of carbon emission management, and the system comprises a data obtaining module which obtains carbon emission data in real time, and carries out the processing and fusion of the data based on a distributed big data storage technology; the carbon emission accounting engine module is used for processing the fused data based on a big data analysis algorithm, establishing a carbon emission calculation model and calculating the carbon emission; the intelligent prediction module is used for predicting future carbon emission by adopting a deep learning model; the carbon credit automatic evaluation and transaction module establishes a carbon credit scoring algorithm, dynamically evaluates the carbon emission reduction performance of the user based on the real-time carbon emission data and the carbon emission prediction data, and automatically generates the carbon credit. According to the invention, by integrating multi-source large-scale data and combining adaptive data weighting, a deep learning prediction model and a carbon credit automatic evaluation algorithm, accurate accounting, dynamic prediction and intelligent carbon credit evaluation of carbon emission can be realized.

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.

A climate technology ecosystem is disclosed that automates the collection and processing of data by way of programmed computer software to automatically generate uniform encrypted carbon credit certificates that can be traded on peer-to-peer exchanges or as derivatives. The Autonomous Climate Technology Ecosystem (ACTE) creates a network of information derived from nine systems designed to: sensor, qualify, measure, encode, encrypt, issue, index, register, and exchange, all of which rely upon artificial intelligence to identify, calculate and quantify the source and origin of carbon and automatically generate uniform encrypted carbon credit certificates based upon the nature and attributes of the carbon and associated CO2e.

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 livestock industry must be able to easily calculate the amount of emissions reduction required to utilize the carbon credit system, so that livestock breeders who raise livestock to reduce greenhouse gases emitted from their manure and waste can do so. [Solution] The number of livestock raised in each unit period is obtained, the operating status of the treatment tank that performs excrement treatment in each unit period is received, and the number of livestock and the operating status in the corresponding unit period are used to calculate a second emission amount when the livestock excrement is treated using a second excrement treatment method.

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 carbon credit marketplace (CCM) implements a platform for the exchange, and rating, of carbon credits and associated offsets. The platform receives entity carbon credit data as well as structured and unstructured data from disparate sources including general economic data sources, government data sources, and proprietary data sources. The received data is used by a carbon credit rating model to assign a carbon credit rating for a particular carbon credit, offset, or capture. Compliance with governmental regulations is achieved through the exchange, or sale of carbon credits and / or offsets.

A method for carbon sequestration and management through a wood storage project includes: determining source of wood used for storage for carbon sequestration with an optimization technique; preparing storage facilities (Wood Vaults) with an optimized ratio between carbon sequestration efficiency and cost; storing the sourced wood in the storage facilities; monitoring, evaluating, verifying and certifying carbon credit for the wood storage project; and conducting carbon credit trade for the wood storage project.

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.

Climate change poses a significant threat to human well-being, the planet's sustainability, and the global economy, mainly caused by excessive greenhouse gas emissions, particularly CO2. To combat this phenomenon, various tools have been adopted, with the most effective being the carbon emission trading scheme established by the United Nations which created a system that monetizes and reduces CO2 emissions. However, the current system faces multiple challenges, such as manipulation, complexity, and a lack of integrity, preventing it from achieving its ultimate objectives. To tackle these issues, blockchain technology has been proposed due to its distinguishing characteristics of security, traceability, decentralization, and trust. However, blockchain frameworks existing in the literature have been inefficient and inadequate. This research aims to design and develop a practical blockchain system that employs smart contracts and Internet of Things (IoTs) with the use of oracles to solve the problems facing the present carbon emission trading scheme and elevate its operations. The developed smart contracts automate the participating entities' registration and suspension processes and emitters released CO2 measurements as well as carbon credit assignment and trading operations. Our smart contracts were simulated, tested and analyzed where results proved the efficiency, integrity, traceability and security of all processes under the carbon trading market at a reduced cost.

Embodiments of the present disclosure provide a computer-implemented method for executing one or more sustainable vehicle fuel (SVF) operations related to an SVF platform. The computer-implemented method includes requesting SVF supplier source data from one or more SVF suppliers, where the SVF supplier source data can be configured in various data formats. The computer-implemented method also includes aggregating the SVF supplier source data in order to determine and display a current SVF availability associated with a respective SVF supplier associated with a respective travel hub. The computer-implemented method also includes determining, via an SVF optimization model, a suggested SVF mixing ratio for a vehicle associated with a user profile, as well as a carbon offset and / or a carbon credit generated by the user profile for using SVF. The carbon credit and / or carbon offset can be generated by verifying one or more user purchases of SVF on a blockchain-enabled database.

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.

Carbon dioxide containing gas is collected from a point source or atmosphere and is dried, treated, and compressed. The compressed gas is fed into an algae reactor which maintains optimal conditions for algae growth. The algae grows until it reaches sufficient density to be harvested. The harvested algae is processed and packaged for sale. Additionally, revenues may be earned by quantifying the amount of CO2 captured and sequestered by the algae and determining the carbon credit equivalent value. Byproducts may additionally be sold in addition to equipment sales and licensing.

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.

Provided are a rice cultivation management device, a rice cultivation management method, and a rice cultivation management system that acquire one or more types of satellite data of a paddy field, calculate a water index for each day of each of a plurality of water management sections included in the paddy field on the basis of the satellite data, and classify the status for each day of each of the plurality of water management sections on the basis of the water index. It is possible to classify the daily state of each of the plurality of water management sections on the basis of the water index, store the daily state data in a calendar (time-series database), detect the water management technique that is implemented using data, and check the contents of a log book of the farmer. Furthermore, it is possible to replace the log book with the calendar in the future by using data from a water level sensor in combination. It is also possible to more accurately estimate the daily greenhouse gas emissions from individual paddy fields for the purpose of creating carbon credits.

To provide a calculation method for emission reductions using a management system, allowing livestock breeders rearing livestock in such a manner as to reduce greenhouse gas emissions from the livestock and excrement thereof in a livestock industry, to easily calculate emission reductions for using a carbon credit system.SOLUTION: A calculation method for emission reductions includes: a livestock counting step of causing a livestock counter installed in a farm in which a plurality of pigs are reared, to count the number of reared pigs that are reared within a predetermined period and are fed with amino acid balance-improved feed; a base emission calculation step of allowing an emission reduction calculation unit to calculate base emissions of greenhouse gases based on the number of pigs counted in the livestock counting step; an improved emissions calculation step of calculating improved greenhouse gas emissions when amino acid balance-improved feed is fed; and an emission reductions calculation step of calculating emission reductions in a predetermined period by using the base emissions and the improved emissions.SELECTED DRAWING: Figure 3

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.

Systems and methods are provided for collecting data on multiple mitigation activities and generating carbon credits based on the data. The systems and methods incorporate the use of digital measurement, reporting, and verification (MRV) technologies. The system includes one or more application programming interfaces (APIs) for accessing data on the mitigation activities, and a communications module for real-time communication with third party verifiers and offset registries. The system also includes a computational module for qualification and quantification of the environmental benefits based on the collected data, and a reporting module for generating reports on the carbon credits and the mitigation activities. The system may also include a credit trading module to market and sell the credits.

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.