34 results about "Carbon flow" patented technology

This invention discloses a digital carbon monitoring system and platform, comprising: a carbon production collaborative analysis module that analyzes the carbon production correlation between production line-level carbon emission data and process-level production cycle data in a carbon flow time series graph, penetrating carbon emission data to specific processes and equipment; a real-time carbon reduction control module that generates production cycle fine-tuning instructions based on the real-time deviation between process-level carbon emission data and preset carbon emission upper limits; a dynamic optimization management module that corrects the carbon production correlation based on the changing trends of carbon production correlation in multiple carbon flow time series graphs; and a park-level carbon flow aggregation module that aggregates multiple carbon flow time series graphs into a park-level carbon flow analysis report and generates a park carbon quota allocation scheme. This invention achieves penetrating management and real-time carbon reduction control of carbon emission data by constructing a dynamic coupling analytical model of carbon flow and production flow, and dynamically optimizes the carbon production correlation through a dual closed-loop feedback mechanism, while simultaneously realizing carbon quota allocation from the production line level to the park level, thus improving the accuracy and synergy of carbon management.

The invention relates to a low-carbon park optimal scheduling method based on dynamic carbon flow tracking, and the method comprises the steps: constructing and describing a park integrated energy system multi-energy flow coupling model, and building a dynamic carbon flow calculation model based on a dynamic carbon flow tracking mechanism; carrying out carbon constraint based on a dynamic carbon flow calculation result by using a park integrated energy system hour-level rolling optimization scheduling model with operation cost and carbon emission minimization as a target; and converting the optimal scheduling model into a mixed integer linear programming problem, and obtaining a Pareto optimal solution set by using an epsilon-constraint method and taking the minimum operation cost as a target and carbon emission as a constraint. Compared with the prior art, the method provided by the invention overcomes the defect that the traditional static accounting method cannot reflect the spatial-temporal dynamic characteristics of the carbon flow, and provides an accurate carbon measurement basis for implementing low-carbon scheduling in a park.

The application provides a line loss analysis method and system based on carbon flow tracking, and belongs to the technical field of power data anomaly analysis. CE = CE in ‑ CE o , CE The total loss carbon amount of the node i ; CE in The total input carbon amount of the node i ; CE o The total output carbon amount of the node i ; an XGBoost model for carbon amount anomaly screening is constructed based on a gradient decision tree XGBoost, and a target function of the model; each node in a network topology is analyzed based on the XGBoost model, and a carbon amount anomaly node is predicted based on the power and carbon emission density of each node; each user corresponding to the carbon amount anomaly node is subjected to power analysis, the power analysis includes high-voltage user abnormal power analysis and low-voltage user abnormal power analysis, and the type of abnormal situation existing in the user is obtained.

The present application relates to a kind of low-carbon park integrated energy system multi-agent collaborative carbon responsibility allocation method, steps include: the multi-source data of park is collected, with the minimum integrated energy system total operating cost as goal to carry out multi-energy flow optimization scheduling;With the dynamic correction model of two-way carbon flow considering the carbon flow transfer caused by energy storage charging and discharging process, dynamic carbon flow distribution matrix is constructed;Using load carbon responsibility decoupling allocation model, total load is decoupled into multiple sub-load categories, and different carbon responsibility allocation coefficients are given for each type of sub-load;With each interest party in park as the participant of game, Nash bargaining as collaborative optimization framework, maximum all participant utility gain as objective function, Shapley value as the basis for carbon responsibility allocation, multi-agent collaborative optimization is carried out, and the carbon responsibility allocation scheme of each subject is obtained in combination with user carbon responsibility allocation coefficient.Compared with prior art, the present application ensures the fairness, efficiency and operability of carbon responsibility allocation scheme.

The present application relates to the technical field of industrial park environmental governance, and discloses a park waste gas collaborative monitoring and carbon flow regulation system and method based on edge computing, which comprises a sampling pretreatment module, a sensor integration module, an edge computing unit, a dynamic regulation module and a wireless communication module, and the sensor integration module comprises a shared optical chamber, a tunable laser emitter and a detector array. Through the integrated sensing design of the shared optical chamber combined with time division multiplexing laser detection, the present application realizes the synchronous and accurate collection of multiple pollutants and carbon flow concentrations, and breaks the monitoring data island. At the same time, through the local closed-loop processing of the edge computing unit and the collaborative index threshold trigger mechanism, the present application eliminates environmental interference and avoids the problem of pollution reduction and carbon increase, and greatly improves the response speed and regulation coordination.

This application relates to the field of biotechnology, specifically disclosing a *Pichia pastoris* yeast, its construction method, and its applications. This application involves knocking out the *gas1* gene, which is related to β-glucan synthesis, in *Pichia pastoris*. By deleting the *gas1* gene, which encodes β-glucan in the cell wall of *Pichia pastoris*, this application reduces cell size, decreases the transfer distance from the cell surface to the nucleus, improves oxygen transfer and product secretion during high-density culture, and enhances fermentation efficiency. Furthermore, the *Pichia pastoris* yeast constructed using this application enhances the synthesis of the intracellular product bisabolol and also enhances its secretion capacity. This application, by reducing cell size and decreasing the carbon flow to cell wall polysaccharide synthesis while increasing the carbon source flow to target product synthesis, has significant implications for industrial production.

This invention relates to the field of industrial process management and optimization scheduling technology, and particularly to a method for tracking and optimizing carbon emission flows in a multi-product co-production process in the fluorochemical industry. First, a directed graph model of the product chain with process units as vertices is constructed. A multi-dimensional carbon emission flow calculation model is established, including direct carbon flows from fuel combustion, indirect carbon flows from purchased electricity and heat, direct carbon flows from the process itself, and carbon flows from the emission of fluorinated greenhouse gases. A dynamic evolution algorithm for node carbon potential and an iterative algorithm for reverse tracing of branch carbon flows are employed to achieve accurate tracking of spatiotemporally coupled carbon flows throughout the entire process. Using the time-varying carbon intensity coefficient as the core parameter, a dual-objective optimization scheduling model is established to minimize both total system carbon emissions and overall operating costs. An adaptive penalty mechanism with carbon constraints is introduced to solve for the optimal scheduling scheme, constructing a rolling optimization closed-loop control link for the production process. This invention effectively solves the problems of calculating carbon flows from the emission of fluorinated gases and allocating carbon flows among multiple products in the fluorochemical industry, achieving a synergistic improvement in carbon emission reduction and economic benefits.

This invention relates to a multi-energy flow carbon footprint tracking method based on a carbon memory matrix and conservation constraints, belonging to the technical fields of energy internet, industrial carbon management, and intelligent manufacturing. It constructs a multi-source energy-carbon coupled data foundation to achieve unified data across multiple time scales; establishes an energy storage carbon memory matrix model with time and temperature hierarchies to characterize the dynamic evolution of carbon intensity in the energy storage system; based on this, it constructs a multi-energy flow directed carbon flow graph to achieve unified carbon tracking and allocation for electrical, thermal, and cooling energy flows; introduces carbon flow conservation constraints and a weighted least squares state estimation method to achieve physical consistency verification and self-repair of carbon data; finally, it constructs a mixed-integer linear programming model with explicit embedded carbon memory constraints to achieve optimal multi-energy coordinated scheduling of carbon emissions throughout the entire life cycle. This invention realizes the transformation of carbon footprint from static accounting to dynamic tracking, and from post-event statistics to proactive optimization, significantly improving the reliability of carbon data and the effectiveness of low-carbon scheduling.

This invention discloses an engineered bacterial strain for producing xylitol using glucose as the sole carbon source, its construction method, and its applications, belonging to the field of genetic engineering. Using *Escherichia coli* as the starting strain, this invention optimizes the metabolic pathway by knocking out the 2-keto-3-deoxy-6-phosphate glucuronide gene (eda), knocking out the 6-phosphoglucuronide dehydratase gene (edd), and weakening the glucose phosphoisomerase gene (pgi), thus concentrating the carbon flow in the pentose phosphate pathway. Furthermore, it optimizes the metabolic pathway by knocking out or overexpressing endogenous genes such as the ribulokinase gene (araB). Subsequently, the synthesis of xylitol from glucose was experimentally tested by expressing a recombinant expression plasmid containing 2-arabinol dehydrogenase, 4-arabinol dehydrogenase, and xylitol dehydrogenase. This invention, through optimized metabolic pathways, efficiently converts glucose to xylitol without the need for glycerol addition, and significantly increases the yields of both the precursor arabinol and the product xylitol, demonstrating promising production prospects.

This invention discloses a probabilistic carbon flow calculation method and system based on data-physics fusion, belonging to the field of power system carbon emission calculation technology. The data-physics fusion-driven probabilistic carbon flow calculation method includes: acquiring distribution network operation data; extracting physical rules for distribution network carbon flow calculation based on the semi-invariant method, establishing a linearized mapping model from node injected power fluctuations to node carbon potential, and calculating the physical prior values ​​of each order of semi-invariants of node carbon potential; constructing a Bayesian deep neural network model, setting the network's learnable weight parameters as random variables; constructing a composite loss function integrating physical rules based on the physical prior values ​​of each order of semi-invariants of node carbon potential, and iteratively training the Bayesian deep neural network model; and outputting the probability distribution results of node carbon potential based on the trained model. This invention simultaneously considers computational efficiency, fitting accuracy, physical consistency, and uncertainty quantification, enabling real-time and accurate calculation of probabilistic carbon flow in distribution networks.

The application discloses a continuous fluid chemical product carbon tracking method and system based on RTD dynamic compensation, comprising: reactor RTD mathematical characterization modeling and generating a probability density sequence; the reactor is abstracted into a one-stage or multi-stage series stirred tank model, and a residence time distribution density function is used to describe the residence probability of fluid microgroups in the reactor; an instantaneous carbon load factor is constructed; reactor inlet flow, raw material implicit carbon intensity and multi-path energy consumption are collected in real time, and dispersed energy consumption and material data are integrated into a carbon flow signal changing with time; and output carbon accounting based on time domain convolution. The application applies mixing theory in chemical engineering to carbon accounting, realizes a leap from average carbon to instantaneous carbon, and can provide a precise carbon single with a time stamp for downstream customers.

The application discloses a kind of multi-energy complementary power generation system optimization scheduling method based on carbon emission minimization, to solve the problems such as insufficient carbon emission reduction pertinence, multi-objective imbalance and multi-constraint coupling conflict of existing scheduling scheme.The method realizes optimization through six-step core process: clear system boundary and build "source-net-load" whole chain carbon flow transfer function, establish dynamic weight driven carbon emission-economic-stability multidimensional objective function, quantize each sub-objective function and multidimensional constraint condition, design carbon flow dominant double-layer nested iteration algorithm and realize scheduling result real-time update output through programmed platform.The application integrates carbon flow dynamic tracking, adaptive weight adjustment and constraint priority mechanism, maximally reduces whole cycle carbon emission under the premise of guaranteeing system safety and stability operation, considers economy and operability, provides technical support for multi-energy complementary power generation system low-carbon and efficient operation, and is suitable for complex energy system scheduling scene containing renewable energy, fossil energy, energy storage and coupling unit.

This invention relates to a low-carbon scheduling method, system, device, and medium for a power-transportation cooperative system coupled with dynamic carbon flow. The method includes: constructing a carbon flow tracking model to generate carbon intensity data for power grid nodes; associating power grid nodes with charging facility identifiers to generate a mapping table; updating the mapping table by carbon intensity matching or carbon intensity interpolation in response to the charging behavior of electric vehicles to obtain a carbon energy dataset; constructing an initial grid based on the carbon energy dataset and charging facility locations, and generating a carbon metering grid after processing; generating a first carbon emission and a second carbon emission; aggregating the first and second carbon emissions to form a carbon emission map; and generating scheduling instructions by coupling the carbon emission map to the carbon metering grid and implementing constraints on global and local carbon emissions and spatial extension along the path. Therefore, this invention innovatively proposes the aforementioned cooperative scheme, solving the core pain points of traditional technologies such as dynamic response lag, spatial adaptation imbalance, and rigid metering standards.

This invention relates to the field of intelligent park carbon flow optimization technology, and discloses a method and system for intelligent park carbon flow optimization and trading-assisted decision-making. It aims to solve the problems of existing technologies, such as single-dimensional carbon emission data, static analysis models, lagging decision response, and lack of in-depth analysis of complex carbon flow coupling relationships within parks. The method includes: aggregating multi-source heterogeneous carbon-related data to construct a unified carbon data time-series basis; constructing a dynamic spatiotemporal knowledge graph based on this; using a graph convolutional neural network to predict future carbon flow sequences; and employing a non-dominated sorting genetic algorithm to solve for the Pareto optimal solution set; selecting a compromise solution by combining decision preference weights; and generating an interpretable decision report through causal attribution analysis. The system includes five modules: carbon data basis construction, dynamic knowledge graph generation, carbon flow prediction, multi-objective optimization decision-making, and decision analysis. This application achieves panoramic dynamic management of carbon flows, accurate prediction, multi-objective collaborative optimization, and transparent decision support.

The application discloses a carbon flow tracking and simulation evaluation system for a power distribution network, and belongs to the technical field of power distribution network energy management and carbon emission reduction, and specifically relates to a carbon flow tracking and simulation evaluation system for a power distribution network, which comprises a carbon flow data acquisition module, is used for deploying edge terminals and sensor sampling data at feeder lines, transformers, user electricity meters and distributed new energy stations, and performs encrypted transmission through a 5G / edge gateway to ensure data real-time performance; and a hierarchical carbon flow tracking module is used for constructing a four-layer model of a power distribution network master station, a feeder line, a power distribution transformer and a user side, each layer is superimposed with a differentiated calculation factor, and each node real-time carbon flow is calculated through a weighted algorithm of upper layer carbon flow x node power proportion x loss correction coefficient. The carbon flow data acquisition module is arranged, all key nodes associated with carbon flow can be covered, fragmented data originally scattered in multiple links is integrated into a unified acquisition link, and the problem that data is scattered in different scenes and needs to be found across links is completely solved.

The application provides a kind of steel production facility level carbon emission real-time accounting method and system based on dynamic factor iteration, relating to carbon emission monitoring technical field, by building facility level dynamic emission factor calculation model containing trainable parameters, replace traditional static factor, make accounting result real-time adapt to production condition change, through facility level carbon flow topology network modeling and carbon flow balance equation, form global mass conservation constraint;Through the first loss function and the second loss function, the dynamic emission factor calculation model parameters are optimized, and the trained facility level dynamic emission factor calculation model is obtained, based on real-time preprocessing sensor data and the final dynamic emission factor calculation model, the real-time dynamic emission factor is calculated, and based on the real-time dynamic emission factor, the real-time and accuracy of carbon emission accounting are improved, carbon flow tracking and closed-loop optimization in steel production are realized, to drive energy efficiency improvement and precise carbon reduction.

The present application relates to a kind of carbon emission accounting method of composite production area, comprising: determining the system boundary of composite production area, respectively establishing the carbon input list and carbon output list of each process, according to material balance and polymerization reaction principle, determine the carbon conversion path in each process, form the carbon flow evolution model describing the carbon element flow, conversion and loss path of each process in production process;According to carbon flow evolution model, identify key carbon flow node, deploy monitoring instrument for each key carbon flow node, obtain solid carbon-containing material information, gas carbon-containing emission information, process parameters and real-time monitoring data of energy consumption information;Establish the carbon balance equation of each process and the overall production area, calculate the direct CO2 emission of each process by carbon difference subtraction method, obtain the direct carbon emission of production area;Calculate the total amount of indirect carbon emission of production area.The present application improves the process level accounting accuracy, meets the fine carbon emission management needs of composite production area.

The application discloses a method for solving the minimum carbon emission capacity of a power-gas coupling energy system and its contour line, and first constructs the safe operation constraint of the power-gas coupling energy system and a carbon flow model, solves the maximum carbon emission capacity operation condition of the system under the condition of meeting the safe operation constraint; secondly, the energy supply capacity of the system under the safe operation constraint is solved and taken as the same energy supply value; then the minimum carbon emission capacity of the same energy supply under different load distributions of the observation node is solved based on the same energy supply value; the carbon emission safety domain of the system is drawn; the carbon flow coordinate points corresponding to the minimum carbon emission capacity operation condition of the same energy supply solved are connected to obtain the minimum carbon emission capacity contour line of the same energy supply, which directly describes the minimum carbon emission capacity of the same energy supply of the power-gas coupling energy system under different load distributions of the observation node, and provides a quantifiable decision tool for realizing safe-same energy supply-low carbon dispatching.

The present application relates to the technical field of carbon metering of integrated energy systems, and discloses a multi-energy complementary system carbon flow distribution method, system, medium and product, which comprises the following steps: obtaining real-time operation data sets of a multi-energy complementary system and a plurality of energy flow carbon flow models of a plurality of devices in the multi-energy complementary system; preprocessing the real-time operation data sets to obtain target operation data sets; calculating a plurality of target carbon emissions and a plurality of target dynamic carbon emission factors of the multi-energy complementary system based on the target operation data sets and the plurality of energy flow carbon flow models; dynamically distributing and tracing the carbon flow of the multi-energy complementary system according to the target operation data sets, the plurality of target carbon emissions and the plurality of target dynamic carbon emission factors, and realizing the analysis of the carbon emission sources and the calculation of the contribution degrees of a plurality of load nodes of the multi-energy complementary system, which accurately depicts the specific carbon emission behaviors inside the multi-energy complementary system and meets the accurate metering requirements of the multi-energy complementary system.

The application discloses a kind of based on implicit carbon flow explicit resolution distributed energy system energy carbon collaborative optimization method, system, equipment and storage medium, the method includes: collecting the operation data of electric hydrogen thermal coupling distributed energy system and external market environment data;Based on the data collected, the physical operation model of distributed energy system including energy transfer matrix and energy storage device dynamic evolution equation is constructed;Based on the node power distribution result in energy transfer matrix and the device conversion efficiency collected, the explicit resolution model of cross-medium implicit carbon flow is established, the explicit carbon emission of each node is obtained, the total carbon emission after the explicit of implicit carbon flow is calculated;Based on total carbon emission, with the minimum purchase power cost and carbon emission penalty cost as total objective function, establish energy carbon collaborative scheduling model and solve, obtain energy efficiency and carbon efficiency operation optimization scheme.The purpose is to realize the minimum of comprehensive operation cost and the strict standard of real cumulative carbon emission, economic low-carbon win-win.

The application discloses a high-yield beta-alanine engineering bacterium and method based on a type I CRISPRi screening system, wherein by knocking out a pckA gene encoding oxaloacetate to phosphoenolpyruvate and a nadB gene encoding L-aspartate to oxaloacetate, a countercurrent pathway for synthesizing beta-alanine is blocked, and carbon flow loss is reduced; by knocking out an ldhA gene and a poxB gene, the content of synthesized pyruvate is increased; by overexpressing an NCgl0580 gene, the tolerance of EcN to products is improved; by knocking out a lacI gene in a genome, the adding cost of an inducing agent in a fermentation process is reduced; by optimizing a type I CRISPRi system for high-throughput screening of target genes affecting the yield of beta-alanine in the engineering bacterium, the screening efficiency and accuracy are significantly improved, an aspartate tRNA ligase gene aspS capable of improving the yield of beta-alanine is obtained, by overexpressing the aspS, the PanD enzyme activity is increased, and the yield of beta-alanine is further improved.

This invention relates to the field of carbon tracking information technology, and provides a method, system, electronic device, and storage medium for real-time tracking of coal mine carbon emissions based on dynamic carbon characterization modeling. The method includes: identifying anomalous emission nodes within a preset carbon flow path based on detected carbon emission imbalances; generating a first corrected emission value for the anomalous emission nodes based on emission trends associated with the carbon flow path; performing a conservation balance check on the carbon flow path using the first corrected emission value; and generating a final corrected emission value based on cluster analysis of multiple nodes in the carbon flow path in response to the conservation balance check failing. This invention ensures the accuracy and consistency of carbon emission data through multi-level data processing and verification, effectively improving the integrity and accuracy of carbon emission data and reducing calculation bias caused by missing or abnormal data.

This invention discloses a method and system for predicting carbon emission factors based on the temporal characteristics of multi-regional carbon flows. The method includes: acquiring a first data sequence, a second data sequence, and a third data sequence. The first data sequence includes carbon emission data from a first power generation region at multiple time points; the second data sequence includes carbon emission data from at least one second power generation region transmitting electricity to the first power generation region at multiple time points; and the third data sequence includes carbon emission data from at least one third power generation region receiving electricity from the first power generation region at multiple time points. A target feature vector is constructed based on the first, second, and third carbon emission data, and input into a pre-trained sequence prediction model for temporal feature modeling. This invention fully considers the influence of electricity transmission and carbon flows between power generation regions, solving the problems of existing technologies that can only predict historical carbon emissions, have low spatial resolution, and do not fully model multi-regional interaction effects.

The application discloses a kind of electric carbon flow multi-dimensional visualization method, system, equipment and medium, it is related to energy information visualization technical field, its specific steps are: access power grid dispatching system obtains load response control information.Calculation node injects the flow direction difference between power and external power, generates path offset migration characteristic quantity.Compare the sequence of adjacent nodes, and obtain the path replacement aggregation mapping data.Calculation node adjacent power difference component, generate gradient turning density information, assess the abnormal response characteristics of node in carbon propagation diagram, identify and judge abnormal behavior type.The application realizes the real-time response and dynamic optimization of electric carbon distribution with load fluctuation.Through path migration correction and structure rearrangement, the dynamic propagation path and spatial aggregation relationship of carbon flow in power grid are presented, and the power time sequence change is analyzed by gradient turning density extraction technology, and finally the type of abnormal behavior is identified and judged.

A wind-solar carbon flow correlation analysis method and system based on PLHS sampling and sample optimization, comprising: constructing a wind-solar output probability distribution model; constructing a system carbon flow rate comprehensive analysis model under the coupling uncertainty of wind-solar output; using a hierarchical Latin hypercube sampling method to sample wind speed and light intensity to obtain a sample sequence; an adaptive sequence search algorithm is proposed, a composite index based on spatial dispersion is used as an optimization target to optimize the sample sequence, and the sample sequence is input into the wind-solar output probability distribution model to obtain a wind-solar output sample set; traversing the sample points in the wind-solar output sample set, the system carbon flow rate and its probability distribution characteristics are calculated; for each sample point in the wind-solar output sample set, the change amount of the system node, branch and network loss carbon flow rate caused by the wind-solar output injection is calculated respectively, and the weighted average of the change amount is obtained to obtain the average influence factor of the wind-solar output on the node, branch and network loss carbon flow rate. The present application realizes reliable evaluation of system carbon emission.

The application is suitable for the technical field of electric power engineering, and provides a carbon flow distribution obtaining method and device, terminal equipment and computer program product, wherein the method comprises the following steps: establishing a partial voltage expression of each node in an alternating current power network and a partial power expression of each branch transmission by means of the parameters and the power flow solution of the alternating current power network; establishing a total carbon flow expression of each branch transmission driven by equivalent current sources of all nodes according to the partial power expression of each branch transmission; establishing a total carbon flow expression of each load carried by equivalent current sources of all nodes according to the partial voltage expression of each node; and obtaining and outputting distribution data of corresponding total carbon flow based on the total carbon flow expression of each branch transmission and the total carbon flow expression of each load. The application can effectively improve the accuracy of carbon flow distribution data obtaining in the alternating current power network.

The application provides a carbon flow regulation method, device, medium and product for low-carbon operation of a sewage plant. In the method, the carbon flow regulation device first combines the real-time inflow and the liquid-phase carbon carrier concentration to calculate the real-time inflow load and the load difference. Then, the carbon flow regulation device inputs the load difference into a carbon flow path correction model to obtain the carbon source expected destination ratio; at the same time, the concentration difference is calculated based on the methane value, and the target sludge age is calculated based on the concentration difference to generate sludge discharge control instructions; and the integrated carbon emission intensity and the dissolved oxygen concentration deviation value are input into a fuzzy controller to obtain the aeration amount and the internal return flow adjustment factor. Finally, the carbon flow regulation device combines the carbon source expected destination ratio, the two types of adjustment factors and the initial dissolved oxygen control instructions to reconstruct the operation parameter table and issue it to the execution device. The method is used to solve the technical problem of the increase of the integrated carbon emission of the sewage plant when the inflow load fluctuates, and to reduce the integrated carbon emission of the sewage plant.

The present application relates to the technical field of carbon management of power system, and more particularly to a renewable energy carbon emission reduction accounting method considering electric-carbon coupling, comprising: obtaining an electric-carbon coupling risk coefficient based on the net load-carbon emission joint time series data collected by the power grid dispatching system; obtaining an optimal power flow distribution result through electric-carbon coupling risk coefficient for electric-carbon collaborative optimization dispatching; obtaining a full-node carbon potential vector and a load node carbon flow rate vector through the optimal power flow distribution result for carbon emission flow dynamic tracking; obtaining the actual carbon reduction contribution value of each renewable energy unit through renewable energy carbon reduction contribution distribution according to the renewable energy unit grid-connected operation data; and coupling the full-node carbon potential vector, the load node carbon flow rate vector and the actual carbon reduction contribution value to generate the renewable energy carbon emission reduction amount. The present application realizes accurate real-time accounting of renewable energy carbon emission reduction amount through electric-carbon coupling risk quantification and full-chain carbon emission flow tracking.

The application discloses a kind of park fine carbon flow dynamic tracking methods based on whole life cycle, it is related to industrial park carbon management technical field, can solve how to realize the accurate time period binding and dynamic control of park power carbon emission responsibility, to support the problem of fine carbon reduction decision-making, including: determining the carbon emission intensity signal of target regional power grid;According to carbon emission intensity signal, the power purchase data of target park at target time and the photovoltaic power generation data of target park, determine the carbon responsibility allocation value of target park at target time;Cluster analysis is carried out to the electricity consumption behavior of target park in historical period, and multiple typical electricity consumption modes are identified;Quantify the carbon reduction potential corresponding to each typical electricity consumption mode, and dynamically adjust the carbon quota allocation quota of target park in future period based on carbon reduction potential.