145 results about "Carbon potential" patented technology

Provided are a method for tracking carbon flow of a power system, a device and a medium. The method includes: acquiring related data of carbon flow tracking, where the related data include an injected active power sum column matrix of generator sets of all substations to be tracked, an injected carbon flow rate sum column matrix of generator sets of all substations to be tracked, an output power distribution matrix of a branch formed between substations to be tracked, and a power flow proportion distribution matrix of the branch formed between substations to be tracked; acquiring a carbon potential matrix EN of each substation to be tracked; and acquiring a carbon flow rate of each substation to be tracked, a carbon flow rate of the branch, and a carbon flow rate of an output load on the basis of the carbon potential matrix of each substation to be tracked.

The invention discloses a distributed energy system source load coordinated optimization method based on a quasi-potential game method, and the method comprises the steps: constructing a distributed energy system model, inputting system parameters, and predicting renewable energy power generation and initial load demands. In a source side optimization stage, a leader layer potential function of a quasi-potential game is established by taking minimization of source side cost # imgabs0 # as a target, and an initial power generation plan is generated by comprehensively considering economical efficiency and carbon emission constraints; and then, based on a scheduling result, calculating a carbon potential epsilon t of each node and a dynamic carbon emission factor # imgabs1 # of each stage, optimizing a load side response based on an LCDR scheme, constructing a local potential function of a follower layer, reflecting a relationship between a user profit maximization target and carbon emission, and adjusting user behaviors through a distributed decision. And the updated load demand is fed back to the source side, and the source side optimizes the output plan of each unit based on the updated load, so that an iterative process of source side potential function optimization-load side equilibrium response is formed, and an optimal scheduling strategy and scheduling result of the energy supply side are obtained. According to the framework, the global consistency requirement of a traditional potential game is relaxed, independent optimization of source-load two sides under the guidance of respective potential functions is allowed, and a Nash equilibrium state is finally achieved only by ensuring monotonous convergence of total potential energy of a system in an iteration process. According to the method, the convergence advantage of the potential game is reserved, the method is also adapted to the characteristics of a source-load heterogeneous decision subject, efficient consumption of renewable energy and collaborative optimization of carbon emission are realized through bidirectional transmission of the carbon potential signal, and the overall efficiency of the system is remarkably improved.

The invention discloses an industrial park carbon emission reduction benefit evaluation method and system, and belongs to the technical field of power system energy conservation and emission reduction, and the method comprises the steps: S1, obtaining industrial park integrated data, carrying out the preprocessing of the integrated data, obtaining carbon data, and building an equivalent physical network model according to the topological structure and equipment parameters of an industrial park; s2, calculating a carbon footprint according to the carbon data and a carbon footprint rule, and extracting carbon features based on the carbon footprint in combination with a reference mode; s3, calculating carbon efficiency according to the carbon footprint and economic data in the carbon data, and performing fine-grained dynamic measurement and calculation according to the carbon footprint, the carbon characteristics and the equivalent physical network model to obtain a carbon emission flow; s4, performing benefit evaluation according to the carbon efficiency and the carbon emission flow to obtain a carbon benefit, a carbon potential and a carbon relationship, and generating a carbon emission reduction strategy report according to the carbon benefit, the carbon potential and the carbon relationship; according to the method, the problem that the park carbon emission reduction benefit evaluation is inaccurate due to the fact that the mutual influence relation between different carbon links is not considered in the prior art is solved.

The invention discloses a power distribution network carbon emission metering and responsibility distribution method and device and a medium, and relates to the technical field of smart power grids. The method comprises the following steps: collecting multi-source carbon emission data in real time, and preprocessing the multi-source carbon emission data to obtain standard carbon emission data; inputting the standard carbon emission data into a preset dynamic carbon factor model to obtain a dynamic carbon factor of the thermal power generating unit, and combining the dynamic carbon factor of the thermal power generating unit with a carbon factor of the photovoltaic power generation system to obtain a dynamic carbon intensity vector; performing load flow calculation on the multi-source carbon emission data to obtain a node active flux matrix and a branch load flow distribution matrix, and combining the dynamic carbon intensity vector, the node active flux matrix and the branch load flow distribution matrix to obtain the total carbon potential of each node on the load side; and based on the total carbon potential and the real-time load distribution matrix, calculating the carbon flow rate distributed to each node on the load side so as to obtain the carbon emission responsibility of each node on the load side.

The invention discloses a carbon emission accounting system and method based on the whole process of a power system. A data acquisition module is used for historical activity data of various energy main bodies and desulfurizer consumption, historical operation data of a power system grid topological structure and a power system, power consumption data, load data and SF6 equipment parameters; the source side carbon emission conversion module is used for obtaining the total carbon emission of the source side; the electric power carbon emission flow calculation module is used for obtaining direct carbon emission and indirect carbon emission of a network side; and the load side power carbon emission calculation module is used for calculating the carbon emission of the load side according to the load side node carbon potential and the power consumption data. According to the method, the whole processes of the source side, the network side and the load side of the power system are comprehensively considered, the node carbon potential and the load side node carbon emission factor are dynamically calculated through the power system carbon emission flow method, and the problem that a traditional carbon emission accounting method cannot cover the whole process of source-network-load and cannot adapt to the dynamic power system is solved.

The invention discloses a virtual power plant optimization regulation and control method and system considering power-carbon cooperation, and is used for solving the problems that a current virtual power plant resource regulation and control method is not systematic and comprehensive enough, and is lack of systematic consideration on a carbon emission target. Generating set historical output data and external power data of a power system where the virtual power plant cluster is located are obtained, carbon emission factor prediction is carried out according to the generating set historical output data and the external power data, and carbon emission prediction information is obtained; performing carbon potential calculation according to the carbon emission prediction information to form a whole-network carbon emission flow; key feature parameters are calculated based on the whole network carbon emission flow, and a user electricity-carbon fusion image is drawn according to the key feature parameters; carrying out resource aggregation according to the key feature parameters, and drawing an electric-carbon coupling portrait of the virtual power plant; and in combination with a preset constraint condition, constructing a low-carbon scheduling optimization model considering carbon reduction and peak clipping at the same time, so as to perform virtual power plant resource optimization calling on the virtual power plant cluster based on the low-carbon scheduling optimization model.

The invention discloses a carbon emission flow analysis method for carbon emission evaluation in multiple application scenes, belongs to the technical field of power system carbon emission modeling and evaluation, constructs a connection relationship among nodes, branches and a power supply in a power system, and collects output data and type information of a power generation power supply and a power flow result in multiple operation conditions. The method comprises the following steps: calculating carbon emission of a power generation node, distributing the carbon emission to a load node according to a power flow path, identifying a carbon emission source of the load node by adopting a power tracking method, and calculating carbon emission intensity and a carbon potential index; a transmission structure of carbon emission in a power grid is defined, step-by-step distribution and flow direction tracking of the carbon emission are realized, and the defect that a carbon emission path is unobservable in the prior art is overcome; the identification precision of the carbon emission composition is improved, and a basis is provided for the priority division of energy-saving and emission-reducing measures; a carbon emission path mapping matrix and a transition probability matrix are constructed, dynamic identification of path changes is realized, and discovery of key paths and nodes is facilitated.

The invention relates to the field of power system carbon emission flow analysis, in particular to a closed-loop power grid-oriented electric energy tracking and power flow tracing coupled carbon emission flow analysis method, which is based on power flow distribution of an actual power grid and comprehensively utilizes an electric energy tracking method and a power flow tracing method. According to the invention, fine allocation and full-link physical traceability of nodes, branches and loads in a closed-loop power grid structure by carbon emission are realized. By establishing a power flow distribution matrix, a unit injection matrix, a load distribution matrix and a carbon emission intensity vector, the carbon potential of each node, the branch carbon flow rate and the load carbon flow rate are calculated in a recursive manner, an electric energy tracking method and power flow traceability are coupled, and node allocation is iteratively optimized, so that the actual flow path and spatial distribution characteristics of the carbon flow in a power grid are disclosed. The method can adapt to scenes such as complex multi-source access and a looped network structure, the scientificity and fairness of closed-loop power grid carbon emission management are improved, and theoretical and method support is provided for development of low-carbon scheduling, carbon accounting and low-carbon economy.

The invention discloses a power distribution network low-carbon scheduling method based on large language model assisted multi-agent reinforcement learning. The method comprises the steps of establishing a system model considering carbon flow, quantifying a carbon potential distribution and transmission path based on a carbon emission flow theory, and integrating distributed resource constraints, a second-order cone relaxation power flow model and a low-carbon objective function; a large language model auxiliary module is constructed, task targets and constraints are analyzed through a prompt project, and a strategy and a reward function are automatically generated; establishing a multi-agent reinforcement learning module, and integrating a priori strategy and a reward function; based on a multi-agent depth deterministic strategy gradient algorithm, a scheduling strategy is optimized in an off-line collaborative manner. According to the method, the traditional two-stage scheduling limitation is broken through, and target unified optimization is realized; manual reward and strategy function design is not needed, and the threshold is lowered; the reinforcement learning convergence speed is accelerated, and the sample efficiency is improved; carbon emission is accurately quantified, and the resource utilization efficiency and the low-carbon scheduling effect are improved.

The invention relates to the technical field of comprehensive energy system optimization scheduling, in particular to an energy-carbon excitation-based farm comprehensive energy system optimization scheduling method, which comprises the following steps: S1, constructing a comprehensive energy system covering an energy operator and farm users, providing electric heating energy by the operator, and supplying heat by the farm users through biogas power generation, the three types of loads are combined to construct an equipment and load model; s2, carbon potential is calculated based on a carbon emission flow theory, an energy-carbon price is formulated, and a stepped carbon transaction and segmented subsidy mechanism is adopted to stimulate a user to use low-carbon energy; s3, constructing a master-slave game model, performing upper-layer pricing excitation and lower-layer optimization response, and performing joint iterative solution by adopting a genetic algorithm and GUROBI; according to the invention, by constructing a master-slave game scheduling framework and introducing an energy-carbon joint pricing and stepped carbon excitation mechanism, collaborative optimization of system economy and a low-carbon target is realized, and user response enthusiasm and carbon emission reduction potential are effectively improved.

The invention discloses a power system carbon emission dynamic traceability and evaluation method, system and device based on life cycle and topological entropy fusion and a medium, and belongs to the technical field of power system low-carbon operation and carbon emission evaluation, and the method comprises the steps: collecting carbon emission data of different stages; establishing a stage set, calculating the emission of each stage, and solving a life cycle carbon entropy; abstracting a power system into a weighted directed graph, calculating a branch carbon flow rate based on the weighted directed graph, and calculating a graph theory carbon entropy based on node inflow; introducing a weight parameter, fusing the life cycle carbon entropy and the graph theory carbon entropy, and defining a fusion entropy; under a multi-period operation condition, calculating a time evolution sequence based on the fusion entropy, and defining a sensitivity coefficient; and generating a visual carbon flow map containing node carbon potential distribution, a branch carbon flow rate, a carbon entropy evolution curve and a responsibility allocation matrix. According to the method, dynamic conduction and node-level tracking of carbon emission along the electric power flow are realized, and the complexity and balance of carbon emission space distribution are quantified through an entropy theory.

The invention relates to the technical field of energy internet and intelligent micro-grids, and discloses a dynamic energy-carbon coupling modeling and collaborative optimization method for a wind and light storage and charging system, which comprises the following steps of: a, acquiring operation data of the wind and light storage and charging system; b, calculating to obtain the equipment-level dynamic real-time carbon potential of the output port of the energy conversion equipment; step c, updating the virtual total carbon load by using the state data of the energy storage unit and the real-time carbon potential; step d, constructing and solving a rolling horizon optimization problem to obtain an optimal control strategy covering the prediction horizon; and step e, issuing and executing a control instruction, and repeating the step a to the step e. According to the method, the physical working condition and the real efficiency of the equipment are dynamically mapped, the carbon emission intensity and the equipment operation state are associated in real time, and then static emission factors are replaced, so that the influence of the equipment on the carbon flow is accurately and dynamically reflected, and the precision and the real-time performance of microscopic carbon accounting are improved.

The invention discloses an electrical carbon power flow solving model construction method and device based on a physical guidance correction neural network and an electrical carbon power flow solving method. The model construction method comprises the following steps: acquiring historical operation data of each node of a power system; constructing and initializing an electrical carbon power flow solving model; in the training process, the model outputs a voltage amplitude, a voltage phase angle and node carbon potential according to input unit injection power and load power; calculating boundary condition loss by comparing a predicted value with an actual value; calculating a power residual error and a carbon potential residual error, and determining physical constraint loss by combining physical constraints of power balance and carbon potential balance; based on the assumption that the power residual error and the carbon potential residual error at the next historical moment are 0, physical guidance correction loss is determined, and then total loss is obtained; and converging the model through iterative training to obtain a trained model. By implementing the method, the problem of low calculation efficiency caused by depending on load flow calculation in the prior art can be solved, and efficient calculation of the carbon emission of the power system is realized.

The invention discloses a high-energy-consumption industry carbon reduction potential quantitative analysis method, and belongs to the field of high-energy-consumption industry low-carbon transformation simulation analysis. The energy consumption mode, the production process, the carbon emission condition and the overall benefit to the environment and the society of the high-energy-consumption industry under different economic environments and policy backgrounds are investigated and analyzed, and the potential of each industry in the process of realizing the carbon emission reduction target is determined by quantifying key indexes such as the carbon reduction intensity and the marginal carbon reduction cost of the industry; secondly, a scientific and comprehensive carbon reduction potential evaluation index system is established by integrating the influences of economic benefits and environmental benefits on the carbon reduction willingness of the high-energy-consumption industry, the index system not only comprises economic indexes such as the annual profit rate and the annual return on investment, but also introduces brand new evaluation indexes such as the'carbon reduction index 'and the'standard marginal carbon reduction cost'; the carbon reduction capability and the cost-benefit relationship of each industry are accurately quantified; and finally, by constructing an analytic hierarchy model, carrying out comprehensive scoring and comparative analysis on the carbon reduction potentials of five types of typical high-energy-consumption industries (cement, steel, petrochemical engineering, electric power and coal industries), and evaluating relative priorities of various industries under different carbon reduction paths through a comprehensive scoring result to obtain the most potential carbon reduction path and strategy. In addition, in combination with expert evaluation and data analysis, selection of carbon reduction strategies is more scientific and practical.

The invention relates to the technical field of park comprehensive energy system low-carbon operation, in particular to a park comprehensive energy system low-carbon demand response method and system, and the method comprises the following steps: carrying out the low-carbon demand response of a load side and an energy storage side based on a power side CCS-P2G coupling operation mechanism; constructing a source-load-storage collaborative carbon reduction park integrated energy system low-carbon operation framework; aiming at carbon emission characteristics of park equipment and energy storage, establishing a park integrated energy system extended carbon emission flow model; calculating a dynamic carbon emission factor based on an extended carbon emission flow model; and the dynamic carbon emission factor is used as a guide to excite a user to change a power utilization mode and change charging and discharging behaviors through energy storage so as to carry out low-carbon demand response. Compared with the prior art, the method has the advantages that the low-carbon potential of resources on the load side and the energy storage side is effectively excavated, and the carbon emission of PIES is effectively reduced; the extended carbon emission flow model provided by the invention can overcome the difficulty of carbon emission flow analysis caused by diversified equipment in PIES.

The invention relates to an intelligent carbon potential control method and system based on multi-source data perception, and the method comprises the steps: collecting parameter vectors corresponding to M parameter types, comprehensively obtaining the multi-source information related to the carbon potential, carrying out the reasonable splicing and processing of the parameter vectors, and obtaining the multi-source information related to the carbon potential. The carbon potential corresponding to the preset target time point can be accurately predicted through the trained time sequence offset prediction model, the offset mapping model and the parameter prediction model, and compared with a traditional prediction mode depending on a single parameter or a small number of parameters, potential relations and time sequence characteristics among different parameters are fully mined, and the prediction accuracy is improved. The accuracy of carbon potential prediction is greatly improved, and a reliable basis is provided for subsequent accurate control. The multi-source data sensing mode can comprehensively reflect complex and changeable working conditions in actual production, the model can learn and adapt to the relation between parameters and carbon potential under different working conditions, high robustness and adaptability are achieved, and the application range of the method in different production environments is widened.

The invention is suitable for the technical field of carbon emission, and provides a multi-dimensional carbon emission monitoring method and system based on spatial and temporal distribution, and the method comprises the following steps: collecting time series data, spatial topological data and carbon intensity data, binding real-time carbon intensity for each generator set, and building a set-node mapping table; a carbon topology matrix Tc is constructed, the carbon conduction weight of each connection line is calculated, a dynamic carbon potential field is constructed, and node carbon potential = (local power generation carbon emission + carbon emission carried in the line) / (local net power generation amount + total output power); line-level carbon flow is monitored, real-time carbon flow of each line is calculated, user-level carbon emission is monitored according to the carbon flow, and regional net carbon transfer is analyzed. According to the method, the carbon emission condition of each node and each line can be accurately calculated, the distribution condition of the carbon emission at different time and different spatial positions can be reflected, the hot spot region and peak period of the carbon emission can be found, and the refined monitoring of the carbon emission can be realized.

The invention discloses a carbon emission evaluation method, system, equipment and medium based on a multi-energy electric power system, and relates to the field of carbon emission evaluation of electric power systems, comprising the steps of dividing the operation cycle of the electric power system into three time scales of day-ahead, day-in and real-time, and performing data acquisition at each time scale; constructing a day-ahead model, an intra-day model and a real-time model based on the collected data; obtaining a predicted unit plan and a predicted carbon potential based on the day-ahead model; inputting the predicted unit plan and the predicted carbon potential into the intra-day model, and optimizing and correcting the predicted carbon potential; real-time data is collected and compared with the predicted carbon potential, real-time carbon potential is obtained through real-time model calculation, and corrected parameters are fed back to a day-ahead model. According to the method, the day-ahead, intra-day and real-time three-level dynamic carbon flow model is constructed, and the hysteresis problem of a traditional method in a new energy fluctuation scene is solved. Seamless connection of data in different time dimensions is realized through a cross-scale carbon potential transfer function and a coordination controller.

The invention provides a scheduling method and system for PIES to participate in an electricity-carbon-green certificate market, and belongs to the technical field of comprehensive energy. The method comprises the following steps: acquiring a carbon deal tax amount of a park integrated energy system, and allocating electric quantity corresponding to green certificates on demand on demand on the basis of a user side green certificate hour-by-hour allocation strategy of carbon potential response according to the carbon potential of each time period; the method comprises the following steps: discretizing time scales of a continuous carbon market and a green certificate market to the same scheduling time scale of an electricity market, establishing an electricity-carbon-green certificate market connection transaction strategy, determining a green certificate transaction volume and a deductable carbon emission reduction volume, and realizing dynamic conduction of key variables of the three markets; and based on the green certificate transaction volume and the deducted carbon emission reduction, constructing a PIES multi-agent double-layer game optimization scheduling model, and realizing scheduling of the park integrated energy system. The method can effectively reduce the cost of carbon tax, retains the initial energy consumption demand of the load, accords with the energy consumption will of an enterprise, and shows obvious economical efficiency and low carbon compared with a pairwise market connection transaction strategy.

The invention discloses a park dynamic carbon portrait generation method and system, and the method comprises the steps: collecting building, equipment and traffic multi-source energy consumption data in real time through Internet of Things equipment, and calculating the carbon emission intensity in combination with a dynamic carbon emission factor library; constructing a three-dimensional park model, mapping the carbon emission data into a dynamic thermodynamic diagram layer according to a spatial hierarchical structure (park-building-floor-equipment), and synchronously generating a vehicle carbon emission intensity diagram; positioning a key emission source based on the energy flow-carbon flow mulberry-based graph, setting a grading early warning threshold value, and triggering a three-dimensional highlight alarm and carbon reduction strategy suggestion; an optimization algorithm is adopted to generate a multi-energy cooperative regulation and control instruction, and the instruction is pushed to the energy management system for execution; and closed-loop verification and iterative optimization are realized by monitoring emission reduction, economic benefits and carbon potential indexes. The space-time dynamic visualization of carbon emission, key source intelligent positioning and adaptive optimization closed loop are realized, the problems of lack of real-time performance and low traceability precision of park carbon management are solved, and the carbon emission intensity is reduced through actual measurement.

The invention discloses a power distribution network scheduling method and system for guiding demand response through dynamic carbon emission factors. The method comprises the steps that related data of a power distribution network are collected in real time; determining the carbon potential of each node in the power distribution network topology based on the related data of the power distribution network; calculating a dynamic carbon emission factor of each node based on the load of each node and the carbon potential of each node; correspondingly calculating the electricity-carbon coupling time-of-use electricity price based on the power distribution network time-of-use electricity price and the dynamic carbon emission factor; a power distribution network node load low-carbon demand response model is adopted to determine the variable quantity of a price type demand response load; calculating the carbon emission quota of the power distribution network and the actual carbon emission of the power distribution network; determining the stepped carbon emission cost of the power distribution network based on the carbon emission quota of the power distribution network and the actual carbon emission of the power distribution network; constructing a low-carbon dispatching model of the power distribution network; and solving the power distribution network low-carbon scheduling model, and generating a power distribution network low-carbon scheduling strategy. The method has the advantages that the low-carbon performance of the power distribution network can be guaranteed, and the load demand response precision is good.

The invention provides a transformer area carbon reduction potential evaluation method considering user side interaction response. The method comprises the following steps: obtaining transformer area node carbon potential according to transformer area power data and a sampling time period; obtaining user side carbon emission according to the transformer area node carbon potential, the user side power data and the sampling time period; obtaining a new energy output ratio average value and an energy storage equipment capacity ratio according to the transformer area power data; according to the user-side power data, obtaining the power supply reliability and the user comfort of the transformer area; obtaining a user side interaction response capability according to the user side carbon emission; according to the user side interaction response capability, the new energy output ratio average value, the energy storage equipment capacity ratio, the transformer area power supply reliability and the user comfort, constructing an evaluation matrix of the transformer area to be evaluated; and selecting the zone area with the highest carbon reduction potential based on the evaluation matrix. According to the evaluation method provided by the invention, the carbon reduction potential of the transformer area can be scientifically and comprehensively evaluated, and decision support is provided for making effective carbon emission reduction strategies and action plans.

The invention discloses a comprehensive energy system source-load collaborative low-carbon economic dispatching method based on extended carbon emission flow. The method comprises the following steps: constructing a comprehensive energy system extended carbon emission flow model based on an energy hub; constructing a combined operation model of a wind turbine generator, a carbon capture unit and power-to-gas based on carbon flow; a low-carbon demand response mechanism based on carbon potential is designed, and the carbon reduction potential of the load side is released; a carbon flow-based master-slave game framework is constructed, and the high-carbon attribute of the system is improved; and designing a source-load cooperative operation method under a carbon flow view angle to realize low-carbon economic operation of the system. According to the method, an extended carbon emission flow model of the comprehensive energy system is constructed, a combined operation model of a wind turbine generator, a carbon capture unit and power-to-gas is constructed based on the extended carbon emission flow model, and the coupling characteristic of the source side of the system is improved; a low-carbon demand response mechanism based on carbon potential is designed, and the perceptibility of a user to carbon difference is improved; source-load cooperative operation is realized based on the master-slave game, and the low-carbon economic level of the system is improved.

The present invention discloses a heat treatment process for gear parts, comprising five carbon potential carburizing steps: S1, carburizing at a temperature of 930-940°C under specified carbon potential conditions for 40-50 hours; S2, carburizing at a temperature of 900-920°C under specified carbon potential conditions for X hours according to the relationship between the depth of the carburized layer of the part and the carburizing time; S3, carburizing at a temperature of 900-920°C under specified carbon potential conditions for 10-15 hours; S4, carburizing at a temperature of 900-920°C under specified carbon potential conditions for Y hours according to the relationship between the depth of the carburized layer of the part and the carburizing time; S5, carburizing at a temperature of 900-920°C under specified carbon potential conditions for Z hours; the depth of the carburized layer in S2, S4 and S5 is positively correlated with the carburizing time. The technical effect of the present invention is to reduce the depth of the grain boundary oxide layer of parts with a carburized layer depth of 4.00mm-5.00mm.

The invention discloses a hollow cathode discharge composite rare earth oxide assisted enhanced ion carburization method. According to the method, hollow cathode discharge composite rare earth oxide is adopted to realize enhanced ion carburization. The discharge of the hollow cathode is realized by utilizing an auxiliary cathode which is arranged in parallel opposite to the infiltrated surface of the metal sample piece, and the auxiliary cathode is a profiling cathode which is homogeneous with the metal sample piece; and the rare earth oxide is one of granular yttrium oxide, cerium oxide and lanthanum oxide and is uniformly physically adsorbed on the surface of the auxiliary cathode or the infiltrated surface of the metal sample piece. And during ion carburization, the auxiliary cathode and the carburized metal form a hollow cathode, hollow cathode discharge occurs, and the hollow cathode discharge interacts with the rare earth oxide particles, so that enhanced ion carburization can be realized. Compared with conventional ion carburization, the carbon potential of the infiltrated surface of the metal sample can be obviously improved, the carbon concentration in the infiltrated layer is increased, and the hardness and thickness of the infiltrated layer are improved. The method is simple, easy to master, energy-saving, environment-friendly and remarkable in economic benefit.

The invention discloses an energy conversion carbon hub model construction method, system, equipment and medium, belongs to the technical field of comprehensive energy analysis modeling, and aims to construct single-input single-output and single-input multi-output device carbon flow models considering equipment carbon loss by uniformly quantifying heterogeneous energy quality difference with efficiency. Defining a carbon potential coupling relationship and a distribution mechanism through efficiency; establishing an efficiency-based carbon flow rate coupling matrix, and accurately representing energy station input and output port carbon potential association; and by solving the carbon flow conversion coefficient, a carbon hub model fused with energy quality attributes is formed, and technical support is provided for a carbon emission reduction strategy of an energy station.

The invention belongs to the technical field of electric power, and discloses a virtual power plant energy management collaborative optimization method, system, device and medium, and the method comprises the following steps: S1, constructing a distributed robust optimization multi-market bidding model, and outputting a bidding power plan of a virtual power plant in multiple markets; s2, constructing an internal power market of the virtual power plant and the producer, and calculating a transaction strategy of the virtual power plant and the producer by adopting a Starburg game model; s3, constructing a real-time power consumption deviation management and control mechanism of the production and consumer; calculating a credit value based on the deviation between the real-time electricity consumption and the day-ahead contract amount, and dynamically adjusting a penalty factor and collecting a fine in combination with a historical credit value; s4, constructing a low-carbon scheduling model, defining the equivalent carbon potential of the energy storage equipment, and calculating the carbon emission of the virtual power plant and the producer in combination with each power supply carbon emission factor and the stepped carbon price; and S5, realizing virtual power plant energy management collaborative optimization based on the bidding power plan, the transaction strategy, the deviation management and control result and the carbon cost constraint.

This application discloses a method, device, and medium for carbon emission metering and responsibility allocation in a power distribution network, relating to the field of smart grid technology. The method includes: real-time acquisition of multi-source carbon emission data, preprocessing the multi-source carbon emission data to obtain standard carbon emission data; inputting the standard carbon emission data into a preset dynamic carbon factor model to obtain the dynamic carbon factor of thermal power units, and combining the dynamic carbon factor of thermal power units with the carbon factor of photovoltaic power generation systems to obtain a dynamic carbon intensity vector; performing power flow calculations on the multi-source carbon emission data to obtain a node active power flux matrix and a branch power flow distribution matrix, and combining the dynamic carbon intensity vector, the node active power flux matrix, and the branch power flow distribution matrix to obtain the total carbon potential of each node on the load side; and calculating the carbon flow rate allocated to each node on the load side based on the total carbon potential and the real-time load distribution matrix to obtain the carbon emission responsibility of each node on the load side.

The present invention relates to a carburizing method for high hardenability steel parts, specifically to a heat treatment method for obtaining high hardenability steel parts with low retained austenite, which is used to solve the problems that cryogenic treatment is not suitable for mass production and there is a risk of part cracking, as well as the deficiencies that carburizing normalizing + secondary heating quenching consumes electric energy and the process is relatively complex. In the heat treatment method for obtaining high hardenability steel parts with low retained austenite, the carbon potential in the fourth stage is 0.45%, and the carbon potential remains unchanged during the cooling in the fifth stage. Before the final quenching, the carbon potential is increased to 0.60 - 0.70% in the sixth stage to avoid decarburization of the parts due to low surface carbon potential, so that the volume percentage of retained austenite of high hardenability steel parts such as 17NiCrMo6-4 and 20MnCr5HHA can be maintained at ≤15% after one-time heating quenching.

The invention discloses an energy storage system carbon emission calculation method and system based on SOC data. The method comprises the steps that charging and discharging data of an energy storage system at all moments are acquired; judging whether the energy storage system is in a charging state or a discharging state between the TN moment and the TN + 1 moment based on the charging and discharging data; when the energy storage system is in the charging state, based on the charging carbon potential of the energy storage system at the TN moment and the charging data of the energy storage system at the TN moment and the TN + 1 moment, the carbon storage amount and the electric storage amount of the energy storage system at the TN + 1 moment are calculated; when the energy storage system is in the discharging state, the ratio of the carbon amount stored at the TN moment of the energy storage system to the electric quantity stored at the TN moment of the energy storage system serves as the discharging carbon potential of the energy storage system at the TN moment, and the carbon amount and the electric quantity stored at the TN + 1 moment after discharging of the energy storage system are calculated based on the discharging carbon potential of the energy storage system at the TN moment and the discharging data at the TN + 1 moment; and after all charging and discharging moments of the energy storage system are traversed, the charging and discharging carbon potential of the energy storage system at each charging and discharging moment is obtained.