1023 results about "Green electricity" patented technology

The present disclosure provides a real-time carbon emission accounting method and apparatus considering green electricity. The real-time carbon emission accounting method includes: periodically obtaining influencing factor data, where the influencing factor data includes at least green electricity in net electricity exported from another country to China, and green electricity in an annual total generating capacity within a geographical scope of China's power grid; inputting the influencing factor data into a preset real-time carbon emission factor prediction model for processing to obtain an updated real-time carbon emission factor; obtaining activity data of a to-be-accounted enterprise; and calculating a carbon emission accounting result based on the activity data and the updated real-time carbon emission factor. This solution utilizes the real-time carbon emission factor prediction model to predict and update a carbon emission factor to avoid a current existing hysteresis nature of the carbon emission factor, and considers the green electricity when predicting and updating the carbon emission factor, such that the carbon emission accounting result can accurately reflect an indirect carbon emission generated by use of electricity under the existing energy structure.

The invention discloses an electricity-hydrogen combined scheduling method and system for large-scale renewable energy source hydrogen production. The method comprises the steps of defining projects, equipment, units and systems, configuring topological relations, setting working conditions, grading loads and accessing data. Adjusting, optimizing and correcting ultra-short time power generation prediction, predicting hydrogen production allowance and identifying a current working condition; pre-judging future working conditions, power supply quantity and hydrogen production direct-current power; simulating balance, and solving an optimal scheduling strategy by multiple targets; and decomposing the scheduling strategy and issuing an asynchronous control instruction. According to the invention, the thought of mutual assistance of source and load is adopted, energy balance and hydrogen production balance are jointly dispatched, the purposes of power-hydrogen coupling as a main part, energy storage stabilization as an auxiliary part and off-grid or grid-connected non-grid are achieved, off-grid stability and 100% green power consumption of a renewable energy hydrogen production system are achieved, the policy requirements of green hydrogen production are met, the dependence on a large power grid is fundamentally reduced, and the green hydrogen production efficiency is improved. The electricity cost is reduced; and meanwhile, the support dependence on energy storage is reduced, and the use cost of energy storage is reduced.

The invention provides a green power consumption classification accounting and right tracing method and system of a multi-dimensional account, and relates to the technical field of power, and the method comprises the steps: generating green power transaction matching data through collecting power utilization data and power generation plan data in real time; constructing a distributed account book node network, verifying the matched data, and generating a green power transaction block; and constructing a green power right traceability model based on the transaction block, calculating a green power consumption weight coefficient of the power consumption enterprise, and generating a green power consumption level and a right certificate. According to the invention, precise accounting and right traceability of green power consumption are realized, and the energy management efficiency is improved.

The invention relates to the technical field of new energy power systems, and discloses an energy storage coordination system and control method based on meteorological prediction and multi-energy complementation, and the system comprises a power generation end module which carries out the dynamic adjustment according to a power adjustment instruction of a power generation end; the meteorological prediction and data acquisition module is used for acquiring meteorological data in a future time period in real time and sending the meteorological data to the intelligent control and scheduling platform; the energy storage end module sends data including lithium battery SOC and hydrogen storage tank pressure to the intelligent control and scheduling platform and performs charging and discharging according to an energy storage end charging and discharging priority strategy; and the intelligent control and scheduling platform receives the electricity price data of the weather prediction and data acquisition module, the energy storage end module and the power grid in real time, generates a power generation end power regulation instruction and an energy storage end charging and discharging priority strategy, and meanwhile, improves the income and maximizes the hydrogen energy use proportion through electricity price peak-valley arbitrage and green electricity transaction premium. The power grid stability and the energy utilization rate are greatly improved, the energy storage life is prolonged, and the investment payback period is shortened.

The invention discloses a green power computing power fusion scheduling model construction method and a scheduling platform, and relates to the technical field of green computing power. The green power computing power fusion scheduling model construction method comprises the steps of determining an adjustable reference load, determining a peak clipping and valley filling optimization load, determining a clean energy output load, determining a computing power center computing power task execution optimal load curve, monitoring a computing power center fusion scheduling task execution process and the like. A green electric power computing power fusion scheduling platform is constructed, and fusion scheduling task execution responsivity monitoring, computing power center electricity charge economy analysis, computing power center carbon emission reduction analysis and the like of a computing power center are carried out. The beneficial effects of the invention are that the system employs the technologies of big data, cloud computing and the like, builds a green power calculation power scheduling platform, monitors and analyzes the clean energy supply and demand conditions of the calculation power centers of the whole province, provides calculation power task scheduling services for the calculation power centers of the whole province, integrates clean energy consumption and green power calculation power, and improves the efficiency of the whole province. And the calculation power load active matching clean energy supply is realized.

Disclosed in the present invention a green power tracing method for a high-proportion renewable energy supply park, comprising: building a park network architecture model, and, on the basis of power flow data at any moment t throughout the year, splitting the park network architecture model into a plurality of active radiation-type power distribution lines; calculating the green power component of each renewable energy in each power distribution line in a single power user; accumulating the green power components to obtain green power consumed by the single power user at any time t and green power generation capacity output by a single renewable energy at any moment t; and forming a green power consumption matrix of the single power user throughout the year and a green power generation capacity matrix of the single renewable energy throughout the year. According to the present invention, the green power consumption of power users can be accurately evaluated, thereby providing accurate data support for green power tracing for users within parks.

The invention relates to the technical field of data center interaction, and particularly discloses an information interaction method and system for computing power and electric power collaborative scheduling of a data center, which integrates multi-source heterogeneous data and constructs a space-time correlation model to realize accurate prediction and dynamic modeling of resource demands of the data center. The real-time learning ability of the DRL and the discrete decision advantage of the MIP are utilized to realize multi-objective synchronous optimization, the energy efficiency and economy of the data center are significantly improved, the multi-objective optimization can realize "computing power-electric power-heating power" coupling, the block chain technology ensures that data cannot be tampered and is transparent and credible, the security and auditing performance of the system are improved, and the system performance is improved. Carbon footprint tracking, green power authentication and PUE index dynamic energy efficiency optimization are supported, green power use is directly stimulated, the carbon footprint and operation cost is reduced, thermal data is used for cooling control, power data is used for task scheduling, resource conflicts are avoided, the limitation of traditional single resource scheduling is broken through, and the response speed is increased.

The invention provides an elastic computing power scheduling method and device based on space-time prediction and a medium, and belongs to the technical field of cloud computing and edge computing. The method comprises the following steps: acquiring a historical load, a satellite cloud picture, meteorological data, a burst flow mark, an energy price and a green electricity proportion in real time; constructing a fusion prediction model which comprises a multi-modal feature coding module, a space-time attention fusion module and a prediction output layer; a multi-objective optimization function is constructed, cost, delay and resource fluctuation are minimized, and green rewards are maximized; solving a task allocation variable and a resource adjustment amount by adopting mixed integer programming; the actual green electricity utilization rate is monitored, and the green reward coefficient is dynamically adjusted to correct prediction and scheduling deviations. According to the method, the computing power demand fluctuation of different areas in the future time period can be predicted in advance, so that resource allocation is dynamically adjusted, resource idleness and waste are reduced, and the utilization rate of computing power resources is remarkably improved.

The invention provides a new energy green electricity transaction quantity reporting strategy algorithm based on deep learning. The new energy green electricity transaction quantity reporting strategy algorithm based on deep learning comprises the following steps: a, data collection: acquiring multi-source data from an electricity market, a weather forecast system, historical power generation data and a load prediction system, the data including historical electricity price, weather conditions, power generation power and power grid load data, and recording as X = {x1, x2,..., xn}, wherein xi is a time sequence data feature vector. According to the new energy green power transaction quantity reporting strategy algorithm based on deep learning, the problem of prediction errors caused by randomness and intermittency in new energy power generation is innovatively solved through a deep learning technology, and the prediction accuracy of the new energy green power transaction quantity reporting strategy algorithm based on deep learning is improved. Power generation fluctuation and weather change features are extracted through a multilayer convolutional neural network, and extreme weather events are automatically identified in combination with an attention mechanism, so that the algorithm can more accurately capture market fluctuation.

The invention relates to the field of electricity transaction, in particular to an electricity transaction intelligent algorithm platform based on block chain consensus. The method comprises the following steps: acquiring a real-time green electricity encrypted data set, uploading the real-time green electricity encrypted data set to a block chain node, and generating an unactivated digital green certificate data set; based on the non-activated digital green certificate data set, generating a grid-connected verification instruction, updating the non-activated digital green certificate data set to a tradable state, and generating a tradable digital green certificate data set; obtaining a power grid dynamic parameter set, and generating a green certificate time pricing data set through a space-time right dynamic pricing strategy based on the power grid dynamic parameter set and the tradable digital green certificate data set; and according to the green certificate time pricing data set, the digital green certificate is cancelled after verification in the power utilization process of the user, and a green power consumption traceability report is output. In the green electricity transaction process, fair and orderly development of the green electricity transaction market is promoted.

The invention relates to the technical field of power systems, in particular to an indirect carbon emission method considering new energy and green power transactions, which comprises the following steps: S1, load flow calculation and network loss consideration: determining load flow distribution and forming a matrix required by calculation; s2, unit carbon emission intensity calculation and node carbon potential determination: determining the carbon emission property and intensity of the connected unit; s3, carbon emission responsibility affiliation and green power transaction allocation: distinguishing carbon emission responsibilities of contract power and non-contract power; s4, carbon emission property right distribution and time weighted calculation: after obtaining the carbon emission flow rate allocated by the power supply and the load of each unit, multiplying the carbon emission flow rate by a preset time scale to obtain the carbon emission property right limit of each part of each power grid; according to the method, the accuracy of carbon emission accounting is improved, the definition of the carbon emission distribution characteristics of the power system is enhanced, and the method is suitable for analysis of a lossy network and carbon emission management.

The invention discloses a regional carbon emission responsibility determination method and device based on a carbon emission factor, terminal equipment and a storage medium. The method comprises the following steps: acquiring the electric power type, the called-in electric power total amount, the called-out electric power total amount, a first carbon emission factor, the net consumption data of fossil fuel, fuel characteristic parameters, the fuel type number, the transaction electric quantity, the local power generation amount and the non-green power utilization electric quantity of a target area; calculating the total direct carbon emission according to the net consumption data, the fuel characteristic parameters and the fuel type quantity; calculating the total indirect carbon emission according to the electric power type, the total called-in electric power, the total called-out electric power and the first carbon emission factor; calculating a regional power average carbon emission factor of the target region according to the transaction power quantity, the local power generation quantity, the total direct carbon emission quantity and the total indirect carbon emission quantity; and according to the regional power average carbon emission factor and the non-green power consumption quantity, the carbon emission responsibility of the target region is checked. According to the invention, accurate accounting of electric power carbon emission is realized.

The invention provides a comprehensive energy system optimization scheduling method and device considering diversified application of wind, light and green power, electronic equipment and a storage medium, and relates to the technical field of new energy technology and power system integration optimization. According to the method, a comprehensive energy system mathematical model integrating wind, light, green electricity, a hydrogen and ammonia production process, thermal power ammonia-doped combustion and thermal power oxygen-enriched combustion is constructed; combining the comprehensive energy system mathematical model to construct a comprehensive energy system scheduling model considering cost effectiveness, new energy utilization rate and environmental protection; and selecting a target solution algorithm from the plurality of solution algorithms, constructing an operation scene, and performing simulation solution on the integrated energy system scheduling model to obtain an integrated energy system optimization scheduling result. According to the embodiment of the invention, wind-solar-green-electricity hydrogen production ammonia synthesis and thermal-electricity ammonia-doped combustion and oxygen-enriched combustion technologies are effectively integrated, an ecological system for efficient cyclic utilization of energy and resources is created, and green transformation and industrial upgrading of an energy structure are promoted.

The invention discloses an energy storage-photovoltaic-electrolytic aluminum system dynamic optimization method suitable for multiple scenes, and relates to the technical field of intelligent power grids, and the method comprises the steps: collecting and preprocessing energy storage-photovoltaic-electrolytic aluminum system data, obtaining photovoltaic, load and electricity price characteristics, constructing an equipment mathematical model, and carrying out the optimization of the equipment mathematical model; the method comprises the steps of predicting a state of charge, battery cycle aging cost, photovoltaic output power, load baseline power and an adjustable flexible interval, constructing a system state prediction model, an economic dispatching optimization model and a self-adaptive control model, outputting a power prediction report, a day-ahead optimal economic dispatching plan and an energy storage power control instruction, and carrying out energy storage control. The energy storage power control instruction is subjected to multi-scene logic judgment and then is transmitted to the energy storage converter to be executed, feedback is obtained, and visualization is carried out through the integrated digital board. Through intelligent prediction and adaptive control, collaborative optimization of economy, reliability and green power consumption efficiency is realized, and the comprehensive performance of the energy storage-photovoltaic-electrolytic aluminum system under variable working conditions is improved.

The invention provides a wind-solar hydrogen production and ammonia synthesis system and a configuration method thereof, electronic equipment and a storage medium. The wind and light hydrogen production and ammonia synthesis system comprises a wind and light hydrogen production subsystem, an ammonia synthesis subsystem and a coordination controller which are relatively independent, the ammonia synthesis subsystem comprises a hydrogen storage tank, the hydrogen storage tank is connected with the wind and light hydrogen production subsystem, and the configuration method of the wind and light hydrogen production and ammonia synthesis system can be executed by the coordination controller. The configuration method of the wind-solar hydrogen production ammonia synthesis system comprises the following steps: firstly, determining capacity configuration parameters of a wind-solar hydrogen production subsystem by taking the minimum leveling hydrogen production cost as a target; and determining the capacity configuration parameters of the ammonia synthesis subsystem based on the capacity configuration parameters of the wind-solar hydrogen production subsystem by taking the maximization of the wind-solar absorption rate, the minimization of the total cost of the system and the minimization of the operation cost of the system as targets. The wind and light hydrogen production subsystem and the ammonia synthesis subsystem are subjected to two-stage decoupling type system configuration, and stable operation of the ammonia synthesis process is ensured while efficient utilization of green electricity is achieved.

The invention discloses a carbon right-green certificate collaborative transaction method based on a block chain, and belongs to the field of block chain technology and environment management. The method specifically comprises the following steps: 1) deploying an intelligent contract based on an Ethereum platform, and integrating power transaction, carbon quota delivery and green certificate issuing process chains to realize automatic execution of transaction rules and non-tampering of data; (2) a Carbon Token excitation mechanism is innovatively designed, a DPoS-CT consensus algorithm considering the right of the Carbon Token is proposed, and a market subject is excited to continuously reduce emission; 3) a dynamic reputation model and a reward and punishment mechanism are used to quantify subject performance behaviors and distribute on-chain rights and interests; and 4) resetting the transaction cycle every 24 hours, and optimizing quota allocation and consensus parameters based on historical data. According to the mechanism provided by the invention, renewable energy transaction can be effectively stimulated, and after the block chain carbon pass system is introduced, the quota completion rate, the green electricity utilization rate, the carbon emission, the carbon right-green certificate transaction volume and the economic benefit are optimized to a certain extent.

The invention relates to the technical field of electricity transaction, in particular to an hour-level green electricity transaction matching method and system considering a green certificate transaction blockchain, and the method comprises the following steps: S1, data collection and preprocessing: collecting the power generation operation data of a green electricity supplier and the power utilization behavior data of a user, preprocessing the collected power generation operation data and power consumption behavior data; s2, constructing a green certificate block chain: constructing a green certificate transaction platform based on a block chain technology, and recording green certificate transaction information; s3, establishing a matching model: constructing a multi-objective optimization model, and integrating multiple factors to carry out transaction matching; s4, transaction execution monitoring: after successful matching, executing the transaction and performing real-time monitoring; s5, transaction settlement evaluation: performing settlement and evaluation after the transaction is completed; according to the invention, the efficiency of green electricity transaction and the satisfaction degree of users and suppliers are effectively improved, and efficient utilization of green electricity resources and vitality improvement of the energy market are realized.

The invention belongs to the technical field of high-energy-consumption industrial energy conservation and carbon reduction, and particularly relates to an electrolysis process waste heat gradient utilization and green electricity energy storage coupling system and a regulation and control method thereof. An electrolysis process waste heat gradient utilization and green electricity energy storage coupling system comprises a waste heat recovery module used for recovering and gradient utilization of electrolysis high-temperature and medium-low-temperature waste heat for power generation or heat supply; the green electricity direct supply module comprises a photovoltaic unit, a hybrid energy storage unit and an electricity-heat conversion unit and is used for preferential direct supply, fluctuation absorption and storage of green electricity; and the multi-energy coupling regulation and control module is in communication connection with each module and a power grid, and dynamically optimizes and coordinates energy distribution among waste heat power, green power, energy storage and the power grid based on a preset algorithm.

The invention relates to the technical field of electricity transaction, in particular to a green electricity-carbon market linkage-based green electricity transaction matching method, which comprises the following steps of S1, data acquisition and preprocessing: acquiring green electricity transaction data, and cleaning, screening and preprocessing the acquired green electricity transaction data; s2, establishing a green electricity-carbon market linkage model: establishing the green electricity-carbon market linkage model; s3, green electricity transaction matching calculation: calculating an optimal green electricity transaction matching scheme to realize cost and benefit optimization; s4, risk assessment and control: assessing the risk of the transaction scheme, and formulating risk control measures; s5, transaction execution and monitoring: executing the transaction according to the transaction scheme and performing real-time monitoring, collecting and analyzing data, and dynamically adjusting and optimizing the scheme; according to the invention, energy structure optimization and greenhouse gas emission reduction targets are promoted to be realized, and powerful support is provided for development of renewable energy sources and carbon emission reduction.

The invention belongs to the technical field of intelligent heat supply, and provides a green power consumption heat storage and release matching control method and system based on a water heat storage boiler, and the method comprises the steps: firstly obtaining a heat load prediction sequence and an electric power spot market price prediction sequence of a heat supply system; secondly, regarding the heat supply network as a graph structure composed of nodes and pipelines, and establishing a pipe network dynamic model for describing the hydraulic and thermal characteristics of the heat supply pipe network; and finally, with the purpose of minimizing the comprehensive operation cost of the heat supply system in the whole scheduling period, and with the whole network heat balance, heat source operation, centralized heat storage device operation, heat supply network safety and user comfort as constraint conditions, solving to obtain a source network load storage cooperative control strategy. The purpose of integrated collaborative optimization of the heat source, the energy storage, the pipe network and the load is achieved, a scheduling strategy with better economical efficiency can be generated, and the problems that the absorption capacity is insufficient, and the overall operation economical efficiency of the system is not high are solved.

The invention discloses a system and a method for rapidly and efficiently decomposing ammonia to produce hydrogen through cooperation of plasma catalysis. Ammonia gas enters the normal-pressure arc temperature plasma reactor to form rotating gas flow, is ionized into high-activity plasma under the driving of high-voltage electricity, and is pushed by the rotating gas flow and a gradually-shrinking opening of the reactor to form large-area three-dimensional plasma jet flow, and jet flow gas upwards flows into a coaxial upper-layer catalytic area and downwards flows into a coaxial outer-layer catalytic area due to the limitation of a wall surface; and the reacted gas flows out from a gas guide hole at the lower part. Ammonia gas is firstly activated and pre-decomposed in the arc temperature plasma area and then secondarily decomposed in the coaxial catalytic area, heat of the temperature plasma area directly acts on the catalytic area, and external heating is not needed. The whole structure is that the temperature plasma area and the catalytic area are coaxially integrated, so that the waste heat utilization rate and the reaction energy efficiency are improved. The system is simple and compact in structure, can flexibly supply hydrogen in a distributed manner, is high in energy density, and can be directly driven by wind, light and green electricity.

The invention discloses a methane-methanol co-production capacity configuration method coupling green electricity hydrogen production and carbon capture technology, which comprises the following steps: obtaining load data and meteorological data in an energy supply area, and obtaining a load curve, an illumination curve and a wind speed curve of the energy supply area through a clustering method; establishing a steady-state model of the equipment according to the operation mechanism of the equipment in the integrated energy system and the coupling relation between the equipment; establishing a mixed integer linear programming model according to the coupling relationship and the steady-state model, and solving the mixed integer linear programming model; and the investment cost of the electrolytic cell is changed, a CPLEX solver is called to solve the mixed integer linear programming model, and capacity configuration optimization results of the methanation equipment and the methanation equipment are obtained. According to the method provided by the invention, a configuration scheme and a scheduling plan of the comprehensive energy system can be scientifically planned, and the capacity of methanation equipment and methanation equipment can be determined in an auxiliary manner on the basis of sensitivity analysis of the investment cost of the electrolytic cell.

The invention discloses a photovoltaic output prediction-based green electricity hydrogen production power adaptive regulation and control system and a photovoltaic output prediction-based green electricity hydrogen production power adaptive regulation and control method, relates to the technical field of green electricity hydrogen production, and solves the technical problems of high light abandoning rate, unstable equipment operation and difficulty in maximizing green electricity absorption efficiency on the premise of guaranteeing equipment safety caused by real-time matching of photovoltaic output. According to the method, historical photovoltaic data and weather forecast data are fused, the sun position and theoretical irradiance are calculated, short-term photovoltaic power generation output power is predicted, an advance is provided for hydrogen production power adjustment, power deviation is calculated through a PID controller, the hydrogen production power is dynamically adjusted, and second-level response is achieved. Meanwhile, an equipment constraint upper limit is introduced, when the total power exceeds a safety threshold value, the adjusting power is automatically corrected, overload is avoided, then secondary adjusting signals are combined, the adjusting power is reversely deduced directly through the safety threshold value, signal processing links are reduced, and the adjusting efficiency is improved.

The invention provides a renewable energy driven iron-based zero-carbon-emission energy storage power generation system based on iron-oxygen circulation, and belongs to the technical field of renewable energy utilization and power generation, and the renewable energy driven iron-based zero-carbon-emission energy storage power generation system comprises a renewable energy consumption module, an alkaline water electrolysis hydrogen production module, a hydrogen reduction reaction module, a combustion energy supply module and a steam Rankine cycle module; the renewable energy consumption module is used for acquiring and converting renewable energy into electric energy; the alkaline water electrolysis hydrogen production module is used for producing hydrogen by using electric energy; the hydrogen reduction reaction module utilizes hydrogen to carry out reduction reaction to store energy; and the steam Rankine cycle module is used for converting energy released by combustion into electric energy. Based on iron-oxygen circulation and through cooperative operation of the renewable energy consumption module, the alkaline water electrolysis hydrogen production module, the hydrogen reduction reaction module, the combustion energy supply module and the steam Rankine cycle module, efficient consumption of renewable energy, effective storage and conversion of energy and zero-carbon-emission green electricity production are achieved.

The embodiment of the invention discloses an intelligent energy consumption regulation and control steel smelting system based on multi-energy complementation, and the system comprises a multi-energy complementation energy supply system which is used for integrating various energy forms, forming a dynamic cooperative energy supply network, and carrying out the energy cooperative operation according to an energy priority strategy and a dynamic matching mechanism; the intelligent regulation and control platform adopts a three-layer framework of'perception-decision-execution 'to coordinate energy flow and process operation between the multi-energy complementary energy supply system and the multi-energy coupling process equipment; the multi-energy coupling process equipment comprises hydrogen-based direct reduction ironmaking equipment, and hydrogen is used for replacing traditional coke to serve as a reducing agent for ironmaking; comprehensive energy supply monitoring and optimization can be carried out on the steel smelting process, various renewable energy sources are combined, and the problems that a single renewable energy source is intermittent, depends on a power grid and the like are effectively solved; meanwhile, the multi-energy complementary hydrogen storage process is coupled with the hydrogen metallurgy process, and the multi-energy cooperation problems of whole-process green power supply, waste heat utilization and the like are solved.

The invention discloses a universal method and system for dynamically defining a carbon footprint of a product and a related device, and relates to the field of intelligent accounting of the carbon footprint of the product, and the method comprises the steps: obtaining a bill of material of the product, carrying out the disassembly, obtaining a function unit, and associating with a corresponding production process link; the carbon emission of each production process link is automatically calculated; calculating the carbon emission of the dynamic data; describing the unstructured text, and identifying recessive carbon emission; acquiring regional real-time green electricity proportion data, and calculating the green electricity emission reduction of the product after correction; and based on the carbon emission of each production process link, the carbon emission of the dynamic data, the hidden carbon emission, the green electricity emission reduction and the carbon emission of the waste recovery stage, calculating the life cycle carbon footprint of the product, then carrying out balance verification, generating a three-level structured report, and carrying out uplink storage. According to the method, the integrity of the accounting boundary can be improved, the emission source coverage rate and the recognition efficiency are improved, and the accuracy and timeliness of the product carbon footprint accounting result are improved.

The invention discloses an energy storage type virtual power plant energy distribution method considering green power transaction and new energy consumption, and the method comprises the steps: building an uncertainty model of each random variable under a green power transaction condition through a scene random differential method through generating a classification scene data set of frequency modulation demands and wind and light output original data under a green power transaction environment; generating a frequency modulation demand and a wind and light output scene with time sequence correlation; with the optimal benefit of the energy storage type virtual power plant as a target function, establishing an energy management two-stage stochastic optimization model of the energy storage type virtual power plant participating in the electric energy-frequency modulation combined market, and setting energy management model constraint conditions of the energy storage type virtual power plant participating in the electric energy-frequency modulation combined market; and solving the energy management model to obtain an optimization scheme that the energy storage type virtual power plant participates in power market profit. According to the method, the specific flexible adjustment characteristic of the energy storage type virtual power plant in a novel power system can be exerted, the scheduling plan performability is improved, the income mode of the virtual power plant is enriched, and the income level of the independent virtual power plant participating in the green electricity transaction market is effectively improved.

The invention provides a plasma heating hydrogen-rich direct reduction ironmaking system and method. The system comprises a plasma shaft furnace, a heat exchanger, a washer, a desulfurization device, a dehydration device and a pressurization device, the plasma shaft furnace comprises a feeding area, a reduction area, a blanking area and a plasma heating area from top to bottom; the plasma heating area is provided with a hydrogen plasma torch, a thermal reduction gas circulation outlet and a hydrogen inlet; and the hydrogen plasma torch is used for heating and ionizing hydrogen entering from the hydrogen inlet. According to the system and method, the green electricity hydrogen plasma torch is adopted for heating and ionizing hydrogen, then sponge iron is heated and reduced to produce molten iron, compared with a traditional hydrogen heating mode, the heating speed is high, the temperature is high, carbon-containing fuel is not combusted, safety and hydrogen embrittlement are achieved, compared with a traditional shaft furnace for producing sponge iron, low-quality ore can be adopted for producing molten iron, and the production cost is low. The control is convenient.

The invention discloses an intelligent electric energy meter data acquisition device, method and equipment for electric carbon metering and a storage medium, and relates to the technical field of electric power systems and carbon emission management, and the device comprises a carbon emission hardware calculation circuit module which verifies frozen data and regional-level electric carbon factors and line loss power of a superior node, and generates carbon emission data; a first non-volatile processor storing carbon emission data; and the second nonvolatile processor and the first nonvolatile processor are backups for each other and store electric quantity freezing data. The device expands a carbon emission metering function at low cost through an idle RS485 port of an existing intelligent electric energy meter, generates a dynamic electric carbon factor through local calculation, accurately calculates carbon emission data, and improves the accuracy of the carbon emission data. The data accuracy, real-time performance and reliability are improved, the centralized calculation burden is relieved, the system modification cost is reduced, large-scale popularization and application are supported, and low-carbon transformation and green power management are effectively promoted.

The invention discloses a community distributed green electricity hydrogen production and cogeneration integrated system and a control method. In the system, a photovoltaic / wind power generation module converts solar energy / wind energy into electric energy and supplies power to user side electric equipment connected with a converter and a water electrolysis hydrogen production module; the water electrolysis hydrogen production module is used for electrolyzing water to produce hydrogen; the hydrogen storage module is used for storing the prepared hydrogen, and a storage period from several hours to several months can be realized; the hydrogen fuel cell heat and power cogeneration module is used for supplying electric energy generated by hydrogen to user side electric equipment, heat energy is transmitted to the heat storage water tank for heat storage, and heat is supplied to users and domestic hot water is provided. According to the system, community renewable energy green electricity can be utilized to produce hydrogen and store the hydrogen, the hydrogen is supplied to the hydrogen fuel cell combined heat and power module when a user side needs to use energy, the capacity and energy consumption volatility and time difference are balanced, the distributed renewable energy utilization rate is increased, dependence of a community on power grid energy is relieved, and carbon emission is reduced.