122 results about "Green certificate" patented technology

The invention relates to the technical field of system dynamics, and discloses an electricity certificate carbon market price analysis method and system based on system dynamics, and the method comprises the steps: S1, determining the main body of a green certificate transaction market and the main body of a carbon emission permit transaction market, and determining a renewable energy power generation mode; s2, constructing a TCC cost control mechanism; s3, TCC cost is calculated according to a TCC cost control mechanism; s4, establishing stock flow dynamic model frames of the green certificate market and the electricity market and the carbon emission permit trading market and the electricity market, and combining the two dynamic model frames to generate an electricity certificate carbon market stock flow dynamic model frame; and S5, analyzing the electricity evidence carbon market price. The system comprises an information input unit, a mechanism construction unit, a calculation and analysis unit and a system dynamics model framework construction unit. According to the method, the system dynamics and the method for controlling and optimizing the TCC cost are combined, and the analysis accuracy and reliability are improved.

The present application relates to a kind of cross-border integrated energy system collaborative operation optimization method considering carbon-green certificate combined transaction, first, build cross-border integrated energy system CBIES, cross-border integrated energy system CBIES including gas turbine, gas boiler, renewable energy unit, energy storage device, electric boiler, wherein renewable energy unit includes wind power generation and photovoltaic power generation, energy storage device includes battery and heat storage tank;Second, propose the cross-border integrated energy system model considering heat network, power grid loss, on the basis of fully considering cross-border energy flow and conversion, introduce cross-border green certificate, carbon transaction, establish the cross-border integrated energy system collaborative optimization model considering carbon-green certificate combined transaction;Finally, the collaborative operation optimization result is obtained by the model simulation established.This application provides optimization method, which can reduce the operation cost of integrated energy system in different countries, and also improve energy optimization configuration and renewable energy consumption amount.

An electricity-carbon-green certificate market transaction method based on chaotic mapping considering carbon capturing, comprising: building a transaction strategy for describing the interaction of the market entities in a multi-element market, the multi-element market comprises an electricity market, a carbon market and a green certificate market; and building an upper-layer electricity-carbon-green certificate multi-market combined transaction model considering carbon emission settlement based on the transaction strategy. With the method proposed in the present invention, the model is built according to the energy transaction flow existing in among the transaction entities, efficient utilization of renewable energies and low carbon emissions can be realized, national requirement on low carbonization of market transaction can be satisfied, and a multi-element market transaction mechanism that complies with the dual-carbon target is provided for the existing energy transaction market.

The invention relates to an electricity-carbon-green evidence fusion multi-market collaborative service equilibrium decision-making method. The method comprises the following steps: step 1, analyzing electricity-carbon-green evidence benefits under a multi-coupling mechanism; step 2, based on the electricity-carbon-green evidence benefit analysis result under the multi-coupling mechanism in the step 1, constructing a system operation optimization model under the multi-coupling mechanism; step 3, training and calibrating the system operation optimization model under the multi-coupling mechanism constructed in the step 2; 4, performing optimization verification on the system operation optimization model under the multi-coupling mechanism after training and calibration in the step 3; and step 5, using the system operation optimization model under the multi-coupling mechanism after optimization verification in the step 4 to output a daily optimal decision strategy to participate in market decision execution. According to the method, collaborative optimization of electric quantity distribution, carbon emission reduction accounting and green certificate configuration can be realized, and the green power consumption accuracy and the multi-market collaborative operation efficiency are improved.

The invention discloses an electricity-hydrogen-gas comprehensive energy system self-adaptive optimization method oriented to multi-dimensional carbon asset collaborative transaction, and the method comprises the following steps: 1, introducing a dynamic emission factor and a multi-dimensional carbon asset collaborative transaction mechanism, and constructing a carbon emission optimization model of an electricity-hydrogen-gas three-energy coupling system; 2, performing dynamic allocation of carbon emission responsibility by adopting a game equilibrium-deep learning hybrid model; step 3, taking minimization of energy supply cost, carbon emission cost and green certificate-carbon transaction cost as targets, and constructing an electricity-hydrogen-gas coupled comprehensive energy system scheduling model; 4, simulation is carried out, and the effectiveness of the optimization model and method is verified; according to the invention, the cooperative efficiency of the power system, the natural gas network and the hydrogen energy system is effectively improved, so that the energy utilization is optimized, and the carbon emission of the system is reduced.

The invention discloses a hydrogen-electricity coupling power market multi-mode collaborative optimization method and system, and relates to the technical field of power system automation and comprehensive energy management, and the method comprises the steps: collecting wind-solar new energy output prediction data and power market data in real time; a multi-income model integrating spot goods, auxiliary services, green certificates and carbon transactions is constructed, an equipment depreciation cost constraint is introduced, and an optimal income combination is calculated through mixed integer linear programming; based on the critical electricity price, rapid switching between a hydrogen production mode and a power generation mode is achieved, and an optimal scheduling instruction set and a collaborative transaction strategy are generated and automatically reported to the market; and carrying out full-life-cycle economical efficiency and safety verification on the operation strategy by using a digital twin simulation platform. According to the method, flexible switching and multi-market income maximization of the hydrogen-electricity coupling system are realized, the internal yield of a project is remarkably improved, the peak regulation and frequency modulation capability of a new energy power grid is enhanced, and a full-process automatic closed-loop system is constructed.

The invention discloses a park integrated energy system double-layer scheduling method and system considering carbon emission. The method comprises the following steps: establishing a park-oriented integrated energy system model; establishing a green certificate-stepped carbon transaction mechanism model in the integrated energy system; establishing an operator and user model and a target function in the integrated energy system; a Stackelberg game framework is established; solving the master-slave game to obtain an optimal scheduling result; according to the method, an integrated energy system double-layer optimization model fusing green certificate-stepped carbon transaction is established, and an integrated energy system operation optimization model taking economical efficiency and environmental protection as targets and taking power balance, equipment operation and the like as constraints is constructed; the system carbon emission is limited, the user comprehensive demand response and the user satisfaction degree are considered in the master-slave game, the carbon emission is reduced, the user cost is reduced, the low-carbon emission reduction potential of the park comprehensive energy system is excavated, the low-carbon property and the economical efficiency are considered, and the win-win situation of an operator and the user is achieved.

The invention provides an electricity-carbon-green evidence distributed collaborative optimization method and equipment. The method comprises the following steps: constructing a power transmission network side scheduling model; constructing a power distribution network side scheduling model, and converting joint opportunity constraints in the power transmission network side scheduling model and the power distribution network side scheduling model into linear constraints based on an improved sample average approximation MSAA method; and based on an alternating direction multiplier method ADMM, carrying out distributed collaborative optimization solution on the converted power transmission network side scheduling model and the power distribution network side scheduling model to obtain a collaborative scheduling scheme of the power transmission network and the power distribution network. Based on the method, the invention further provides electricity-carbon-green evidence distributed collaborative optimization equipment. According to the method, the flexibility of distributed resources in the power transmission and distribution network can be fully excavated and coordinated, three markets of electric energy, carbon emission permit and green certificate are planned as a whole on the premise of ensuring the dynamic frequency safety of the system, and the distributed collaborative optimization scheduling of the power transmission and distribution network is realized.

The invention discloses a comprehensive energy system low-carbon optimization scheduling method considering wind and light uncertainty and dynamic hydrogen price, and relates to the technical field of comprehensive energy system scheduling, and the method comprises the steps: building an adjustable heat-to-electricity ratio model and a power-to-gas refinement model based on a preset regional comprehensive energy system model; on the basis of a regional comprehensive energy system model, a dynamic hydrogen price model linked with the new energy output proportion and the hydrogen storage state is constructed, and real-time dynamic adjustment is conducted on the hydrogen price to achieve hydrogen energy supply and demand balance; integrating the dynamic hydrogen price model and the green certificate-carbon transaction model into a regional comprehensive energy system model; a simulation model is introduced into the integrated regional comprehensive energy system model; based on an equipment output scheme, fuzzy opportunity constraints are introduced. According to the method, by considering the wind and light uncertainty, the green evidence-carbon joint transaction and the dynamic hydrogen price, the utilization rate and the economical efficiency of new energy are improved, the system operation cost is reduced, and the effectiveness of the proposed method is further proved.

The invention belongs to the technical field of enterprise management, and particularly relates to a green transformation cost optimization method and system based on green premium, and the method comprises the steps: collecting the specified parameters of a target enterprise, so as to determine the green premium cost, the green premium cost comprises self-generation and self-use cost, special line direct supply cost, green electricity direct purchase cost, green electricity transaction participation cost, green certificate cost and green electricity investment cost; and formulating or optimizing an existing green transformation method according to the green premium cost so as to minimize the green transformation cost. Collecting specified parameters of the target enterprise to determine green premium cost; and according to the green premium cost, an existing green transformation method is formulated or optimized, so that the green transformation cost is minimized, reasonable suggestions can be provided for transformation of enterprises, and the transformation efficiency is improved.

The invention relates to the technical field of power systems and carbon trading, in particular to a zero-carbon park electricity-carbon joint distributed trading method based on carbon-green certificate market coupling. The method comprises the steps of constructing an objective function of a zero-carbon park electricity-carbon joint distributed transaction model based on carbon-green certificate market coupling, and constructing a carbon and green certificate market transaction model and a carbon-green certificate market coupling method of the zero-carbon park. The method comprises the following steps: constructing gas turbine, energy storage equipment, central air conditioning equipment, electric power balance and carbon emission balance constraints of a zero-carbon park electricity-carbon joint distributed transaction model based on carbon-green certificate market coupling, and carrying out distributed solution on the multi-park electricity-carbon joint transaction model by adopting an adaptive step length alternating direction multiplier algorithm; and obtaining an operation decision of the zero-carbon park system, and scheduling the zero-carbon park system. According to the zero-carbon park electricity-carbon joint distributed transaction method based on carbon-green certificate market coupling provided by the invention, collaborative optimization of electricity transaction and carbon emission right and green certificate matching is realized, the utilization efficiency of renewable energy sources in the park is remarkably improved, and the overall carbon emission level of the zero-carbon park is reduced.

The invention provides a park integrated energy system optimization scheduling method considering green certificate carbon transaction, which comprises the steps of establishing an optimization scheduling model comprising a step green certificate transaction model, a step type carbon transaction model and a demand response model, establishing a master-slave game double-layer optimization model on the basis of the model, taking an energy operator as a leader, and taking the energy operator as the leader as a leader; and an energy supplier, an energy storage operator and a load aggregator serve as followers. And then, solving the established double-layer master-slave game model by adopting a differential evolution algorithm in combination with a Cplex solver. And finally, verifying the effectiveness of the model and the solving method by adopting example analysis. After a green certificate transaction mechanism, a stepped carbon transaction mechanism and demand response are introduced, the peak clipping and valley filling effect is obvious, reduction of electric, thermal and cold loads is realized in a reasonable range, an optimization result can form a reasonable energy purchase and sale price and supply and demand balance relationship, the carbon emission of the system is reduced, and the energy consumption of the system is reduced. The method is of great significance to energy conservation and emission reduction of a park comprehensive energy system and improvement of main body benefits.

Provided are a method for regulating a wind-photovoltaic-storage power station based on electricity, green certificate, and carbon price prediction, a device, a medium, and a product. The method includes: inputting acquired historical price data into a price prediction model, and outputting a predicted price; determining a deviation vector of price data based on the historical price data and the predicted price, and generating an uncertainty set of the predicted price by using a multi-kernel-based one-class support vector machine algorithm; classifying the uncertainty set of the predicted price by using a neural network classifier, to obtain multiple types of price scenarios; solving, based on predicted prices under the multiple types of price scenarios, a joint clearing model by using a Pied Kingfisher Optimization (PKO) algorithm, to obtain an operation strategy for the wind-photovoltaic-storage power station; and regulating the wind-photovoltaic-storage power station based on the operation strategy for the wind-photovoltaic-storage power station.

The invention relates to a virtual power plant operation control method and device based on fuzzy demand response, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring operation state data, external market environment data and user load data of internal components of a virtual power plant; based on the power attribute data, performing fuzzy quantization processing on the user load data by adopting a logic function to obtain a target load curve; based on the operation state data, the carbon quota allocation data, the green certificate transfer data and the target load curve, determining a target operation strategy of the virtual power plant by taking resource minimization required by operation of the virtual power plant as a target; and controlling operation of the virtual power plant based on the target operation strategy, and adjusting parameters in the logic function according to an operation result of the virtual power plant. By adopting the method, the adaptive capacity of the system to renewable energy fluctuation can be improved, and the coordination and reliability of overall operation are enhanced.

The invention relates to the technical field of multi-energy complementary system optimization scheduling, and discloses a wind, light, water and fire storage optimization scheduling method, system and device based on carbon-green certificate transaction, and a medium. The method comprises the following steps: respectively establishing a stepped carbon transaction cost model and a green certificate transaction cost model; taking the renewable energy carbon emission reduction as an interaction bridge, and establishing an interaction cost model of the carbon-green certificate transaction; constructing an optimal scheduling model of the wind-solar-water-fire-storage multi-energy complementary system based on the interaction model; taking the minimum total operation cost of the system as an objective function, and integrating the carbon-green evidence interaction cost, the thermal power operation cost, the wind curtailment and light curtailment penalty cost and the energy storage cost; constructing a constraint condition set covering power balance, unit operation, cascade hydroelectric coupling, line transmission and energy storage dynamics; and through multi-strategy comparison verification, outputting an optimal scheduling scheme. Linkage excitation of the carbon market and the green certificate market is achieved, and the economical efficiency, the low-carbon level and the new energy consumption capacity of the system are improved.

The invention provides an electricity-carbon-green certificate multi-mode dynamic coupling pricing and cross-chain clearing method based on a federated learning-block chain fusion framework. Data islands are broken through differential privacy horizontal federation aggregation, an LSTM-GRU hybrid model is trained, and global price prediction with the error smaller than 5% is achieved; a TD3 reinforcement learning agent is introduced, a nonlinear linkage coefficient is generated in real time, the policy mutation response speed is increased by 50%, and the arbitrage space is compressed by 40%; a private chain and alliance chain double-chain heterogeneous architecture is constructed, an HTLC is used for binding electricity purchasing, carbon selling and green certificate purchasing as an inseparable transaction, the clearing delay is smaller than or equal to 800 ms, and the failure rate is smaller than 0.01%; zK-SNARK zero-knowledge proof is adopted to ensure that transactions can be audited and privacy is not leaked. The provincial 100-node cluster actual measurement shows that the prediction error is reduced by 75%, the policy delay is shortened by 51%, the combined transaction failure rate is reduced by 99.9%, and safe, efficient and compliant technical support is provided for multi-market collaboration in a high-fluctuation environment.

The invention discloses a green electricity-green certificate-carbon collaborative transaction system and an implementation method thereof, and belongs to the technical field of electricity market transaction. The system comprises an inter-province / intra-province unified market balancing module, a green certificate market clearing module, a green certificate-carbon linkage deduction module and a data interaction and settlement module. Based on an inter-province / intra-province unified market equilibrium model, inter-province tie line power is incorporated into a unified optimization variable, and a physical network and multi-element market integrated decision is realized; establishing a green certificate market clearing mechanism based on the generalized Nash game, dynamically forming fair green certificate prices, and optimizing environmental value distribution; a green certificate-carbon market linkage deduction mechanism is designed, and linkage connection of green certificates and carbon quotas is achieved; and a transaction closed loop of electric energy, green certificate and carbon quota is completed through joint settlement. According to the method, the inter-provincial market barrier is effectively broken, and the problems that high-proportion new energy transmission end areas are limited in thermal power transmission economy, low in new energy consumption rate, uneven in environmental value distribution and the like are solved.

This invention provides a method and apparatus for distribution network planning, relating to the field of new energy power generation technology. The method for distribution network planning includes: acquiring current distribution network parameters; determining a two-layer model of the distribution network system based on these parameters; wherein the upper-layer model of the two-layer model is constructed based on new energy investment inputs, green certificate trading costs, and carbon emission trading costs, while the lower-layer model is constructed based on distribution network operation problems; transforming the opportunity constraints of the upper-layer model into deterministic constraints, and constructing KKT conditions based on the lower-layer model; merging the deterministic constraints, KKT conditions, and the original constraints of the lower-layer model into the upper-layer model to generate a solution model; and determining the optimal system planning and operation scheme for the current distribution network based on the solution model, and configuring the distribution network accordingly. This method enables distribution network planning and operation while simultaneously considering new energy unit investment decisions, carbon emission trading, and green electricity certificate trading.

The invention provides a carbon effect evaluation method and device for enterprises considering green lights and green certificates. The method comprises the following steps: acquiring weights and magnitudes corresponding to a plurality of indexes of a plurality of enterprises; constructing an initial decision matrix based on the plurality of enterprises, the plurality of indexes and the corresponding magnitudes; performing normalization processing on different values of the same index in the initial decision matrix; performing forward processing on numerical values corresponding to the negative indexes in the first matrix; multiplying the numerical value corresponding to each index in the second matrix by the weight of the corresponding index; obtaining a minimum value and a maximum value of each index in the decision matrix; the distance between the numerical value of each index of each enterprise in the decision matrix and the minimum value of the corresponding index and the distance between the numerical value of each index of each enterprise and the maximum value of the corresponding index are calculated, and the positive distance and the negative distance of each enterprise are obtained; and sorting the plurality of enterprises based on the positive distance and the negative distance of each enterprise to obtain carbon effect evaluation results of the plurality of enterprises. And the sequencing accuracy of a carbon emission enterprise is improved.

This invention belongs to the field of integrated energy systems, specifically relating to a collaborative optimization method for a wind-solar-hydrogen-storage integrated energy system, aiming to solve the problem of the inability to dynamically optimize the allocation of environmental rights and interests in green electricity. The method includes: acquiring operational status information; establishing a dynamic decision-making model for environmental rights and interests in green electricity, calculating the marginal revenue of surplus green electricity between the green certificate selling path and the hydrogen production, storage, and emission reduction path based on real-time carbon prices, green certificate prices, and hydrogen prices, and outputting flow direction decision instructions; constructing a multi-timescale collaborative scheduling strategy, configuring lithium batteries as resources for minute-level power fluctuation mitigation, and configuring electrolyzers and hydrogen storage tanks as hour-level long-cycle energy time-shifting resources; executing multi-timescale energy management scheduling, and outputting an operational scheduling scheme. This invention also constructs a planning-operation two-layer optimization framework and a feedback correction mechanism, and uses an improved multi-objective particle swarm optimization algorithm for solution.

The invention discloses a calculation load green electricity direct connection operation method integrating multiple market mechanisms and business logic, which comprises the following steps of: firstly, providing a calculation load operation feature extraction method integrating historical information and business logic to output operation features; outputting a direct connection task priority, an electric energy marginal price, a carbon green certificate subsidy rate and a payment function of the time sequence; and then constructing a new energy green power multi-scene supply mechanism for calculating the load, constructing a new energy output scene tree based on the optimal transmission center of gravity, learning a dynamic distribution strategy of a power grid and direct connection green power by using a generative flow network, and finally, combining the operation characteristics, a time sequence and the dynamic distribution strategy, and through a constraint reinforcement learning and action feasible region projection algorithm, calculating the new energy output scene tree. And a green power direct connection optimization operation strategy with controllable cost, guaranteed task priority and reachable carbon target of the calculation load in a power and carbon transaction double-market environment is realized.

The embodiment of the invention discloses a method and device for determining an operation strategy of an electrolytic aluminum industrial park, and the method comprises the steps: determining a target operation strategy enabling a preset target function to be minimized from a plurality of candidate operation strategies of the electrolytic aluminum industrial park; wherein the target function comprises a target function under the condition that the electrolytic aluminum industrial park operates according to a candidate operation strategy; the operation and maintenance cost of a photovoltaic unit and an energy storage system in the electrolytic aluminum industrial park, the cost of purchasing and selling electricity from a superior power grid of the electrolytic aluminum industrial park, the carbon emission cost of the electrolytic aluminum industrial park participating in carbon market transaction and the cost of the electrolytic aluminum industrial park participating in green certificate transaction are converted into a target operation strategy; and determining an operation strategy of the electrolytic aluminum industrial park. Thus, collaborative optimization of multiple factors such as photovoltaic, energy storage, power grid electricity purchase and sale, carbon transaction and green certificate transaction is realized, through linkage with a multi-transaction market, the comprehensive operation cost of the park is effectively reduced, the energy economy and environment compliance of the park are remarkably improved, and the effectiveness of operation strategy optimization can be improved.

The invention discloses a micro-energy network alliance P2P transaction method based on a carbon cooperation mechanism and a storage medium. The method comprises the following steps: carrying out differential modeling on micro-energy networks according to different geographic positions, equipment resources, load characteristics and operation modes of the micro-energy networks; a dynamic carbon transaction and green certificate transaction mechanism responding to demand relationship changes is designed, and a micro energy network alliance multi-energy P2P transaction double-layer optimization scheduling model based on a carbon-green certificate collaborative interaction mechanism is established; and solving a lower-layer asymmetric Nash game problem by adopting an accelerated near-end atom coordination algorithm (APAC), and performing upper-lower layer iterative solution on the double-layer model to determine a transaction strategy. The P2P transaction mechanism constructed by the invention effectively considers the characteristics of different micro-energy networks, and the multi-energy P2P transaction mode based on distribution and micro-power cooperation and Nash game can improve the income of different types of micro-energy networks according to the energy contribution, thereby promoting the multi-energy coupling and transaction enthusiasm of different micro-energy networks in the power distribution network. And the autonomous decision-making capability in the energy transaction is improved.

The present application relates to a kind of micro-grid adaptive point-to-point cooperation method, device, system and medium, wherein the method of the present application, when requiring each micro-grid to build optimal transaction volume model locally, comprehensively considers its internal resource constraint, backup constraint, operating cost and coupling relationship with external associated market, such as electricity trading market, carbon emission trading market, green certificate trading market, ensures that transaction decision is not only based on internal economy, but also actively responds to external policy and physical constraint such as carbon emission reduction and system backup demand.Carbon emission trading cost and green certificate trading income are included in the objective function, directly stimulating low-carbon energy production and consumption, and improving the low-carbon nature of the overall transaction.Considering the uncertainty of new energy output and modeling the related backup constraint as an opportunity constraint, the transaction scheme can better respond to renewable energy fluctuations, ensuring the safety and reliability of system operation, effectively balancing the economy, low-carbon and safety of the transaction scheme.

This invention discloses a method and system for coordinated optimization of carbon emissions in a multi-park integrated energy system, belonging to the field of integrated energy optimization and scheduling technology. The method includes: constructing a dynamic carbon trading and green certificate flexible offsetting mechanism; building a two-layer game optimization model with the system operator as the leader and multiple park agents as followers; the upper-layer system operator optimization model uses the DQN algorithm to dynamically optimize and publish energy trading prices; the lower-layer park agent optimization model uses the PPO algorithm to perform distributed optimization scheduling of equipment within the park based on the received energy trading prices; improving the Shapley value benefit allocation method based on carbon emission reduction contributions to fairly distribute the total alliance benefits generated by the coordinated operation of multiple parks; and conducting collaborative iterative training of the two-layer game optimization model until game equilibrium is reached, outputting the optimal energy trading price and scheduling strategies for each park. This invention achieves a synergistic improvement in both the overall economic benefits and carbon emission reduction levels of the system.

The application discloses a kind of based on energy consumption side's province and land two-level non-fossil energy power consumption accounting method, belong to power system data management and green energy accounting technical field.The method follows user subject and consumption base principle, first determines accounting period and boundary, collects total social power consumption, power market transaction, cross-provincial power flow direction and other basic data;Secondly, a provincial accounting model is constructed, and five types of power consumption, including medium and long-term transaction, cross-provincial net inflow and self-generation and self-use, are integrated to calculate the total consumption of the province;At the same time, a city-level accounting model is constructed, and the city consumption is accounted according to the user types of direct entry into the city and proxy power purchase, combined with the provincial allocation coefficient.The application realizes the coordination and unification of physical power and green certificate rights and interests, solves the problems of repeated calculation and province-city disconnection in existing accounting, and provides reliable technical support for government energy-saving assessment, renewable energy responsibility weight calculation and non-fossil energy consumption accounting.

The invention provides a method and a device for determining an index weight of carbon emission of a green power and green certificate enterprise. The method comprises the following steps: determining a target enterprise of which the carbon emission is to be calculated; determining a plurality of associated enterprises associated with the target enterprise; obtaining quantities corresponding to a carbon input index, a carbon output index and a carbon transfer index corresponding to the target enterprise and the plurality of associated enterprises; determining first weights respectively corresponding to the carbon input index, the carbon output index and the carbon transfer index according to historical experience; determining second weights respectively corresponding to the carbon input index, the carbon output index and the carbon transfer index according to the fluctuation between the quantity values of the carbon input indexes respectively corresponding to the target enterprise and the plurality of associated enterprises; and generating a corresponding weight based on the first weight and the second weight corresponding to the carbon input index, the carbon output index and the carbon transfer index respectively. And the accuracy of determining the weight of each index in enterprise carbon emission calculation is improved, so that the accuracy of enterprise carbon emission calculation is improved.

The invention discloses an integrated energy system IES carbon-green certificate quota optimization method considering repeated income, and the method comprises the steps: firstly, building an optimization scheduling model in four scenes that the IES does not participate in a carbon market and a green certificate market, independently participates in the carbon market, independently participates in the green certificate market, and participates in a carbon-green certificate combined market, and obtaining the optimization scheduling results in the four scenes; secondly, carbon income and green evidence income obtained by unit new energy in the three markets are calculated, and whether hidden repeated income exists in the combined markets or not is analyzed; and establishing a carbon-green evidence quota optimization model, and obtaining a carbon-green evidence quota optimization result by using a particle swarm optimization algorithm. And finally, re-scheduling the IES according to the optimized quota, and verifying the weakening effect of the repeated income in the joint market under the new quota. According to the method, the problem of repeated income under the condition that the IES participates in the carbon-green evidence combined market can be effectively solved, the uniqueness of the new energy environment value is guaranteed, the sustainable development of the carbon-green evidence market is promoted, and excitation guidance is provided for new energy.

The application provides a multi-time-scale intelligent energy station cooperative operation control method and device, which is used for optimizing scheduling of the intelligent energy station by considering renewable energy consumption. The method constructs an optimization scheduling model of the intelligent energy station by considering operation cost and green certificate-carbon trading cost. Then, operation of the intelligent energy station is divided into three scales of day-ahead optimization scheduling, rolling optimization scheduling and real-time control, and specific control algorithms are respectively formulated. Then, according to equipment characteristics of the intelligent energy station, equipment in the station is divided into three categories according to start-stop flexibility, and is involved in control of different time scales with different margins. Finally, the operation state of the intelligent energy station is monitored in the operation day, and the optimization scheduling model is solved rolling to obtain an optimal scheduling plan of the intelligent energy station. The application overcomes the problems of not being able to fully encourage renewable energy consumption and carbon emission reduction, and not fully considering renewable energy output uncertainty and flexibility of the comprehensive energy system.

This invention discloses a multi-market collaborative bidding method for virtual power plants from a low-carbon perspective, belonging to the field of multi-market collaborative bidding for electricity. The method includes the following steps: S1, constructing a five-flow coupling model of electricity, carbon, heat, hydrogen, and green certificates, and classifying virtual power plant types to generate a triple uncertainty scenario; S2, building a three-order nested game bidding model; S3, constructing a joint risk management model, outputting risk costs and robust bidding feasible regions; S4, based on the electricity-carbon supply-demand ratio and robust feasible regions, realizing bidirectional matching and pairing transactions of electricity and carbon among multiple virtual power plants, generating initial bidding schemes for the five markets; S5, coupling the game bidding model, risk costs, and initial bidding schemes to obtain the optimal equilibrium bidding solution for the five markets; S6, feasibility verification and closed-loop optimization. Using the above-mentioned multi-market collaborative bidding method for virtual power plants from a low-carbon perspective, the economic benefits and long-term stable operation of the multi-virtual power plant alliance are maximized under the premise of low-carbon compliance.