176 results about "Green certificate" patented technology

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 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 discloses a renewable energy scheduling control method based on electricity-carbon-green evidence market coupling, and relates to the technical field of renewable energy control, and the method comprises the following steps: predicting wind and light output fluctuation intervals based on a neural network, and classifying the wind and light output fluctuation intervals; constructing a first simulator based on chaotic mapping, and constructing a second simulator based on quantum machine learning; controlling to switch the first simulator and the second simulator according to a classification result, and outputting a wind-light output predicted value; and controlling energy storage output according to the wind-solar output predicted value and a preset electricity-carbon interaction model. The method is used for solving the problem of insufficient simulator adaptability in different wind and light output fluctuation scenes and insufficient energy storage control capability in an electricity, carbon and green evidence cooperative scene.

The invention discloses a hydrogen-containing integrated energy system robust optimization scheduling method considering a dynamic green certificate-carbon emission collaborative transaction mechanism. The method comprises the following steps: establishing the dynamic green certificate-carbon emission collaborative transaction mechanism considering reward and punishment characteristics; establishing a hydrogen-containing comprehensive energy system equipment model according to a hydrogen-containing comprehensive energy system architecture; determining a target function and constraint conditions according to the dynamic green certificate-carbon emission collaborative transaction mechanism considering the reward and punishment characteristics and the hydrogen-containing integrated energy system equipment model so as to establish a hydrogen-containing integrated energy system robust optimization scheduling model considering the dynamic green certificate-carbon emission collaborative transaction mechanism; and solving the hydrogen-containing integrated energy system robust optimization scheduling model considering the dynamic green certificate-carbon emission collaborative transaction mechanism based on a robust linear optimization theory. According to the method provided by the invention, the running flexibility of the hydrogen-containing comprehensive energy system is improved, and meanwhile, the running economy and the carbon emission level of the system are improved.

The invention relates to the technical field of clean energy market optimization, and particularly provides an optimal scheduling method and device for a power system, and the method comprises the steps: obtaining a policy factor adjustment vector of the power system through a pre-trained Markov chain prediction model based on a policy factor vector of a current power system; adjusting the policy factor vector of the current power system by using the policy factor adjustment vector of the power system; wherein the policy factor comprises at least one of the following: carbon quota demand, carbon emission reduction and green evidence obligation consumption. According to the technical scheme, the market mechanism can be optimized, development of renewable energy sources can be promoted, the electric power structure can be optimized, and the aim of carbon emission reduction can be achieved.

The application discloses a kind of zero carbon scheduling method of virtual power plant with photothermal power station considering and multi-element resource game, first, according to the different division of resource, the park controlled by the virtual power plant with photothermal power station is divided into park 1, park 2, park 3;Establish the game architecture of virtual power plant with photothermal power station and its internal multi-element resource;Establish the output model of photothermal power station containing organic rankine cycle ORC, heat collection mirror field HF, heat storage tank TES;Establish the output model of combined heat and power unit CHP, combined cooling heating and power unit CCHP, and establish actual carbon emission model based on it;Carbon responsibility on power supply side is apportioned to park 1, park 2 by position fair apportionment rule;Establish carbon capture-electricity to gas coupling model;Establish carbon trading model and green certificate income model after responsibility apportionment;According to photothermal power station output model, carbon capture-electricity to gas coupling model, carbon trading model and green certificate income model after responsibility apportionment, construct the master-slave game model of one master and multiple slaves with power balance as constraint condition, leader with realizing zero carbon operation and total income maximum as target, follower with income maximum as target;And solve the maximum income of leader and follower in master-slave game, obtain scheduling scheme.

The invention relates to the technical field of power-hydrogen coupling system planning, in particular to a planning method, system and device for a power-hydrogen coupling system considering carbon-green certificate market and hydrogen load uncertainty and a storage medium, and the method comprises the steps: obtaining the historical operation data of the power-hydrogen coupling system and the historical transaction data of the carbon-green certificate market; generating a plurality of hydrogen load typical random scenes by utilizing a Monte Carlo simulation method according to historical operation data of the electricity-hydrogen coupling system; reducing the number of typical random scenes through a synchronous backward reduction method, and obtaining a typical reduced scene; based on the objective function and the constraint condition, constructing an electricity-hydrogen coupling system planning model considering the carbon-green evidence market and hydrogen load uncertainty; and inputting the obtained data into the electro-hydrogen coupling system planning model, and solving and calculating to obtain an electro-hydrogen coupling system planning scheme. The energy utilization efficiency of the electro-hydrogen coupling system can be improved, the system investment cost is reduced, the system stability is improved, and the system carbon emission is reduced.

The invention provides a low-carbon optimal scheduling method for an integrated energy system based on a green certificate-carbon transaction mechanism, so as to reduce the carbon emission of the integrated energy system and improve the renewable energy consumption capability. In order to improve the running flexibility of the IES containing the electro-hydrogen coupling unit, a proton exchange membrane electrolytic cell is introduced, and refined modeling is carried out on the hydrogen energy using process and equipment. A transaction model of a common stepped carbon transaction is improved and combined with a green certificate transaction mechanism, and a combined heat and power energy system model with an adjustable heat and power ratio is constructed; secondly, taking the minimum total cost of the system as an objective function, coupling a carbon transaction mechanism and a green certificate strategy, and performing optimization solution by using a Cplex solver; analyzing the influence of different carbon transaction mechanism parameters and green evidence parameters on the system; finally, four typical scenes are established, the proposed strategy is obtained through comparative analysis, the carbon emission can be remarkably reduced, the consumption amount of renewable energy sources is increased, meanwhile, good economic benefits are achieved, and reference can be provided for low-carbon economic dispatching of the comprehensive energy system.

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 invention provides a renewable energy dynamic binding green certificate time-sharing and step-by-step issuing method, and belongs to the technical field of green certificate issuing. Firstly, active power and timestamps of power generation equipment are collected in a fixed period to form collected data, independent windows are divided according to energy types, and real-time generating capacity is calculated based on the collected data; time-sharing and step-by-step issuing is carried out by comparing the real-time generating capacity with the preset reference electric quantity; a certificate is issued immediately when the electric quantity reaches the standard; if not, the electric quantity is stored in the scattered electric quantity pool. In the process, by calculating the window power generation characteristics of the independent window, the green certificate and the window power generation characteristics are bound to generate an irreplaceable digital green certificate, and the irreplaceable digital green certificate is written into the block chain. When the user cancels after verification, the system verifies the similarity between the data integrity and the feature vector, and the user can cancel after verification if the similarity reaches the standard. Through the above design, the green certificate is accurately checked and issued, the association between the green certificate and the power generation characteristics is enhanced, and the data is ensured to be safe and traceable.

The invention discloses a cross-regional green electricity spot-medium and long term linkage pricing method based on reinforcement learning, and relates to the technical field of electricity market scheduling, and the method comprises the steps: firstly constructing a state bus on a transaction platform, and converging spot price, contract price, power transmission margin, green certificate price and load prediction to generate a transaction state vector; a node quotation interval is output by adopting sharing-private security reinforcement learning, and a credibility score is recorded; when the node credibility is lower than a threshold value, calculating a credibility coefficient by using synchronous spectrum characteristics and a price difference tail form, and locking a suspicious subject through graph convolution; performing contract remapping and price-limited auction on the suspicious subjects, and rearranging and clearing the order to correct the price sequence; and finally, carrying out discount settlement on the corrected price and the contract reference, and carrying out double-layer training and static period write-back according to a priority playback sample, thereby realizing high collaboration of price signal credibility, power transmission safety and green power consumption.

The invention discloses a virtual power plant scheduling method for evolutionary deep reinforcement learning, and belongs to the technical field of power control. According to the method, a hydrogen-containing virtual power plant low-carbon economic dispatching model is constructed, hydrogen energy gradient utilization is realized through electric hydrogen production, electric-to-gas and hydrogen-to-ammonia technologies, a stepped carbon trading model is improved, a hydrogen energy green certificate trading model is introduced, and an evolutionary soft action device-evaluator (ESAC) algorithm is adopted to carry out optimized dispatching. According to the algorithm, population optimization and deep reinforcement learning of an evolutionary strategy are fused, and the mutation rate is dynamically adjusted through an automatic mutation adjustment mechanism. According to the method, the optimization precision and robustness of virtual power plant scheduling are remarkably improved, the operation cost is effectively reduced, and low-carbon operation of a multi-energy system is promoted.

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.

A VCG mechanism-based comprehensive energy system optimization operation method in an electricity-gas-carbon combined market comprises the following steps: constructing a comprehensive energy system coupling model integrating electric power, natural gas, carbon cycle and green certificate transaction, maximizing social welfare through a distributed robust optimization model, processing carbon price and green certificate price uncertainty by adopting a Wasserstein fuzzy uncertainty set, and obtaining a comprehensive energy system optimization model; and calculating an external payment value of each unit by using a VCG mechanism, endogenously determining an electricity price and a gas price, and finally outputting an optimal scheduling scheme meeting multiple constraints. The method can solve the problems that an existing single market mechanism is low in resource allocation efficiency, insufficient in carbon emission reduction excitation and the like, the reliability of multi-market data association analysis is improved by mining energy conversion, carbon circulation and other associations, the robustness under data limitation is enhanced through a Wasserstein uncertainty set, strategy quotation distortion is avoided through a VCG mechanism, and the reliability of multi-market data association analysis is improved. The data analysis reliability and optimization decision accuracy of the complex energy system are remarkably improved, and support is provided for construction of a novel electric power system.

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 relates to an integrated energy system scheduling method considering dynamic characteristics of a heat supply network under a green certificate-carbon transaction interaction mechanism. The method comprises the following steps: constructing an integrated energy system framework; constructing a green certificate transaction model and a stepped carbon transaction model based on the integrated energy system framework, further constructing a green certificate-carbon transaction interaction model by mining carbon emission reduction attributes contained in green certificates, and linking a green certificate market and a carbon market by taking a green certificate transaction volume and a carbon emission right transaction volume as interaction media; according to the heat delay and heat loss characteristics of the heat supply network in the integrated energy system framework, a heat supply network dynamic model is constructed; and on the basis of the dynamic models of the green evidence market, the carbon market and the heat supply network after interaction, constructing an optimal scheduling model by taking the minimum cost of the integrated energy system as a target, and solving and outputting a scheduling result to complete a scheduling process. Compared with the prior art, the method has the advantages of low carbon, economical operation and the like.

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 an electricity selling operation method and system based on dynamic game and multi-time scale rolling optimization. The method comprises the following steps: firstly, acquiring historical data of a power market and users, and establishing a user package selection model based on an evolutionary game theory so as to simulate user selection proportions and aggregation load curves under different pricing strategies; and then, establishing a multi-market combined transaction optimization model which takes benefit maximization after risk adjustment as a target, and taking a user selection result as a core constraint. And by solving the optimization model, an optimal electric power package pricing strategy and a combined purchasing strategy in multiple markets such as electric power, carbon and green certificates are cooperatively generated. According to the method, the technical problems of decision splitting, inaccurate user behavior prediction, rigid risk management and the like in traditional electricity selling operation are effectively solved, closed-loop collaborative optimization of package pricing and multi-market transaction is realized, and decision scientificity, risk resisting capability and market adaptive capability are remarkably improved.

The invention relates to the technical field of power system optimization scheduling, in particular to a virtual power plant alliance optimization scheduling method and system based on electricity-carbon certificate transaction, and the method comprises the steps: constructing a virtual power plant alliance cooperation cost minimization model considering the multi-dimensional value flow of electric energy, carbon right and green certificate; a second-class special ordered set is adopted to accurately linearize the stepped carbon price; constructing a dynamic internal collaborative green certificate conversion mechanism, defining an electric energy transaction volume, a carbon transaction volume and a green certificate transaction volume for each virtual power plant, and forming a multi-commodity internal market in which electricity, carbon and green certificates are coupled; carrying out distributed solution on the interior of the alliance by adopting an asynchronous self-adaptive alternating direction multiplier method; and fairly distributing cooperation surplus according to the contribution degree index of each alliance member based on a cooperative game theory. By constructing the multi-dimensional value flow collaborative model and the fair cost allocation mechanism, the total operation cost and carbon emission of the virtual power plant alliance can be remarkably reduced, and meanwhile, the cost allocation fairness is guaranteed to maintain the alliance stability.

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 present invention discloses a low-carbon scheduling method for a multi-agent integrated energy system that considers the correlation between wind and solar power. The method comprises the following steps: S1: establishing an integrated energy system structure and constructing an integrated energy system energy trading process that includes a green certificate-tiered carbon trading joint trading market mechanism; S2: within the integrated energy system structure, energy trading service providers are set as upper-level leaders, and energy suppliers and users are set as lower-level followers, establishing a multi-agent master-slave game scheduling mechanism; S3: generating wind-solar combined output scenarios based on historical distributed energy data, and introducing wind-solar correlation into the integrated energy system structure; S4: constructing a decision-making model for each stakeholder in the integrated energy system, including energy trading service providers, energy suppliers, and users; and S5: introducing a hierarchical differential evolution algorithm as a solution method and performing game-based solutions on the decision-making models of each subject in different scenarios to generate optimized scheduling results.

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.