213 results about "Green certificate" patented technology

The invention discloses a carbon neutralization target-oriented electricity-carbon-green certificate multi-target scheduling optimization method and system, and relates to the technical field of carbon neutralization control, and the method comprises the following steps: obtaining first data of a target energy storage unit, constructing a constraint generation network, and dynamically updating an energy storage operation constraint domain based on a dynamic time warping algorithm; based on the updated operation constraint domain, establishing an electricity-carbon coupling model, extracting a nonlinear mapping relation between an electric energy output behavior and carbon emission intensity, and outputting a dynamic incidence matrix through a multi-dimensional time sequence predictor; constructing a carbon flow distribution topological graph according to the dynamic incidence matrix, and obtaining an optimal carbon flow path through a Dijkstra algorithm; based on the operation constraint domain and the optimal carbon flow path, establishing a multi-subject collaborative decision-making mechanism, solving a multi-target unit equilibrium solution by adopting a distributed alternating direction multiplier method, and generating a global scheduling instruction set; according to the method, a carbon flow topology and dynamic constraint domain cooperation mechanism is constructed, so that efficient solving of a multi-main-body carbon response optimization scheduling problem is realized.

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 invention discloses a large-scale public building demand response intelligent regulation and control method based on a multi-mode reinforcement learning agent system. According to the method, a multi-modal reinforcement learning agent system is constructed by introducing a multi-modal data processing and multi-agent cooperation mechanism; the multi-modal reinforcement learning agent system is deployed in the large-scale public building, and cooperative control of the multi-modal reinforcement learning agent system is realized through a distributed execution mechanism; and cooperatively solving the demand response double-layer regulation and control model of the large-scale public building in the electricity-carbon-green certificate market based on a multi-mode reinforcement learning agent system, thereby regulating and controlling key adjustable and controllable equipment, and realizing participation of the large-scale public building in demand response regulation and control of the electricity market, the carbon market and the green certificate market. The method has the advantages that through multi-modal data fusion, the operation and maintenance state sensing capability of the large-scale public building is improved, and the adaptability of the large-scale public building to a dynamic market and a complex environment is enhanced.

The invention discloses a virtual power plant optimal scheduling method based on carbon-green certificate transaction, and relates to the technical field of electric power, and the method comprises the steps: S1, building a carbon-green certificate joint transaction model according to a stepped carbon transaction mechanism and a green certificate transaction mechanism; s2, establishing a virtual power plant low-carbon model according to the P2G-CCS coupling model, the hydrogen fuel cell operation model and the hydrogen-doped gas unit model, and establishing constraint conditions in combination with system energy demand response; s3, determining an optimization target according to the carbon-green certificate combined transaction model and the virtual power plant low-carbon model, and constructing a virtual power plant optimization scheduling model; s4, a CPLEX solver is adopted to process the virtual power plant optimization scheduling model based on optimization constraints, and an optimization scheduling result is obtained; the energy utilization efficiency and the energy consumption efficiency in the operation process of the virtual power plant are improved, meanwhile, low-carbon operation of the virtual power plant is considered, and the problem that in conventional P2G-CCS coupling operation, the virtual power plant cannot give consideration to the energy utilization rate, the energy consumption efficiency and the low-carbon operation at the same time is solved.

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 power generation alliance electricity-carbon-green certificate market bidding decision-making method based on an MADDPG algorithm. The power generation alliance comprises a renewable energy unit and a conventional thermal power unit, and the market further comprises a traditional thermal power generation body and a wind and light new energy power generation body. The method comprises the following steps: constructing a quotation decision-making model of each market subject participating in the electricity-carbon-green certificate market based on the selling income of each market subject in the electricity-carbon-green certificate market, and taking the quotation decision-making model as a decision-making model; constructing an electricity market day-ahead clearing model, a carbon market clearing model and a green certificate market clearing model as coupling clearing models by taking minimum electricity purchase cost, carbon market welfare maximization and green certificate market welfare maximization of the electricity market as targets; constructing a double-layer coupling transaction model by taking the decision model as an upper-layer model and the coupling clearing model as a lower-layer model; and adopting an MADDPG algorithm to solve the double-layer coupling transaction model, and determining the middle bid price, the middle bid amount and the total income of each market subject in the electricity market, the carbon market and the green certificate market.

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 relates to a CMIES multi-time scale optimization scheduling method considering carbon-green certificate transaction and CCS-P2G joint operation, and belongs to the technical field of mining area energy comprehensive utilization. According to the CMIES low-carbon economic dispatching method, the energy characteristics of the CMIES, the market characteristics of a carbon-green certificate transaction mechanism and the low-carbon characteristics of the CCS and the two-stage P2G are comprehensively considered, and the CMIES low-carbon economic dispatching method considering carbon-green certificate transaction and CCS-P2G combined operation under the multi-time scale is provided. And establishing a CMIES day-ahead and intra-day rolling optimization scheduling model based on MPC by taking minimization of energy purchasing cost, energy abandoning punishment cost, carbon-green certificate transaction cost, equipment operation and maintenance cost, carbon sequestration cost and load calling cost as economic targets. According to the method, loads under different time dimensions and mining area multi-energy output fluctuation can be well coped with, graded adjustment is carried out according to the flexibility of CMIES internal equipment and the multi-time scale characteristic of demand response resources, and the wind, light and associated energy consumption capacity, the CMIES low-carbon property and the CMIES economical efficiency can be effectively improved.

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

The invention 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 internal and external collaborative low-carbon economic optimization scheduling method for a port integrated energy system. The method comprises the following steps: S1, obtaining output prediction data, time-of-use electricity prices, capacities of various devices and output constraints of photovoltaic, wind power and cold and heat power loads; s2, building a green certificate-carbon transaction mechanism model and a comprehensive demand response model based on carbon flow characteristics; s3, constructing a port objective function and a port area objective function by taking the minimum operation cost after internal and external cooperation as an objective function; and S4, the port objective function solves a port external coordination optimization problem, the solved interaction power is transmitted to the basic energy supply unit, and the port area objective function solves a port area internal optimization problem. The method fully considers the carbon transaction mechanism of the harbor districts and the energy interaction among the multiple harbor districts, and can effectively improve the economic benefit and low-carbon characteristic of the comprehensive energy system of the harbor.

The invention discloses a new energy supply-based integrated energy system optimization scheduling method, and relates to the technical field of integrated energy system optimization scheduling, and the method comprises the following steps: constructing a supply side new energy model and a demand side load classification regulation and control model according to the integrated energy system optimization scheduling demand; establishing a price regulation and control model according to the uncertainty of the new energy output and the randomness of the energy consumption load; with an economical operation strategy as a scheduling target, a price regulation and control model is established by using a supply side new energy model, a demand side load classification regulation and control model, uncertainty of new energy output and randomness of an energy consumption load, and a comprehensive energy system optimization scheduling model with new energy supply as a main part is constructed. Related constraint conditions are constructed based on system model parameters; establishing a carbon quota transaction and green certificate transaction optimization scheduling model under a carbon emission accounting mechanism based on an economical operation strategy by taking an environment-friendly operation strategy as a scheduling target; and establishing a model optimization scheduling system optimization strategy according to the system model parameters and the new energy output condition. According to the method, optimal scheduling of the comprehensive energy system based on new energy is established, particularly hydroelectric generation is used in the optimal scheduling of the system, uncertainty of energy output and energy consumption load is considered, analog simulation of data of a certain region is realized by utilizing Matlab, and the optimal scheduling of the comprehensive energy system is realized. The optimized scheduling of two energy market strategies of carbon quota transaction and green certificate quota transaction under the conditions of economical and low-cost operation and environmental protection is realized.

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 provides a load side green evidence income-based wind and light consumption low-carbon scheduling method and system, and the method comprises the steps: determining the wind and light renewable energy consumption of a load side according to a power generation side system scheduling cost model; determining a load curve after the power user participates in the load source cooperation based on the load side wind and light renewable energy consumption; according to the load curve and the lowest cost of the system, determining the green proof total income of the wind-light renewable energy power generator and the power consumer participating in the source-load cooperation; based on a pre-constructed Shapley green certificate income distribution model, distributing the green certificate total income, and determining the green certificate income obtained by the power consumers participating in the source-load cooperation; establishing a load-side wind and light consumption low-carbon scheduling model by taking the minimum total cost of the transfer load of the power consumer as a target according to the green evidence income obtained by the power consumer and the electricity price cost of the transfer load; and through the load-side wind and light absorption low-carbon scheduling model, completing load-side wind and light absorption low-carbon scheduling. And wind and light abandoning power of the system is reduced.

The invention provides an electricity market equilibrium analysis method, device and equipment considering green electricity and green certificate transactions. The method comprises the following steps: constructing an independent system operator decision model by taking minimization of total cost as a first objective function and taking power for balancing electric power as a first constraint condition; constructing a power generation enterprise decision model by taking the maximum total income as a second objective function and the maximum power generation amount as a second constraint condition; taking the minimization of the total electricity purchase cost as a third objective function and taking the green electricity consumption responsibility weight as a third constraint condition to construct a consumer decision model; with supply and demand balance of conventional electric energy, green electricity and green certificate transaction as a constraint, a market balance condition is constructed; based on the independent system operator decision-making model, the power generation enterprise decision-making model, the consumer decision-making model and the market equilibrium condition, constructing a power market equilibrium model; and outputting the generating capacity of various types of electric power and the transmission electric quantity of each power transmission line by using the electric power market equalization model.