347 results about "Green power" patented technology

The invention discloses a green data center scheduling optimization method under computing power and electric power coupling, data load types of a data center comprise a transferable load, a reducible load and a rigid load, and the method comprises the following steps: constructing a double-target scheduling optimization model by taking the minimum power consumption cost of the data center and the maximum green power fitting degree as targets; the power consumption cost of the data center is used for representing the sum of expenses generated by the data center for purchasing power from a power grid in order to meet the power required for processing the data load in each time period, and the green power fitting degree is used for evaluating the matching degree between the power consumption demand of the data center and the renewable energy source supply; solving the dual-target scheduling optimization model by using a multi-target dogvessel swarm algorithm to obtain a Pareto frontier; and determining an optimal scheduling scheme based on the Pareto frontier, wherein the optimal scheduling scheme comprises a data center power consumption curve, an energy storage power station charging and discharging curve and a transferable load scheduling strategy. According to the invention, the power consumption cost of the data center can be reduced, and the renewable energy consumption capability can be improved.

The invention relates to the technical field of sewage plant-oriented carbon neutralization regulation and control scheme design, in particular to a sewage plant-oriented carbon neutralization regulation and control method and a sewage plant-oriented carbon neutralization regulation and control system. The method comprises the steps of collecting water quality, energy consumption and gas emission data in real time through a multi-source sensor, inputting the data into a space-time diagram convolutional network to predict a carbon emission trend after edge computing node cleaning, and dynamically optimizing an aeration rate and a sludge reflux ratio based on a fuzzy PID controller. A whole-process carbon footprint is tracked by adopting a life cycle evaluation method, a multi-target compensation strategy is generated in combination with an improved NSGA-III algorithm, and photovoltaic, biogas and green power resources are scheduled preferentially. A digital twin platform and a block chain evidence storage module are innovatively integrated, the former calibrates model parameters in real time, and the latter generates a non-tampering carbon neutralization voucher. According to the method, the problems of one-sided data, regulation and control lag and insufficient credibility of a traditional method are solved, and minute-level sensing, prediction and offset closed-loop control of carbon emission in the sewage treatment process is realized.

The invention relates to the technical field of power grids, and discloses a port green power virtual energy storage aggregation regulation and control method, which comprises the following steps: acquiring an aggregation scene and resource data; generating a power hard constraint mapping and pile division execution reference by calculating a multi-band energy index and identifying a system power transfer characteristic; a local rapid control configuration set is generated by solving a virtual impedance feasible region and combining power hard constraint allocation compensation budget; and fusing a sub-pile execution reference (slow channel) generated based on the power hard constraint with a fast channel execution track obtained after local online execution compensation, performing priority arbitration under the constraint of the power hard constraint, and outputting a final execution power track. According to the invention, a double-layer regulation and control framework of slow channel planning and fast channel compensation is constructed, and through a core link of power hard constraint mapping, coordinated operation of fast and slow channels and safety and stability of the whole system are ensured, and fast and reliable dynamic support capability can be provided for a power grid.

The invention relates to the field of electric power systems, and particularly discloses a combined dispatching method for charging and configuring a mobile robot, the mobile robot is suitable for charging electric vehicles in an expressway service area, and the method comprises the following steps: constructing a combined dispatching system for charging and configuring the mobile robot, the dispatching link of the combined dispatching system comprises a charging link and a distribution link; on the basis of a sequential relationship between a charging link and a distribution link, taking the optimal green power consumption capability as an upper-layer target and taking the lowest scheduling cost as a lower-layer target, constructing a combined scheduling double-layer model of charging and configuration of the mobile robot; and solving the joint scheduling double-layer model, and obtaining a scheduling scheme of the mobile robots, so that the distribution vehicle distributes the corresponding number of mobile robots to the service area with the energy supplement demand in advance according to the distribution path. The method not only can meet the urgent energy supplement demand of the vehicle owner in the peak period of the traffic flow, but also can assist the green power consumption and relieve the power grid pressure.

The invention belongs to the technical field of power systems, and particularly relates to a virtual power plant carbon-green transaction optimal scheduling method considering a green power and carbon emission coupling relationship, which comprises the following steps: S1, by taking the lowest total cost as an objective function, constructing an optimal scheduling model for a virtual power plant to participate in carbon transaction and green certificate transaction; the optimal scheduling model comprises a calculation model or a calculation formula of carbon transaction cost, green certificate transaction cost and operation cost of each device; s2, solving the optimal scheduling model according to actual parameters of a virtual power plant to be subjected to optimal scheduling to obtain an optimal scheduling scheme of the virtual power plant participating in carbon transaction and green certificate transaction; and S3, optimizing the operation scheduling of the virtual power plant by using the optimized scheduling scheme obtained in the S2. The method can ensure that the operation scheduling of the virtual power plant comprehensively complies with and optimizes the complex operation mechanism of the power market while considering the carbon transaction cost and the green certificate transaction cost, and realizes accurate regulation and control.

The invention discloses a collaborative scheduling method and system for a centralized energy storage power station to participate in a joint market, and the method comprises the steps: enabling an energy storage station and a new energy station to form a joint system, taking the maximization of the income of the joint system in a green power and spot market as an optimization target, and constructing a joint system optimization scheduling model considering a green power transaction electric quantity decomposition curve; carrying out optimization scheduling on the capacity of the shared part of the energy storage; independently participating in power market competition by using the residual capacity after energy storage sharing, constructing a double-layer optimization model of participating in spot goods-peak regulation-green power combined market by energy storage, and solving the double-layer optimization model to obtain an energy storage operation strategy; and calculating the contribution degree level of each subject in the joint system, calculating a profit distribution proportion according to the contribution degree level, and further performing profit distribution on each subject in the joint system. According to the invention, flexible diversity of participation of centralized energy storage in multiple types of markets and multiple operation modes can be brought into full play, so that the energy storage utilization rate and the operation income are improved.

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

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

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

The invention discloses an isolated network green power-green hydrogen-green ammonia three-flexible coupling integrated system and an operation method. The system comprises a wind-light storage flexible power generation system, a renewable energy flexible water electrolysis hydrogen production system and a flexible low-temperature low-pressure ammonia synthesis system. The wind and light storage flexible power generation system is used for carrying out green energy power generation through wind power generation equipment and photovoltaic power generation equipment, and carrying out flexible adjustment on the output power generation amount according to a wind power and photovoltaic output curve coupled by electric energy storage equipment; the renewable energy flexible water electrolysis hydrogen production system is used for flexibly adjusting the hydrogen output quantity by starting and stopping the number of hydrogen production electrolytic cells in the hydrogen electrolysis hydrogen production device and the hydrogen energy storage equipment; the flexible low-temperature and low-pressure ammonia synthesis system is used for automatically reducing or increasing the load of the ammonia reactor and generating green ammonia according to the hydrogen output quantity of the renewable energy flexible electrolytic water hydrogen production system and the nitrogen output quantity of the air separation equipment. The problems that a stable power supply is needed for traditional ammonia hydrogen production and flexible production cannot be achieved due to the fact that traditional ammonia synthesis is limited by the narrow load application range are solved.

The invention discloses a wind, light and green power coupled pumping unit well group operation collaborative optimization method. The method comprises the following steps: acquiring field data of a multi-energy micro-grid pumping unit well group; establishing a wind and light output uncertainty model, an energy storage battery model, a pumping unit power model and bidirectional AC / DC converter equipment; based on each model, establishing a multi-objective optimization scheduling model for the intermittent pumping operation of the multi-energy micro-grid pumping unit well group; an NSGA-II method is adopted to solve the established multi-objective optimization scheduling model, and a Pareto optimal scheduling scheme is obtained; and carrying out comprehensive evaluation and decision analysis based on an entropy weight TOPSIS method, and selecting an optimal scheme from a Pareto optimal scheduling scheme set obtained by NSGA-II. According to the multi-energy micro-grid rod-pumped well group off-peak interval pumping operation multi-objective optimization method based on NSGA-II and entropy weight TOPSIS, the power utilization requirement of the rod-pumped well group can be met, the working system of rod-pumped well group interval pumping operation is optimized, the economical efficiency and stability of the operation of a rod-pumped well interval pumping system under a wind-solar storage micro-grid are ensured, and the green power consumption capability of the system is enhanced.

The embodiment of the invention is suitable for the technical field of computing power, and provides a computing power and electric power cooperative scheduling method, computer equipment and a medium, and the method comprises the steps: determining the predicted green power generation amount within a preset time; current electricity consumption information, to-be-executed calculation task information and available calculation power information of the data center are obtained, the current electricity consumption information comprises the current electricity consumption demand, and the calculation task information comprises calculation time information and interaction relation information of a plurality of calculation tasks; on the basis of the calculation time information and the interaction relationship information, sorting the calculation tasks by using a queuing network model to obtain a calculation task sequence; and determining a plurality of calculation tasks from the calculation task sequence as target calculation tasks in the preset time based on the predicted green power generation amount, the current power consumption demand and the available calculation power information. Through the method, the operation cost can be reduced when the cooperative scheduling of the computing power and the electric power is realized.

The invention discloses a port equipment green power system risk early warning method and system, and belongs to the technical field of risk assessment. Comprising the steps of collecting operation data related to new energy in a port equipment green power system; the method comprises the following steps of: constructing a risk map by taking port equipment as nodes and energy transmission and operation coordination relationships among the port equipment as edges, and endowing each node and each edge with characteristics by utilizing acquired operation data; constructing a graph convolutional network model, processing the risk graph data, and marking potential risk nodes; and calculating a risk level for the potential risk node, and implementing a layered alarm system. According to the invention, the limitation that a traditional method is only used for monitoring single equipment or single energy is overcome. And the collaborative operation intensity coefficient and the energy transmission loss coefficient between equipment in the port scene are considered in learning and analyzing the risk map in the graph convolutional network, so that the potential risk nodes can be identified more accurately, and the accuracy and reliability of risk identification are improved.

The invention relates to the technical field of electricity markets, in particular to a green electricity transaction tracing method and system, and the method comprises the following steps: collecting original green electricity transaction information generated after the transaction of a green electricity producer is completed, and carrying out the preprocessing of the original green electricity transaction information, and obtaining the standardized green electricity transaction information; verifying the standardized green electricity transaction information by using an intelligent contract, and calculating a decision factor value of each node in the block chain network by using a node decision model after the verification is passed; based on the decision factor value, using a diffusion storage strategy to perform uplink storage on the verified standardized green electricity transaction information; and retrieving each block in the block chain according to the query information provided by the producer, thereby obtaining the corresponding traceability information and feeding back the traceability information to the producer. According to the method, the security of the consensus node is improved by using the node judgment model and the diffusion storage strategy, the transaction processing speed and throughput are improved, and the credibility and speed of transaction tracing are further improved.

The invention relates to the technical field of charging scheduling, in particular to an expressway unmanned heavy truck intelligent charging system which comprises a data acquisition and preprocessing system and a vehicle pile network cloud integrated cooperative operation and green electricity source tracing carbon emission reduction module. Driving and charging strategies are optimized in combination with algorithms such as reinforcement learning, the energy consumption of the unmanned heavy truck can be effectively reduced, the transportation resource utilization rate is improved, and it is guaranteed that transportation tasks are efficiently completed in a time window; green power full-link traceability is realized based on the block chain technology, and the charging time is dynamically adjusted in combination with peak and valley electricity prices, so that the authenticity of use of green power is ensured, low-cost green power can be preferentially selected, and the charging and overall operation cost is remarkably reduced; the carbon emission in the charging and operation process is accurately quantified, the emission reduction benefit of a traditional heavy truck is scientifically evaluated, meanwhile, the method is in butt joint with a green logistics authentication system, support is provided for obtaining authoritative green authentication for transportation services, and low-carbon transformation of the industry is assisted.

The invention is suitable for the technical field of green power consumption traceability, and provides a green power consumption traceability method and system based on a block chain technology, and the method comprises the steps: obtaining initial data of a power generation link, a power transmission link, a power distribution link and a user side; constructing a power generation model, a power transmission model, a power distribution model and a user side model based on the initial data; extracting historical data related to green power consumption from the historical database, constructing a statistical model, and calibrating and optimizing the power generation model, the power transmission model, the power distribution model and the user side model by using the statistical model; respectively performing uncertainty analysis on the models to obtain a comprehensive evaluation result; performing encryption processing on the comprehensive evaluation result, the initial data, the model parameters and the data processing timestamp information through a block chain encryption technology, and storing the data to a block chain; and according to the query request of the user, a corresponding green power consumption traceability visualization result is generated, so that the green power consumption traceability depth and precision are effectively improved.

The invention provides a green electricity consumption accounting optimization method and device based on a carbon emission factor and a medium, and belongs to the technical field of carbon emission optimization based on green electricity accounting. The method comprises the following steps: establishing a corresponding relation table between a power purchasing form and a tracing tool according to multi-source data to execute power-proof collaborative tracing; performing inter-region green attribute replacement through a calculation engine, constructing a region green power consumption accounting model, and calculating the total region green power consumption; and calculating a residual power carbon emission factor based on the accounting result, and generating a cross-regional green power consumption report so as to realize carbon emission optimization. According to the method, a green electricity consumption source is accurately positioned through an evidence-electricity collaborative traceability mechanism, the problem of cross-regional repeated calculation is reduced, the calculation reliability is remarkably improved based on a carbon emission factor generated by an accurate accounting result, and thus the path and the cost for achieving a carbon reduction target are optimized.

The invention provides a method, a device and equipment for determining a green power substitution scheme of a power grid. The method comprises the following steps: acquiring basic data of a green power substitution optimization object of a target power grid; generating a plurality of wind power and photovoltaic combination schemes with different wind-solar proportions according to the basic data; determining an off-grid power range according to the basic data; according to the off-grid power range, simulating to obtain power balance data of each wind power and photovoltaic combination scheme in a target time period; obtaining target index data of each wind power and photovoltaic combination scheme according to the power balance data; and determining a target wind power and photovoltaic combination scheme according to the target index data. According to the scheme, after green power replacement, the peak regulation pressure of the power grid can be reduced while the power supply and demand balance is met.

The invention discloses a charging and discharging cooperative control method for a green power direct connection energy storage system, and aims to solve the problems of low efficiency, short service life and weak power grid support caused by renewable energy source volatility and energy storage response lag. The method comprises the following steps: collecting green power output, energy storage state and load demand data in real time; based on a three-layer collaborative architecture, an upper-layer energy scheduling layer determines target power according to an operation mode (such as green power consumption, peak clipping and valley filling), a middle-layer power distribution layer dynamically distributes power to each sub-cluster according to a health state and temperature and voltage consistency, and a lower-layer equipment execution layer drives a converter to perform precise execution through double-closed-loop control; and a closed-loop feedback correction and hierarchical protection mechanism is introduced. The green power consumption rate is effectively improved, the energy storage life is prolonged, and the system safety and the power grid supporting capacity are enhanced.

The invention discloses a paper mill load green power consumption potential evaluation method fusing ProbSparse and FEDformer, and belongs to the technical field of power system regulation and control, and the method comprises the steps: constructing an up-regulation capability evaluation model and a down-regulation capability evaluation model, and obtaining a maximum up-regulation capability and a maximum down-regulation capability; based on time-frequency domain decoupling modeling, predicting a future green power factor sequence; and based on the maximum up-regulation capacity, the maximum down-regulation capacity and the future green power factor sequence, a load green power consumption potential evaluation model is constructed, and according to the ProbSparse and FEDformer fused paper mill load green power consumption potential evaluation method, a ProbSparse-based paper mill load operation feature extraction method, the maximum up-regulation capacity, the maximum down-regulation capacity and the future green power factor sequence are extracted, and the maximum up-regulation capacity, the maximum down-regulation capacity and the future green power factor sequence are calculated. Improving the global perception capability of long-sequence load data by using a sparse attention mechanism, and accurately extracting the running rhythm, state change and key load mutation characteristics of each device; and on the basis of a green power factor prediction model of FEDformer, time sequence decomposition and frequency domain modeling capabilities are fused, and high-precision prediction of a future green power ratio factor is realized.

The invention relates to the technical field of electricity market models, and provides a micro-grid energy storage cost income accounting method and system. The method comprises the following steps: acquiring historical daily operation data of a wind-solar storage power supply and a load in a micro-grid, and data of power purchase and power transmission from a main network by the micro-grid; selecting an adaptive first constraint model or second constraint model according to the self-supply degree of the micro-grid power supply to calculate a cost coefficient and an income coefficient of energy storage and green power allocation; and solving the first constraint model or the second constraint model to obtain a cost coefficient and an income coefficient in the current micro-grid, and optimizing daily charging cost and daily income of energy storage in the current micro-grid. According to the method, the adaptive constraint model is dynamically selected in combination with the self-sufficient degree of the micro-grid power supply, so that the cost coefficient and the income coefficient conforming to the energy storage condition of the current micro-grid are obtained, the daily charging cost and the daily income of the energy storage in the current micro-grid are further calculated, and a high-precision energy storage cost income accounting result is obtained.

The invention relates to a breakwater structure for wave power generation and a construction method of the breakwater structure. The breakwater structure comprises a lower barrel body, an upper caisson and a power generation device. A compartment is arranged in the upper caisson, and the power generation device is installed in the compartment. A wave inlet hole is formed in the wave facing side of the upper caisson, a cast-in-place adjusting node is arranged on the top of the upper caisson, and a wave wall, a cable pipe trench, a detachable road plate and an overhauling device are sequentially arranged above the node. The breakwater structure and the wave power generation system are integrated by adopting standard barrel type foundation factory prefabrication and floating transportation installation and combining cast-in-place joint leveling and the detachable road plates. The structure has the advantages of being convenient to construct, controllable in cost, stable in structure, convenient to maintain and the like, is suitable for wave power generation under medium and small wave conditions, and is particularly suitable for green power supply and coast protection in areas such as ports and islands.

The invention relates to a power grid hour-level green electricity source tracing method and system based on space-time matching. The method comprises the following steps: firstly, collecting power generation data of a power generation end containing a power generation equipment identifier, power generation quantity and a power generation timestamp and power utilization data of a power utilization end containing a user identifier, power utilization quantity and a power utilization timestamp, and preprocessing and integrating into a power generation record and a power utilization record; for each to-be-traced power utilization record, dynamically delimiting a time window according to the power utilization timestamp; all power generation records in the window are inquired and aggregated to calculate the total power generation amount; then, according to the proportion of the generating capacity of each power generation device in the total generating capacity, green electric quantity distributed to the electricity utilization record is calculated, and a distribution relation is recorded to generate a traceability result containing a user identifier, a power generation device identifier, the distributed electric quantity, a time window and matching confidence; and finally, generating an ESG report and an electronic certificate based on the traceability result. Compared with the prior art, the method has the advantages of high traceability precision, high automation degree, high reliability and the like.

The invention discloses a balance unit quotation decision-making method considering uncertainty, and relates to the technical field of power systems, and the method comprises the steps: describing the output of renewable energy sources based on a scene method, carrying out the new energy modeling of the uncertainty of the output of the renewable energy sources, outputting a green power distribution proportion, and collecting market data and the data of a balance unit; building a balance unit quotation decision model based on new energy modeling and input balance unit data; a combined clearing model of the spot market and the green electricity market is constructed through new energy modeling and input market data and balance unit data; and optimizing the balance unit quotation decision model and the joint clearing model, and outputting an optimal quotation strategy of the balance unit. The method has the beneficial effects that the uncertainty of renewable energy sources can be effectively dealt with, the operation risk of the balance unit is reduced, and the operation stability of the system is improved.

The invention discloses an electric power and computing power coordinated regulation and control method and system, and relates to the field of load regulation and control, and the method comprises the steps: obtaining the electric power data of a power generation side and the electric power data of a computing power center, inputting the electric power data into a preset multi-target coordinated optimization algorithm, and obtaining the power generation and consumption data of a target time period meeting the requirements of the minimum power consumption cost and the maximum green power consumption, load distribution parameters are generated in combination with load demand data of the computing power center, and power generation and utilization loads of a computing task, computing power equipment, refrigeration equipment, a power generation side and the like of the computing power center are accurately controlled in a target time period. Through collaborative optimization of the power generation side and the computing power center, the green power intermittency and the computing power load fluctuation are effectively balanced, the green power consumption rate is improved, the power consumption cost of the computing power center is reduced, and the power supply and computing power operation stability is guaranteed.

The present application relates to photovoltaic lithium electricity energy storage and air conditioning system intelligent control technical field, specifically, the present application relates to photovoltaic lithium electricity air conditioner terminal machine room AI optimization method based on digital twinning, the present application is through the deployment of distributed optical fiber temperature sensor array, combined with k-epsilon turbulence model generates three-dimensional temperature field positioning hotspot area and calculates the maximum refrigerating capacity increment of air conditioner, fusion this increment, photovoltaic forecast power and lithium charge state, superimposed inverter efficiency compensation factor gets air conditioner callable green electricity quota, bind hot spot and quota generates thermal-electric coupling factor, combined with photovoltaic fluctuation intensity activates linkage mode, triggers deep deterministic policy gradient model to execute air valve opening, water temperature setting, lithium charge and discharge collaborative decision, through joint reward function binding evaluation three control quantity, output joint control vector, the method improves green power consumption rate and temperature control precision, guarantees equipment safety, applicable to machine room efficient operation.

The invention provides an electricity utilization carbon emission metering method and system based on carbon emission trend and green electricity transaction. A regional power grid is used as a calculation object, according to the levels of power generation, power transmission and power distribution, conduction of carbon emission factors is refined, comprehensive metering of a carbon emission source in a power system is achieved, a carbon emission calculation result can be updated in real time in the process that power is transmitted to a user side from a power generation side, and metering accuracy is ensured; in addition, the method particularly pays attention to the influence of green power transaction on user side carbon emission, and counteracts the power utilization carbon emission by distinguishing whether the user purchases green power or owns a renewable energy power generation facility or not. Furthermore, for users who have self-provided power generation facilities and have electric quantity on-line access, the influence of green power on-line access on regional carbon emission factors is further considered, and the total carbon emission amount of the users is accurately calculated, so that accurate accounting of the carbon emission factors and accurate metering of the total carbon emission amount of the users are realized.

The invention relates to the technical field of electricity market transaction and new energy scheduling, and discloses a high altitude area green electricity transaction volume decomposition method, system, device and medium, and the method comprises the steps: constructing a probability distribution model of historical electricity prices, generating an initial electricity price path reflecting spot electricity price fluctuation characteristics through a stratified sampling method, k representative scenes and corresponding probabilities are screened through a scene similarity calculation method to form a representative scene set; based on a multi-dimensional power transmission constraint condition, constructing a dynamic constraint system for sensing the power transmission capability in real time; the multi-dimensional power transmission constraint conditions comprise wind and light output prediction, power transmission line icing risk, spot electricity price fluctuation, green power total amount and time period performance constraint; and based on the representative scene set and the dynamic constraint system, a green power distribution scheme per hour is solved through a random optimization method, and green power transaction volume decomposition is realized. According to the invention, safe performance and economic benefit maximization of the green electricity contract can be realized.

The invention relates to a user distribution and storage and contract electric quantity collaborative optimization method oriented to green power performance, belongs to the technical field of power system optimization configuration, and solves the problems of low long-term contract performance rate, insufficient time sequence matching degree and unreasonable contract electric quantity configuration in the existing green power. Comprising the steps of predicting a new energy output curve and a user load curve in a planning period; constructing a first objective function and a first constraint condition for minimizing the power utilization cost of the user as an upper layer model; constructing a second objective function and a second constraint condition for minimizing the operating cost of the power system as a lower-layer model; and performing iterative solution on the upper layer model and the lower layer model based on the predicted new energy output curve and the user load curve in the planning period, and finally obtaining the optimal energy storage configuration capacity and the green electricity contract signing electric quantity of each user in the planning period. The green power performance capability and the resource configuration efficiency are improved.

The invention discloses a park-level energy and carbon accounting collaborative scheduling method and system, and the method and system achieve the efficient integration and collaborative utilization of data through breaking the barrier between energy data and IT data, improve the green power consumption rate, effectively reduce the carbon emission, and remarkably improve the overall operation efficiency and economical efficiency of a park energy system. According to the method, energy and IT data are collected and processed in real time, a basis is provided for accurate prediction and optimal scheduling, an LSTM model and an XGBoost model are adopted for prediction, an NSGA-II multi-target optimization algorithm is combined, and two-channel optimal control over green power consumption and carbon emission is achieved under the condition that energy storage and server operation constraints are met; meanwhile, scheduling instructions are continuously optimized through a feedback mechanism, and continuous stability and high efficiency of operation of the whole system are ensured.