15 results about "Market model" patented technology

The invention discloses an optical storage direct-flexible system power scheduling method based on market model prediction response, which comprises the following steps: determining the composition of an optical storage direct-flexible system, and collecting operation state data and external environment data; constructing a hybrid prediction model, and predicting the market price and the uncertainty interval of the market price in the scheduling period; establishing a power scheduling optimization model, and solving to obtain an optimal power scheduling strategy; according to the optimal power scheduling strategy, a control instruction is issued to each control unit of the optical storage direct flexible system, and cooperative adjustment is carried out through a bidirectional coupling feedback mechanism of voltage and power; the market price and the system operation state are monitored in real time, and when the market price deviation exceeds a price deviation threshold value, scheduling strategy online correction is triggered. According to the robust optimization architecture, traditional power scheduling is converted into a confrontation game structure between the system and the market, and the resistance of the system to extreme price situations is improved while economic benefits are guaranteed.

The present invention discloses a power dispatching method for a photovoltaic, storage, direct-to-flexible system based on a market model prediction response, including determining the composition of the photovoltaic, storage, direct-to-flexible system and collecting operating status data and external environment data; constructing a hybrid prediction model to predict the market price and the uncertainty interval of the market price within the dispatching period; establishing a power dispatching optimization model to solve and obtain the optimal power dispatching strategy; according to the optimal power dispatching strategy, issuing control instructions to each control unit of the photovoltaic, storage, direct-to-flexible system, and performing coordinated regulation through a bidirectional coupling feedback mechanism of voltage and power; real-time monitoring of market prices and system operating status, and triggering online correction of the dispatching strategy when the market price deviation exceeds the price deviation threshold. The robust optimization architecture in the present invention transforms traditional power dispatching into an adversarial game structure between the system and the market, which improves the system's ability to resist extreme price scenarios while ensuring economic benefits.

The invention belongs to the field of electric power markets, and discloses a day-ahead electric energy-inertia combined market transaction method considering inertia safety, and the method comprises the steps: predicting the next-day load of a power grid through employing an improved random forest method, constructing a power balance constraint, carrying out the next-day wind and light output prediction through employing an ARIMA-LSTM method, and constructing a new energy unit output constraint; evaluating a minimum inertia demand based on a system frequency response model and establishing an inertia demand constraint; based on an Aumann-Shapley method, performing inertia support responsibility allocation according to marginal contribution inertia suppliers of various types of resources; and in combination with the above conditions, minimizing the total cost of the power generation side considering the electric energy transaction and the inertia service transaction is taken as a target function, the market model is solved, and a clearing result is determined. A power generation side unit is guided to reasonably make a next-day power generation plan through a marketization mechanism, electric energy supply is guaranteed, and related subjects are stimulated to provide inertia services.

The invention discloses a virtual power plant coupling multi-market operation optimization and risk evaluation method, and relates to the technical field of virtual power plants. Comprising the steps of 1, establishing a resource model in a virtual power plant; 2, establishing corresponding market models for different participated markets, and establishing an interface model of the virtual power plant and the markets; 3, designing a virtual power plant overall operation optimization model; 4, establishing a risk evaluation model, and considering various risks possibly faced by the virtual power plant participating in the market; 5, coupling the overall operation optimization model and the risk evaluation model to form a comprehensive model; 6, a real-time scheduling system is established, and market changes and resource states are monitored; and 7, performing system simulation verification by using actual data, adjusting model parameters, and optimizing an algorithm. According to the invention, the overall operation problem of the virtual power plant in a complex market environment is solved, including the technical problems in the aspects of resource scheduling, market transaction and risk management.

The invention discloses a data warehouse model design method, and belongs to the technical field of data warehouse modeling. According to the method, a dimension modeling method is adopted to construct and analyze a mart model, data is organized into a non-standardized relation model, and the relation between tables is defined through keywords and foreign keys. And designing a dimension table system comprising a product dimension, a calendar day dimension, an institution dimension, an insurance policy attribute dimension and a customer dimension, and a fact table system comprising an insurance claim settlement analysis fact table, a payment analysis fact table, a claim settlement efficiency analysis fact table and a corresponding intermediate fact table. The analysis subject domain data is formatted into a star model or snowflake model, where the analysis fact table is a lightly summarized transactional fact table, and the intermediate fact table is a versioned historical table. According to the method, repeated data construction is avoided through a unified modeling method, and the cost is reduced; an efficient query analysis function is provided by optimizing a model structure; and the data traceability is ensured through versioning management.

The present invention discloses a trading method for a two-tier market architecture for multi-subject end-to-end transactions on the distribution network side. The upper layer is a DLMP centralized pricing model trading layer, which calculates the marginal electricity price of different nodes in the distribution network based on the node load, providing a base price for the lower layer multi-subject distributed end-to-end trading market model; the lower layer multi-subject distributed end-to-end trading market model trading layer implements distributed transactions for new users within the node, determines the node load based on the transaction results, and returns them to the upper layer DLMP centralized pricing model for centralized clearing. The two-tier market architecture achieves the coupled coordination of centralized clearing and distributed end-to-end transactions; it provides a feasible market architecture for large-scale new users, and improves the economy and flexibility of distribution network operation and user-side resources.

The invention relates to the technical field of smart power grids and energy transaction, and discloses a micro-grid P2P electric energy transaction bidding and matching optimization method, which comprises the following steps of: constructing a micro-grid bilateral P2P electric energy transaction market model, defining a buyer, a consumer, as an energy-deficient micro-grid and a seller, as an energy-rich micro-grid, and establishing a micro-grid bilateral P2P electric energy transaction market model; designing a transaction matching and settlement mechanism based on the second price auction mechanism; modeling a transaction environment in the market model as a Markov decision process, introducing a multi-agent reinforcement learning algorithm under a Markov decision process framework, and learning and generating a dynamic bidding strategy oriented to multiple rounds of transactions; in the market matching stage, the dynamic bidding strategy of the producer and the consumer is input into the microgrid bilateral P2P electric energy trading market model, a settlement list is output, the problems that the bidding strategy is static and the market efficiency is low in a traditional trading method are solved, and the method has high adaptability and generalization ability and is suitable for scenes such as intelligent power grid demand side management and energy internet.

The invention discloses a multi-type energy storage day-ahead peak regulation plan compilation method and system, equipment and a medium. The method comprises the steps that equipment physical data and market-oriented unit declaration data are acquired; generating a system operation data set through cleaning, checking and packaging merging; a prospective pre-clearing scheduling model is constructed, and a marketization unit clearing result is obtained by solving output arrangement under thermal power unit start-stop and segmented quotation; constructing a multi-type energy storage day-ahead peak regulation optimization model, and obtaining a non-marketization energy storage peak regulation plan by optimizing non-marketization energy storage operation; and obtaining a peak regulation plan compilation system through integrated compilation and standardized output. According to the method, the whole-process connection of the market operation boundary and the non-marketization unit scheduling is realized, and the smooth transition of power production from a plan mode to a market mode and the efficient calling of energy storage resources are supported.

The application relates to the field of power market analysis, and discloses a power demand side management optimization method based on electricity-carbon coupling and dynamic carbon emission, which comprises the following steps: obtaining multiple demand response schemes and multiple energy generator unit data in a power market; constructing a multiple energy generator unit market model according to the multiple energy generator unit data in the power market; constructing a two-stage power market clearing model based on the multiple energy generator unit market model, wherein the two-stage power market clearing model comprises a first-stage model and a second-stage model, the first-stage model is a market planning and dispatching model, and the second-stage model is a demand response model; inputting each demand response scheme into the two-stage power market clearing model in sequence to obtain market operation parameter analysis results under each demand response scheme; and obtaining market performance analysis and demand response decision through comparison of all market operation parameter analysis results. The application can realize expansion of implementation comparison of different market-oriented demand response schemes.

The embodiment of the invention provides an edge-enabled adaptive resource transaction method and device. The method comprises the steps that a resource transaction system model and a reputation model based on the dynamic edge network are established, and the resource transaction system model comprises a buyer model, a seller model and a market model; establishing a transaction strategy optimization model according to the resource transaction system model and the reputation model; performing reputation evaluation on the buyer and the seller to obtain a reputation evaluation result; monitoring and analyzing the market to obtain a monitoring and analyzing result; generating a contract adjustment strategy according to a reputation evaluation result and a monitoring analysis result, and adjusting a contract according to the contract adjustment strategy; performing optimization solution on the transaction strategy optimization model in combination with the adjusted contract to obtain an optimal transaction strategy; and executing the transaction operation according to the optimal transaction strategy. In this way, efficient, flexible and safe resource scheduling can be achieved in the dynamic edge network environment, meanwhile, the transaction risk is reduced, and the resource utilization rate and the market stability are improved.

The invention discloses a method for generating a data transaction market model based on differential privacy, and the method comprises the steps: obtaining the quality, training cost and market demand of a machine learning model of each version through collecting market data, and deducing the optimal price of the machine learning model based on an income maximization principle; secondly, designing a cost minimization model based on privacy budget and privacy preference, preferentially selecting a data owner with the lowest cost in combination with a greedy selection algorithm, ensuring the balance between model quality and privacy cost through constraint conditions, and optimizing training cost at the same time; then, a reverse auction mechanism is introduced, a winner selection target function based on the expected selling price and the privacy budget is designed, and it is ensured that a data owner honest reports the privacy cost in combination with an incentive compatible payment rule; and finally, training a machine learning model by using the winner set, compensating a data owner according to a payment rule, and finally constructing an efficient and fair data transaction market model.

The invention relates to a quantity and price reporting method considering distributed fault risk and adjustable capability scarcity. The method comprises the following steps: calculating the fault probability of distributed resources at the current moment; calculating the clearing power of the distributed resource m in the day-ahead electric energy market; a scarcity factor and the upper adjustable capacity, the lower adjustable capacity and the scarcity price of the distributed resources m in the intra-day stage are calculated; and constructing an intra-day electric energy and auxiliary service market model, and dynamically clearing the power of the resources. According to the method, the operation state of the distributed resources and the action mechanism of the fault characteristics are analyzed, the potential fault risk of the distributed resources is evaluated, dependence on the high-fault-probability resources is reduced, the resource scheduling structure is optimized, and the power supply reliability is improved; through distributed resource scarcity pricing and adjustable capacity evaluation based on marginal cost characteristics, market pricing can reflect the adjustable capacity and the opportunity cost of the resources, and the resources are guided to reasonably participate in different markets.

This invention discloses a method and apparatus for joint optimization evaluation of green certificates and green electricity systems under a unified clearing market, relating to the fields of electricity market and energy economics. The method includes: collecting multi-source data from the electricity market and dispatch system; after preprocessing and verification, unifying the clearing results and unit markings of green certificates and the all-weather green electricity market to form shared standardized data; based on this, formulating collaborative rules, timing sequences, and shared interfaces, establishing an anti-duplication metering mechanism, and forming a standardized interaction system; building a system optimization evaluation model integrating multiple factors according to the interaction specifications, integrating the two market models and modeling them differently on a unified time axis; based on this model, implementing solutions for switching between three operating modes and comparing multiple scenarios, conducting multi-factor sensitivity analysis, and outputting results using large-scale power grid solution technology and connecting to existing systems to complete the dual-market collaborative optimization evaluation. This invention solves the problems of data conflict and duplication metering through unified data and collaborative constraints.

The invention provides a ship main size type selection design method, a medium and a terminal. The method comprises the steps of establishing a design variable based on a ship main size; establishing a ship type evaluation index and constraint function database; constructing an objective function of the evaluation indexes; introducing a genetic evolutionary algorithm to solve the objective function and obtain an optimal solution set database; and establishing a market model based on the optimal solution set, and calculating a maximum value of the market model to determine an optimal design variable. Through the method, the iterative calculation time of ship main scale type selection can be effectively shortened.