20 results about "Electricity retailing" patented technology

The invention relates to the technical field of power retail, in particular to a power retail package recommendation method and system, and the method comprises the steps: obtaining user historical power consumption data through an intelligent electric meter or a power data collection terminal, and constructing user power consumption sample data after denoising and abnormal value processing; and in combination with the user attribute data and the power retail package attribute data, adding a user power consumption feature tag for the sample data. And training a package recommendation model by using the power consumption sample data and the feature tags. And acquiring real-time power consumption data and user attribute data of the current user as model input, calculating a recommendation score of each power retail package through a model, and pushing the package with the highest score to a user terminal as a recommendation result. According to the method, personalized recommendation is realized through data driving, the power retail service precision is improved, and the user experience is optimized.

The application discloses a kind of based on customer portrait's electric power retail package push method and system, it is related to electric power market technical field.The method includes: constructing the customer peak clipping and valley filling portrait model based on DDPM, the historical load of customer is mined, the peak clipping and valley filling characteristics of customer are extracted, and peak clipping and valley filling time difference model and peak clipping and valley filling electric quantity difference model are constructed in combination with grid peak value characteristics, valley value characteristics, according to the height of peak clipping and valley filling time difference and the height of peak clipping and valley filling electric quantity difference, four kinds of electric power retail package are formulated respectively;Construct the electric power retail package judgment model based on GPT, judge the peak clipping and valley filling time difference and peak clipping and valley filling electric quantity difference of customer, according to the judgment result of GPT selects to push one of package one to package four to customer.The application can realize according to the peak clipping and valley filling characteristics of customer, and the appropriate electric power retail package is customized and pushed to user, improves the accuracy of push, improves the enthusiasm of user participation electric power package activity.

A power management apparatus includes: a manager configured to manage one or more facilities connected to a power system; a controller configured to perform specific control to control a distributed power supply installed at each of the one or more facilities; and a receiving unit configured to receive first rate-related information regarding a first electricity rate determined between an electricity market and an electricity retailer that sells power to each of the one or more facilities. The controller performs the specific control based on the first rate-related information.

A power retail market price risk monitoring method and system. The method comprises the following steps: acquiring provincial power retail market monthly operation data; constructing a retail market overall price monitoring index based on the power retail market monthly operation data; establishing a retail market price risk early warning model based on threshold dynamic correction to generate a list of retail electricity companies that need to be warned; and directing the disclosure of retail market overall price monitoring information to corresponding retail users. The present application realizes accurate quantitative evaluation of the overall price risk of the power retail market.

The application relates to the field of power systems, and particularly discloses a method for determining the power market behavior strategy of multiple users in a new power system, wherein the power market comprises a power wholesale market and a power retail market, the main bodies of the retail market include retail users on the demand side and aggregated users on the power supply side, the main bodies of the wholesale market include wholesale users on the demand side and power suppliers on the power supply side, and the wholesale users include the aggregated users on the power supply side of the retail market. The method comprises the following steps: constructing a double-layer decision optimization model of the power suppliers and the wholesale users in the power wholesale market and a double-layer decision optimization model of the aggregated users in the power retail market, with the maximum social welfare as a lower target and the maximum income as an upper target; then, a corresponding Markov decision process is established, and each model is solved based on the DQN algorithm to obtain the behavior decisions of each main body. The application fully considers the multiple participating main bodies and multiple market levels of the power market, and can promote the construction of the new power system.

The application discloses a power carbon emission right joint transaction method based on a block chain technology, and is suitable for joint transaction of power transaction and carbon emission right generated due to the power transaction under a power distribution network. The method comprises the following steps: inputting data such as carbon emission curve parameters of different types of units, carbon emission limits and power retailer prices; establishing a regional user carbon emission constraint and a carbon tax penalty function; establishing a power and carbon emission joint transaction market optimization model under the power distribution network; solving market decisions of each participant in the market under an alternating direction multiplier method framework; and uploading the decision results of the user to a block chain node in an encrypted manner. The method can realize power transaction in the power distribution network, calculate carbon emission of an energy system in a park, manage joint transaction of power and carbon emission through an intelligent contract, realize privacy protection of transaction information, and ensure the executable of transaction results under a power grid voltage safety constraint.

To provide an electronic money system that serves as a common currency for overseas remittance and overseas travel.SOLUTION: A hardware constituting an electronic money system according to the present invention comprises a computer maintained by a power supply provider, a computer maintained by a financial institution, a card issued by a financial institution to an electricity retailer, and a card issued by a financial institution to their overseas and domestic users. The computer maintained by the electricity supplier incorporates software that converts electricity transmitted from the electricity retailer into a corresponding value of the common currency, and the converted value (numerical value) calculated by the electricity supplier's computer is transmitted to the financial institution as the value of the common currency.SELECTED DRAWING: Figure 1

The invention discloses a power retail market risk assessment method and electronic equipment. According to the power retail market risk assessment method provided by the invention, the analytic hierarchy process weight dynamically generated based on historical objective data is introduced, so that the defect that a fixed weight is set depending on subjective experience in a traditional method is effectively overcome, and the risk assessment result is more objective and accurate. Meanwhile, risk probability prediction is carried out in combination with a time sequence deep learning model, market dynamic changes can be caught sensitively, and the timeliness of risk early warning is remarkably improved. And finally, the objective weight, the prediction probability and the current market state information are deeply fused by using a fuzzy comprehensive evaluation method, and the generated comprehensive risk evaluation result not only has high reliability, but also has adaptive ability to market change, and provides powerful decision support for accurate supervision and risk prevention and control of the power retail market.

This invention relates to the field of electricity retail trading technology, and more particularly to a work order service recommendation system and method for electricity retail platforms and reputation perception. Based on blockchain technology, this invention utilizes the immutability and full lifecycle auditing capabilities of distributed ledgers to ensure the authenticity and integrity of user data and key event data of work orders, avoiding security risks such as score fraud and work order record tampering. It employs a fusion model of local and global reputation values, combining prediction accuracy and historical behavior quality for comprehensive scoring. K-Means clustering and Euclidean distance calculation are used to dynamically evaluate the contribution of data providers, effectively improving the accuracy and fairness of recommendation results. The introduction of the Gompertz function enables nonlinear reputation updates, making the reputation system more discriminative and convergent. This invention solves the technical problems of existing electricity retail trading service recommendation systems, such as lack of trust mechanisms, insufficient privacy protection, lack of incentive mechanisms, and low efficiency of consensus mechanisms.

This invention provides a model-free reinforcement learning method for energy demand response management, comprising: constructing a residential appliance model; determining social welfare by combining the comprehensive cost of residential electricity consumption and the profit of electricity retailers; balancing the comprehensive cost of residential electricity consumption and the profit of retailers based on the social welfare, wherein the social welfare is represented as a price-based non-convex optimization problem for residential demand response management; constructing reinforcement learning solutions for the price-based non-convex optimization problem for residential demand response management using Q-learning algorithms based on Q-tables, Q-network algorithms combining deep learning and Q-learning, and Actor-Critic algorithms, respectively, based on the transmission data of the power grid; and determining the optimal solution and the optimal retail price sequence based on the three reinforcement learning solutions for the price-based non-convex optimization problem for residential demand response management. This invention can use three algorithms to perform modeling respectively, achieving optimal retail price planning under unknown electricity market conditions.

The application discloses a power sale market transaction information management system and relates to the technical field of power retail information management.The system comprises a data gathering and storage module, a user portrait construction module, a dynamic settlement engine, a rule base and configuration center and a bill generation and traceability module.The data gathering and storage module is used for acquiring and storing actual power consumption data of users in a preset time granularity from an external power grid metering system.The user portrait construction module is connected with the data gathering and storage module.The dynamic settlement engine is connected with the data gathering and storage module and the user portrait construction module.The rule base and configuration center are used in a parameterized and formulated form.The settlement accounting core is configured to be triggered at a settlement period.The bill generation and traceability module is connected with the dynamic settlement engine.The system collects and analyzes user power consumption and transaction behavior data, generates a quantitative portrait and maps the portrait to an N-dimensional settlement judgment space as a structural factor, realizes adaptive division and differentiated settlement strategy matching, supports flexible pricing and personalized services.

To suppress an economic loss of a power consumer who performs a demand response.SOLUTION: In the control unit 11 of the aggregator server 10 constituting the information processing system, the acquisition unit 101 acquires retail-side information including at least a procurement cost of electric power in a retail electric utility, consumer information including at least information regarding a demand amount of electric power and an electricity rate in a consumer, and DR request information regarding a request for demand response, the calculation unit 103 calculates a profit of the retail electric utility and a loss of the consumer from the retail-side information, the consumer information, and the DR request information, and the generation unit 104 outputs information for determining whether or not to implement demand response on the basis of a calculation result.SELECTED DRAWING: Figure 4

The invention discloses a power retail market target risk information generation method and electronic equipment. According to the method, the risk factor extraction algorithm for the unstructured text is introduced, and dynamic weighted fusion is carried out on the risk factor extraction algorithm and the monitoring indexes based on the structured data, so that blind areas of traditional risk monitoring on soft risk factors such as policies and public opinions are effectively filled up, and the limitation of a single data source and a static analysis model is overcome; therefore, comprehensive risk information which is more complete in coverage dimension, higher in timeliness and higher in precision is generated, and more reliable data support is provided for risk identification and early warning of the power retail market.

The application discloses a kind of power retail package formulation methods and systems considering user adjustment capacity, it is related to electric power market technical field.The method includes: constructing the power retail package score model considering user adjustment capacity, for giving the corresponding power retail package score of user according to the actual adjustment situation of user;According to the number of times of participating in adjustment, sustainable adjustment time and cumulative power of adjustable user in power retail package, construct the adjustable user power retail package economic model based on LSTM, give user economic reward;And construct the power retail package power model of adjustable user based on LSTM, give user power reward;Construct the power retail package model considering user adjustment capacity, according to economic reward and power reward, adjust original power retail package.The application improves the participation and satisfaction of user by formulating intelligent and personalized power retail package, improves the flexibility of power system.

The invention discloses an optimized bidding method for a hybrid power supply chain, and relates to the technical field of electric power market bidding. According to the method, a mixed competitive power supply chain including renewable energy power generation enterprises, fossil fuel power generation enterprises and power retailers is constructed, and four operation modes of centralized decision making, simultaneous bidding, first bidding of the renewable energy power generation enterprises and first bidding of the fossil fuel power generation enterprises are considered. By establishing a demand function and a profit function of each participant, an equilibrium solution in different modes is solved by applying a reverse induction method, and the optimal wholesale electricity price and the optimal electricity purchase quantity are determined. According to the method, internal independent resource autonomous bidding right and aggregator overall collaborative scheduling are deeply combined for the first time, a distributed robust optimization model is fused to process renewable energy uncertainty, unified decision of risk control, market game and internal collaboration is realized, and economic robustness and strategy competitiveness of a hybrid power supply chain are improved.

The invention discloses an electric power retail market dynamic pricing and user management system, which relates to the technical field of intelligent electric power systems and comprises a data acquisition module for acquiring multivariate state data including power grid line load, node voltage and frequency deviation in real time and converging the multivariate state data into a power grid state vector; the instruction generation module is used for automatically triggering and generating an original electricity price regulation and control instruction containing a regulation and control target, effective time and a price floating coefficient if at least one index in the state vector is judged to exceed a preset safety threshold value; the power retail market dynamic pricing and user management system realizes power grid state real-time monitoring, instruction standardized transmission and transparent settlement, and improves power grid operation efficiency and user trust.

The application discloses a kind of electric power retail market dynamic pricing and user management system, it is related to intelligent electric power system technical field, including: data acquisition module, real-time acquisition includes grid line load, node voltage, frequency deviation multivariate state data, and multivariate state data is gathered into grid state vector;Instruction generation module, if at least one index in state vector is judged to exceed preset safety threshold, automatically trigger to generate original electricity price control instruction containing control target, effective time, price floating coefficient;The electric power retail market dynamic pricing and user management system, realize grid state real-time monitoring, instruction standardization transmission and transparent settlement, improve grid operation efficiency and user trust.

To calculate a consideration to be paid to an interested person according to the execution content of a demand response.SOLUTION: In the control unit 11 of the retail electricity provider server 10 constituting the information processing system, the effect calculation unit 103 calculates an effect of implementation of demand response on a demand response request from the retail electricity provider based on the power usage amount of the consumer, and the consideration calculation unit 104 calculates a consideration to be paid to a stakeholder other than the consumer who has contributed to implementation of demand response separately from a consideration to be paid to the consumer based on the effect of implementation of demand response and a profit of the retail electricity provider associated with implementation of demand response.SELECTED DRAWING: Figure 4

Systems and methods for advanced energy settlements in electric power grid are proposed. At least one energy customer, at least one retail electric provider and at least one distributed generator connect to an advanced energy settlement platform communicatively. The advanced energy settlement platform is operable to summate a customer balance from all the settlement blocks during a billing period and collect payments from the at least one energy customer automatically; aggregate and settle distributed energy charges with distributed generators and fixed energy charges with the energy retailer or retail energy provider for the at least one energy customer during the billing period. The advanced energy settlement platform also provides interactive graphical user interface for different participants in the advanced energy settlement and for advanced energy settlements application development kit (ADK) for access to functionality within the advanced energy settlement platform.

The invention discloses an electric power retail package recommendation method, system and device and a storage medium, and belongs to the technical field of electric power information processing. The method comprises the following steps: acquiring electricity consumption information of a user, acquiring a to-be-measured package specified by the user, and acquiring a current real-time electricity price; according to the electricity consumption information and the current real-time electricity price, the to-be-recommended package with the lowest price in the to-be-measured packages is determined through a preset measurement and calculation price comparison model, and the measurement and calculation price comparison model is constructed by a preset power retail standard package and a preset pricing algorithm; the power retail standard package is a unified package customized after integrating power retail packages in the power market; the related information of the to-be-recommended package is recommended to the user, so that the package with the lowest price is determined and provided to the user in a measurement and calculation mode through the preset measurement and calculation price comparison model according to the demand of the user, and the convenience when the user purchases the power retail package is greatly improved.