42 results about "Market based" patented technology

Various embodiments described herein relate to providing and / or employing a system and a method for managing a plurality of market-based instruments in a facility. In this regard, emission factors corresponding to a plurality of assets in the facility are stored in an emission factor repository. As a result, total actual emissions corresponding to the plurality of assets is calculated based on the stored emission factors. Then the total actual emissions are compared with a carbon emission target, wherein the carbon emission target corresponds to a specific period. Furthermore, total emissions are predicted in the facility for the specific period based on the stored emission factors and a result of the comparison. Accordingly, the predicted total emissions in the facility is displayed via a user interface of a display device.

The invention relates to a transaction mechanism and a clearing method for an electric power alternative spot market, and aims to solve the adjustment problem caused by access of high-proportion renewable energy in a novel electric power system. The method comprises the following steps: firstly, defining volume adjustment commodities and a transaction mechanism thereof, generating and correcting a system adjustment demand curve based on an adjustment demand curve reported by a market subject, collecting the volume adjustment quotation of each market subject to construct a clearing model, carrying out clearing by adopting an equal volume adjustment increment criterion, and determining a bid-winning volume. And dynamically adjusting the adjustment demand of the system through multiple rounds of adjustment transactions until the adjustment demand converges to zero. The method further comprises an external quantity adjustment price determination method and a transaction surplus allocation mechanism, and can eliminate the negative extrinsic property of the adjustment capability, realize the marketization configuration of the adjustment capability, improve the market operation transparency and predictability, reduce the total electricity purchase cost of the system, simplify the market clearing process, and improve the user experience. The method is suitable for a novel power system with high-proportion renewable energy access.

The invention discloses a marketing management method and system based on big data analysis, and relates to the technical field of marketing management, and the method comprises the steps: analyzing the behavior data of a marketing target user, and constructing a marketing target user portrait; outputting a marketing strategy of the marketing target user and the associated user through the behavior record of the associated user in combination with the portrayal analysis of the marketing target user; adjusting marketing strategies of the marketing target user and the associated user based on the market data; the adjusted marketing strategy is applied to market activities, and the marketing process and the market risk condition are monitored in real time; marketing achievements of all stages are obtained based on real-time monitoring, the marketing achievements are analyzed, a marketing change trend is recognized, a marketing strategy optimization mechanism is triggered based on the marketing change trend, and a marketing strategy is adjusted and optimized. Accurate marketing, strategy dynamic adjustment and resource optimal configuration are realized, and the marketing efficiency and effect are remarkably improved.

The invention discloses an electric power spot market risk evaluation method and system based on risk identification. The method comprises the steps of collecting a grid structure, generator set parameters and system operation prediction data of an analyzed electric power system; using a Monte Carlo method to simulate six basic risk events, and generating a market risk operation scene; a single-period clearing model with cost minimization as a target is constructed, and market clearing calculation in a risk scene is carried out; identifying the risk of each scene through a scene analysis method, and establishing a three-level risk evaluation index system of the spot market; adopting an analytic hierarchy process to distribute index weights; and setting five evaluation grades as {extremely low, low, medium, high and extremely high}, calculating the overall risk score of the market by using a fuzzy comprehensive evaluation method, and determining the risk evaluation grade. According to the invention, the operation risk of the electric power spot market can be assessed comprehensively and specifically, accurate risk rating is provided, and a sufficient basis is provided for risk management and control and decision making. And a more efficient risk management tool is provided for operators.

The invention discloses a market demand-based product research and development process and management method. The method comprises the following steps of 1, market demand acquisition and standardized modeling; step 2, demand decomposition and association degree quantization; step 3, project information integration and plan generation; 4, performing dynamic plan management and conflict detection; step 5, task execution and state tracking; and step 6, demand closed-loop verification and feedback. According to the method, the requirements are integrated through standardized modeling, quantifiable research and development input is realized, and the problem of analysis fragmentation is solved; by means of automatic tracing and dynamic management and control, the demand change influence is accurately evaluated, and resource waste is avoided; through whole-process standardized collaborative operation, human intervention is reduced, a PDCA cycle optimization mechanism is formed, human error risks are reduced, market demand full-life-cycle closed-loop management is achieved, and research and development efficiency and quality are improved.

The invention belongs to the technical field of virtual power plants, and particularly relates to a virtual power plant day-ahead strategy optimization method in a spot mode, which comprises the following steps of: performing correlation analysis and feature extraction on Spearman time-phased medium and long-term markets, spot prices and market boundary information; a time-phased spot market price prediction model is formed, and time-phased spot market prices are predicted; adopting a bidding space linear regression method to carry out time-phased medium-and-long-term market transaction price prediction; a difference algorithm is adopted to establish a virtual power plant electric power spot market price declaration strategy optimization model; and generating a virtual power plant spot market declaration strategy. According to the method, the correlation between the market boundary factor-based time-sharing spot price and the medium and long term transaction price is analyzed, the market boundary data is utilized to predict the future time-sharing thermal power load rate mean value, and the future time-sharing thermal power load rate mean value is input into the pre-trained model, so that the accurate prediction of the time-sharing average price of the electric power spot market is realized.

The invention relates to a market power discrimination method and device, equipment, a storage medium and a program product. The method comprises the steps of obtaining to-be-discriminated market data of a generator set, inputting the to-be-discriminated market data into an isolated forest model, determining an abnormal score of the to-be-discriminated market data according to the depth of the to-be-discriminated market data and the depth of the isolated forest model, and determining a market power discrimination result of the to-be-discriminated market data according to the abnormal score and a preset threshold value. Wherein the isolated forest model is determined based on the market data samples and discrimination indexes, and the discrimination indexes comprise the holding capacity, quotation consistency and quantity reporting consistency of the generator set. According to the embodiment of the invention, the isolated forest model is introduced when the market power is discriminated, so that the accuracy during unsupervised learning is improved, and the accuracy and efficiency of market power discrimination are improved.

The invention provides an electric power spot market day-ahead clearing method and system based on flexible resource participation, and belongs to the technical field of electric power system operation and market transaction. Comprising the following steps: constructing a medium and long term transaction auxiliary decision-making model, and performing parameter optimization by adopting a gradient descent algorithm; according to a decision-making thought of the medium and long term transaction auxiliary decision-making model after parameter optimization, transaction variety weights are set, and transaction bins are formulated; optimizing the set weight by taking risk benefit balance as a decision-making target, and executing electric quantity distribution; and constructing an income risk quantification model, and adjusting the weights and transaction bins of different transaction varieties according to a quantification result to realize continuous optimization of the day-ahead clearing strategy of the electric power spot market. According to the method, the reasonability of power resource allocation can be remarkably improved, and strategic guidance is provided for day-ahead clearing of a power spot market.

The invention belongs to a power market simulation method, and provides a power market transaction simulation drilling method and a related device for solving the problems that a practical operation training tool is lacked in a current power market construction process, and the adaptability with actual operation is insufficient in a market system design and rule optimization process. After a power market subject model, market load demand data and an adaptive environment are determined, power medium-and-long-term centralized bidding transaction simulation is performed according to the power market subject model and the adaptive environment by adopting a mode of cooperative interaction of a master station end and a substation end, and power medium-and-long-term rolling matchmaking transaction simulation is performed based on a marketization transaction rule. The method comprises the following steps: carrying out the whole-process closed-loop simulation of an electric power spot day-ahead market, calculating the comprehensive income score of a competitor according to a simulation result, and obtaining an electric power market transaction simulation drill result in combination with a model result and the comprehensive income score. The method is superior to the prior art in the aspects of simulation efficiency, operation stability and practical training.

An object of the system according to the embodiment is to evaluate market suitability of a business idea of a user and provide a specific action plan.SOLUTION: A system includes an idea input part, a market evaluation part, a customer specification part, and a competition analysis part. The idea input unit inputs an idea of a user. A market evaluation part evaluates the market needs on the basis of the idea input by the idea input part. A customer specification part specifies a target customer layer on the basis of the market needs evaluated by the market evaluation part. The competition analysis unit analyzes a situation of a competitor based on the target customer layer specified by the customer specification unit.SELECTED DRAWING: Figure 1

The invention discloses a regional electricity-gas-carbon market equilibrium analysis method, which comprises the following steps: respectively constructing market participant models based on data of each participant in a regional electricity-gas-carbon comprehensive market; constructing a market operator model based on the market operator data: constructing a power market operator model by taking maximization of social welfare as a target in the power market; constructing a gas market operator model by taking maximization of social welfare as a target in the regional natural gas market; constructing a carbon market operator model by taking the income brought by maximizing the distribution of the carbon quota to the market as a target; converting a market equilibrium problem into a generalized Nash equilibrium problem on the basis of operation characteristics of market participants and strategies adopted by the market participants, and converting a convex optimization problem of the model into a complementary model according to a Karush-Kuhn-Tucker condition to obtain a market equilibrium model; and solving the market equilibrium model to obtain a market equilibrium deduction result. According to the method, an effective basis is better provided for regional electricity, gas and carbon price change deduction.

The present disclosure relates to a power spot market clearing simulation method based on energy block transaction, comprising the following steps: obtaining the estimated bidding plan of each market participant; dividing the reported power of each market participant into several energy blocks; establishing a power-price pair model; establishing a day-ahead clearing model of the power spot market based on energy block transaction to obtain a day-ahead market clearing result; establishing a real-time clearing model of the power spot market based on energy block transaction and solving to obtain a real-time market clearing result, wherein the real-time market clearing result comprises real-time market clearing power and real-time market clearing price; and settling the income of each market participant according to the day-ahead market clearing result and the real-time market clearing result. The present disclosure considers the physical and economic constraints of multiple types of energy blocks in the day-ahead and real-time markets and the physical constraints of the power system, and can more accurately simulate the day-ahead-real-time two-stage clearing process of the power spot market based on energy block transaction in a market environment.

The invention relates to the technical field of market feedback multi-source data calculation, discloses a dynamic rebate calculation method and system based on market feedback and multi-source data fusion, and aims at solving the problems that a traditional rebate mechanism is extensive in excitation and lacks market responsiveness and service quality coupling. The method comprises the following steps: constructing a multi-source heterogeneous data acquisition system covering job seekers, human resource specialists and community promoters; performing cleaning, normalization and layered embedded feature engineering on the original data to form a unified feature vector; establishing a service quality evaluation system integrating post authenticity, complaint rate and credit records; and carrying out nonlinear weighting on the contribution score and the service quality score, and dynamically generating a personalized rebate amount in combination with industry supply and demand popularity and a time decay compensation formula. According to the scheme, excitation precision, risk control preposition and market self-adaption are achieved, and the rebate input-output ratio, the matching efficiency and the platform credibility are remarkably improved.

An object of a system according to an embodiment is to collectively support planning and execution of a sales strategy in a global market.SOLUTION: A system according to an embodiment includes a market analysis unit, a customer targeting unit, a translation unit, a customer support unit, and a marketing optimization unit. The market analyzer analyzes the market using the generated AI. The customer targeting unit identifies a customer segment based on the market identified by the market analysis unit. The translation unit translates the product description to the customer segment specified by the customer targeting unit. The customer support unit responds to the inquiry from the customer based on the product description translated by the translation unit. The marketing optimization unit optimizes a marketing strategy based on the data collected by the customer support unit.SELECTED DRAWING: Figure 1

The invention provides an energy storage income optimization strategy method and system based on a market mechanism, and relates to the technical field of energy storage income, and the method comprises the steps: recognizing an asymmetric risk conduction path through obtaining a multi-time scale price curve and a bidirectional option contract term, and building a network model; performing state-aware dynamic mapping to construct a cross-space-time hedging strategy group; introducing energy loss and response time delay constraints to establish a state dependent pricing equation; and the energy storage capacity bidirectional option transaction is executed, and the risk conduction weight and the hedging strategy are optimized by using feedback information, so that closed-loop optimization of pricing accuracy and hedging effectiveness is realized, and the income level of the energy storage equipment is improved.

The invention relates to a method for analyzing the influence of market element changes on power transmission and transformation project cost. The method comprises the following steps: collecting market element data and power transmission and transformation project cost element data; constructing a direct influence matrix based on the market element data and the power transmission and transformation project cost element data; constructing a comprehensive influence matrix based on the direct influence matrix to obtain the influence degree, the influenced degree, the centrality and the reason degree of the market elements and the power transmission project cost elements; and respectively analyzing the relationship between the centrality and the reason degree and the relationship between the influence degree and the influenced degree in a drawing mode.

The invention provides a carbon transaction game prediction method based on a Stackelberg game and a stochastic differential equation. The method comprises the following steps: step 1, determining marginal revenue functions of both carbon transaction parties; step 2, constructing utility functions of different risk preference carbon traders; 3, calculating the balanced price and quantity of carbon transactions; 4, predicting the future change trend of the market based on the historical carbon quota transaction price; and 5, determining the optimal transaction opportunity based on the future change trend of the market and the balanced transaction price. The invention aims to deeply analyze the optimal decision of the two types of participants, effectively improve the transaction income of the seller enterprise, reduce the transaction cost of the buyer enterprise and remarkably enhance the market mobility by accurately matching the market supply and demand, thereby promoting the efficient operation and sustainable development of the carbon emission permit transaction market.

The invention relates to a market behavior evaluation method and device, equipment, a storage medium and a program product. The method comprises the steps of constructing a market behavior evaluation model based on historical behavior data of an electricity market and a Bayesian network constructed based on an evaluation index system, obtaining to-be-evaluated market behavior data of the electricity market, and determining a market behavior evaluation result of the to-be-evaluated market behavior data based on the market behavior evaluation model, therefore, market behavior evaluation results under different evaluation indexes can be comprehensively considered based on the Bayesian network structure, the influence of uncertain factors of the electricity market on the market behavior evaluation results is reduced, and the accuracy and reliability of market behavior evaluation are improved.

Systems, apparatuses, and methods are described for contextually augmenting content, which may be offered based on segment types associated with various sentiments, emotions, and / or excitement levels which may be detected and / or aligned in the content. The contextual content augmentation may comprise in-video contextual advertising, which may be based on advertisement strategies such as segment-based, alignment / detection-based, market-based, and / or user-based strategies.

This invention provides a market-based energy storage revenue optimization strategy method and system, relating to the field of energy storage revenue technology. The method includes: acquiring price curves across multiple time scales and two-way option contract terms; identifying asymmetric risk transmission paths and establishing a network model; performing state-aware dynamic mapping to construct a cross-temporal hedging strategy group; introducing energy loss and response delay constraints to establish a state-dependent pricing equation; executing two-way option transactions for energy storage capacity and utilizing feedback information to optimize risk transmission weights and hedging strategies, achieving closed-loop optimization of pricing accuracy and hedging effectiveness, and improving the revenue level of energy storage equipment.

The application discloses a kind of based on VCG mechanism's electricity-gas-carbon combined market under comprehensive energy system optimization operation method, constructs integrated power, natural gas, carbon cycle and green certificate transaction comprehensive energy system coupling model, maximizes social welfare by distribution robust optimization model, adopts Wasserstein fuzzy uncertainty set to process carbon price and green certificate price uncertainty, calculates each unit externality payment value using VCG mechanism and endogenously determines electricity price and gas price, finally outputs optimal scheduling scheme satisfying multiple constraints.The method can solve the problems of low efficiency of resource allocation and insufficient carbon emission reduction incentives in existing single market mechanism, improve the reliability of multi-market data correlation analysis by exploiting energy conversion and carbon cycle, enhance the robustness of data under constraints using Wasserstein uncertainty set, and significantly improve the reliability of data analysis and the accuracy of optimization decision-making in complex energy systems by avoiding strategic pricing distortion using VCG mechanism, providing support for the construction of new power systems.

In one implementation, a device assigns a budget to a bidding agent associated with a networking entity in a computer network. The device obtains a bid from the bidding agent selected by the bidding agent based on the budget. The device conducts an auction using the bid. The device excludes the networking entity from being eligible for performance of an energy-saving action, based on a result of the auction.

The invention provides a circuit-assisted market operation strategy optimization method and device based on model analysis, relates to the field of power markets, and solves the problem that in the prior art, when a market is optimized, due to unstable power supply of renewable resources, excessive production capacity of an adjusted market operation strategy is possibly caused, and the market operation strategy optimization efficiency is improved. And the development of a power system is not facilitated. The method comprises the following steps: acquiring operation parameter data of a power system and market transaction data of a power market; analyzing the operation parameter data of the power system to obtain market demand data; adjusting a transaction strategy based on the market demand data and the market transaction; predicting the market demand data according to the operation parameter data of the power system to obtain predicted demand data; evaluating the market risk according to the predicted demand data to obtain a risk level; and implementing risk management and control measures according to the risk level. The method and the device are used in a circuit-assisted market operation strategy optimization process.

Disclosed herein are method, system, and computer product aspects for queue management and facilitating transactions based on an exchange of queue position. This may include a physical change in relative queue position between queuing devices and / or an exchange of queue position in an electronic queue. Upon exchanging queue positions, the queuing devices may conduct a transaction to transfer value for the exchanged position. The exchange of queue positions may include vehicles traveling on a roadway and exchanging positions in traffic, exchanging positions between mobile device users standing in a line, and / or exchanging positions in an electronic queue. Monetary funding may be transferred between the queuing devices when exchanging positions in the queue. A queue management system may generate a suggested positional exchange amount based on user parameters, conditions, and / or preferences for interacting with the queue.

The invention relates to an electric power spot market clearing simulation method based on energy block transaction. The method comprises the following steps: obtaining an estimated bidding plan of each market participant; dividing the reported electric quantity of each market participant into a plurality of energy blocks; establishing an electric quantity-price pair model; an electric power spot market day-ahead clearing model based on energy block transaction is established to obtain a day-ahead market clearing result, an electric power spot market real-time clearing model based on energy block transaction is established and solved to obtain a real-time market clearing result, and the real-time market clearing result comprises real-time market clearing electric quantity and real-time market clearing price; and according to the day-ahead market clearing result and the real-time market clearing result, the income of each market participant is settled. Physical economic constraints of multiple types of energy blocks and physical constraints of a power system in the day-ahead and real-time markets are considered, and the day-ahead-real-time two-stage clearing process of the power spot market based on energy block transaction can be simulated more accurately in a marketization environment.

The invention discloses a multi-subject energy differentiation transaction method and system driven by dynamic cognition, and relates to the field of energy internet transaction.The method comprises the steps that personalized modeling of market subject cognitive competence is achieved based on multivariate data, initial division of cognitive levels is achieved based on a clustering algorithm, and cognitive level initial labels are obtained; on the basis of a dynamic cognitive level updating mechanism of market performance and behavior evolution characteristics, obtaining a cognitive level updated tag; and determining a target transaction mode corresponding to the tag after the cognitive hierarchy is updated for the tag after the cognitive hierarchy is updated based on a differentiated transaction strategy and a cooperation mechanism of the cognitive hierarchy. In conclusion, fine identification and dynamic adaptation of the cognitive heterogeneity subject are realized, the market fairness, the operation efficiency and the system robustness are effectively improved, and key support is provided for constructing intelligent, differentiated and collaborative energy internet transaction ecology.

The invention belongs to the technical field of electricity market risk identification, and discloses a multi-level spot market risk identification method and a related device, and the method comprises the steps: reading the market data of a multi-level spot market; based on the market data, risk assessment index values of the multi-level spot market are calculated, and the risk assessment index values comprise a market price risk index value, a multi-level market association risk index value and a market power risk index value; calculating a weight coefficient of the risk assessment index value of the multi-level spot market by adopting an improved entropy weight method; and based on the risk assessment index value and the weight coefficient of the multi-level spot market, calculating a market risk comprehensive assessment value, and identifying a risk type and a risk level according to the market risk comprehensive assessment value. An improved entropy weight method is adopted to determine various risk index weights, and the improved entropy weight method can effectively overcome the defects of a traditional entropy weight method and can also enable the entropy weight method to keep the capability of distinguishing entropy value differences.

The invention relates to the technical field of credit management, in particular to a credit monitoring and checking method and system based on market risk quantitative analysis. According to the credit monitoring and assessment method based on market risk quantitative analysis, the potential loss of financial assets in a user-defined time period is evaluated, then a credit risk rating model is constructed, and the credit risk grade of an enterprise is predicted; then constructing a dishonesty probability model, and predicting the dishonesty probability of the enterprise; and finally, step S4, generating a credit detection report based on the prediction results of the maximum loss amount VaR, the enterprise credit risk level and the enterprise dishonesty probability that the enterprise will face in the customized time period. The credit monitoring assessment method and system based on market risk quantitative analysis not only improve the scientificity and accuracy of credit monitoring, but also enhance the ability of a management department in market supervision and risk prevention.

The application discloses a market subject management method and system based on multi-source data fusion, relates to the technical field of intelligent supervision, and comprises the following steps: based on a plurality of data holders, feature data of a market subject risk state is generated locally; the plurality of data holders interact through a privacy protection cooperation mechanism, participate in the construction process of cross-domain risk cognition consensus, and form a cross-domain risk consensus discriminator locally; the cross-domain risk consensus discriminator is used to filter high-risk market subjects from the feature data of the market subject risk state, and a high-risk market subject list is formed; for each market subject in the high-risk market subject list, an actual behavior track is formed based on the feature data of the market subject risk state. The application realizes local risk cognition model iterative optimization through inspection feedback, and forms a process from risk accurate identification, deep attribution analysis to intelligent supervision intervention and self-sustaining optimization.

The present invention discloses a method and system for multi-level sentiment analysis of a trading market based on mixed-frequency data, comprising: real-time acquisition of multi-source heterogeneous mixed-frequency data sets related to market transactions, including a low-frequency macro-policy data set, a medium-frequency market transaction information data set, a high-frequency transaction-related policy news corpus, and an expert market sentiment judgment data set; generating a long-term policy sentiment index based on the low-frequency macro-policy data set; generating a medium-term trading sentiment index based on the medium-frequency market transaction information data set after eliminating the influence of macro-policy indicators; generating a short-term news sentiment index based on the high-frequency transaction-related policy news corpus; predicting a comprehensive sentiment index based on the long-term policy sentiment index, the medium-term trading sentiment index, the short-term news sentiment index, and the expert market sentiment judgment data set; real-time storage and display of all sentiment indices, so as to achieve more reasonable and accurate multi-level sentiment analysis of the trading market.