172 results about "Ancillary service" patented technology

The invention discloses a flexible load multi-time scale coordination control method for a novel power system, and the method comprises the specific steps: collecting millisecond, minute and hour level flexible loads and environment data, and constructing a multi-time scale load response model; a millisecond-level model and a second-level model are utilized, a real-time operation state is combined, a second-level adjusting instruction is generated, and an execution result is fed back; based on minute-to-hour level prediction data, integrating adjustable load, distributed energy and energy storage constraints, optimizing a load operation plan in a rolling manner, and coordinating source-network load-storage combined operation; and making a long-term load operation plan in combination with day-level and above prediction data, and executing deviation self-adaptive correction according to short and medium periods. According to the method, hierarchical control and collaborative optimization of the adjustable load under different time scales from millisecond level to day level are realized, and the operation stability, the adjustment flexibility and the auxiliary service capability of the novel power system under the high-proportion new energy access condition are remarkably improved.

The invention discloses an energy storage system multi-scene optimization scheduling method and device, equipment, a medium and a product, and relates to the field of model optimization, and the method comprises the steps: obtaining an initial decision variable and a constraint term which are used for training a scheduling model; obtaining a prediction data set; based on the predicted photovoltaic output in the prediction data set, the first predicted electricity price set, the second predicted electricity price set, the initial decision variable and the constraint term, generating the predicted total income of the electric energy market and the auxiliary service market; on the basis of the predicted total income, updating the initial decision variable so as to optimize the scheduling model, and obtaining an optimized target scheduling model; based on the optimal decision variable of the target scheduling model, adjusting a charging and discharging control strategy of the energy storage system; according to the predicted electricity price and total income, the charging and discharging strategy of the energy storage system is dynamically adjusted, so that the energy storage system can participate in an electric energy market and an auxiliary service market at the same time, and the economic benefit of the whole electric power market is maximized.

The invention discloses a layered and distributed cooperative scheduling method and system for a smart rod cluster and a computer program product, and belongs to the technical field of power system energy optimization scheduling, and the method comprises the steps: building a day-ahead scheduling optimization model that smart rod cluster aggregation resources participate in an electric energy market and a peak regulation auxiliary service market at the same time; according to the day-ahead scheduling optimization model, proposing a layered and distributed cooperative scheduling method based on an alternating direction multiplier method scaling form; based on a hierarchical distributed collaborative scheduling method, respectively solving an upper-layer smart rod cluster operator management platform sub-problem and a lower-layer smart rod cluster sub-problem; and after the sub-problems of the upper layer and the lower layer are solved, an aggregation power allocation method considering the flexible resource feasible region of the multi-type smart rod cluster is proposed, and the aggregation power of the smart rod cluster is allocated to each smart rod. Based on the alternating direction multiplier method, the scheduling problem of a large-scale resource cluster can be efficiently solved, higher economy is achieved, and privacy of various resource users is better protected.

The invention provides an operation optimization method, device and equipment of a pumped storage power station and a storage medium, and relates to the technical field of operation optimization of a power system. The method comprises the following steps: taking the maximum expected revenue and the minimum participation risk when the pumped storage power station participates in an electric energy market and a frequency modulation auxiliary service market as an optimization target, and according to the expected revenue and the participation risk of the pumped storage power station at each moment in an optimization time period and a target function of the next moment corresponding to each moment, optimizing the optimization time period of the pumped storage power station; target functions of the pumped storage power station at all moments in the optimization time period are established respectively; and a constraint condition is established, iterative solution is performed on the target function at each moment based on the constraint condition, and optimal operation strategies of the pumped storage power station at different moments in the optimization time period are obtained, so that operation of the pumped storage power station is controlled according to the optimal operation strategies in the optimization time period. The operation strategy of the pumped storage power station can be prevented from falling into local optimum.

The invention discloses an energy storage electricity market bidding method, device and equipment and a storage medium, and relates to the field of energy storage optimization scheduling, and the method comprises the steps: an independent energy storage bidding decision model sends first quotation data to an electricity market clearing model; the electricity market clearing model determines the total electricity purchase cost based on the first quotation data and the second quotation data of each conventional unit in the plurality of conventional units; the power market clearing model determines bid-winning data of the independent energy storage bidding decision-making model based on the total power purchase cost, and sends the bid-winning data to the independent energy storage bidding decision-making model; the independent energy storage bidding decision model determines the total income of the electric energy market and the frequency modulation auxiliary service market based on the bid winning data; and the independent energy storage bidding decision-making model optimizes the first quotation data based on the total income, and sends the optimized first quotation data to the electricity market clearing model, and the optimization is ended until the reduction of the total electricity purchase cost and the increase of the total income are both smaller than a preset threshold value or the number of iterations is reached.

The invention provides an operation optimization method and system for an energy storage participation auxiliary service market, and the method comprises the steps: determining an energy storage performance aging factor, and defining an energy storage aging time function according to the energy storage performance aging factor; the energy storage performance aging factors comprise calendar aging and cycle aging; based on the energy storage aging time function, constructing an intra-day operation model taking energy storage expected life maximization and intra-day benefit maximization as objective functions; and solving the intra-day operation model by adopting a multi-agent algorithm of a non-adversarial game to obtain an optimal strategy of energy storage intra-day operation. According to the invention, the relation between the energy storage aging characteristic and the working characteristic is introduced to carry out the energy storage intra-day operation decision, the economic benefit can be truly evaluated, the energy efficiency of energy storage and the stability of scheduling are considered, and the operation maintenance level is greatly improved.

A method, system and apparatus are disclosed. A management node configured to communicate with a power grid operator and with a plurality of RBSs is provided. Each of the plurality of RBSs is configured to be switchable between power from a power grid and power from a respective plurality of backup battery units associated with the RBS. The management node is configured to: determine a primary subset of the plurality of RBSs to participate in at least one FCR event occurring over a predefined time interval, and determine a standby subset of the plurality of RBSs that are each configured to participate in the at least one FCR event in place of a failure of a respective one of the primary subset of the plurality of RBSs.

The invention discloses an environment deployment method and system of a cloud native electric power auxiliary service market system, and belongs to the technical field of electric power system informatization. The method comprises the following steps: acquiring test environment configuration information and a system running state; constructing an infrastructure and deploying a system service component according to the test environment configuration information, and generating a test environment consistent with the production environment; testing the test case in the test environment to obtain a test result; verifying the system operation state and the test result according to a preset verification rule to obtain a test report; the test report comprises a test success report and a test failure report; when the test success report exists and the test coverage is in accordance with the preset range, allowing the system to be deployed to the production environment; and when the test report does not exist, the test failure report exists or the test coverage does not meet the preset requirement, the system is prohibited from being deployed to the production environment. The problems that the test environment generation efficiency is low and deployment verification is not strict can be solved.

The invention discloses a virtual power plant game transaction rapid convergence method and system, a storage medium and equipment. The method comprises the following steps: constructing a reference auxiliary service electricity price coefficient including response efficiency, response quality and response reliability of a virtual power plant based on response information; constructing a basic electricity price based on the real-time supply and demand condition and the real-time electricity price of the power grid; constructing a virtual power plant game transaction model based on the reference auxiliary service electricity price coefficient and the basic electricity price; and finally, carrying out iterative convergence on the virtual power plant game transaction model based on the reference auxiliary service electricity price through a Markov decision process and a reinforcement learning algorithm. According to the method, the reference auxiliary service electricity price is constructed in the game transaction model between the virtual power plant and the auxiliary service market, so that the deviation between the initial electricity price and the final market clearing electricity price can be effectively reduced, the number of times of game iteration is reduced, the convergence speed of the game is improved, and the market clearing efficiency is improved.

The invention discloses a collaborative charging optimization strategy for an electric vehicle aggregator EVA participating in a day-ahead energy market and a frequency modulation auxiliary service market, belongs to the technical field of energy internet regulation and control, considers the influence of multi-stage income evaluation and an actual frequency modulation effect on income, meets the diversified charging requirements of users, and improves the energy utilization rate of the users. A collaborative charging optimization strategy that EVA participates in a day-ahead energy market and a frequency modulation auxiliary service market is provided, and a control system that EVA participates in peak regulation and frequency modulation of a power grid is constructed to analyze a frequency response effect. In the influence of the actual frequency modulation effect on earnings, in order to improve the frequency modulation quality in the power market, the performance of frequency modulation resources is assessed according to the actual frequency modulation effect, the resources with high scores obtain high earnings, and the frequency modulation earnings are paid according to the assessment result. According to the method, the influence of the frequency modulation effect on earnings is considered, and the value and benefit brought by EVA charging control to a power grid are reflected by researching the charging control of aggregators for aggregating the electric vehicles and realizing marketization transaction.

The invention provides a benefit evaluation method for participation of energy storage equipment in electric power auxiliary service, and the method comprises the steps: extracting a peak regulation service emergency degree and a frequency modulation response real-time requirement, recognizing the priority order of each service response, distributing mixed output data to a peak regulation part and a frequency modulation part according to the priority, and obtaining a power share after preliminary decomposition; standby loss data of standby standby are obtained and matched with the charging and discharging power overlapping part, if the loss data are matched with non-allocation residues in the power share obtained after preliminary decomposition, the residues are assigned to the standby standby, and complete service type power allocation is obtained; and extracting a revenue adjustment coefficient from the allocated revenue value, identifying an allocation weight of the revenue adjustment coefficient between the services, and if a deviation exceeds a threshold value, reallocating to obtain an optimized accurate allocation result.

The embodiment of the invention discloses a data processing method, device and equipment, and the method comprises the steps: obtaining an execution request of a core service in a target business, and when it is detected that other services except the core service need to be executed in the execution process of the core service, executing the execution request of the core service; according to the method, verification parameters and auxiliary processing demand data used for calling auxiliary services are obtained, then, target auxiliary services matched with the verification parameters can be searched in an auxiliary service database based on the verification parameters, the target auxiliary services are called, and the auxiliary services are called through the target auxiliary services. And executing auxiliary processing corresponding to the auxiliary service calling request based on the auxiliary processing demand data to obtain an auxiliary processing result corresponding to the auxiliary service calling request, and finally, continuing to execute the core service based on the auxiliary processing result corresponding to the auxiliary service calling request.

The invention relates to the technical field of power system auxiliary services, in particular to a multi-agent participated user group dynamic combination and economic optimization method in power auxiliary services, which comprises the following steps of: constructing a multi-agent collaborative model of'upper-layer scheduling-middle-layer aggregation-lower-layer execution ', formulating an incentive price through a Stackelberg game between upper-layer ISO (International Standard Organization) and LAs (Local Assisted Services), and establishing a multi-agent collaborative model of'upper-layer scheduling-middle-layer aggregation-lower-layer execution'; the evolutionary game between the lower-layer LAs and the user realizes user strategy interaction; introducing maximum profit power reduction and power transfer potential indexes, and performing user group preliminary screening in combination with a multi-energy profit map; and outputting an optimal user group combination scheme through iterative solution and joint uncertainty analysis. The invention further provides an alternative scheme, and dynamic combination optimization is realized by utilizing the user potential portrait and a reinforcement learning mechanism. The method can effectively improve the economy, flexibility and robustness of the power auxiliary service, and gives consideration to the comfort of the user and the adjustment demands of the system.

The present application relates to a kind of multi-purpose virtual power plant economy and auxiliary service optimization method, belong to virtual power plant dispatching technical field, including the following steps: considering renewable energy uncertainty, construct virtual power plant economy and auxiliary service joint optimization model;Using the hybrid optimization strategy of fusion improved particle swarm optimization algorithm and snow melting optimizer is solved to joint optimization model, obtains optimal scheduling scheme.The present application realizes the collaborative balance between minimum operating cost and auxiliary service maximization;Optimization method has the advantages of few parameters, convergence fast, high precision, significantly enhances the solving performance of model and the optimization quality of scheduling scheme.

Described herein are techniques for analyzing assisted service requests received so that the service provider can identify new services to create for purposes of enriching the service catalog. The assisted service requests can be analyzed and organized into a plurality of clusters based on similarity. The service provider may review the clusters when deciding which new service requests to create for the service catalog. In one example, clusters containing more assisted service requests may be prioritized over clusters containing fewer assisted service requests since the newly created service request would be able to service a larger number of customer requests.

The invention discloses a method, a system, equipment and a medium for constructing a flexibility auxiliary service market clearing model considering energy storage and demand side resources, and belongs to the technical field of electric power auxiliary service market optimizing.The method comprises the steps that basic modeling is completed through a multivariate heterogeneous resource unified modeling system, resource differences are depicted, a comprehensive flexibility potential index is calculated, and the comprehensive flexibility potential index is calculated; establishing a flexibility potential evaluation model to quantify the resource adjustment capability; setting a multi-objective function and integrating the key constraint conditions to form a multi-objective flexibility auxiliary service market clearing model; and designing a model solving method based on a chaotic particle swarm-simulated annealing fusion algorithm. According to the method, key parameters such as energy storage life loss and demand side user comfort are introduced, so that a traditional homogenization hypothesis is broken through; constructing an adjustment capability-response speed-economy multi-index evaluation system, and quantifying the resource flexibility potential in combination with an entropy weight method; a multi-target clearing model of flexible value is established, and market cost, system benefit and resource cost are optimized.

The invention discloses a method, a system, equipment and a medium for sharing a user participating in an auxiliary service based on dynamic analysis, and relates to the technical field of electric power auxiliary services, and the method comprises the steps: building a user participating in auxiliary service benefit degree quantification model, and quantifying the benefit degree of each user obtained by participating in the auxiliary service; determining a corresponding cost sharing proportion based on the total benefit degree of the user, and calculating the sharing amount of each user in combination with the supply cost, the operation cost and the risk cost of the auxiliary service; setting a stepped excitation coefficient and an influence factor according to the sharing amount, the participation frequency and the response quality of each user, and calculating the final excitation amount of the user; and establishing a dynamic adjustment and constraint model for mechanism operation, and periodically adjusting each parameter and factor. According to the method, the user benefit degree is taken as the calculation basis of cost sharing, and the participation behavior quality is brought into incentive adjustment, so that the fairness of auxiliary service cost distribution is improved, and the participation enthusiasm of the user and the operation flexibility are enhanced.

The invention provides a thermal power enterprise profit distribution method, device and equipment considering different transaction categories, and the method comprises the steps: forming an optimization function model: MAX ((1-beta) * expected profit + beta * Cvar); determining an optimal target function value by combining an electric energy balance constraint, an auxiliary service demand constraint, a unit capacity constraint, a participation state constraint and a conditional risk constraint; wherein beta is a risk coefficient of Cvar, beta is greater than or equal to 0 and less than or equal to 1, and the larger the beta value is, the smaller the corresponding risk is; cvar is a conditional value at risk. According to the invention, the influence of different transaction varieties on the profitability of the power generation enterprise and the internal unit thereof can be analyzed more accurately, and the problems of participation of the thermal power enterprise in clearing and profit distribution of the electric energy and auxiliary service market under different weather conditions are reasonably quantified.

The invention relates to the technical field of pension service, and discloses a smart nursing home optimization auxiliary service system, which comprises a high-dimensional situation sensing module, which is used for collecting multi-modal biological and environmental signals in real time through an integrated sensor array; the professional cognitive reconstruction module is used for deducing a cognitive path sequence and a decision intention; the service behavior generation module is used for reversely deriving a complete language expression sequence and a limb behavior sequence required by the old-age care service; the dynamic calibration module is used for comparing the actual situation change with the service system expectation in real time; the body memory module is used for constructing body memory experience for immersive backtracking of service personnel; and the cognitive sharing module is used for anonymously extracting the situational cognitive fingerprints. According to the invention, the service instruction is transmitted to the service personnel without perception through the cross-sensory customized instruction transmission unit, the standardization and accurate control of the service behavior are realized, dynamic adjustment is carried out according to the actual situation change, and the real-time adaptability of the service process is ensured.

The invention discloses a service pushing method, electronic equipment and a readable storage medium, and belongs to the technical field of terminals. The method comprises the steps that parameter information of all auxiliary services supported by the electronic equipment is obtained, the parameter information of one auxiliary service comprises an application list and scene triggering information, and the application list comprises application information of application programs supported by one auxiliary service and installed in the electronic equipment; and querying the scene detection capability supported by the electronic equipment. And subscribing the target scene fence according to the parameter information of each auxiliary service and the scene detection capability supported by the electronic equipment. Thus, the parameter information of the auxiliary service and the scene detection capability supported by the electronic equipment are merged to determine the auxiliary service which is finally allowed to be provided by the electronic equipment, and the corresponding scene fence is subscribed according to the determined auxiliary service which is allowed to be provided. The auxiliary service can be accurately pushed to the user under the condition that the scene fence is detected to be triggered.

The invention discloses a resident air conditioner load multi-mode configuration method for various auxiliary service requirements. The resident air conditioner load multi-mode configuration method comprises the steps that a matching mapping relation between differential control modes and auxiliary service types is constructed; establishing a resident user participation willingness response model based on the incentive price; building a physical aggregation power calculation model of the resident air conditioning load in multiple modes; the theoretical aggregation power interval is corrected, and an air conditioner load reliable aggregation power interval is generated; and based on the matching mapping relation, the resident user participation willingness response model and the air conditioner load reliable aggregation power interval, constructing and solving a collaborative configuration optimization model considering both reliability and economy, and outputting an optimal resource configuration scheme. According to different requirements of secondary frequency modulation, peak regulation and spinning reserve, the configuration combination of the three modes of the intelligent control switch, the intelligent temperature controller and non-intrusive reminding can be differentially optimized, and the operation cost of the system is minimized on the premise that the aggregation reliability is guaranteed.

The invention discloses a calculation method and system for an inertia auxiliary service market optimization clearing result considering an inertia demand, and a medium, and the calculation method comprises the steps: solving a system minimum inertia demand based on RoCoF and FN constraints, determining a system minimum inertia purchasing demand, and taking the system minimum inertia purchasing demand as one of the constraints of a market joint optimization clearing model, therefore, a reasonable power supply structure is guided to be formed, the adequacy of inertia resources in the transaction process is guaranteed, and the frequency safety problem caused by insufficient inertia supply capacity of a power system is solved. According to the invention, the electric energy purchase cost, the unit start-stop cost and the inertia purchase cost are taken as the total scheduling cost, and the respective supply cost of the inertia and the electric energy is considered as a whole, so that the overall economic operation of the system is realized.

The invention discloses a privacy protection smart medical service recommendation method based on weight matching. The method comprises the steps that a medical management center generates materials needed by a security key and sends the materials to a patient user and a server cluster; the medical management center carries out doctor registration service and patient user registration service through copy secret sharing and the server group; after registration is completed, each server in the server cluster obtains a pair of shared values; screening doctors by calculating a similarity vector between the user demand vector and the doctor attribute vector; and after the doctor service is completed, calculating the weight of each dimension of the score vector of the user, and updating the score of the doctor based on each dimension value of the score vector and the corresponding weight. According to the method, the most suitable doctor is recommended by calculating the similarity among the patient demand, the doctor attribute and the score vector; multi-party calculation of data is realized through a function secret sharing technology, and the data security is enhanced. Calculation and auxiliary servers are introduced, so that the online calculation cost is reduced, and malicious scoring is effectively resisted.

The present application relates to the technical field of power system energy scheduling, and discloses a virtual power plant electric energy frequency modulation method and system. In the joint clearing mode of the electric energy market and the frequency modulation auxiliary service market, the virtual power plant participates in the electric energy frequency modulation market transaction model, can reasonably allocate the bidding capacity in the two types of markets, establishes the basis for the optimal bidding scheme of the virtual power plant, and at the same time provides framework support for the virtual power plant to participate in multi-market coupling transaction. At the moment when wind and light are in full swing, the virtual power plant can obtain more bidding opportunities in the electric energy market with lower bidding; by aggregating high-quality frequency modulation resources such as energy storage, the virtual power plant can improve the comprehensive frequency modulation performance and the competitiveness in the frequency modulation market.

A technique involves modular storage of network service plan components and provisioning of same. A subset of the capabilities of a service design system can be granted to a sandbox system to enable customization of service plan offerings or other controls.

This invention discloses a dual-track coordinated control method for photovoltaic-storage charging stations targeting both the electricity spot market and ancillary services markets. The method first constructs a day-ahead dual-track coordinated bidding optimization model embedded with conditional risk value, simultaneously deciding on electricity volume in the spot market and capacity in the ancillary services market. It also employs a hierarchical structure combining upper-level instruction decomposition and lower-level model predictive control to achieve precise tracking of grid instructions and smooth handling of internal fluctuations. Through day-ahead risk optimization and real-time multi-objective coordinated control in a dual-track closed-loop control system, this invention significantly improves the overall profitability and operational stability of photovoltaic-storage charging stations participating in the electricity market, while simultaneously ensuring charging service quality and optimizing equipment lifespan.

The invention relates to a novel power system risk prevention method and device and a storage medium, and is applied to the technical field of power market risk protection, and the method comprises the steps: constructing a multi-dimensional risk monitoring index system covering economy, society, fairness and the like, and driving market optimization through the system; the crossing from single price limitation to systematic risk active management is realized, and the ability of the market to deal with complex uncertainty is improved; through design of collaborative constraints of electric energy, capacity, auxiliary service and green electricity markets, the relationships among the markets are straightened out, optimal configuration of various resources is promoted, and the overall market efficiency is improved; a dynamic planning and closed-loop feedback mechanism is introduced, so that market parameters (such as a price limit value and a risk weight) and an operation strategy can be dynamically adjusted according to real-time states such as supply and demand, new energy output and the like, and the adaptability of the market mechanism to the dynamic characteristics of the novel power system is remarkably enhanced.

The invention relates to a regional peak regulation auxiliary service market pricing method and device and electronic equipment, and relates to the field of power system automation control, and the method comprises the steps: carrying out the peak regulation cost calculation of conventional hydropower in multiple resources, and obtaining the unit peak regulation cost of the conventional hydropower, determining a multivariate resource price limit according to the difference between the unit peak regulation cost and the multivariate peak regulation resource transaction mechanism; preferential market clearing is carried out on conventional hydropower with corresponding price limitation, grading price limitation processing is carried out on the price of the power generation right replacement transaction, and grading clearing processing is carried out on the clearing price of the power generation right replacement transaction exceeding the grading price limitation; determining a peak regulation compensation price adapted to the multi-element resources according to the clearing price, and settling a peak regulation auxiliary service cost based on the peak regulation compensation price; and the peak regulation auxiliary service cost is allocated to the target power generation enterprise and / or the target energy storage power station. According to the scheme, the peak regulation cost of the system can be reduced, the optimal configuration efficiency in the resource area is improved, and better connection with the provincial peak regulation market price is ensured.

The invention discloses an auxiliary service optimization scheduling method applied to an electric power market environment, and relates to the technical field of electric power markets, and the main points of the technical scheme are that the method comprises the steps: constructing a unified transaction rule framework, and integrating the transaction process and the settlement mode of an electric power auxiliary service market; collecting real-time operation data of the power system and auxiliary service transaction information in the power market; market clearing is carried out based on a unified transaction rule framework; constructing an optimal scheduling model with multi-factor comprehensive consideration and solving the optimal scheduling model; and selecting an optimal scheduling scheme from the non-inferior solutions, and converting the optimal scheduling scheme into a specific scheduling instruction to be issued. According to the method, a unified transaction rule framework is constructed, the transaction process of the electric power auxiliary service market is simplified, the dynamic characteristics of the electric power system, the uncertainty of new energy power generation and the random change factors of the load are integrated into the optimal scheduling model, the actual operation condition of the electric power system can be accurately reflected, and the operation efficiency of the electric power system is improved. And the rationality and adaptability of the scheduling scheme are improved.

In some embodiments, systems and methods described here provide the ability to automatically generate scripts and optimize them for execution on a remotely managed endpoint. In some embodiments, a method includes receiving a request, optionally augmented, at a user interface of a managed service provider. The request is a request for assistive service implementing the managed service provider. The method further includes selecting generative model to respond to the request. The generative model is selected based on information of a profile of the managed service provider. The method further includes receiving, from the selected generative model, a response to the request. The response provides the assistive service implementing the managed service provider.