113 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 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 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.

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.

The application discloses a kind of climbing auxiliary service demand price curve drawing method, device and storage medium, wherein method includes: obtaining the system net load value of preset scheduling interval, system net load value includes system net load forecast value and system net load measured value;System net load value is classified as the typical day data set of different time periods;Calculate the system net load error of each scheduling interval, obtain the system net load error set corresponding to different time periods;According to system net load error set, the frequency of system net load prediction error in different error intervals is counted, and the error frequency of frequency relative to the data quantity in the system net load error set of current period is calculated;According to error frequency, probability density distribution histogram is drawn, and the climbing auxiliary service demand price curve of each period is drawn.The present application can comprehensively reflect electric energy cost and climbing auxiliary service benefit, and provide effective data support for building climbing auxiliary service market.

The invention discloses a dynamic combination method and system for participation of a user group in an auxiliary service market, and a medium, and the method comprises the steps: solving an optimal adjustable power curve of the user group according to the adjustable power level, the duration time and the fluctuation rate with the comprehensive dynamic adjustment characteristic index of the maximum user group as a target, and obtaining the optimal adjustable power curve of the user group; a hierarchical matching user group dynamic combination strategy is adopted, an outer layer is matched with an optimal adjustable power curve of a pair to a user group, and a set pair with the strongest complementarity is screened out through complementary coefficient calculation; in the inner layer matching, a pairwise combination result of user groups in a set is obtained by calculating a complementary coefficient between individuals. Through pairwise dynamic combination of the user groups, the dynamic adjustment characteristics of the combined user groups are effectively improved, so that the user groups can play a greater role while obtaining greater benefits in an auxiliary service market.

The invention provides an optimal scheduling method for a wind power and pumped storage combined operation system. The method comprises the following steps: solving a decision model based on a real-time data set and a risk preference coefficient to obtain a decision value set comprising an electric energy market standard, a frequency modulation capacity standard and a frequency modulation mileage standard of a power generation monomer, and scheduling the combined operation system; the objective function of the decision model aims at minimizing the total electricity purchase cost of the electric energy market and the frequency modulation auxiliary service market; the decision-making model is based on a historical data set, and the power market model and the joint operation system model are constructed by adopting multi-agent reinforcement learning and a deep neural network. The method is high in dynamic adaptability and robustness, facilitates improvement of declaration efficiency and result accuracy of the power market, can achieve collaborative scheduling of various energy sources, improves system stability, equipment utilization rate and energy utilization rate, reduces power generation cost and improves power generation benefits. And meanwhile, the coping capacity and the anti-risk capacity of the system for sudden load increase are improved.

The invention discloses a novel power system inertia auxiliary service acquisition method. The method comprises the following steps: step 1, carrying out day-ahead electric energy market pre-clearing; step 2, performing system frequency security check; step 3, calculating inertia vacancy required by the frequency safety of the system for a time period in which the frequency safety is not satisfied; step 4, performing optimization acquisition of inertia auxiliary service, and determining a conventional unit needing to be added and an inertia clearing price; step 5, carrying out day-ahead electric energy market formal clearing, and carrying out day-ahead electric energy market clearing optimization calculation under the determined startup mode; 6, based on the inertia clearing price, all the units providing the inertia are settled; the technical problem of obtaining inertia auxiliary service for maintaining safety and stability of a power grid under the condition of large disturbance is solved.

The application relates to the field of power systems, and particularly discloses a dispatching operation method for new energy power stations with energy storage participating in a frequency modulation auxiliary service market, which comprises the following steps: inputting the output values of each new energy power station with energy storage in the days to be aggregated into a trained day-ahead output prediction model, generating the predicted output values of each new energy power station in each day, reducing the day scenarios by using a probability reduction method, and obtaining the occurrence probabilities of multiple typical days; based on the occurrence probabilities of the multiple typical days and the predicted output values of each new energy power station in the multiple typical days, using a particle swarm algorithm, taking the dispatching operation revenue of the alliance structure as the fitness value, optimizing the initialized multiple alliance structures, obtaining a target alliance structure, and outputting the capacity of each new energy power station in each alliance in the target alliance structure allocated to the frequency modulation auxiliary service market and the electric energy market in each typical day. The application can not only improve the energy storage utilization rate of new energy, but also improve the power supply quality of the power grid.

The application discloses a new energy output control method and system considering VPP providing multiple types of auxiliary services, relates to the technical field of power distribution network dispatching, and comprises the following steps: receiving historical data of PV and WT output power, obtaining expectation and variance of PV and WT prediction errors, and generating a fuzzy set containing moment information according to the expectation and variance of the PV and WT prediction errors; inputting the fuzzy set containing moment information into a pre-established new energy output control model considering VPP providing multiple types of auxiliary services, generating a new energy output control model considering VPP providing multiple types of auxiliary services under uncertainty based on affine theory and by selecting the safe operation constraint of the power distribution network as a distributed robust opportunity constraint; receiving various types of power commodity price data and supply-demand relationships of various types of power commodities, inputting the various types of power commodity price data and the supply-demand relationships of various types of power commodities into the new energy output control model considering VPP providing multiple types of auxiliary services under uncertainty, and outputting to obtain a multiple types of power commodity clearing result.

The invention discloses an internal income comprehensive distribution method, system and device capable of adjusting load after large-scale aggregation and a storage medium, and relates to the technical field of energy optimization scheduling and energy management, and the method comprises the steps: constructing a comprehensive contribution index system based on safety, economy and risk indexes; outputting the comprehensive contribution degree of each load resource according to the comprehensive contribution degree index system by adopting a comprehensive evaluation method fusing TOPSIS, grey correlation and an entropy weight method; creating an energy-auxiliary service market joint income model, and quantifying the value contribution of the adjustable load polymer; and according to the comprehensive contribution degree of each load resource and the energy-auxiliary service market joint income model, performing internal income distribution by using a double-layer settlement framework of fixed protocol electricity price and contribution degree assessment. According to the method, a comprehensive contribution degree model based on safety, economy and risk indexes is constructed, TOPSIS grey correlation and an entropy weight method are fused, and accurate quantification and fair distribution of load resource values are achieved.

The invention discloses a new energy power system frequency modulation auxiliary service scheduling method and a new energy power system frequency modulation auxiliary service scheduling system, and belongs to the technical field of power systems. Calculating and determining a new energy power system scheduling scheme according to the new energy power system load, the new energy output, the system frequency modulation service demand and the new energy power system scheduling model; wherein the system operation cost comprises power generation cost and frequency modulation auxiliary service cost, and the frequency modulation auxiliary service cost is calculated and determined according to frequency modulation auxiliary service capacity provided by a generator; the system frequency modulation auxiliary service vacancy is calculated and determined according to the system frequency modulation service requirement and the frequency modulation auxiliary service capacity provided by the generator. The finally determined electric power system scheduling scheme can ensure stable and economical operation of the electric power system, and the technical problem that the optimal electric power scheduling scheme cannot be determined by a traditional method is solved.

The present application relates to a kind of industrial user resource aggregation scheduling method driven by energy efficiency fingerprint, first by improving K-means algorithm, realize the accurate extraction and dynamic update of industrial user electricity energy efficiency fingerprint, then, by constructing energy efficiency fingerprint-price response elastic coupling model, quantification user price response sensitivity, realize the generation of time-sharing energy efficiency optimization strategy, to abandon traditional scheduling "one size fits all" mode;Afterwards, establish resource attribute database and resource service capability evaluation model, quantify the ability of various resources to participate in grid frequency modulation, standby auxiliary service, finally, introduce multi-objective optimization and closed-loop feedback mechanism, consider the constraint of cost, carbon emission, response speed comprehensively, realize the dynamic iterative optimization of scheduling strategy, and through the simulation verification of fusion digital twin technology, the theoretical optimization scheme is converted into implementable implementation strategy, provides complete technical scheme for industrial user;The present application has the advantages of accurate and efficient, stable and strong adaptive.

The application discloses a user-side energy storage participating auxiliary service method and belongs to the technical field of power system dispatching control. The method comprises the following steps: performing load prediction on a prediction day by adopting a pre-constructed load prediction clustering method to obtain a load prediction value of each adjustable resource; adopting a pre-constructed user-side energy storage physical-behavior model to calculate the adjustment cost of each adjustable resource on the prediction day, and then obtaining the willingness of the user to participate in power grid aggregation; and according to the adjustment cost of each adjustable resource, the willingness of the user to participate in power grid aggregation, the load prediction value of each adjustable resource and pre-acquired auxiliary service transaction announcement information, the adjustable resource participating in peak shaving auxiliary service is declared in quantity and price with the target of maximizing the user benefits. The method can improve the power grid asset utilization rate, delay or reduce the power grid investment, and can also create additional economic value for the user-side energy storage.

The application discloses a kind of regional backup auxiliary service transaction method and system, the method includes calculating the next day backup capacity margin reference value of provincial power grid, and is issued to each provincial power grid dispatching agency;Complete tie-line day-ahead plan update and issue, and publish day-ahead backup market clearing result to market subject;After rationality and safety check to day-ahead unit saleable capacity, form the next day whole network intra-day available up-regulating unit sequence, and publish the next day intra-day backup price index and whole network next day intra-day available up-regulating unit sequence to market subject;Receive the intra-day initial generation plan cycle of provincial power grid reported rolling;Complete tie-line intra-day plan update and issue, and publish intra-day backup market clearing result to market subject, the application establishes marketized backup auxiliary service inter-provincial regulation mechanism, gives full play to the decisive role of market in resource allocation, and comprehensively improves the power security guarantee capability of regional power grid.