14 results about "Ancillary service" patented technology

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.

This invention discloses a master-slave game optimization method for differentiated service combinations in shared energy storage, taking into account the flexible adjustment capabilities of resources. Shared energy storage clusters are suitable for providing capacity leasing services, electricity retail services, and frequency regulation ancillary services. The method includes: constructing an upper-level model with the goal of maximizing the total revenue of the shared energy storage cluster; constructing a lower-level model with the goal of minimizing the energy consumption costs of energy storage users; obtaining a two-layer master-slave game optimization model based on the upper and lower-level models; and solving the two-layer master-slave game optimization model to determine the optimal service price of the shared energy storage cluster and the optimal energy consumption strategy for energy storage users. This invention enables shared energy storage operators to design a scientific and reasonable pricing mechanism, improving the revenue of shared energy storage while reducing the energy consumption costs for users.

This application discloses a method, system, equipment, medium, and product for peak shaving and scheduling of electric vehicles (EVs), relating to the field of power system and grid integration and interaction. The method includes: acquiring key factors of the regional power grid; constructing a multi-objective optimization scheduling model based on these key factors, with objectives of maximizing the charging and discharging benefits for EV users, maximizing the ancillary service benefits for charging and discharging stations, and minimizing the charging and discharging time of EV clusters; constructing an objective function for EV charging and discharging optimization scheduling based on the multi-objective optimization scheduling model; and solving the objective function for EV charging and discharging optimization scheduling using a particle swarm optimization algorithm to obtain the optimal scheduling scheme for EV clusters. This application improves the effectiveness of EVs participating in grid peak shaving and valley filling by using a particle swarm optimization algorithm to solve the objective function for EV charging and discharging optimization scheduling and obtaining the optimal scheduling scheme for EV clusters.

A power auxiliary service providing method and system considering new energy prediction error. The method calculates the total cost of frequency modulation auxiliary service based on the clearing price and the winning capacity of the frequency modulation in the thermal power unit, calculates the allocated frequency modulation auxiliary service fee of the power generation side and the user side based on the total cost of the frequency modulation auxiliary service and the on-grid power of the power generation side and the user side, calculates the allocated peak shaving auxiliary service fee and the allocated standby auxiliary service fee of the power generation side and the user side based on the power correction coefficient, constructs a characteristic function based on the prediction error, quantifies the excess function according to the characteristic function, solves the excess function by using the kernel method, and forms a new energy auxiliary service fee allocation scheme. The scheme improves the fairness, accuracy and stability of the power auxiliary service fee allocation mechanism.

This invention proposes an intelligent analysis and regulation system for hydropower ancillary services in the electricity market. The system includes: acquiring real-time electricity price signals, system frequency data, and hydropower unit operating status data; cleaning, time-aligning, standardizing, and extracting features from the collected multi-source data to generate a standardized dataset suitable for market signal analysis; establishing a market signal-driven quantity-price synergistic optimization model based on the standardized dataset and preset regulation performance indicators, and generating time-segmented regulation strategies; executing open-loop regulation operations according to the regulation strategies, and dynamically adjusting model parameters through a strategy effect evaluation module to achieve synergistic optimization of regulation capacity and economic benefits. This system enables quantity-price synergistic optimization control of non-frequency-regulating power plants under all operating conditions, improving the regulation response capability and ancillary service economic benefits of hydropower units in the electricity market.

This application relates to a method, system, device, and medium for evaluating the profit and loss of medium- and long-term electricity transactions based on spot market rules. The method generates a structured sequence of computational tasks by parsing the electricity spot market settlement rules and constructing a directed acyclic computational graph, transforming complex settlement rules into a differentiable dependency network. It performs forward propagation, calculating and storing intermediate values ​​node by node to obtain the total profit and loss value relative to the benchmark electricity purchase cost. Based on the stored intermediate values, it performs automatic differential backward propagation in a reverse mode, calculating gradients node by node to form a gradient table. Based on the gradient table, it generates multi-level attribution results at the input variable level and intermediate rule level. This method combines automatic differentiation with rule graph modeling, penetrating deviation assessments of nonlinear coupled rules such as tiered pricing and ancillary service allocation, accurately quantifying the marginal contribution of any variable or parameter change to profit and loss, and providing a refined and interpretable quantitative basis for trading decisions.

The application discloses a day-ahead electric energy and reserve auxiliary service joint clearing method, comprising the following steps: obtaining parameter data; inputting the parameter data into a pre-constructed robust optimization model considering net load uncertainty to obtain an optimal clearing scheme under the worst scenario; wherein, the robust optimization model is constructed based on a risk cost model and a day-ahead electric energy and reserve market joint clearing model; the risk cost model comprises an upper reserve risk cost model considering unit fault and net load prediction error, and a lower reserve risk cost model considering load unplanned exit and net load prediction error; the day-ahead electric energy and reserve market joint clearing model is constructed with the minimum system operation cost as the target. The application can find the optimal clearing scheme under the worst scenario in the system for market decision makers, and provides a more perfect reference decision for market resistance to the risk of uncertainty.

This invention discloses a method and system for bidirectional energy interaction and multi-period regulation of electric vehicle aggregators (EVs) for ancillary services, relating to the fields of smart grid and electric vehicle aggregator operation optimization technology. The method includes: calculating the energy and power feasible domain boundaries of the EV cluster within the scheduling cycle based on the framework of EV aggregator (EVA) participation in ancillary services; establishing a user willingness discrimination model to determine the probability of EV users' willingness to participate in regulation; combining charging demand response strategy (CBDR) and discharging demand response strategy (DBDR) to determine the user participation ratio; constructing an optimization model with maximizing the operating revenue of EV aggregators as the objective function; and obtaining the optimal charging and discharging scheduling scheme by solving this optimization model. This method employs a composite strategy when the EV access scale expands, helping to improve regulation capacity and user acceptance, and enhancing the stability of revenue.

This invention discloses a multi-zone power control and separate performance calculation energy storage management system, specifically relating to the field of grid ancillary services technology. It includes: a physical energy storage unit; a multi-zone power controller, used to receive power control commands from at least two different grid zones and dynamically divide the total power into logical virtual zones corresponding to each zone, and independently control each virtual zone; a zone performance calculator, used to collect real-time grid status data for each zone and response data for each virtual zone, independently calculate ancillary service performance indicators for each virtual zone, and generate a calculation report; and a dynamic coordination optimizer, used to receive performance indicators and dynamically adjust control parameters to form closed-loop optimization control. This invention achieves independent and precise power control across zones and separate calculation of service performance for each zone, solving the problems of power coupling and coarse calculation in multi-zone scenarios.

The invention belongs to the technical field of peak regulation auxiliary service market clearing, and particularly relates to a virtual power plant transaction auxiliary decision-making method and system oriented to an auxiliary peak regulation market. The method comprises the following steps: establishing a peak regulation auxiliary market clearing model by taking the minimum sum of the total cost of a virtual power plant and the total cost of a generator set as a target; the virtual power plant bidding constraint, the generator set constraint and the power grid constraint serve as constraint conditions of the clearing model, the peak regulation auxiliary market clearing model is solved, and clearing prices of all nodes of the peak regulation auxiliary service market in all time periods are obtained; wherein the virtual power plant bidding constraint is established according to the energy constraint and the power constraint of the virtual power plant, and the energy constraint comprises the constraints of the upper and lower limits of the energy state and the energy loss, so that the problem that the actual output of the virtual power plant has a certain error and uncertainty is solved; the method reduces the deviation of the clearing price during the peak regulation auxiliary market transaction of the electric power system, and achieves the optimal income of the virtual power plant while guaranteeing the minimum total cost of the electric power market.

An example method for assisted services, the method performed by a coordination device and comprising: determining a need for a service that uses network coordination; identifying a first mobile edge device for providing the service, wherein the first mobile edge device is associated with a first vehicle and communicatively coupled with a network, and wherein providing the service includes sharing device resources of an edge device associated with the vehicle for assisted edge computing; determining a configuration for the first mobile edge device to provide the service in response to the first mobile edge device being able to provide the service; and transmitting the configuration to the first mobile edge device for providing the service.

This invention discloses a market-based incentive method for distributed resource safety regulation in distribution systems. The method includes: real-time safety monitoring using a safety domain; triggering safety warnings or alarms based on the safety distance of operating points; the distribution system operator (DSO) determining safety requirements; safety warnings or alarms driving the Distribution Safety Ancillary Services Market (DSSASM), i.e., a market where the DSO purchases safety regulation ancillary services from distributed resource providers (DERs) to address distribution network safety issues; the DSO broadcasts safety regulation guidance information and a safety premium, which is an additional incentive fee paid by the DSO to the DERs for addressing safety issues, in addition to compensating for regulation costs; DERs submitting their bidding regulation power and prices; and, taking into account the DER regulation effect, market clearing to obtain DER safety regulation solutions, minimizing the total cost for the DSO to solve safety issues. This invention achieves accurate identification of safety issues, differentiated incentives for DERs, and clearing considering the DER regulation effect, ultimately yielding DER safety regulation solutions to address safety issues.

The application discloses a real-time demand response method based on flexible resource adjustable control capability evaluation, comprising the following steps: 1, a new type of distribution system interactive collaborative operation framework considering the participation of demand flexible resources in regulation and control is constructed, wherein a real-time response demand is issued by a distribution network operator, and a production and sales aggregator with multiple flexible resources responds to the task in real time; 2, a flexible resource adjustable control capability evaluation method participating in system collaborative interaction demand is proposed, including the adjustable control capability of multiple flexible resources in time and power; 3, according to the collected adjustable control capability data of the flexible resources, the auxiliary service price of the demand response is designed, and the response task of each aggregator is optimized. The application solves the real-time demand response problem based on multiple models under the new type of distribution system interactive collaborative operation framework, and achieves the purposes of peak load shifting and reducing the overall operation cost of the system.

This invention discloses a multi-mode configuration method for residential air conditioning loads accommodating various ancillary service needs, comprising: constructing a matching mapping relationship between differentiated control modes and ancillary service types; establishing a residential user participation willingness response model based on incentive prices; constructing a physical aggregated power calculation model for residential air conditioning loads under multiple modes; correcting the theoretical aggregated power range to generate a reliable aggregated power range for air conditioning loads; and constructing and solving a collaborative configuration optimization model that balances reliability and economy based on the matching mapping relationship, the residential user participation willingness response model, and the reliable aggregated power range for air conditioning loads, outputting the optimal resource allocation scheme. This invention can differentiate and optimize the configuration combination of three modes—intelligent control switch, intelligent thermostat, and non-intrusive reminder—according to different needs of secondary frequency regulation, peak shaving, and spinning reserve, minimizing system operating costs while ensuring aggregated reliability.