205 results about "Load Shedding" patented technology

The invention discloses a distributed emergency frequency control method based on multi-agent near-end strategy optimization. The method comprises the following steps: establishing a frequency response model representing frequency dynamic characteristics and physical constraints of a power system under disturbance; each emergency power support station and each low-frequency load shedding station in the power system are modeled as independent agents, a distributed multi-agent cooperative control model is constructed, each agent makes a decision based on a local observation vector, and the action output of the agent is a continuous power regulation variable. The cooperative control model has a global reward function including frequency security and control cost; performing centralized cooperative training on the cooperative control model based on a multi-agent near-end strategy optimization algorithm; on the basis of the trained strategy network of each intelligent agent, online distributed execution is carried out, in the online distributed execution process, each intelligent agent does not need to communicate with each other, each intelligent agent can obtain a better cooperative control strategy only based on local observation, and the engineering adaptability and robustness of emergency frequency control are remarkably enhanced.

Disclosed in the present application are a configuration-free and maintenance-free method and system for relay protection and fault information substations, relating to the technical field of computer platform load balancing. The method comprises: acquiring all network node information by means of a relay protection and fault information master station, and constructing a network topology diagram; marking a newly added node in the network topology diagram; establishing communication with the marked network node, and uploading the original version of all data of the marked network node to a secure area I by means of a dispatching data network; performing account configuration on a plant side relay protection and fault information substation, and downloading configuration file data to the relay protection and fault information substation; parsing a packet at the relay protection and fault information master station; and establishing a protocol library at the relay protection and fault information master station, and performing protocol conversion and data parsing on the original version packet uploaded by the newly added node. The configuration-free and maintenance-free method for relay protection and fault information substations provided by the present application allows for the data received by the relay protection and fault information master station being completely consistent with the raw data of the plant side, thereby improving the working efficiency and reducing the working cost.

A wireless transmit and receive unit (WTRU) may receive, from a network, first configuration information including a first resource identification (ID) and an indication of time and frequency resources to be used in ambient Internet of things (AIoT) access procedure. The WTRU may also receive first assistance information associated with the first resource ID. The WTRU may determine, based on the first configuration and first assistance information, first resource to be used to send a first AIoT message. The WTRU may send the first message and monitor the access occasions to determine if an overload occasion occurred. Upon overload detection, the WTRU may send, to the network, an overload indication. The WTRU may receive, from the network, second assistance information. The WTRU may determine, based on the first configuration and first and second assistance information, a second resource to be used to send a second AIoT message.

The invention discloses a reliability evaluation method for a power distribution network containing network construction type energy storage and flexible resources, and the method comprises the steps: firstly constructing a wind power and photovoltaic combined output probability distribution model considering the output uncertainty and spatial-temporal correlation of new energy, and a typical load scene; then establishing a'operation-fault 'two-state shutdown model, and generating a system operation state through sequential Monte Carlo simulation; simulating the power distribution network according to the fault information, and analyzing the power output characteristics of the constructed network type energy storage and the voltage support effect of the constructed network type energy storage on the near-area distributed new energy; and finally, constructing an optimal load shedding model considering the network-forming type energy storage power support effect, calculating the fault consequence of the system, and calculating the reliability index of the system according to the fault consequence. According to the method, the improvement effect of network construction type energy storage on the reliability of the power distribution network is analyzed; and meanwhile, the accurate reliability evaluation capability is still kept in a high-permeability scene of the distributed power supply, and a theoretical support is provided for network construction type energy storage planning investment for improving the reliability of the power distribution network.

A microgrid controller of a microgrid includes a communication interface configured to receive load information corresponding to a plurality of loads connected to the microgrid, receive energy resource information corresponding to a plurality of energy resource systems connected to the microgrid, and output control signals for controlling an operation of each energy resource system; and one or more processors configured to perform at least two dispatch operations selected from a load balance dispatch operation, an export dispatch operation, or a charge / discharge dispatch operation according to a prioritization dispatch scheme. The load balance dispatch operation, the export dispatch operation, and the charge / discharge dispatch operation are assigned different dispatch priorities that define a sequence of dispatch operations of the prioritization dispatch scheme. The plurality of energy resource systems includes energy storage systems (ESSs), unidirectional non-ESSs, and bidirectional non-ESSs.

The invention discloses an emergency control method and an emergency control system considering network construction type energy storage power fast regulation, and belongs to the technical field of power systems and automation thereof. Operation information of a tie line is collected in real time, energy storage adjustable capacity is evaluated, when it is detected that the tie line is broken due to a fault, power vacancy is calculated based on an equal-capacity cutting-off principle, and the energy storage power fast regulation is completed. For a power receiving system, network construction type energy storage is preferentially called to carry out power fast adjustment, and load removal is carried out cooperatively when the energy storage capability is insufficient; and for a power delivery system, the new energy unit with the corresponding capacity is directly cut off. Through issuing a power adjusting instruction and an emergency control instruction, energy storage is driven to execute large-step fast adjustment and self-response fine adjustment, and finally fast and stable operation of the isolated network is realized. According to the method, the problem of frequency stability when the high-proportion new energy is connected to the isolated grid for operation is effectively solved, and the toughness and the safe operation level of the high-proportion new energy connected to the grid are remarkably improved.

Methods, apparatus, systems, and articles of manufacture are disclosed to improve webservers using dynamic load balancers. An example method includes identifying a first and second data object type associated with media and with first and second data objects of the media. The example method also includes enqueuing first and second event data associated with the first and second data object in a first and second queue in first circuitry in a die of programmable circuitry. The example method further includes dequeuing the first and second event data into a third and fourth queue associated with a first and second core of the programmable circuitry, the first circuitry separate from the first core and the second core. The example method additionally includes causing the first and second core to execute a first and second computing operation based on the first and second event data in the third and fourth queues.

The invention provides an energy storage load shedding control method and device based on SOC estimation and mode self-adaption. The method comprises the steps of fault detection and demand evaluation, wherein frequency deviation is collected in real time, adjustment is triggered when the frequency deviation exceeds a threshold value, and power vacancy is calculated; sOC estimation and resource screening: predicting SOC based on a long short-term memory network, input voltage, current, temperature and the like, and screening an adjustable energy storage set; the control mode is self-adaptive, wherein tripping or power adjustment is selected according to the frequency deviation and the SOC; optimization and power distribution: taking power vacancy as a target, constructing a'minimum frequency deviation + minimum control cost 'multi-target optimization model, and solving an adjustment power or tripping instruction; and instruction execution and closed loop: issuing an instruction to execute adjustment or tripping to form a closed loop. According to the invention, the resource allocation accuracy is improved through SOC estimation; dual-mode collaborative dynamic optimization is carried out, and rigidity and flexibility are fused; the multi-objective optimization overall planning frequency stability and economical efficiency is better in response speed, resource utilization and reliability.

The invention provides a load balancing method and system for an automobile charging demand, and is applied to the field of electric data processing. According to the method, the charging load distribution information is identified and dynamically managed and controlled under the multi-layer architecture of the power distribution network, closed-loop control from load identification to model construction to risk prediction to constraint update is realized, the operation state of the charging pile and the operation constraint of the power distribution network can be sensed in real time under the condition of centralized charging of the electric vehicle, and the reliability of the system is improved. The power demand is predicted in advance, a potential risk area is identified, local feeder overload, voltage out-of-limit and electric energy quality deterioration are prevented, risk node power can be actively reduced by introducing risk upper limit judgment and protection measures, three-phase loads are balanced, and stable power supply is guaranteed.

Systems and methods for content-based routing of network traffic for distributed computing services are disclosed. A load balancing device monitors real-time network traffic data communicated to distributed computing services hosted on computing devices across multiple data centers. The load balancing device receives a user request to add a new distributed computing service, including a content map mapping service parameters to target devices. The load balancing device is configured to transmit incoming traffic requests for the new service to computing devices in either a cloud-based or on-premises data center by adding the content map to its routing configuration. Upon receiving an incoming request, the system determines if it corresponds to the new service, identifies a target device mapped to the request parameters using the content map, and transmits the request to the target device.

The application relates to the technical field of power distribution networks of power systems, and discloses a fault post-recovery control method for a power distribution network containing flexible soft switches, which comprises the following steps: after a fault occurs, the original main station converter is exited, the active power, the reactive power and the rated capacity of the remaining converters are collected to calculate the dynamic capacity margin, the electrical distance from each converter node to the load center of the system is calculated, the comprehensive score is obtained based on the capacity margin and the electrical distance weighting, the converter with the highest comprehensive score and the capacity margin greater than the preset threshold is selected as the new main station, and the control mode of the new main station is switched; the main station selection mechanism based on the comprehensive evaluation of the dynamic capacity margin and the electrical distance is used to quickly establish a stable voltage frequency reference for the power failure area, the load shedding penalty sub-target and the load hierarchical and phased recovery strategy are used to preferentially guarantee uninterrupted power supply for the first important load under the condition that the transfer supply capacity is limited, and the influence of power failure on sensitive users is effectively reduced.

The application provides a load balancing method and system for automobile charging demand, which is applied to the field of electric data processing; through identification and dynamic management and control of charging load distribution information under a multi-layer architecture of a power distribution network, the application realizes closed-loop control from "load identification-model construction-risk prediction-constraint update", can realize real-time sensing of charging pile operation state and power distribution network operation constraint under the condition of concentrated charging of electric vehicles, can predict power demand and identify potential risk areas in advance, can prevent local feeder overload, voltage out-of-limit and deterioration of power quality, and can also actively reduce power of a risk node and balance three-phase load through introduction of risk upper limit judgment and protection measures, so as to guarantee power supply stability.

This invention discloses a method and system for configuring and restoring flexible resources and mobile energy storage in a power distribution network, belonging to the field of smart power distribution network technology. Based on a typhoon wind field and wind and rain load model, this invention constructs a time-varying failure rate for power lines and uses Latin hypercube sampling to generate a set of failure scenarios. Typical scenarios are obtained through scenario reduction. Based on the failure scenarios, in the pre-disaster stage, the invention identifies the deployment locations of smart soft switches (SOPs) and mobile energy storage systems (MESSs) that minimize the sum of pre-disaster investment costs and post-disaster recovery period weighted load shedding costs. In the post-disaster stage, time-varying accessibility constraints are constructed based on road travel time preprocessing results, establishing a collaborative recovery model that includes SOP operation, network reconfiguration, and MESS time-varying scheduling. This invention, based on the collaborative configuration and post-disaster control of flexible resources and mobile energy storage, effectively reduces the configuration cost of the power distribution network while improving its support and recovery capabilities in the face of extreme disasters such as typhoons.

A load balancing and failover load routing scheme is determined including receiving business data associated with data centers. The first data center is identified as non-responsive. The customers associated with the first data center are identified. The customer resource groups are linked to the customers. The responsive data centers with available compute capacity to serve as failover targets are identified. The global rebalance table (GRT) associating the customer resource groups with the responsive data centers with available compute capacity to serve as failover targets is constructed. The optimum load balancing and failover load routing scheme is determined.

The application provides a wind farm backup frequency modulation capacity control method, a control device, a system and equipment. First, a dispatching instruction issued by a wind farm control center is received and the wind speed of each wind turbine is obtained. Then, the load shedding mode of each wind turbine is determined according to the wind speed of each wind turbine. The load shedding mode of the wind turbine with the wind speed less than a first preset threshold is an overspeed load shedding mode, and the load shedding mode of the wind turbine with the wind speed greater than a second preset threshold is a low-speed load shedding mode. The second preset threshold is greater than or equal to the first preset threshold. Meanwhile, the load shedding power of each wind turbine is determined according to the wind speed of each wind turbine and the dispatching load shedding power indicated by the dispatching instruction. Finally, the load shedding of each wind turbine is realized according to the load shedding mode and the load shedding power of each wind turbine. By matching the low-speed load shedding mode for the high-speed wind turbine, compared with the variable pitch control of the prior art, the response speed can be improved, the wind turbine can be quickly adjusted to the backup capacity, and therefore the practicability of the control strategy is improved.

The invention relates to the technical field of load adjustment, in particular to a high-proportion renewable energy power system operation state evaluation method. The method comprises the following steps: analyzing and extracting dominant voltage-reactive sensitivity by using random sampling consistency regression, generating a positive correlation indication bit through sensitivity polarity, analyzing differential fluctuation characteristics of a fitting deviation sequence, and determining an impedance characteristic weight; and correcting the periodic active sequence in combination with the impedance characteristic weight to obtain an active income value, and introducing a risk penalty term based on voltage urgency to obtain an effective load shedding value to generate a load shedding control strategy. According to the method, the decoupling identification model based on the voltage-reactive micro-response mechanism is constructed, so that accurate evaluation of the feeder line source load attributes is realized, the identification robustness is improved, and the safety and the accuracy of emergency control of the power system are improved.

The invention discloses an elastic electric power system operation method and an elastic electric power system.The elastic electric power system operation method for resisting vehicle charging disturbance comprises the following steps that 1, node loads are divided into basic loads and electric vehicle charging loads, respectively establishing removal loss influence evaluation models of the basic load and the electric vehicle charging load; the cut-off loss of the charging load of the electric vehicle comprises instant loss and subsequent loss; step 2, based on the optimal power flow problem model, designing and setting a target function by taking the minimum load shedding loss as a target; 3, a mixed dragonfly-particle swarm optimization algorithm is adopted for solving, and a load removal scheme is obtained; the method has the advantages of being fast in solving and small in influence caused by load shedding.

The invention provides an optimization control method considering the safety and stability of a power grid, and relates to the technical field of power system dispatching operation control, and the method comprises the steps: building a voltage stability prediction model based on a time sequence convolution residual network, inputting the voltage time sequence data of a sensitive node of the power grid into the voltage stability prediction model, and outputting a voltage stability evaluation quantitative index; based on the voltage stability evaluation quantitative index, taking the minimum total capacity of generator tripping and load shedding as an objective function, and constructing a voltage stability control model containing voltage stability constraint and power balance constraint; solving the voltage stability control model by adopting a pelican optimization algorithm, and outputting an optimal control strategy; according to the optimization control method considering the safety and stability of the power grid, the prediction precision and control efficiency of the power grid in a complex scene can be improved, and safe and stable operation of a power grid system is guaranteed.

A system for adaptive electrical load balancing and phase balancing in a multi-node power grid, the system comprising: a plurality of electrical nodes interconnected via a multi-phase power distribution network, each electrical node comprising a sensor unit configured to measure electrical parameters such as phase voltage, phase current, phase angle, and power factor; an analog-to-digital converter unit coupled to the sensor unit and configured to convert measured electrical parameters into digital signals; a processing unit operationally coupled to the analog-to-digital converter unit and configured to determine the load distribution characteristics and phase imbalance states across the plurality of electrical nodes;a switching unit with a plurality of controllable switching elements arranged such that electrical loads can be selectively connected to different phases and nodes; and a communication unit configured to send and receive data between the numerous electrical nodes and at least one processing unit, the processing unit being configured to generate control signals based on the determined load distribution characteristics and phase imbalance conditions to actuate the switching unit to redistribute electrical loads across phases and nodes in order to achieve a balanced phase load.

This invention relates to the field of power system fault quantification technology, and discloses a method, system, equipment, and medium for quantifying distribution network line faults under typhoon weather. It calculates the wind-induced fault rate of distribution network lines by constructing a wind field correction model that incorporates micro-topography correction factors and wind direction-line angle correction factors. With the goal of minimizing power outage losses in the distribution network, a coupled influence model of transmission network faults on the distribution network line fault rate is constructed and solved to obtain the optimal load shedding amount for each load node in the distribution network and its corresponding operational constraint boundary. Under this boundary, the random process of load shedding allocation and load transfer of faulty lines within the distribution network is simulated using a double Monte Carlo sampling method, and the probability of line cascading faults caused by transmission-distribution coupling is calculated based on the simulation results. The combined time-varying fault rate and type of distribution network lines are determined by integrating the two fault rates, achieving accurate quantification of distribution network line faults under the influence of transmission-distribution coupling.

Systems and methods for providing a seamless automatic repeat request (ARQ) stream are provided. The system can include a plurality of streaming servers, a load balancer, and an ARQ streaming service.

The embodiment of the invention relates to a system and a method for load balancing business based on flow attributes and intentions. A system for load balancing traffic based on flow attributes and intent may include at least one storage device and / or circuitry. In this example, a storage device may be configured to store data identifying a set of load balancing options available for network traffic. Additionally or alternatively, the circuitry may be configured to (1) identify a set of attributes for packets corresponding to the traffic flow, (2) determine an intent of the traffic flow based at least in part on the set of attributes, and (3) assign load balancing options included in a set of load balancing options to the traffic flow based at least in part on the intent and the set of attributes. Various other devices, systems, and methods are also disclosed.

Proliferation of edge devices has significantly advanced technologies in sectors such as autonomous driving and surveillance. However, deploying machine learning models on these resource-constrained devices presents challenges including scalability and managing unpredictable workloads thereby affecting real-time performance in edge-only environments. The present disclosure discloses a method and system for workload deployment in a content guided and service level agreement (SLA) aware edge-cloud architecture. In the present disclosure, a camera feed content-guided load balancing technique is provided that dynamically manages workloads between edge and cloud. Features are extracted from an incoming camera feed to perform load-balancing process efficiently. The load balancer determines a maximum number of concurrent feeds for processing at the edge, with the remaining feeds handled by the cloud based on content of the incoming camera feed. Additionally, a cost model to estimate expenses of deploying the edge-cloud architecture in real-world scenarios with dynamic workloads is provided.

The invention discloses a novel power system operation risk assessment method considering source load space-time distribution in extreme weather, and relates to the technical field of power system risk assessment, comprising the following steps: constructing a sensitivity model of meteorological sensitive source loads to generate source load coupling characteristics; based on historical meteorological data, calculating a spatial correlation matrix of a meteorological prediction mean vector and a regional meteorological variable, and combining the spatial correlation matrix to generate a time-space characteristic meteorological scene; calculating a scene probability based on the meteorological scene and a preset meteorological feature threshold; establishing an operation cost target optimization function containing a safety margin penalty term, establishing a power grid safety constraint based on a source-load coupling characteristic, and solving the target optimization function to obtain a scheduling decision variable; and calculating risk assessment indexes based on the scheduling decision variable and the scene probability, wherein the risk assessment indexes comprise a load shedding risk, a line out-of-limit risk, a wind abandoning risk and a light abandoning risk. The method is used for solving the problem that existing risk assessment is difficult to consider influence on extreme weather space-time characteristics and source-load coupling.

The invention belongs to the technical field of industrial internet and distributed time sequence data management, and discloses an industrial internet distributed power time sequence database. The database is composed of a time sequence data acquisition unit, a dynamic partition storage unit, a node load balance scheduling unit, a multi-stage data consistency maintenance unit, a time sequence perception index construction unit, a data compression and time sequence aggregation unit, an asynchronous data recovery and fault switching unit and a query optimization and result cache unit. According to the method, a dynamic sliding partition algorithm is designed, and real-time partition adjustment of the data in the time dimension is achieved according to the characteristic of continuous high-frequency writing of the power time sequence data; the system can dynamically slide the partition boundary according to the current data writing rate and the node load state, data is prevented from being continuously and intensively written into a certain single area, and node writing inclination and local hot spot phenomena are remarkably reduced.

The application provides an evaluation method based on an operation reliability intelligent evaluation model and related devices. System data of a power system is obtained, and after a minimum load shedding model is established according to the system data of the power system, the inherent mode of the minimum load shedding model is determined, and a robust learning loss function is constructed based on the inherent mode of the minimum load shedding model. Finally, strong generalization learning is performed according to the minimum load shedding neural network, the robust learning loss function and load disturbance, and an operation reliability intelligent evaluation model is obtained. The system data of the power system is input into the operation reliability intelligent evaluation model, and a result capable of evaluating the operation reliability of the system can be obtained, effectively improving the efficiency and accuracy of the evaluation result.

The invention provides a new energy power system reliability evaluation method based on environment variables, and relates to the technical field of power systems. According to the method, a non-parametric self-adaptive quantile regression forest model is adopted to perform modeling on wind speed and sunlight intensity, and online incremental updating is triggered based on Kolmogorov-Smirnov statistics; setting a cross-scale state coupling interface layer in the double-layer nested reliability evaluation architecture, defining a shared state vector including an energy storage charge state, an equipment aging index and an available reserve capacity, and applying Lyapunov stability constraint; a period economic value dynamic pricing module based on Q-learning is integrated in a short-term evaluation layer, and a real-time electricity price, a user interruption contract and a load elastic coefficient are used as state spaces to correct a load shedding strategy. According to the scheme, through adaptive modeling of environment variable distribution and cross-scale state stable transmission, the problem of evaluation result lag is effectively solved, and the real-time performance and economical efficiency of reliability evaluation are improved.

The application discloses a power grid key line comprehensive identification method based on a maximum deviation thought. Based on power grid structure information, combined with current operation state, four line key evaluation indexes of voltage stability, capacity margin, real-time failure rate and topological contact degree are established; based on the maximum deviation thought, a line comprehensive importance identification method considering subjective and objective weighting of different factors is proposed; a power supply capacity evaluation method of the system under line fault is proposed by adopting a control strategy of minimum load shedding amount of system optimal power flow, and it is verified that the identified lines are high-risk lines which will have a key influence on system operation. In the identification of the power grid key line, the application fully considers node voltage, line load, line fault, network topology and other information, considers the special situation of power grid splitting to form an island, excavates the information carried by the identification indexes, improves the identification accuracy of the power grid key line, and has guiding significance for the operation and maintenance management of the power transmission line.

The invention relates to the technical field of energy storage, in particular to an energy optimization control method, system, equipment and medium for a compressed air energy storage system in a load shedding stage, which monitors the running state of a unit in real time, presets a running strategy, detects a load shedding event of the unit, acquires splitting duration information of the unit with the load shedding event, and sends the splitting duration information to a server. Based on the splitting duration information, air quality consumption of preset operation strategies is obtained through a first-level algorithm and a second-level algorithm, a first threshold value and a second threshold value are determined according to the air consumption quality obtained through calculation, and strategy selection is conducted in the preset operation strategies according to the splitting duration information, the first threshold value and the second threshold value. According to the method, the selection strategy is executed, operation of the unit is controlled, the traditional operation mode of single strategy and experience judgment is changed, the system can automatically select the most economical operation scheme according to the actual working condition, and the problem that the operation efficiency is low due to the fact that the splitting time is not considered under the load shedding working condition of an existing CAES system is solved.

This disclosure relates to a method and system for assessing frequency regulation demand capacity based on Vine Copula and a spatiotemporal graph network. The method includes: acquiring historical power and prediction error data of multi-dimensional source-load nodes in the power system to generate a typical power deficit scenario set; transforming the power system into a graph data structure, constructing and training a graph neural network-long short-term memory network spatiotemporal proxy model; integrating dynamic load shedding mechanisms and virtual synchronization control, and combining the prediction and verification results of the maximum frequency change rate and the minimum maximum frequency drop of each node by the graph neural network-long short-term memory network spatiotemporal proxy model to establish a dynamic frequency safety boundary; and based on the dynamic frequency safety boundary and the typical power deficit scenario set, establishing a two-stage sub-Bluerstein bar optimization model based on Wasserstein distance to solve and determine the optimal frequency regulation demand capacity configuration scheme for each node in the system.