24 results about "Load profile" patented technology

This application relates to a method, apparatus, device, and computer-readable medium for dynamic garbage data recycling. The method includes: collecting operating parameters of a distributed object storage cluster and submitting these parameters to an analysis cluster; constructing dynamic load profiles of multiple storage buckets in the distributed object storage cluster based on the operating parameters in the analysis cluster; generating corresponding dynamic recycling strategies for each storage bucket according to its dynamic load profile; and recycling garbage data from each storage bucket according to the dynamic recycling strategies. This application constructs dynamic load profiles of storage buckets based on the collected operating parameters, achieving real-time perception and accurate characterization of the cluster's load status. This allows for the generation of targeted dynamic recycling strategies adapted to the load characteristics of each storage bucket, replacing the traditional static threshold triggering mechanism. This avoids resource contention during peak business periods and solves the technical problem that the static threshold triggering mechanism for garbage data recycling cannot adapt to dynamic load changes, leading to system performance degradation.

The invention relates to a method for detecting a dangerous posture of a first person in a means of transport and issuing a recommendation for action taking into account the detected dangerous posture, a device for carrying out such a method, and a means of transport. The method comprises the following steps: determining initial sensor values ​​using the first load-sensitive sensor, deriving a first load profile from the initial sensor values, determining the current posture of the first person based on the first load profile, determining a dangerous posture of the first person based on the current posture of the first person, determining a recommendation for action to avoid the detected dangerous posture, and issuing a second signal representing the determined recommendation for action.

A procedure for operating an electrical energy system in a building includes a step for collecting a variety of consumption data on the electrical active energy drawn. This active energy is drawn from the public electricity grid and / or from existing energy generators within the building's energy system via a grid connection point. A load profile is determined based on the consumption data. This load profile describes the expected or historical trend of the active energy drawn over a given period. A backup generator for generating and / or supplying electrical energy is then selected based on the load profile. The backup generator is intended to operate instead of, or in addition to, existing energy generators within the building's energy system and / or to reduce the amount of active energy drawn from the public grid.

The present invention relates to a computer-implemented method and apparatus for determining a load profile of a building and / or an industrial facility. The apparatus includes at least one interface circuit configured to receive first data indicative of a geographic location and static information about structural conditions and usage of the building and / or industrial facility, and to receive second data indicative of a weather profile of the indicated geographic location. Further, the apparatus includes processing circuitry configured to determine a load profile of the building and / or industrial facility based on the first data and the second data. Furthermore, the invention relates to the use of such a load profile, a computer program and a computer readable medium.

This invention relates to the field of automatic management technology for ship power plants, specifically to an automatic management system and method for ship power plants based on load prediction. The system includes a load prediction module that receives multi-source data acquired by a data acquisition and fusion module and outputs a predicted load curve for the ship using a pre-trained load prediction model. An optimization decision module dynamically calculates the ship's safety margin based on the predicted load curve obtained by the load prediction module and dynamically generates start-up, shutdown, paralleling, and disconnection control commands for the ship's generator sets. By predicting the future load curve of the ship, this invention can start standby generator sets in advance before the predicted overload risk point, ensuring that paralleling and load transfer are completed before the peak load arrives. This effectively avoids the risk of overload tripping due to generator start-up delays and greatly enhances the robustness of the ship power plant.

The present application belongs to the technical field of non-vehicle charger efficiency testing, and discloses an intelligent program-controlled analog load system, a non-vehicle charger dynamic efficiency testing method, equipment and a medium to solve the problem of testability. The system comprises, connected in turn: a charging behavior portrait modeling module, which clusters high-dimensional charging behavior data based on a SOM network to generate multiple charging behavior portrait categories; a dynamic load simulation module, which generates a corresponding dynamic load curve for each charging behavior portrait category based on GAN and LSTM; a multi-modal load fusion module, which performs collaborative weighted fusion on the dynamic load curves corresponding to each charging behavior portrait category based on the Shapley value in the cooperative game theory to generate a comprehensive multi-modal load curve; and an intelligent program-controlled load generation module, which converts the multi-modal load curve into a power electronic load signal based on power electronic technology and outputs the signal to a power device to generate a physical load.

The present disclosure generally relates to an electronic control unit (ECU) for a vehicle, specifically adapted for controlling a transition between and active and an inactive state in case a thereto-connected electrically controllable vehicle component is operating outside an individualized and predefined load profile. The present disclosure also relates to a method for operating such an electrical control unit and to a corresponding computer program product.

An example discrete, time-domain computational method finds optimal power resources in a microgrid for reliability and resilience. The method involves receiving, by an input module, inputs including microgrid parameters, control conditions, natural resource datasets, and a load profile for the microgrid. The method forecasts, by a forecasting module based on the inputs, forecasted values for a plurality of power grid outcomes related to reliability and resilience, to inform power resource investment decisions. The method generates, by a forecasted results generator, a results report including the forecasted values. The results report is readable by several stakeholders, including Military installations, remote communities, campuses, and institutions.

A system (100) for determining a load profile of an actuator (124) for elastography. The system (100) is configured to generate an actuator driving waveform by modifying a primary driving waveform with an interrogation signal, apply the actuator driving waveform to the actuator (124), determine a first value of a component of an electrical characteristic, determine a second value of the component of the electrical characteristic, and determine the load profile of the actuator (124) based on the first value and second value of the component of the electrical characteristic, the load profile relating values of the component of the electrical characteristic to values of the mechanical load on the actuator (124). The load profile is used to determine a load which is used to adapt signals applied to the actuator.

The invention relates to the technical field of electrical engineering, and discloses an active power distribution network optimization control method, system and device of an integrated data center and a medium. The method comprises the following steps: analyzing space-time transfer characteristics of a data center response load, and constructing a space-time two-dimensional load transfer model; extracting time-delay sensitive and tolerant loads; an optimization control strategy is designed in combination with the server utilization rate, the time-of-use electricity price and the renewable energy source output; and generating an optimized response load curve and introducing a system comprehensive operation cost constraint to realize active management of a response load peak-valley difference. The renewable energy consumption level can be effectively improved, the system operation cost is reduced, the load fluctuation is smoothed, and the power grid operation stability and economy are enhanced.

The invention relates to the technical field of computing power center cold source equipment scheduling, and discloses a cold source host and slave operation scheduling method and system based on multi-load demands, and the method comprises the steps: S1, predicting a load curve of a cooling system in an analysis period based on the outdoor environment temperature, to-be-processed task data and historical data of a data center; s2, according to the range of the load curve, performing time period division on an analysis period, performing optimization analysis on an equipment combination mode in each time period, and selecting an optimization analysis result according to a lowest energy consumption principle; s3, performing secondary screening on the selected optimization analysis result based on the loss data of the equipment to obtain a to-be-selected equipment combination scheme of each time period; and S4, randomly matching the to-be-selected equipment combination schemes in all time periods, sorting a plurality of groups of randomly matched schemes according to the equipment switching rate, and selecting the optimal equipment combination scheme in each time period according to the sorting result of the equipment switching rate.

This invention discloses a differentiated load profile generation method based on load response characteristic clustering, relating to the field of power system operation and dispatching technology. It addresses the problem of inaccurate load profile generation in existing methods. The method includes the following steps: acquiring historical load data and extracting electricity consumption patterns from the historical load data to obtain electricity consumption pattern curves; acquiring response characteristic parameters; decomposing the daily load curves of each node using a non-negative matrix factorization method based on the electricity consumption pattern curves to obtain the load composition coefficients of each node; constructing multi-dimensional feature vectors and clustering the nodes based on these feature vectors to divide them into multiple node groups; and for each node group, constructing a load profile optimization model and generating a load profile curve adapted to that node group by solving the model. This invention obtains accurate load profiles by constructing a complete process scheme for load characteristic analysis, user clustering, and profile generation.

1. Name of the product in this design: Intelligent Control Cabinet for Energy Storage Power Station. 2. Application of this design: It is used for data acquisition and conversion, load curve optimization, and remote control and tuning in energy storage power station systems. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. As shown in the perspective view, the top view is omitted; the bottom surface of this design product is a part that is not easily seen or cannot be seen during use, so the bottom view is omitted.

Techniques for predictive autoscaling and resource optimization for software deployment. In one implementation, the user declares performance objectives, and machine learning is used to determine the lowest-cost resource configuration that satisfies these objectives, based on application behavior and load profiles. In another implementation, deployment convergence is monitored, and relevant feedback is provided to improve predictions, behavioral modeling, and resource estimation over time.

This invention discloses a multifunctional portable power distribution box and its usage method, belonging to the field of power management and power distribution protection technology. The box includes: S1, setting up an intelligent power distribution host, wherein the intelligent power distribution host comprises a sealed metal shell separating an upper sensing and analysis compartment and a lower power execution compartment; a main controller and a high-frequency electrical parameter sensor are installed in the sensing and analysis compartment, and a multi-channel solid-state relay array is installed in the power execution compartment; S2, the main controller estimates the load components online and constructs a load profile, wherein the AC cycle is locked by the voltage zero-crossing point collected by the high-frequency electrical parameter sensor, and the instantaneous power curve within the cycle is calculated. This invention can identify the type of connected load, and based on the power contribution of the instantaneous power curve in the in-phase power region, the lagging power region, and the peak impact region, the proportions of resistive, inductive, and nonlinear components of the load are calculated in reverse, providing a basis for customized protection strategies.

The invention relates to a method for predicting a battery aging state profile based on a user individualized load profile, comprising: - determining a current aging state value at an evaluation time, - providing at least one prediction value for the aging state from the current load profile by means of the current value, - providing a predicted aging state trajectory for the aging state based on the current aging state value and the at least one prediction value, - determining a further current aging state value at a later evaluation time, - providing at least one further aging state prediction value from the current load profile with the further current aging state value, and - performing the steps: - providing a further predicted aging state trajectory with the further current aging state value and the at least one further prediction value, - providing the further predicted aging state trajectory as the predicted aging state profile, if the deviation of the prediction value on the predicted aging state trajectory from the further current aging state value at the further aging state value evaluation time is greater than a predetermined threshold value.

A method is provided, including: (a) providing an initial charging current to a battery; (b) receiving state information about the battery, including: (1) a temperature, (2) a load profile, and (3) a power loss temporal profile including power loss durations and timings of power failure events; (c) determining, based on the state information, a modification, including: (1) in response to detecting that (i) the temperature exceeds a first upper threshold or (ii) the load profile exceeds a second upper threshold, setting the modification to be a decrease in the charging current; and (2) in response to (iii) detecting that the load profile is below a lower threshold or (iv) predicting that the battery won't reach a full charge by a next expected power failure event if the initial charging current is maintained, setting the modification to be an increase in the charging current; and (d) in response to determining the modification, adjusting the charging current provided to the battery based on the determined modification.

The invention relates to a computer-implemented method for power supply structure planning for providing a power supply, in particular power grid planning for a plurality of loads, in particular some of which are designed and operable for power generation, wherein a) a plurality of groups are formed from at least some of the loads according to a geographical association such that a group is assigned loads in the same, in particular predefinable, region, b) each group is connected via at least one data interface such that data from heterogeneous data sources containing data that at least correlate with the group are determined and are provided in a structured manner in association with the respective group, c) at least some of the data provided in a structured manner are supplied to at least one first module providing a simulation, in particular of load profiles and / or generation profiles, for example of PV systems, and / or to at least one second module providing an algorithm that performs an analysis, in particular at least one disaggregation, of the loads per group, d) a visual display is produced at least on the basis of the output from the first and / or second module on a display, e) an input device is polled to determine an input, f) steps a) to e) are repeated or the process is terminated on the basis of an evaluation of the input. The invention also relates to an arrangement for power supply structure planning comprising means for carrying out the method.

This invention provides a method and system for optimizing multi-source coordinated charging and discharging strategies for energy storage systems. The method includes: predicting electricity prices based on acquired multi-source historical data to obtain predicted electricity prices; outputting an optimized load curve with the objective of minimizing the weighted sum of maximum demand power and electricity cost within a scheduling cycle; using the optimized load curve as a consumption benchmark, determining the existence of curtailment risk and identifying a dynamic operating range when the predicted photovoltaic power generation exceeds the sum of the consumption benchmark and the current rechargeable capacity of the energy storage system; constructing a scheduling curve model based on the predicted electricity prices to maximize net revenue; constructing constraints for the scheduling curve model based on the optimized load curve and the dynamic operating range; and solving the scheduling curve model based on the constraints to obtain a charging and discharging scheduling curve and control the operation of the energy storage system. This invention improves energy utilization efficiency and reduces electricity costs.

The invention relates to a computer-implemented method for energy supply structure planning for providing an energy supply, in particular power grid planning, to a multitude of consumers, especially those partially designed and operable for energy generation, in which a a) Forming a multitude of groups from at least parts of the consumers according to a geographical allocation such that a group of consumers is assigned to the same, in particular predeterminable, region, b) Connecting each group via at least one data interface in such a way that data is retrieved from heterogeneous data sources containing at least some correlation with the group and is structured and provided for the respective group. c) Feeding at least parts of the structured data to at least a first module providing a simulation, in particular of load profiles and / or generation profiles, for example of PV systems, and / or at least a second module providing an analysis, in particular at least a disaggregation of the consumers per group, algorithm. d) Generating a visualization at least based on the output of the first and / or second module on a display, e) Querying an input device to determine an input, f) Repeating steps a) to e) or terminating the process based on an evaluation of the input. Furthermore, the invention relates to an arrangement for energy supply structure planning with means for carrying out the method.

This invention relates to a method for assessing the load carrying capacity of electric vehicle charging in distribution networks, considering spatiotemporal profiling. Belonging to the field of distribution network technology, this scheme combines key parameters such as charging pile type, battery capacity, and functional area attributes to construct multi-type charging load profiles and an improved K-means clustering basic load profile. An improved GA optimization algorithm is used to separate the load of existing charging stations, calculating the available capacity under the premise of transformer safety constraints. Kriging interpolation is used to fit the load curve of newly added charging stations, simultaneously calculating their available capacity. Based on the distribution network topology, capacity matching is verified level by level from 10kV to 110kV, and the allocation of mismatched capacity is optimized using an improved entropy weight-TOPSIS multi-criteria algorithm. This invention overcomes the problems of inaccurate profiling, imprecise load separation, and empirical capacity allocation in traditional methods, enabling precise adaptation of the distribution network to charging loads and improving its carrying capacity.

Device condition estimation device (1), comprising: a state variable acquisition unit (101) configured to acquire a state variable of a target device, including a temperature of the target device; a load specification unit (103) configured to specify a load profile of the target device based on the state variable; and a remaining lifetime calculation unit (105) configured to calculate a variety of parameters related to a remaining lifetime of the target device for each of a variety of degradation types, including crack initiation and crack growth, based on the load profile specified by the load specification unit (103), wherein the load specification unit (103) specifies a load range for each cycle of a load fluctuation of the target device based on the state variable.wherein the remaining lifetime calculation unit (105) calculates one of the plurality of parameters relating to crack growth for the case in which another parameter of the plurality of parameters relating to crack occurrence indicates the occurrence of a crack in the target device, and wherein the remaining lifetime calculation unit (105) calculates an accumulated lifetime consumption rate as another parameter of the plurality of parameters, wherein the accumulated lifetime consumption rate is obtained by accumulating, for each cycle, a lifetime consumption rate calculated on the basis of a number of lifetime cycles relating to a crack occurrence in the target device and the load range specified by the load specification unit (103).

A method is provided, including: (a) providing an initial charging current to a battery; (b) receiving state information about the battery, including: (1) a temperature, (2) a load profile, and (3) a power loss temporal profile including power loss durations and timings of power failure events; (c) determining, based on the state information, a modification, including: (1) in response to detecting that (i) the temperature exceeds a first upper threshold or (ii) the load profile exceeds a second upper threshold, setting the modification to be a decrease in the charging current; and (2) in response to (iii) detecting that the load profile is below a lower threshold or (iv) predicting that the battery won't reach a full charge by a next expected power failure event if the initial charging current is maintained, setting the modification to be an increase in the charging current; and (d) in response to determining the modification, adjusting the charging current provided to the battery based on the determined modification.