58 results about "Load profile" patented technology

This invention advances power grid operational planning by introducing a mid-term scheduling framework for integrated hydro-wind-solar systems that accounts for heterogeneous daily load profiles across multiple receiving-end power grids. The proposed approach utilizes an adaptive variable-step search algorithm to segment loads into peak, flat, and valley intervals. By synthesizing five key metrics, including mean daily load, daily load factor, peak-valley differential ratio, load rates during peak / valley periods, and timing of peak / valley occurrences, the method accurately captures region-specific load patterns and peak-shaving demands. This enables a refined reconstruction of load profiles of receiving-end power grids. A nested multi-temporal scheduling model that couples medium- and short-term horizons to simultaneously maximize total energy production and minimize transmission imbalances among power grids. The model is addressed by using the mixed-integer linear programming (MILP) to obtain medium- and short-term generation schedules and power transmission schedules.

The invention discloses a multi-element energy storage collaborative distributed energy system operation regulation and control method, and the method comprises the steps: considering an optimal scheduling strategy of a power-energy type electricity storage, heat storage, cold storage and other technologies for cooperatively regulating and controlling a multi-energy load curve, and constructing a generalized technical model of energy equipment and system operation constraints; designing an energy system operation data preprocessing mechanism and a weight determination model under a given historical window; an energy system scheduling sequence of bipartite dynamic regression coordinated electric heating unit operation is provided, and an economic operation planning model is constructed; the model is applied to a historical window, optimal parameters of key regulation and control nodes are searched and determined through a heuristic algorithm so as to guide future time window scheduling and complete scheduling closed loop, and hyper-parameters of the method, such as historical and future window vision fields, time nodes and weights, are determined based on multiple scheduling closed loop behaviors so as to complete method closed loop. According to the method, a commercial solver is not needed, the economic operation rule of the distributed system is directly mined from historical operation, the method is used for determining the on-off and output plan of each device of the system in a future time sequence, and engineering application is facilitated.

The invention relates to the technical field of equipment monitoring, in particular to an air conditioning equipment state monitoring system and method, and the system comprises a load curve construction module, a compressor power scheduling module, a power fluctuation trend analysis module, a compressor fault prediction module and a refrigerant leakage identification module. According to the method, the load curve of the air conditioning equipment is monitored in real time, the key operation data including the cooling capacity requirement and the compressor exhaust temperature are integrated, load management is more accurate, then energy efficiency is optimized, the load change rate and historical data are compared, accurate prediction of the power requirement can be achieved, and the current power change rate and the historical power change rate are compared, so that the energy efficiency is improved. The power fluctuation trend can be effectively recognized, potential faults can be recognized in an early stage, the refrigerant leakage problem can be found in time by monitoring the pressure change rate and the pressure difference cumulative gradient, safety risks are avoided, the energy efficiency and reliability of an air conditioner system are improved, the service life of equipment is effectively prolonged, and the maintenance cost is reduced.

The invention relates to a computer-implemented method for assigning a specific device battery to further use or recycling, comprising the following steps: - Providing (S1) historical operating size profiles of the device battery; - For each of a set of possible reuses, determine (S3) a predicted aging state progression using a predefined aging state model based on a load profile assigned to the respective reuse, and determine a remaining service life depending on the predicted aging state progression and a limit aging state assigned to the respective reuse, - Select (S5, S6) one of the further uses for the specific device battery depending on the remaining lifetimes specified for the further uses and a minimum remaining lifetime assigned to the respective further use.

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.

Method for initially providing an at least partially data-based aging state model (4) for an electrical energy storage device (3), comprising the following steps: - Providing (S1) a number of energy storage devices (3) on a test bench (1) for measurement depending on a respective load profile, wherein the load profiles are different and characterize a time course of at least one load-bearing operating parameter for the energy storage device (3); - Operating (S2) the number of energy storage devices (3) with their respective assigned load profiles and recording operating parameter profiles over time; - At each given evaluation time, determine (S4) an aging state of a subset of the energy storage devices (3) as a label and generate a training data set with the operating parameter profiles and the determined label for each energy storage device (3) of the subset of energy storage devices (3); - Selecting (S6) the subset of energy storage devices (3) with their respective assigned load profiles depending on an optimization procedure that considers total costs (C J ) a measurement of the energy storage (3) on the test bench (1) and of a total information measure (Info J ) the measurement of the energy storage (3) depends.

Various embodiments of the teachings herein include methods for operating an energy management system of a grid participant electrically connectable to an electrical grid at a grid connection point comprising: a) receiving data from an electricity exchange characterizing a remuneration for a first service provided to the electrical grid by the grid participant and / or a second service obtained by the grid participant from the electrical grid; b) determining a load profile for the grid participant as a function of the received data, wherein the energy management system at least temporarily operates the grid participant according to the determined load profile so the grid participant provides the power to the electrical grid and / or obtains the power from the electrical grid; and c) transmitting the load profile to the electricity exchange.

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 invention relates to a method for ascertaining a vehicle (1) fuel cell system (2) operating strategy which is optimized with respect to efficiency and service life. The method has the steps of:(a) providing a load profile of the fuel cell system (2),(b) dividing the provided load profile into at least two load profile ranges with different load ranges, wherein a proportion of the fuel cell system hydrogen consumption and a proportion of the fuel cell system degradation of the entire load profile is determined for each of the at least two load profile ranges,(c) determining a weighting function for optimizing the efficiency or service life of the fuel cell system in each of the at least two load profile ranges using the proportion of hydrogen consumption and degradation determined for each of the at least two load profile ranges,(d) determining a parameter set for converting the weighting function in each of the at least two load profile ranges, and(e) ascertaining the operating strategy which is optimized with respect to efficiency and service life according to the determined parameter sets.

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.

A smart shopping cart includes internally facing cameras and an integrated scale to identify objects that are placed in the cart. To avoid unnecessary processing of images that are irrelevant, and thereby save battery life, the cart uses the scale to detect when an object is placed in the cart. The cart obtains images from a cache and sends those to an object detection machine learning model. The cart captures and sends a load curve as input to the trained model for object detection. Labeled load data and labeled image data are used by a model training system to train the machine learning model to identify an item when it is added to the shopping cart. The shopping cart also uses weight data and the image data from a timeframe associated with the addition of the item to the cart as inputs.

The invention relates to the technical field of power dispatching systems, and discloses an intelligent power load dispatching system and method based on a user load portrait, and the system comprises a user load portrait construction module, a user power load prediction module, and a user power load dispatching module. Carrying out historical prediction power dispatching load error ratio change trend numerical statistics of user side power load prediction time by combining numerical processing based on user historical prediction power dispatching load error ratio parameters; and according to the user historical predicted power dispatching load parameter, the user historical actual power dispatching load parameter and the user historical predicted power dispatching load error change weight parameter, intelligent and accurate prediction of a power theoretical actual dispatching load prediction result of user-side power load prediction time is carried out. Scientific statistics of power load dispatching parameters is realized based on a user power dispatching load error change trend, and the precision and reliability of power load dispatching are improved.

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.

A utility consumption information system may generate a variety of data that is based on and / or derived from utility consumption or usage associated with a site. In some examples, the utility consumption information system may generate data to be provided or displayed by applying a load profile to utility consumption or usage data obtained at the site over a period of time. The utility consumption information system may generate the load profile based on sample interval data obtained from one or more devices (e.g., utility metering devices) sharing characteristics with the site at which the utility consumption or usage data was obtained.

Disclosed is a vehicle comprising a vehicle system having a system having a number of loads defining a load profile; a validated battery comprising one or more batteries which can fulfill the load profile; an integrated battery selected from the validated battery, the integrated battery selected for longevity relative to other batteries; wherein the validated battery is provided within the vehicle. Further disclosed is a battery longevity predictor comprising a plurality of battery factors; a plurality of electrical load factors; a plurality of cycling or crank data; an output; wherein the output comprises a battery longevity predictor based on the plurality of battery factors, plurality of vehicle loads, and the plurality of cycling or crank data.

Examples described herein relate to energy management and optimization. An energy management system may monitor a microgrid using sensors associated with a utility grid, one or more power sources, and one or more load devices. The energy management system may determine one or more load profiles corresponding to one or more load devices based on measurements from the sensors. The energy management system may determine a priority order of the one or more load devices based on user input or availability of the one or more power sources. The energy management system may then dynamically connect and disconnect the one or more power sources from the one or more load devices based on utility grid conditions, available power from the one or more power sources, the one or more load profiles, and a priority order of the one or more load devices.

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.

An improved power-split control system for managing a load profile of a fuel cell in a fuel cell electric vehicle (FCEV) is provided. The power-split control system is operable to actively manage the power demand between the fuel cell and the battery of a FCEV to optimize the operational life of the fuel cell. The power-split control system can use information gathered solely from historical drive cycle data or from historical drive cycle data combined with look-ahead eHorizon data. The power-split control system meets a power demand by operating the powertrain in either a battery charge sustaining mode or a battery charge depletion mode. The power-split control system is also configured to control the power distribution (to the electric motor) from the fuel cell and the battery in a manner that minimizes the degradation of the fuel cell.

The present invention discloses a method for optimizing the configuration of source and storage capacity of an integrated energy system taking into account comprehensive demand response, and relates to the technical field of optimized configuration of capacity of an integrated energy system. The specific steps are: collecting annual wind speed data, annual irradiation data, and electricity price plan data; processing the annual wind speed data and annual irradiation data using the confidence interval method to obtain a wind speed confidence curve and a photovoltaic confidence curve, and processing the electricity price plan data using the comprehensive demand response model to obtain a load curve; on the basis of the wind speed confidence curve, the photovoltaic confidence curve, and the load curve, taking into account the uncertainty of wind and solar output and the comprehensive demand response of electricity and heat, a two-layer optimization configuration model is constructed; the two-layer optimization configuration model is solved to obtain the optimal configuration solution. The method of the present invention can effectively reduce the total cost of system planning, meet the energy demand of electric and heat users, and improve energy utilization efficiency and the efficiency of intelligent planning of the integrated energy system.

Disclosed is a vehicle comprising a vehicle system having a system having a number of loads defining a load profile; a validated battery comprising one or more batteries which can fulfill the load profile; an integrated battery selected from the validated battery, the integrated battery selected for longevity relative to other batteries; wherein the validated battery is provided within the vehicle. Further disclosed is a battery longevity predictor comprising a plurality of battery factors; a plurality of electrical load factors; a plurality of cycling or crank data; an output; wherein the output comprises a battery longevity predictor based on the plurality of battery factors, plurality of vehicle loads, and the plurality of cycling or crank data.

This application discloses a system that may comprise at least a portion of a supply network. The system may further comprise a load controller that controls current flow with a current level of I1 into a load network that provides power to one or more loads from the at least a portion of the supply network according to a preprogrammed load curve. The system may also comprise a protection system that isolates the at least a portion of the supply network from the load controller in response to detecting a current pattern that is inconsistent with the preprogrammed load curve.