32 results about "Energy indicators" patented technology

The invention discloses a coal mine rock burst risk assessment system which comprises a data acquisition module, an energy accumulation rate calculation module, a roadway network modeling module, a risk assessment module and an early warning regulation and control module. The method comprises the following steps of: firstly, calculating an energy accumulation rate of a roadway, then constructing a roadway network diagram, identifying a high stress conduction path, calculating a dynamic risk index and delimiting a risk area by integrating factors such as a historical impact event and an energy index, and automatically triggering corresponding early warning and regulation measures by a system according to a risk level so as to realize accurate early warning and dynamic regulation. And mine operation decision making and accident prevention are assisted.

The present invention relates to the technical field of concrete construction, and in particular to a concrete environmental impact assessment method based on a life cycle approach. The method comprises the steps of: determining a concrete type on the basis of a construction environment and design requirements of a project; analyzing each stage of concrete engineering in a functional unit, and determining an evaluation range thereof; establishing a region-specific concrete life cycle database; performing inventory analysis on an evaluation range of a concrete life cycle; after the inventory analysis, using component inventories of full-life-cycle concrete to establish indicators on the basis of environmental policies of a construction region, so as to perform an environmental impact assessment; and finally, analyzing and evaluating various energy indicators of the concrete, and guiding the establishment of a subsequent project construction plan. In the assessment method, a full-life-cycle assessment is performed on concrete, the degrees of environmental impact caused by different construction processes in concrete engineering are objectively and holistically assessed, and evaluation and improvement schemes are proposed for the concrete construction, thereby reducing the energy and material consumption in concrete engineering construction.

The invention discloses an energy storage system fault database indexing method, and particularly relates to the technical field of fault prediction. The method comprises the following steps: firstly, constructing an energy disturbance vector sequence matrix in a unified time window, extracting features based on a continuous variation rate and energy residual distribution, and generating an energy disturbance feature spectrogram; establishing an energy propagation path atlas in combination with a system module topological relation, and introducing a time sequence consistency identifier; a fault evolution fingerprint is generated through graph embedding coding, similarity index matching is carried out in combination with a standard fault trajectory, and a fault type and a positioning weight are output; real-time energy indexes are further fused, a micro-fault position prediction map is generated, and dynamic early warning is achieved; according to the method, accurate identification and visual positioning of the micro-fault of the energy storage system in a complex scene can be realized, and the operation safety and the intelligent operation and maintenance capability of the system are improved.

The invention discloses a control system for intelligently detecting the lifting process of a tower crane. The control system comprises a data acquisition module, a self-adaptive frequency spectrum filtering module, an impact retention module, a motion time sequence feature construction module, a linear drift monitoring module, a nonlinear disturbance separation module, a threshold statistical decision module and a lifting process control module. The invention belongs to the field of intelligent control, and particularly relates to a control system for intelligently detecting the lifting process of a tower crane, which adopts a self-adaptive sampling method based on gradient triggering to improve the accuracy of fault detection. The control accuracy of the jacking process is improved by applying an optimized wavelet threshold function; extracting linear dynamic characteristics of a load current linear relation through a linear drift monitoring module; residual difference is constructed in the residual subspace, nonlinear energy indexes and errors are calculated, the method is extremely sensitive to nonlinear disturbance and non-Gaussian noise, and a blind area of linear analysis is reinforced; and the control effect of the tower crane lifting process is improved.

The invention discloses an operation evaluation method and device of an integrated energy system and a management and control system. The method comprises the following steps: obtaining operation data of each subsystem in the integrated energy system; based on a pre-constructed comprehensive energy index library, screening out corresponding evaluation features from the operation data of each subsystem; a principal component analysis method is adopted to analyze the evaluation features, and core features are given; according to the similarity between each evaluation feature and the core feature, determining a target evaluation feature and giving an evaluation weight corresponding to the target evaluation feature; and based on the target evaluation features of each subsystem in the integrated energy system, fusing the evaluation weights corresponding to the target evaluation features, and giving operation evaluation data of the integrated energy system. The operation evaluation data is obtained by collecting the operation data of the integrated energy system, performing feature extraction on the data by applying the principal component analysis method, selecting the target evaluation features with high correlation, and setting the evaluation weight in combination with the information entropy, so that the accuracy of the evaluation of the integrated energy system is improved.

A smart, bi-directional electrical microgrid includes processor-on-demand systems, including a computing device having a processing unit and a memory, an Energy Management System (EMS) configured for regulating power usage and optimizing energy efficiency, a distributed power resource for providing a stable and efficient energy supply, a database configured to store energy metrics, a Large Language Model (LLM) for processing the energy metrics stored to generate an energy management plan, an API gateway providing external systems secure, on-demand access to the processing unit, a software module for managing the processor-on-demand system according to the energy management plan and a communication module for peer-to-peer networking, routing, and forwarding. The microgrid also includes one or more management servers for managing the delivery and distribution of power among the processor-on-demand systems to optimize efficiency and uptime, and a network of power lines that interconnect the processor-on-demand systems.

A machine learning-controlled system (100) for enabling energy-efficient computing, comprising: an energy monitoring unit (102) comprising an energy data processor (102a) configured to acquire real-time measurements of the energy consumption of software components; a central sustainability processing unit (104) comprising a dedicated processor (104a) configured to perform energy optimization functions, the central sustainability processing unit (104) further comprising: an energy analysis module (106) configured to implement machine learning algorithms for analyzing energy consumption patterns and generating efficiency predictions; a performance monitoring module (108) configured to track real-time system metrics, including power consumption, computing power and resource utilization; an adaptive optimization module (110) configured to dynamically adjust the software behavior based on energy consumption patterns and performance measurements; a cross-platform deployment module (112) configured to manage energy-efficient software deployment in cloud and on-premises environments; and an energy metrics dashboard (114) comprising a display unit (114a) and an analytics module (114b), wherein the analytics module (114b) generates visualizations of energy efficiency and the display unit (114a) is configured to display energy metrics in real time and enable the configuration of sustainability policies.

Provided in the present application are a green-energy-based load transfer method and apparatus. The method comprises: acquiring a value of at least one green energy indicator of a first network element by means of a first management function, analyzing the use condition of green energy of the first network element by means of the green energy indicator, and sending instruction information, wherein the instruction information is used for instructing, on the basis of the value of the at least one green energy indicator, the first network element to perform inter-network-element green-energy-based load transfer. In this way, when green energy cannot be flexibly distributed across communication devices, the utilization rate of the green energy can be increased, thereby improving the carbon emissions efficiency of the communication devices.

In one aspect of the present disclosure, a method, computer readable medium, and apparatus are provided. The method may be performed by a UE. In certain configurations, the UE receives one or more energy metrics from a network, the one or more energy metrics being used to indicate energy information for the network. And the UE determines a green level of a network resource based on the energy information of the network. And the UE selects a network resource from the network according to the energy configuration and the determined green level of the network resource. The UE communicates with the selected network resource.

The invention provides a dynamic reserve calculation method and device for data impurity removal and produced water treatment, and the method comprises the steps: obtaining the real-time production data of an oil reservoir well in an elastic drive stage, and removing the impurity data in the real-time production data in the elastic drive stage, according to whether the data quantity meeting the linear fitting requirement in the fitting variables meets the condition of the preset data quantity or not, the linear proportion parameter of the formation pressure about the cumulative oil production value or the linear proportion parameter of the formation pressure about the conversion cumulative liquid production value is obtained, and the reservoir dynamic reserves are obtained by selecting different forms of reserve calculation formulas. According to the dynamic reserve calculation method and device provided by the invention, data in production stages such as pumping, water injection and gas injection are avoided, disturbance of multiple data impurities to an energy indication curve is reduced, a calculation result is more accurate and reliable, a simple water production calculation processing flow is established through condition judgment, decision implementation and calculation functions, and the calculation efficiency is improved. And the calculation efficiency of oil wells with different water production conditions is improved.

To provide an energy index calculation method, a program concerning a calculation system for human power-driven vehicles, and a calculation system for human power-driven vehicles making it possible to calculate an energy index concerning travel of a human power-driven vehicle.SOLUTION: An energy index calculation method includes first processing of calculating an energy index concerning travel of a human power-driven vehicle on the basis of a first parameter concerning the travel of the human power-driven vehicle at a first travel point and a second parameter concerning the travel of the human power-driven vehicle at a second travel point different from the first travel point. The first parameter includes a first vehicle speed and first height at the first travel point, and the second parameter includes a second vehicle speed and second height at the second travel point.SELECTED DRAWING: Figure 2

The invention relates to a cable (50) comprising a single layer (52) consisting of N metal wire elements (54) wound in a helix, each metal wire element (54) of the layer (52) describing, when the cable (50) extends in a substantially rectilinear direction, a helix-shaped trajectory around a main axis (A) substantially parallel to the substantially rectilinear direction, in which: - the cable (50) has a total elongation At ≥ 10.00% determined by the ASTM D2969-04 standard of 2014; and - the breaking energy indicator Er of the cable (50) defined by Er = with F(Ai) being the tensile force in N measured at elongation Ai (in %) and F(Ai+1) being the tensile force measured at elongation Ai+1 such that Er is strictly greater than 4000 N.%. Figure for abstract: Fig.6

The application discloses a kind of operation evaluation method, device and management and control system of integrated energy system, method includes: obtaining the operation data of each subsystem in integrated energy system;Based on the integrated energy index library constructed in advance, the corresponding evaluation characteristics are filtered from the operation data of each subsystem;Using principal component analysis, the evaluation characteristics are analyzed, and the core characteristics are given;According to the similarity of each evaluation characteristic and core characteristic, determine the target evaluation characteristic and give the evaluation weight corresponding to the target evaluation characteristic;Based on the target evaluation characteristic of each subsystem in integrated energy system, the evaluation weight corresponding to the target evaluation characteristic is fused, and the operation evaluation data of integrated energy system is given.Through the operation data of integrated energy system, the data is extracted using principal component analysis and the target evaluation characteristic with high correlation is selected, and the evaluation weight is set by combining information entropy, to obtain operation evaluation data, improve the accuracy of integrated energy system evaluation.

A method (2300) performed by a first network node (901) for coordinating with a second network node (902) with respect to a user equipment, UE, energy state assistance information, UE-ESAI, configuration for a UE (900) or a group of UEs currently being served by the first network node. The method includes generating (s2302) a first coordination message. The method also includes transmitting (s2304) the first coordination message to the second network node. The first coordination message comprises information related to configuring the UE or the group of UEs to store and / or report UE-ESAI, and the UE-ESAI comprises a measured or estimated first energy metric.

The invention discloses a drying equipment operation method and device based on energy index parameters, a clothes airing machine and a medium, and belongs to the technical field of automatic control. The method comprises the following steps: acquiring energy index parameter information and a user pre-selected time range; according to the operation power information of the drying equipment, the required operation duration of the drying equipment is determined; and inputting the energy index parameter information, the user pre-selected time range and the required operation time length into an operation time period dynamic planning algorithm to obtain a target operation time period of the drying equipment. According to the technical scheme, the energy index parameter information, the time range pre-selected by the user and the required operation duration are input into the operation period dynamic planning algorithm, the target operation period of the drying equipment is obtained, and on the basis that the drying requirement is met, the drying efficiency is improved. The operation time of the drying equipment is dynamically planned based on actual and accurate energy index parameter information, so that the operation cost of the drying equipment is minimized.

The invention discloses an AC-DC hybrid optimal topology planning method, system and device for a county power distribution network, and a storage medium, and relates to the technical field of power distribution network planning, and the method comprises the steps: building an undirected graph model based on the node and line data of the power distribution network, calculating a complex network index, recognizing key nodes and lines, and obtaining a topology analysis result; calculating load density and the like by utilizing a topological structure and historical operation data, positioning high-loss and low-voltage regions, and obtaining an electrical characteristic analysis result; combining the load and the distributed energy data, calculating permeability and energy storage configuration, and analyzing influence to obtain a distributed energy index; dividing an alternating current region and a direct current region by using a spectral clustering algorithm according to the result; based on a division result, establishing a multi-objective planning model and performing optimization solution, generating an optimal solution set, and completing optimal topology planning; according to the method, key nodes and lines can be accurately identified, and a new thought and method are provided for fine management and optimization of the power distribution network.

The present invention discloses a method for panoramic intelligent perception of the state of a distribution network, which relates to the technical field of distribution network monitoring and management and is used to solve the problem of poor abnormal monitoring of the distribution network. Through precise acquisition and preprocessing of the node signals of the distribution network, the present invention realizes multi-scale decomposition and baseline construction of the signals, effectively extracts the steady-state and abnormal dynamic characteristics of the distribution network, uses variational mode decomposition technology, constructs a baseline by screening low-frequency modes through the central frequency, and then combines the difference between the baseline and the original signal to construct robust residuals and abnormal energy indicators to accurately determine abnormal events. After an abnormal trigger, the distribution network nodes switch to the ultra-high frequency sampling mode, use time-domain difference to extract local disturbance characteristics, and perform noise reduction through robust filtering, and adaptively adjust the filtering parameters according to the local edge ratio, so as to fully retain the abnormal edge information, thereby realizing real-time and high-precision perception of the abnormal state of the distribution network and improving the response speed and accuracy of the panoramic perception of the distribution network.

The invention discloses an energy transformation and digital economy collaborative analysis method and system based on artificial intelligence, and relates to the technical field of computer models. The energy transformation and digital economy collaborative analysis method based on artificial intelligence comprises the following steps of database construction, data query and data extraction and comprehensive evaluation. According to the method, the energy index database is constructed, then whether query optimization is performed or not is judged based on query monitoring parameters after the data query request is received, finally, feature extraction is performed on the queried energy indexes, and whether a feature extraction life cycle management mechanism is triggered or not is judged based on the extracted energy index features. After a feature extraction life cycle management mechanism is triggered, the extracted energy index features are subjected to quantitative evaluation to construct an energy transformation maturity evaluation model, so that the accuracy of energy transformation quantitative evaluation is improved; the problem that in the prior art, due to the fact that data version updating and mapping updating are not matched, energy transformation quantitative evaluation accuracy is low is solved.

The present invention belongs to the technical field of power project construction investment, and specifically relates to a method for designing and planning economic and energy indicators for source-grid-load-storage integration, including the following steps: obtaining the prediction result of the annual energy consumption demand based on the monthly electric energy demand prediction model of the region where the source-grid-load-storage integration project is located, which is based on a full-dimensional dynamic convolution - bidirectional time series convolution network and decomposition error correction, and giving the annual available electric energy capacity model and the correlation model of the annual electric energy production - sales volume; constructing economic benefit and energy efficiency indicators for the whole process input and output of the source-grid-load-storage integration project; giving the evaluation method for the economic benefit and energy efficiency of the source-grid-load-storage integration project in different states; and optimizing the maximization of economic benefit and energy efficiency by using an improved raccoon optimization algorithm and making it meet the supply and demand constraint verification. The present invention can be used for evaluating the investment value of the source-grid-load-storage integration project and also provides support for the optimized utilization of energy after completion.

The embodiment of the present invention discloses an energy consumption information processing method, device, medium, controller and management module; its core includes a first information collection preprocessing step and a second energy consumption information processing step; by splicing the first multi-source data in the first local initialization information to a preset timestamp, the synchronous processing of the information can be achieved, providing a basis for subsequent energy consumption information processing; specifically, the method and product of the present invention can solve the problem that the energy management strategy of hybrid electric vehicles (HEV) in related technologies lacks consideration of actual operating conditions; it can also realize vehicle status monitoring, remaining road condition information analysis, vehicle energy management strategy planning, energy management strategy execution and other functions; thereby realizing the optimization of energy indicators for the entire journey based on road traffic conditions, with the goal of optimizing energy consumption throughout the journey, and targeted control of the vehicle's power mode and the operating point settings of components such as the engine and motor, thereby realizing optimization of energy indicators for the entire journey.

This disclosure relates to a fuel cell system for vehicles that includes a controller which, among other things, regulates the stack flow and purge or drain valve operations based on an energy indicator used to monitor cell voltage. If the energy indicator exceeds a predefined threshold, the controller reduces the stack flow or adjusts the purge or drain valve—either opening it to reduce flooding or closing it to prevent desiccation.

This disclosure relates to a fuel cell system for vehicles that includes a controller that manages, among other things, the stack current and purge valve or drain valve operations based on a cell voltage monitoring energy indicator. When the energy indicator exceeds a predefined threshold, the controller reduces the stack current or adjusts the purge valve or drain valve—either opening it to mitigate flooding or closing it to prevent drying out.

This invention relates to the field of power grid technology and discloses a method for virtual energy storage aggregation and control of green electricity in ports. The method includes: acquiring aggregation scenario and resource data; generating a power hard constraint mapping and a sub-stake execution reference by calculating multi-band energy indicators and identifying system power transfer characteristics; generating a local fast control configuration set by solving the virtual impedance feasible region and combining it with the power hard constraint amortization compensation budget; fusing the sub-stake execution reference (slow channel) generated based on the power hard constraint with the fast channel execution trajectory obtained after local online execution compensation, and performing priority arbitration under the constraints of the power hard constraint to output the final execution power trajectory. This invention constructs a two-layer control architecture of slow channel planning + fast channel compensation, and through the core link of power hard constraint mapping, ensures the coordinated operation of fast and slow channels and the safety and stability of the entire system, providing the power grid with fast and reliable dynamic support capabilities.

The invention provides a carbon peak reaching prediction method and device based on electricity-certificate-carbon and model selection, and the method comprises the steps: inputting the magnitudes of a plurality of economic indexes, the magnitudes of a plurality of population indexes, and the magnitudes of a plurality of energy indexes into a first model, and obtaining first prediction values of a plurality of energy indexes; inputting the quantity values of the plurality of scientific and technical indexes and the quantity values of the plurality of energy indexes into a second model to obtain second predicted values of the plurality of energy indexes; inputting the quantity values of the plurality of electricity-evidence-carbon indexes into a third model to obtain a predicted value of a key index in the plurality of electricity-evidence-carbon indexes; inputting the quantity values of the plurality of carbon emission indexes, the quantity values of the plurality of energy indexes, the first predicted values of the plurality of energy indexes and the second predicted values of the plurality of energy indexes into a fourth model to obtain an initial carbon peak reaching prediction result; and inputting the initial carbon peak-reaching prediction result and the predicted value of the key index into a fifth model to obtain a final carbon peak-reaching prediction result. And more indexes are combined, so that the accuracy of carbon peak reaching prediction is improved.

The invention relates to a cable (50) comprising a single layer (52) consisting of N metallic wire elements (54) wound in a helix, each metallic wire element (54) of the layer (52) describing, when the cable (50) extends in a substantially rectilinear direction, a helix-shaped trajectory around a main axis (A) substantially parallel to the substantially rectilinear direction, in which: - the cable (50) has a total elongation At ≥ 10.00% determined by the ASTM D2969-04 standard of 2014; and - the breaking energy indicator Er of the cable (50) defined by Er = with F(Ai) being the tensile force in N measured at elongation Ai (in %) and F(Ai+1) being the tensile force measured at elongation Ai+1 such that Er is strictly greater than 4000 N.%. Figure for abstract: Fig.6

The present invention discloses a method and device for assessing the severity of voltage sags, belonging to the technical field of power quality research in distribution networks. The present invention considers the impact of different transformer types on the propagation of different voltage sag events, solving the problem of difficulty in converting data between the grid system side and the user side data; uses a nonlinear least squares method to establish a fusion tolerance curve to comprehensively assess the severity level of voltage sags on the user side, solving the problem that there are multiple load devices on the user side and the severity of the user side cannot be comprehensively assessed based on grid side data; uses an improved hierarchical analysis method to calculate the influence coefficient of the characteristic values ​​of the voltage sag, namely the sag amplitude and duration, and establishes a hierarchical assessment benchmark based on energy indicators, which can quantitatively reflect the more realistic sag degree on the user side and achieve a reasonable and accurate assessment of the severity of the voltage sag event on the user side.

The application provides an intelligent detection method and device for energy abnormal channels, electronic equipment and a storage medium. Through shot point and receiving node distance sorting and first break line leveling processing, geometric distortion and time difference interference in original data are eliminated, and the accuracy of subsequent analysis is improved. Local energy indicators are extracted to capture small abnormalities and enhance the sensitivity to local energy such as noise and local geological abnormal mutation. Global energy indicators are extracted to identify overall energy such as systematic equipment failure or large-scale geological change trend abnormalities, avoid one-sidedness of local detection, and improve detection comprehensiveness. A multi-classification deep network model is adopted, energy sample label data is supervised and trained, classification robustness is improved, the detection and quality control effect of node channel data energy abnormal channels in the seismic data acquisition site quality control is improved, the model output is determined by the most common type of statistics, accidental errors are reduced, and the result stability is enhanced.

The invention provides a carbon peak reaching prediction method and device based on electricity-certificate-carbon and index quantification. The method comprises the following steps: obtaining the quantity values of a plurality of energy indexes, the quantity values of a plurality of economic indexes, the quantity values of a plurality of scientific and technological indexes, the quantity values of a plurality of population indexes and the quantity values of a plurality of electricity-certificate-carbon indexes of a target object in target historical time; selecting a target number of energy indexes, economic indexes, scientific and technological indexes, population indexes and electricity-certificate-carbon indexes with the highest correlation; calculating the weight of each energy index, the weight of each economic index, the weight of each scientific and technological index, the weight of each population index and the weight of each electricity-certificate-carbon index; and inputting the quantity values and the weights of the indexes of the target number into a carbon peak-reaching prediction model, and determining the content output by the carbon peak-reaching prediction model as a carbon peak-reaching prediction result. And the accuracy of carbon peak reaching prediction for different regions or industries can be improved.

In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The method may be performed by a UE. In certain configurations, the UE receives, from a network, one or more energy indicators for indicating energy information of the network. The UE determines, based on the energy information of the network, a level of greenness of network resources. The UE selects network resources from the network according to an energy configuration and the determined level of greenness of the network resources. The UE performs communication with the selected network resources.

The present invention discloses an intelligent detection tower crane lifting process control system, comprising a data acquisition module, an adaptive spectrum filtering module, an impact retention module, a motion timing feature construction module, a linear drift monitoring module, a nonlinear disturbance separation module, a threshold statistical decision module, and a lifting process control module. The present invention belongs to the field of intelligent control, and specifically refers to an intelligent detection tower crane lifting process control system. This solution adopts an adaptive sampling method based on gradient triggering to improve the accuracy of fault detection; applies an optimized wavelet threshold function to improve the accuracy of lifting process control; extracts the linear dynamic characteristics of the linear relationship of load current through a linear drift monitoring module; constructs residual differences in the residual subspace, calculates nonlinear energy indicators and errors, is extremely sensitive to nonlinear disturbances and non-Gaussian noise, and strengthens the blind spots of linear analysis; thereby improving the control effect of the tower crane lifting process.