30 results about "Energy simulation" patented technology

The invention discloses a fabricated building self-optimization energy-saving system and method based on DRL and BIM, and relates to the technical field of building energy management and intelligent control. The system comprises a BIM data acquisition module used for storing and providing BIM data of a prefabricated building; the energy simulation module is used for constructing a digital twin model based on BIM data, providing a simulation environment for the DRL control module in an offline training stage, and assisting verification and retraining in an online stage; the environment monitoring and execution module is used for acquiring operation parameters and energy consumption data in real time through a sensor, an actuator and an interface butted with a transportation system and executing a control instruction; and the DRL control module obtains an optimization control strategy through simulation interaction learning, generates an instruction according to real-time data in an online stage, and issues and executes the instruction. Energy consumption and carbon emission in the whole process of the fabricated building can be optimized, the energy utilization efficiency and comfort are improved, and the self-adaptability and long-term stability of the system are enhanced.

The invention discloses a knowledge distillation method and equipment for nuclear accident deduction and fault diagnosis of a reactor. The method comprises the following steps: acquiring fault data of a nuclear energy simulation device; building a multi-task network; dividing the acquired data set D into a training set, a verification set and a test set, and pre-training the multi-task network by using the training set; after pre-training is completed, parameters in the multi-task network are fixed, that is, a large-parameter pre-training model is frozen to serve as a teacher model; migrating the knowledge of the teacher model to the student model by adopting a method of multi-task proportion-by-proportion penetration knowledge distillation; and obtaining a physical quantity deduction result and a fault result of the target pipeline by utilizing student model reasoning. According to the method, the multi-task network based on the physical information neural network is established, fault diagnosis and parameter deduction in a plurality of reactor nuclear accidents can be processed at the same time, the correlation between different tasks is fully utilized, and the fault diagnosis precision and the deduction capacity for the development process of the nuclear accidents are improved.

The invention discloses a linear cutting path intelligent optimization method based on deep learning image recognition. The method comprises the following steps that a workpiece multi-view image is obtained and imported into an electronic drawing, the image is recognized, workpiece structure information is extracted, a unified coordinate model is established in combination with a datum point, and an element list is output; based on the element list and machine tool and material parameters, a machining graph is constructed with contour segments as nodes and feasible transition between the segments as edges; candidate cutting paths are generated on the machining drawing according to the machining constraint, and an initial cutting scheme is formed; inputting the processing graph into a quantum heuristic neural network, performing optimization selection on the initial cutting scheme, and outputting an optimal cutting scheme; and geometric and energy simulation is conducted on the optimal cutting scheme, the cutting seam crossing, residual area and material falling risks are detected, and local correction is executed when the constraint is not met. According to the invention, through combination of deep learning identification and quantum heuristic optimization, automatic generation and correction of the linear cutting path are realized.

An AI-based platform for enabling intelligent orchestration and management of power and energy is provided herein. The AI-based platform includes a digital twin system including a plurality of digital twins of energy operating assets, the plurality of digital twins of energy operating assets including at least one energy generation digital twin, energy storage digital twin, energy delivery digital twin, and / or energy consumption digital twin, and a set of energy simulation systems configured to generate a simulation of energy-related behavior of at least one of the plurality of digital twins of energy operating assets, and a machine-learning system configured to generate a predicted state of at least one of the energy operating assets. The simulation of energy-related behavior is based on historical patterns, current states, and the predicted state of at least one of the energy operating assets.

The present invention relates to the field of distributed energy simulation, and in particular to a method and system for constructing an equivalent simulation model for a multi-type wind farm. The method comprises: collecting wind turbine information and constructing a multivariate scaled wind farm model, wherein the multivariate scaled wind farm model mainly includes a wind turbine dynamics model and a converter control model; constructing an embedded constant admittance equivalent model and collecting the control characteristics of an ideal switch, solving the control parameters of the embedded constant admittance equivalent model based on the control characteristics, and performing parameter optimization based on steady-state errors to replace the converter control model; performing model equivalence processing on several wind turbine categories according to the multivariate scaled wind farm model to obtain a multivariate wind turbine equivalent simulation model. The present invention effectively solves the problems in existing wind farm simulations, such as low simulation efficiency due to excessive converter calculations and inaccurate simulation results caused by the inability of the equivalent modeling method for multi-type wind farms to fully consider the dynamic characteristics and control strategies of different types of wind turbines.

The invention relates to the field of distributed energy simulation, in particular to a multi-model wind power plant equivalent simulation model construction method and system.The method comprises the steps that wind turbine generator information is collected, a multi-element large-scale wind power plant model is constructed, and the multi-element large-scale wind power plant model mainly comprises a wind turbine dynamical model and a converter control model; an embedded constant admittance equivalent model is constructed, control characteristics of an ideal switch are collected, control parameters of the embedded constant admittance equivalent model are solved according to the control characteristics, parameter selection is carried out according to steady-state errors, and a converter control model is replaced; and according to the multi-element large-scale wind power plant model, carrying out model equivalence processing on the wind turbine categories to obtain a multi-element wind turbine equivalence simulation model. Through the method, the problems that in existing wind power plant simulation, the simulation efficiency is low due to the fact that the calculated amount of a converter is too large, and the simulation result is inaccurate due to the fact that the equivalent modeling method of the multi-model wind power plant cannot fully consider the dynamic characteristics and control strategies of different models are effectively solved.

The invention provides a digital simulation interface system of a face satellite attitude and orbit control subsystem, and relates to the technical field of computer simulation. Interfaces are divided into two classes according to attributes, the first class is simulation class interfaces, and the second class is simulation class interfaces; the interface is used for initialization parameter setting, simulation process control, simulation target data acquisition and data interaction of a simulation state, a running log, a model event, energy simulation data, thermal simulation data and environment simulation data of an attitude and orbit control subsystem model; and the second type is a business type interface, and the interface is used for data interaction with other subsystems or the outside in the function operation of the attitude and orbit control subsystem. Definitions of the two types of interfaces can cover all simulation activities of a satellite attitude and orbit control subsystem, meanwhile, the related internal simulation activities and external simulation activities can be distinguished, and interface testing of a satellite digital subsystem model can be systematically carried out with the fewest units.

The invention discloses a ship plane segmentation workshop fuzzy scheduling method, which comprises the following steps of: firstly, establishing a ship plane segmentation fuzzy scheduling model, adding uncertainty of processing time to the traditional scheduling model, and representing the processing time by using a triangular fuzzy number; secondly, improving the Harlisia eagle algorithm, introducing nonlinear decreasing escape energy and simulated annealing temperature parameters, solving the problems of premature convergence and falling into a local optimal solution of the algorithm, and improving the quality of an initial population by adopting an improved NEH algorithm and chaotic mapping; and finally verifying the validity of the algorithm through a reference function, and applying the optimization method to an engineering example. The method is helpful for improving the efficiency of a ship plane section processing workshop, and has important practical significance.

The application discloses a knowledge distillation method and device for reactor nuclear accident deduction and fault diagnosis, and comprises the following steps: obtaining nuclear energy simulation device fault data; building a multi-task network; dividing the obtained data set into a training set, a verification set and a test set, and pre-training the multi-task network by using the training set; fixing the parameters in the multi-task network after pre-training, that is, freezing the pre-training model with large parameters as a teacher model; adopting a multi-task proportional penetration knowledge distillation method to transfer the knowledge of the teacher model to a student model; and obtaining physical quantity deduction results and fault results of a target pipeline by reasoning by using the student model. D The application can simultaneously process multiple fault diagnoses and parameter deductions in a reactor nuclear accident by building a multi-task network based on a physical information neural network, fully utilizes the correlation between different tasks, and improves the accuracy of fault diagnosis and the deduction capability for the development process of a nuclear accident.

This invention belongs to the field of energy simulation technology and relates to an energy flow network simulation system and method for steel enterprises. It includes: a system configuration module for configuring parameters based on user-inputted information and forming a structured configuration data package; a front-end operation module for configuring a visual interactive interface based on the configuration data package; generating a Gantt chart based on pre-set production and maintenance plans; and drawing a dynamic energy flow diagram based on user-defined equipment and energy nodes; and a back-end service module for calculating energy prediction results based on the Gantt chart, dynamic energy flow diagram, and configuration data package using a pre-set production and consumption model, and performing scheduling optimization when energy prediction results are unbalanced to obtain an energy scheduling balance result. This invention achieves collaborative simulation of production and energy, more intuitively displays the energy balance process, provides a more comprehensive simulation platform for the steel industry, and facilitates systematic management by enterprises.

The invention belongs to the technical field of energy storage, and particularly relates to an energy storage capacity determination method and device, a computer readable storage medium and electronic equipment. The method comprises the following steps: determining photovoltaic power data, load power data and time-of-use electricity price data of a target area in each energy storage scheduling period; traversing various candidate energy storage capacities of the energy storage equipment in the target area, and performing energy storage charging and discharging power scheduling on the energy storage equipment in the target area according to the photovoltaic power data, the load power data and the time-of-use electricity price data to obtain energy storage charging power data and energy storage discharging power data of the energy storage equipment in each energy storage scheduling period; performing energy simulation on the target area according to the photovoltaic power data, the load power data, the energy storage charging power data and the energy storage discharging power data to obtain an energy simulation result of the target area; determining a financial index of the target area according to the energy simulation result; and determining the energy storage capacity of the energy storage equipment from the various candidate energy storage capacities according to the financial indexes.

The invention provides a distributed power supply series-parallel power distribution network fault identification model construction method and system, and the method comprises the steps: constructing a series-parallel simulation power distribution network based on preset power distribution network simulation information, and constructing a distributed energy simulation system based on preset distributed energy structure information; connecting the distributed energy simulation system to the series-parallel simulation power distribution network, performing single-phase earth fault simulation on the series-parallel simulation power distribution network by using the arc model, and collecting a fault transient current simulation signal of the series-parallel simulation power distribution network; performing feature extraction on the fault transient current simulation signal by combining a wavelet transform method to obtain a fault signal training feature, determining a fault recognition result based on the fault signal training feature, and further taking the fault signal training feature as an input and the fault recognition result corresponding to the fault signal training feature as an output to obtain a fault recognition result; and training the fault identification model to obtain a trained fault identification model, thereby realizing accurate identification of the fault of the hybrid power distribution network containing the distributed power supply through the fault identification model.

This invention relates to the field of unmanned aerial vehicle (UAV) application technology, specifically a method for energy consumption prediction and path planning in heavy-payload UAV hoisting operations. The method includes the following steps: loading the original flight data and mission target point data of the heavy-payload UAV; constructing a hybrid energy consumption model coupled with physical mechanisms and residual correction; introducing a heavy-load unbalanced weighted training mechanism to train the hybrid energy consumption model, assigning significantly higher weights to samples exceeding a preset heavy-payload threshold; using an improved K-Means clustering algorithm to divide the spatial domain of discrete operation points, introducing the hybrid energy consumption model as an evaluation function into the clustering iterative closed loop to achieve region clustering based on real operation point corrections; and calling the trained hybrid energy consumption model to perform energy simulation, performing path planning and search based on the limit efficiency of a safe power threshold. This invention effectively solves the safety hazard of inaccurate endurance estimation in heavy-payload operations and maximizes hoisting efficiency within a single takeoff and landing cycle.

The present application relates to the field of energy simulation, and discloses a method and device for predicting urban building energy consumption, electronic equipment and medium. The method comprises: reconstructing each component in the urban climate state of the previous time step by mapping to determine the building boundary state; determining the energy consumption state quantity of the building according to the building boundary state; updating the urban climate state of the current time step according to the energy consumption state quantity, thereby predicting the urban building energy consumption of each time step. The present application can accurately depict the evolution law of urban building energy consumption under future climate change scenarios.

This application relates to the field of wave energy simulation technology and discloses a simulation method and system for dual-mode frequency tuning of oscillating water columns in a double-slit caisson. The method includes: establishing a two-degree-of-freedom dynamic equation system based on the displacements of the water columns in the front and rear cavities, using the slit transmission coefficient as a parameter to obtain the coupling stiffness; substituting the coupling stiffness into the eigenvalue equation to decompose the oscillation modes of the two cavities to obtain the mode transformation matrix and mode amplitude ratio; performing convolution integration on the mode amplitude ratio and the wave power spectrum of the target sea area to obtain the first-order mode weight and second-order mode weight; using a preset target first-order mode weight as the outer convergence target and a preset target natural frequency as the inner convergence constraint to perform a double-layer nested iterative solution on the slit transmission coefficient and the rear cavity volume to obtain the optimal slit width and the optimal rear cavity volume. This application solves the problem of unobservable and undesignable energy contribution ratios of each mode in existing technologies, leading to spectral mismatch.

The invention relates to the technical field of energy system operation management, and particularly provides a digital twin energy simulation processing method, system and equipment based on data credibility and a storage medium, and the method comprises the steps: obtaining original energy data of similar equipment; calculating to obtain a credibility value corresponding to each piece of original energy data; performing credibility interpolation on the original energy data with the credibility value being 0 to obtain interpolation energy data, and recording the original energy data with the credibility value not being 0 and the interpolation energy data as effective operation data; based on the effective operation data and the credibility value, calculating a credibility weighting coefficient to obtain credibility weighted energy data; obtaining a station equivalent energy load based on the credibility weighted energy data and the credibility value; and updating the state variable of the pre-constructed energy digital twin model. By introducing a credibility weighting mechanism, the influence of abnormal data is reduced, and the stability and accuracy of energy simulation are improved.

The invention relates to the technical field of data classification, and discloses an energy big data classification and grading method, system and device and a medium, and the method comprises the steps: obtaining various types of energy simulation data; preprocessing the energy simulation data, and performing data set division and label reconstruction to obtain a first data set; inputting the data to an SVM model and a random forest model for training to obtain an optimized SVM model and an optimized random forest model; and inputting the preprocessed second data set into the optimized SVM model and the random forest model, carrying out collaborative reasoning and grading, and outputting a final grading result. Through deep cooperation of the lightweight SVM and the random forest, a classification strategy is dynamically adjusted by using confidence, low-confidence scene misjudgment is reduced, small sample precision and large-scale processing efficiency are balanced, accurate optimization of classification and classification is realized, generalization ability and robustness of the model are enhanced, and the method is suitable for scenes such as a smart power grid and sensitive load guarantee.

The application discloses a Q-switched laser resonator single-pass loss simulation inversion calculation method and system, and belongs to the technical field of laser simulation. The method comprises the following steps: initializing basic parameters related to a resonator and a laser medium; calculating a laser threshold energy storage according to the basic parameters; calculating the energy storage of a laser crystal under different pump currents according to the laser threshold energy storage; calculating the output energy simulation value under each pump current according to the energy storage of the laser crystal; comparing the output energy simulation value with the actual measured value, and obtaining the final simulation result of the resonator single-pass loss according to the comparison result. The application does not need a large number of experimental tests, has low simulation error, is suitable for multiple pump working conditions, is applicable to the loss solving and performance optimization of various Q-switched solid-state lasers, and can significantly improve the laser design efficiency and simulation precision.

The invention relates to the technical field of simulation calculation, and discloses a photovoltaic support foundation design method based on wind energy simulation calculation, and the method comprises the steps: introducing a self-spectral density function in a random vibration theory to describe the turbulence intensity of a single-point wind speed based on specific meteorological and topographic data of a photovoltaic support target site; outputting a three-dimensional fluctuating wind field model containing complete information of spatial and temporal distribution of wind pressure; taking the obtained three-dimensional fluctuating wind field model as a fluid domain boundary condition, acting on a parameterized photovoltaic array overall structure model, and performing complete transient fluid-solid coupling simulation calculation; outputting the substrate dynamic response time history of the reaction force and the torque of six degrees of freedom at the top connection part of each support foundation along with the time change; and outputting the most unfavorable design internal force and long-term displacement of the foundation after the influence of the quantized wind-induced vibration second-order effect. According to the method, the structural response envelope value of the whole wind vibration process is directly obtained through time-history analysis.

The invention discloses an energy simulation adaptive analysis method, an analysis system, a medium and a product, and relates to the field of energy analysis. By implementing the application, the preset energy model general library comprises comprehensive modules from energy production, conversion, consumption to balance, and the analysis system can automatically screen the related analog variable set and analog variable calculation rule set from the preset energy model general library according to the specific energy analysis target; and a targeted energy target analysis model is constructed. The adaptive method can flexibly meet the analysis requirements of different regions, especially regions with complex energy systems, such as Ordos, and avoids the problem that a traditional standardized analysis framework is difficult to completely describe region features. Meanwhile, through quantitative calculation of the energy target analysis model, the analysis system can obtain a more accurate and reliable analysis result, and scientific decision support is provided for clean and efficient development of a regional energy system.

The invention relates to the technical field of nuclear energy simulation, particularly provides a nuclear energy field HMI joint simulation method and system based on network communication, and aims to solve the problems that in the simulation process, data synchronization delay is high, an HMI designer cannot accurately map the internal state of a PLC, and a simulation result is distorted. In order to achieve the purpose, the simulation method is applied to the PLC simulator and comprises the steps that a simulation task sent by an HMI designer through a pre-developed service gateway is received, the simulation task comprises a simulation control program and a simulation test case set, and the simulation test case set is generated based on the simulation control program; the method comprises the steps of dynamically allocating computing resources for a simulation task on the basis of a predefined task resource scheduling file and the complexity of the simulation task, running a simulation control program on the basis of a simulation test case set, and sending a simulation result in the running process to an HMI designer through a service gateway every preset time interval. According to the invention, the data communication speed of the HMI designer and the PLC simulator can be obviously improved, and the simulation precision is improved.

The invention relates to the technical field of railway contact net icing tests, in particular to a railway contact net icing reproduction supercooled liquid drop spraying device and a design method, and the device comprises a nozzle array, a water supply pipeline, a water tank, a background wind field assembly, an auxiliary wind field assembly and a control system. According to the invention, the M-P distribution spectrum of natural freezing rain can be macroscopically reproduced, so that the icing physical process is highly real, the optimized array layout ensures that the rain field distribution of the test section is uniform, the test repeatability and precision are high, and the real pneumatic environment and liquid drop collision process during train operation can be controlled and simulated through the background wind field. In addition, in cooperation with the auxiliary wind field assembly, accurate control over the end speed when liquid drops impact the contact network is achieved, and the defect that in the prior art, liquid drop impact energy simulation is insufficient is overcome. The railway contact net icing reproduction supercooled liquid drop spraying device provided by the invention is high in design method scientificity and expansibility.

Abstract An AI-based energy edge platform is provided herein with a wide range of features, components and capabilities for management and improvement of legacy infrastructure and coordination with distributed systems to support important use cases for a range of enterprises. The platform may incorporate emerging technologies to enable ecosystem and individual energy edge node efficiencies, agility, engagement, and profitability. Embodiments may forecast, plan for, and manage the demand and utilization of energy in greater distributed environments. Embodiments may use AI, IoT, and technologies that filter, process, and move data more effectively across communication networks. Embodiments of the platform may leverage energy market connection, communication, and transaction enablement platforms. Embodiments may employ intelligent provisioning, data aggregation, and analytics. Abstract 104 110 108 oM Advanced Energy Resources and Systems Data Resources for Energy Edge Orchestration Configured Stakeholder Energy Edge Solutions 112 138 140 114 118 102 130 Energy Energy Intelligent Data Layers Generation Consumption Energy Transaction 144 132 Orchestration Orchestration Enablement Systems 1 / 21 Distributed Ledger and Smart Contract Systems Energy Stakeholder Energy 148 Energy Storage 134 Orchestration Marketplace Digital Twins Adaptive Energy Digital Orchestration Twin Systems 142 136 Energy Delivery 146 Data Integrated 150 Orchestration 147 Microservices Energy Simulation Systems Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence and Automation Systems Modules and Services Al-Based Energy Edge Platform PCT / US2022 / 050932 102 FIG. 1 20 26 21 07 58 30 J ul 2 02 6 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge OrchestrationConfigured Stakeholder Energy Edge Solutions I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems Configurable Data and Intelligence a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2 2 0 2 6 2 1 0 7 5 8 3 0 J u l 2 0 2 6 W O 2 0 2 3 / 0 9 7 0 2 2 Advanced Energy Resources and SystemsData Resources for Energy Edge Orchestration I n t e l l i g e n t D a t a L a y e r s E n e r g y T r a n s a c t i o n O r c h e s t r a t i o n O r c h e s t r a t i o n E n a b l e m e n t S y s t e m s D i s t r i b u t e d L e d g e r a n d S m a r t C o n t r a c t S y s t e m s E n e r g y S t o r a g e S t a k e h o l d e r E n e r g y O r c h e s t r a t i o n A d a p t i v e E n e r g y D i g i t a l O r c h e s t r a t i o n E n e r g y D e l i v e r y D a t a I n t e g r a t e d O r c h e s t r a t i o n M i c r o s e r v i c e s E n e r g y S i m u l a t i o n S y s t e m s Al-Based Energy Orchestration, Optimization Intelligence Enablement Systems a n d A u t o m a t i o n S y s t e m s M o d u l e s a n d S e r v i c e s Al-Based Energy Edge Platform P C T / U S 2 0 2 2 / 0 5 0 9 3 2

The present invention provides a generation method and apparatus for an optimal transformation strategy for building energy, a device, and a medium. An urban building energy simulation result is obtained on the basis of multidimensional data, and a training sample is constructed to perform integrated training on a plurality of machine learning models to obtain a surrogate model, in this way, during subsequent building performance simulation, the surrogate model can be directly used for prediction, so that the processing efficiency is increased; and multi-objective optimization processing is performed on the basis of the surrogate model and a parallel genetic algorithm plugin, so that an optimal transformation strategy for a target building is rapidly generated. Not only is the quantification for a transformation result achieved, but also the generated transformation strategy is more reasonable.

The invention belongs to the technical field of petroleum industry development experiments, and discloses a system and a method for determining a compact / shale reservoir large-liquid-amount energy supplement injection amount, which can perform large-liquid-amount injection fluid energy supplement simulation on core models with different permeability under actual formation conditions. And the displacement pump volume changes at different injection pressures and different injection moments are calculated, and a relation chart between the injection amount and the injection pressure is quantitatively given. And meanwhile, by measuring the nuclear magnetic resonance T2 spectrums at different injection pressures and different injection moments, the dynamic change characteristics of the core microfractures are monitored in real time based on a low-field nuclear magnetic resonance on-line technical means in the fluid injection process. And the on-site injection amount estimation result and the micro-crack dynamic change rule are comprehensively considered, the reasonable injection amount is accurately determined, and a reference basis is provided for compiling a reasonable production working system on an oil field in the later period.

The invention discloses an energy simulation system for electric power standby market transaction, and relates to the technical field of virtual power plant energy simulation. The system comprises an energy system abstraction unit, a simulation equation construction unit, a target function construction unit, an income maximum optimization unit and a scheduling strategy determination unit, the energy system abstraction unit is used for abstracting an energy system composed of electricity standby market participants and an electricity standby market transaction center into a modeling topological structure composed of node objects and flow objects, and the simulation equation construction unit is used for constructing a modeling topological structure for each node object and each flow object. The target function construction unit is used for respectively constructing simulation equations for representing corresponding constraint conditions, the target function construction unit is used for constructing an overall target function, and the income maximum optimization unit is used for solving values of all variables in combination with all the simulation equations by taking the maximum total income in the overall target function as an optimization target; therefore, the optimal energy scheduling strategy of the participants in the power standby market can be easily obtained.

The invention belongs to the technical field of electric vehicle testing, and discloses an endurance test device, system and test method for a new energy power assembly, which are used for an endurance test of the new energy power assembly consisting of an electric drive gearbox and a drive axle. Comprising a test bench, a power energy simulation control device, a resistance simulation loading device, a sensor assembly, a vibration analyzer, a bearing pedestal and a cooling device. The endurance test working condition is formulated according to the real vehicle road spectrum, the first motor and the second motor are controlled to move under different gears, and the endurance test of the electric drive axle is realized by monitoring the drive axle output rotating speed, the drive axle output torque, the motor output rotating speed, the motor output torque, vibration data and the like fed back by the electric drive axle under stable operation. Durability test verification under various working conditions is realized; the test method is high in reliability and high in stability, effective data support is provided for vehicle development, possible failure modes of the power assembly are checked in the test stage, early and reliable fault early warning is achieved, and the product quality is improved.

The invention discloses a spacecraft solar panel battery pack energy simulation system and method. The spacecraft solar panel battery pack energy simulation system and the spacecraft solar panel battery pack energy simulation method adopting the spacecraft solar panel battery pack energy simulation system are included. The system comprises a 1553B bus communication module, a battery pack unit and a closed-loop period control unit. And the 1553B bus communication module communicates with the spacecraft main body through a 1553B bus, and can realize loading of different board cards. The battery pack unit communicates with the 1553B bus communication module and comprises a main battery pack and a standby battery pack. The closed-loop period control unit communicates with the 1553B bus communication module and comprises a parameter linkage calculation module and a man-machine interaction module. The method comprises the steps of parameter configuration, testing, data interaction and recording and the like. Through the function simulation of the energy system connected with the spacecraft main body through the 1553B bus, the problems of low configuration flexibility, poor bus compatibility, insufficient parameter simulation precision and the like of the solar panel battery pack in a ground simulation test are solved.

The invention discloses a comprehensive simulation platform for an AC / DC hybrid power distribution network system, and relates to the technical field of electric power engineering. The system comprises a modeling simulation module, a scheduling simulation module, a multi-energy simulation module and a fault simulation module, the modeling simulation module is used for carrying out independent modeling on each region in the AC / DC hybrid power distribution network and establishing an optimal power distribution model, and the modeling simulation module comprises a modeling unit, a reliability simulation unit and an optimization unit. By arranging the modeling simulation module, the simulation platform can carry out simulation experiments of different scenes, each area is independently modeled, the simulation platform is more suitable for power distribution of the corresponding area, the energy utilization rate can be greatly improved, and by arranging the scheduling simulation module and the multi-energy simulation module, the efficiency and reliability of the system are improved. The problems that the simulation result accuracy of an existing power distribution network simulation platform is not ideal enough, and the goodness of fit between a simulation model and the actual situation of each region is not enough are solved.

The present invention relates to the field of artificial intelligence technology, and provides a method, device, equipment and medium for generating an optimal renovation strategy for building energy. On the one hand, based on multi-dimensional data, the energy simulation results of urban buildings are obtained, and training samples are constructed according to the energy simulation results of urban buildings to perform integrated training on multiple machine learning models to obtain a surrogate model. In this way, during subsequent building performance simulations, the surrogate model can be directly used for prediction without the need for long-term energy consumption simulations each time, improving the processing efficiency. On the other hand, multi-objective optimization processing is carried out based on the surrogate model and the parallel genetic algorithm plug-in to quickly generate the optimal renovation strategy for the target building, which not only realizes the quantification of the renovation results, but also does not rely on empiricism, making the generated renovation strategy more reasonable.