5833 results about "Energy storage" patented technology

The invention discloses a predictive maintenance method for an optical storage and charging integrated power station based on deep learning, and the method comprises the steps: constructing an efficient equipment state evaluation and prediction model based on multi-source data fusion, an intelligent prediction algorithm and a closed-loop optimization feedback mechanism, collecting multi-source data, and carrying out the fusion processing, an improved Attention-LSTM model is utilized to evaluate and predict the state of equipment, a transfer learning method is adopted to improve generalization ability, Bayesian optimization and an adaptive sliding window technology are combined at the same time, dynamic threshold adjustment is performed, a deep reinforcement learning algorithm based on a Markov decision process is adopted to optimize a maintenance strategy, and the maintenance efficiency is improved. Weibull distribution is introduced for failure probability modeling, the maintenance cost and the fault risk are balanced, continuous optimization and dynamic adaptive adjustment of a predictive maintenance scheme are realized through a closed-loop feedback mechanism, the prediction accuracy and the intelligent level of maintenance decision are remarkably improved, planned maintenance and sudden fault maintenance are reduced, and the maintenance efficiency is improved. And the reliability of the charging station is improved.

The invention discloses a wind-light-hydrogen multi-energy complementary system cooperative operation optimization and comprehensive benefit evaluation method, which relates to the technical field of electric energy storage, and comprises the following steps: constructing a hybrid power flow model containing electricity, hydrogen and heat coupling, taking whole life cycle cost and new energy consumption as double targets, introducing grid-connected and off-grid risk constraints, and optimizing equipment capacity configuration; a scheduling baseline and an intra-day dynamic correction strategy are formulated in the day-ahead stage, and hybrid energy storage cooperative control is combined to improve the response speed and flexibility of the system to wind and light fluctuation; a peak regulation and frequency modulation mode is switched according to the power grid state, a power response model is established, fluctuation is stabilized through hydrogen energy storage, the stability of the power grid is enhanced, and auxiliary service benefits are created; the performance of the system is evaluated from the three dimensions of efficiency, economy and interactivity, dynamic weight and Monte Carlo simulation optimization are utilized, system parameters are continuously optimized through a feedback mechanism, and the self-evolution ability is formed. The problem that system instability and economy are difficult to take into account due to wind and light fluctuation is solved.

An electrified fire fighting vehicle includes a chassis, a front axle coupled to the chassis, a rear axle coupled to the chassis, a water pump, an energy storage system, an engine, an electric motor coupled to the engine and the energy storage system, and a power divider positioned between the electric motor, the water pump, and the rear axle. The power divider facilitates selectively driving the water pump and the rear axle with the engine and the electric motor.

A system and method generate a trip plan for a trip of a vehicle system along a route. The usage of an engine during the trip is determined based on engine operational parameters, energy storage device operational parameters, and one or more objectives of the trip desired to be achieved. The usage of the energy storage device during the trip is also determined based on the engine operational parameters, the energy storage device operational parameters, and the one or more objective, including when to charge or discharge the energy storage device during the trip.

The invention discloses an acoustic emission intelligent detection method and system for hydrogen-induced damage of a high-pressure hydrogen system, and the method comprises the steps: collecting a system operation signal through an acoustic emission sensor, carrying out the combined preprocessing of variational mode decomposition and adaptive wavelet threshold noise reduction, restraining noise, constructing a lightweight MobileNet-TCN network, carrying out the deep feature extraction, and carrying out the detection of the hydrogen-induced damage of the high-pressure hydrogen system. GRU and a three-dimensional point cloud technology are fused to realize submillimeter-level positioning of an acoustic emission source, a big data damage case library is associated based on an acoustic emission parameter accumulation model, dynamic assessment and early warning of damage risks are realized, multi-physics field monitoring data are combined, damage classification is optimized through a GCNs (Graph Convolutional Networks), and the above processes are systematically integrated. And full-chain intelligent processing from signal acquisition to risk early warning is completed. The scheme has the advantages of strong anti-interference capability, submillimeter positioning precision, high edge end reasoning efficiency, high damage classification accuracy and dynamic early warning capability, and is suitable for safety monitoring of hydrogen energy storage and transportation equipment.

The invention discloses a rock burst global monitoring and dynamic and static far and near field cooperative early warning method and system, and the early warning method comprises the steps: determining a stope space key monitoring region and a stress wave type based on a dynamic load stress wave far field generation and propagation mechanism, delineating a working face surrounding rock high-stress region, and analyzing the structural characteristics of a rock stratum. Arranging a micro-seismic sensor in a far-field key area, and obtaining parameters such as seismic source fracture size, energy and magnitude through waveform inversion; an acoustoelectric system is arranged in a near-field high-stress area, coal rock fracture characteristics are dynamically monitored, and the static load energy storage state of surrounding rock is quantitatively analyzed. And in combination with a stress wave propagation attenuation coefficient, a far and near field fusion early warning criterion under the action of dynamic and static energy superposition is established, and advanced accurate early warning of the rock burst is realized through collaborative analysis of multi-source monitoring data. The disaster-pregnant space global monitoring technology fusing earthquake, sound and electricity is provided, the chain evolution disaster-causing process of dynamic load generation, cross-space propagation and working face surrounding rock damage is considered, and the accuracy of rock burst early warning can be remarkably improved.

A vehicle includes a chassis including a first frame rail and a second frame rail, a tractive element coupled to the chassis, a drive motor configured to drive the tractive element to propel the vehicle, and an energy storage system. The energy storage system includes a first battery module and a second battery module. The energy storage system is selectively reconfigurable between (a) a first configuration in which the first battery module and the second battery module each provide electrical energy to the drive motor and (b) a second configuration in which the first battery module is removed from the vehicle and the second battery module provides electrical energy to the drive motor.

Disclosed herein are systems and methods for energy management. A system, such as a vehicle, includes a plurality of energy storage units that include a supercapacitor and an electrochemical battery. The system includes an energy controller that tracks historical power draw from the plurality of energy storage units over time in power tracking data, and that identifies a power draw based on the power tracking data. The energy controller switches between a first configuration and a second configuration based on the identified power draw. The first configuration is configured for drawing power from the electrochemical battery and disconnecting from the supercapacitor, while wherein the second configuration is configured for drawing power from the supercapacitor and disconnecting from the electrochemical battery.

A combined floor assembly and energy storage device for an electrically driven passenger car includes a floor assembly on the lower face of which an energy storage device of an electric drive of the passenger car is arranged. A holding element, by which a rear end region of the energy storage device is held on the lower face of the floor assembly, and a rear cross-member, which is arranged on the lower face of the floor assembly and behind the energy storage device in the vehicle longitudinal direction are provided. In order to provide a combined floor assembly and energy storage device which offers especially rigid support for the rear cross-member even in a vehicle with a purely electric drive and in which, additionally, the energy storage device is fixed to the rear end on the lower face of the floor assembly in a particularly stable manner, the energy storage device is secured to the rear cross-member by way of the holding element.

An electric vehicle charging station for charging electric vehicles includes a plurality of energy storage reservoirs configured to receive and store energy from one or more power sources and / or one or more power generators; one or more power heads for charging the electric vehicles at the electric vehicle charging station, the multiple power heads receiving electrical power from the plurality of energy storage reservoirs, the multiple power heads each being configured for releasably connecting to each of the electric vehicles for charging at the electric vehicle charging station; and a computer control system configured to monitor a charging demand at each of the one or more power heads and to connect one or more of the plurality of energy storage reservoirs to one or more of the power heads based on the charging demand of the one or more power heads.

The invention provides an underground heat supply system based on an air energy heat pump as a heat source and a remote monitoring method, and the system comprises a heat source dynamic tuning subsystem which carries out the dynamic parameter optimization processing of environment temperature and energy storage state data, and obtains an air energy heat pump operation instruction; first characteristic adjustment of air energy heat pump output is formed through an air energy heat pump operation instruction, and matching of the temperature of an energy storage water tank and an environment heat source is achieved. The underground hot air accurate adjusting subsystem obtains underground real-time temperature data, the underground real-time temperature data is subjected to spatial thermal field calculation processing to obtain air volume demand parameters, and dynamic balance between the air supply intensity and the underground thermal environment is formed; and the multi-stage cooperative control center subsystem performs three-stage logic verification processing on the signals of the air energy heat pump operation instruction and the fan frequency instruction to obtain an equipment regulation and control instruction set. The underground intelligent heat supply system of the air energy heat pump, which has the environment self-adaption capability, the dynamic balance capability of a thermal field and the remote monitoring characteristic, is constructed.

The invention discloses a semi-submersible wave energy-wind energy integrated power generation platform and a damping regulation and control method of a damping regulation and control system of the semi-submersible wave energy-wind energy integrated power generation platform. The platform comprises a semi-submersible wind driven generator platform, a wind driven generator set, a wave energy power generation device, an energy storage system, a sea area detection system and the damping regulation and control system. The wave energy power generation devices are divided into two groups on the inner side and the outer side of the platform, each wave energy power generation device comprises a platform inner side wave energy power generation device and a platform outer side wave energy power generation device, and each wave energy power generation device comprises a swing arm floater, a universal hinge, a connecting arm and a damping adjusting module. The semi-submersible wind power generation device and the wave power generation device are combined, and offshore renewable resources are comprehensively utilized; the six-buoy design is adopted, buoyancy is dispersed, stability and safety are improved, and meanwhile space is provided for a wave power generation device; the floaters are symmetrically arranged in a hexagonal shape and carry a damping regulation and control system, and the whole structure is more easily stabilized by adjusting the damping of the floaters in all directions.

The invention discloses a cooperative scheduling method for a zero-carbon park complementary energy storage system, and the method comprises the steps: enabling an electric energy quality index to be explicitly incorporated into an optimization target through multi-source resource dynamic modeling and scene prediction, and building a strong coupling relation between a physical constraint and a scheduling decision; the hierarchical execution mechanism gives consideration to global optimization and local quick response, realizes undisturbed switching under abnormal working conditions, forms a prediction-optimization-execution-feedback closed-loop control system, and can accurately describe physical connection and electrical characteristics of a park power grid by establishing a power distribution network equivalent model and acquiring topological parameters, thereby realizing the optimal control of the park power grid. And basic network data is provided for subsequent optimization. By determining the controllable resource set and completing topological mapping, the position and the regulation and control range of each device in the power grid can be determined, and mistaken sending or conflict of instructions can be avoided. An apparent power upper limit constraint and SOC dynamic model is established, overload operation of equipment can be avoided, the energy storage charging and discharging capacity can be accurately represented, and the performability of a scheduling scheme is ensured.

A vehicle including an energy storage device and processing circuitry. The processing circuitry detects a charging session being initiated to charge the energy storage device. The processing circuitry further obtains a current state of charge (SoC) associated with the energy storage device and first vehicle usage information that indicates a usage of the vehicle over a historical time-interval. The processing circuitry further predicts vehicle usage over a first time-interval based on the obtained first vehicle usage information and rate the charging session at current time-instance based on the predicted vehicle usage and the current SoC. The processing circuitry further generates an alternate charging plan based on the charging session at the current time-instance being rated suboptimal and outputs the generated alternate charging plan at the current time-instance.

The invention relates to the field of new energy charging, in particular to a main circuit topology based on an integrated over-charging device for light storage and charging and a control method. The system is composed of the following parts: an ACDC module, a charging DCDC module, a photovoltaic DCDC module, a DCAC module and a battery, wherein the battery is used for storing redundant electric quantity and discharging the electric quantity to a charging pile for use; the invention provides a main circuit topology based on direct-current coupling, a very simple network architecture and an AI intelligent algorithm are fused to greatly expand the application scene of optical storage and charging in the overcharging field, meanwhile, a dynamic intelligent algorithm is combined, the dependence of an overcharging station on a power grid is reduced, and through an economic operation strategy, the system is more reliable and reliable. Efficient collaboration and accurate distribution of energy of all links of light, storage, charging and utilization are achieved, and the operation capacity and economical efficiency of a charging station are improved.

The invention provides a wind-light-water storage integrated scheduling method and system based on big data, and relates to the technical field of energy management, and the method comprises the steps: extracting a driving factor of wind-light-water storage data based on a generalized dynamic factor model, and carrying out the dynamic modeling of the driving factor, and obtaining an output state feature graph of a wind power plant and a photovoltaic power station; constructing an edge dependence structure based on a Copula function to obtain a wind-light-water combined space structure diagram; generating an energy storage response strategy sub-graph according to the wind-light-water combined space structure graph, the charge state of the energy storage system and the device degradation parameters; according to the energy storage response strategy subgraph and the load data and fluctuation data of the regional load center, singular spectrum analysis is carried out to extract periodic load characteristics, and a multi-energy output path field is obtained; and performing fuzzy approximate reasoning on the path field to obtain an optimal joint scheduling sequence. According to the method, the whole-process closed-loop optimization of the dispatching of the wind-light-water storage system is realized, and the method has the advantages of high prediction precision, high response speed and high dispatching flexibility.

Systems and methods for battery system management and monitoring apparatus(es) and equipment using a sensor cluster are described. The systems and methods can be used to automatically repair or otherwise address actual and predicted failure modes of the apparatus(es), which include electrical systems, power systems, energy storage systems, and other systems.

The invention relates to the technical field of charging pile management, and discloses a new energy vehicle charging pile operation management system comprising a data acquisition module used for acquiring charging pile operation data and vehicle arrival data; the vehicle priority calculation module is used for calculating vehicle priorities based on the vehicle arrival data and a preset congestion coefficient and generating a vehicle queuing sequence; the scheduling pricing module is used for constructing a state matrix, matching a current operation state, extracting an energy storage control label and a pricing additional parameter, and generating an energy storage power control instruction and a service gear price; the execution control module is used for executing charging power issuing according to the service gear price, the preset station-level power demand and the energy storage power control instruction; and the parameter updating module is used for counting the triggering times of the operation state item and the queuing waiting duration of the corresponding period, and performing regularization adjustment on the pricing additional parameter. According to the invention, integrated management of intelligent scheduling and dynamic pricing based on a multi-dimensional operation state is realized.

The invention provides a constant-heating defrosting system of a heat recovery air conditioner and a defrosting control method and device. According to the system, a compressor, a first electromagnetic valve, a water tank, a first expansion valve, a first one-way valve, a second electromagnetic valve, an outdoor heat exchanger and a four-way valve are connected to form a first heating loop; a compressor, a first electromagnetic valve, a water tank, a first expansion valve, a first one-way valve, a third electromagnetic valve, an energy storage water tank, a fourth electromagnetic valve and a four-way valve are connected to form a first defrosting loop. A compressor, a fifth electromagnetic valve, a second one-way valve, an outdoor heat exchanger and a four-way valve are connected to form a second defrosting loop; and the first heating loop, the first defrosting loop and the second defrosting loop form a single heating water defrosting loop. The problem that in the prior art, in the defrosting process, the comfort experience of a user is affected due to the fact that an air conditioner does not conduct heating is solved.

A mobile security robot includes a human-sized mannequin mounted on a vehicle. A storage unit, mounted on the vehicle, stores security devices and high-powered energy storage devices for facilitating extended patrols without recharge. A video recording system, disposed in the mannequin, continuously records images of a patrol area. Multiple sensors mounted on and proximal to the mannequin generate sensor data based on environmental conditions of the patrol area. A computing system coupled to the sensors processes the sensor data using artificial intelligence models and generates action commands for execution of tasks by actuators including electric motors, robotic arms, and supplementary attachment devices. The electric motors run the vehicle at different speeds with wheel speed feedback based on the environmental conditions and navigate the vehicle along a predefined travel path with object avoidance during patrols. User interface devices facilitate auditory and visual communication with humans in the patrol area.

The invention discloses a double-layer optimization scheduling method considering electricity-storage-carbon cooperation and user demands, and the method comprises the steps: building a constraint model for the dynamic segmented adjustment of a carbon transaction price along with the carbon emission according to the carbon emission quotas of thermal power, wind power and photovoltaic power and based on a reference carbon transaction cost model; taking the lowest comprehensive power generation cost as a target, jointly optimizing output plans of thermal power, wind power, photovoltaic power and energy storage, coupling the constraint model to limit carbon emission of the thermal power generating unit, and constructing an electricity-storage-carbon collaborative optimization model; a demand response mechanism is constructed based on the user energy consumption mode satisfaction degree and the energy consumption cost satisfaction degree, a user load curve is adjusted and optimized through the electricity price, and a user demand optimization model is established; solving the double-layer optimization model hierarchically by adopting an improved algorithm; and compared with a reference carbon transaction model and a stepped carbon transaction model, the constraint force is stronger, and collaborative optimization of power generation economy, low-carbon property and user satisfaction is realized under the condition of meeting system power balance and power grid security constraint conditions.

Provided is a method of operating a hybrid power plant, including energy generating units including a wind park and at least one unit of another type of renewable energy source and including an energy storage system, the method including: creating a power production schedule based on an actual forecast of power production, an actual forecast of energy price and actual hybrid power plant status, the power production schedule including at least scheduled power for points in time in the future; and controlling, during the points in time in the future the energy generating units and the energy storage system based on the power production schedule, the hybrid power plant status at the points in time in the future, in particular energy storage system status, such as to dispatch power according to the power production schedule, but complying with any grid operator reference at the points in time in the future.

The invention relates to the technical field of heat pumps, and discloses a heat pump heating and cooling system adopting phase change energy storage, which comprises an air source heat pump, a phase change energy storage device and a heating and cooling terminal device, the phase change energy storage device comprises two phase change energy storage modules which are arranged in parallel; the refrigerant circulation pipeline is provided with a pressure protection assembly. The system further comprises a defrosting control module, and the defrosting control module is in signal connection with an evaporator frosting sensor of the air source heat pump and an energy storage capacity monitoring unit of the phase change energy storage device. Two modules of the phase change energy storage device adopt gradient temperature configuration and are matched with a multi-channel switching valve, the working state can be flexibly adjusted according to the environment and load requirements, and efficient energy storage and energy release are achieved. During defrosting, the low-temperature module responds preferentially, and the heat supply effect is guaranteed; and the pressure protection assembly monitors the pipeline pressure in real time and releases pressure and slowly releases the refrigerant in time when abnormity occurs, so that the safety and stability of the system are ensured.

The invention discloses an island energy system opportunity constraint weekly optimization scheduling method and system, and the method comprises the steps: converting the opportunity constraint of the actual output of wind and light into a deterministic inequality constraint based on the prediction error probability distribution characteristics of wind power and photovoltaic; according to the obtained wind and light output constraint, a dynamic operation model is established, and waste heat output of the hydrogen fuel cell is coupled with an absorption refrigerator; with the purpose of minimizing the total operation cost of the system, combining the obtained deterministic inequality constraint and the dynamic operation model, defining the power balance constraint of electricity / heat / cold / fresh water, the hydrogen storage tank capacity constraint and the equipment climbing rate constraint, and constructing an optimization model; and solving the optimization model by adopting mixed integer programming to obtain an optimization scheduling scheme. The requirements of electricity, cold, heat and fresh water of an ocean island energy system are met, and meanwhile energy storage and cross-period utilization during wind and light resource enrichment are achieved.

The invention relates to the technical field of automatic control of a power system, discloses a dynamic response optimization and self-adaptive compensation method for primary frequency modulation of a speed regulator of a hydropower station, and aims to solve the problem that the response speed and the operation economy are difficult to consider in a traditional combined frequency modulation strategy. Meanwhile, a dynamic task allocation threshold value is calculated according to the real-time cost of the hydroelectric generating set and the energy storage. Then, by comparing the size of the disturbance with the threshold value, the system autonomously decides: if the disturbance is small, the stored energy independently responds; and if the disturbance is large disturbance, a prospective optimal control strategy is started, a hydroelectric generating set and stored energy are cooperatively allocated, and a frequency modulation task is completed at the lowest comprehensive cost. According to the method, by introducing pre-judgment on disturbance and dynamic evaluation on cost, economical optimal distribution of frequency modulation tasks among different types of power supplies is realized, and the comprehensive frequency modulation performance and economic benefits of the system are remarkably improved.

A lithium ion battery health state estimation method based on time-frequency domain feature decoupling and a dynamic compensation mechanism comprises the following steps: collecting actual data of multiple times of charging and discharging of a lithium ion battery as an initial data set; performing feature mode decomposition on the initial data set, and obtaining frequency domain data through decoupling; the frequency domain data obtained through decoupling and the original time domain data are input into a training model, and the predicted lithium ion battery capacity is obtained; the real-time capacity and the maximum capacity of the lithium ion battery are fed back to the training model, a predicted value of the capacity is obtained after training is completed, and estimation of the health state of the lithium ion battery is achieved. According to the method, time domain signals and frequency domain features in battery operation are fused, and a decoupling feature extraction and time frequency compensation learning mechanism is combined, so that accurate modeling of battery capacity degradation and internal state evolution is realized, and the method can be applied to battery health monitoring and life prediction of electric vehicles, energy storage systems and consumer electronic equipment.

Provided herein are methods of treating a patient comprising providing a medical apparatus comprising an external system and an implantable system, implanting the implantable system, and delivering at least one of power or data to the implantable system with the external system. The external system comprises: at least one external antenna configured to transmit a first transmission signal to the implantable system; an external transmitter configured to drive the at least one external antenna; an external power supply; and an external controller. The implantable system comprises: at least one implantable antenna configured to receive the first transmission signal from the first external device; an implantable receiver; at least one implantable functional element configured to interface with the patient; an implantable controller; an implantable energy storage assembly; and an implantable housing surrounding at least the implantable controller and the implantable receiver. Medical apparatus are also provided.

The invention discloses a composite cold plate-phase change cold storage coupled liquid cooling server heat dissipation device, which comprises a composite plate assembly, the composite plate assembly comprises a cold plate seat, a cold plate module, a phase change cooling module, an input port, an output port and an assembling mechanism, the cold plate seat is internally provided with a supporting and lining groove, and the supporting and lining groove is internally provided with a supporting and lining groove; the phase change cooling module is installed at the lower end of the cold plate module in an embedded mode, the input port and the output port are installed on the upper end face of the cold plate module, the lower end face of the cold plate module is movably connected with the upper end face of the supporting and lining groove, and the cold plate module is connected with an inner cavity of the cold plate base in a sleeved mode. A first connecting pipe is installed between the circulating pump and the output port and used for circulating cooling liquid in the circulating pump, and the cold storage assembly comprises a liquid storage box, a cover plate, cooling fins and a cooling fan. Through the coupling design of the composite cold plate and the phase change material, efficient absorption, dynamic buffering and multi-stage recovery of heat of the server are achieved, and the bottleneck of traditional liquid cooling heat dissipation is broken through.

The invention provides an air energy storage well coated sand layer alternating injection-production instability mode discrimination and evaluation method, which comprises the following steps of: 1, determining an initial state parameter of an evaluation object, and determining flow in experimental evaluation according to a similarity criterion; 2, collecting parameters of two ends of the coated sand filling layer in the experiment process, classifying alternating injection-production instability failure forms of the coated sand filling layer of the air energy storage well, and identifying instability failure modes; step 3, calculating each index according to the collected parameters; and 4, carrying out production regulation and control and coated sand filling layer evaluation according to an index calculation result. According to the air energy storage well coated sand layer alternating injection-production instability mode distinguishing and evaluating method, the stability of a coated sand filling layer in the experiment (production) process is evaluated through a simple method, the underground production state of the coated sand filling layer is simulated, instability mode distinguishing is carried out, and certain guiding significance is achieved for actual well safety production.

The invention relates to the technical field of battery health management, and provides a battery health state estimation system based on multi-scale feature fusion extraction, which comprises a data acquisition module, a feature processing module, a deep learning model module and a result display module, the data acquisition module is used for acquiring battery data in real time; the feature processing module is used for extracting multi-scale features of the battery data; the deep learning module is used for constructing and training a deep learning model and outputting an actual SOH value; and the result display module is used for displaying the actual SOH value. The application is passed. The method has the advantages of high precision and strong robustness, and is suitable for monitoring and estimating the battery health state of an electric vehicle, an energy storage system and other scenes.