1217 results about "Energy source" patented technology

In an approach to a state of health for grid applications, a system includes one or more battery energy storage systems having a plurality of batteries; energy sources; power distribution systems; and computing devices. The computing devices are configured to: for each of the battery energy storage systems: receive battery parameters for each of the batteries from the battery energy storage systems; determine a lithium plating state, a solid electrolyte interface (SEI) thickness, and a dendrite length for each of the plurality of batteries; determine a battery state of health (SOH) for each of the batteries based on at least one of the lithium plating state, the SEI thickness, and the dendrite length; determine a battery charge profile to mitigate aging for each of batteries based on the SOH; and send updated battery parameters and control thresholds for each of batteries to each of the battery energy storage systems.

The invention provides a multifunctional cycle power generation system and method by a gravity lever. The system comprises a supporting rack and a balance weight arranged on the supporting rack and slidably matched with the supporting rack, wherein engines are arranged on one side or two sides of the balance weight; the input shaft of each engine is connected to a transmission shaft; two or more single-directional clutches are fixedly connected to the middle of the transmission shaft; the locking directions of the single-directional clutches are same, gears are fixed to the peripheries of thesingle-directional clutches, and a rack matched with each gear to drive the transmission shaft to rotate is arranged next to each single-directional clutch; at least one pair of racks is arranged on the upper part and the lower part, separately, the racks and the balance weight which reciprocates are in driving movement and the balance weight is arranged on the supporting rack to swing through a lifting mechanism in a reciprocating manner. As the balance weight which swings in the reciprocating manner pulls the racks to drive the transmission shaft to rotate in the single direction, multiple engines can be driven synchronously to generate electricity synchronously, and the power needed by a supporting rack lifting device is alleviated greatly by means of a swing mode like to a lever, so that the energy sources are saved and the power generation efficiency is improved greatly.

The invention discloses a water-wind-light combined intelligent control system based on multi-energy coordinated control, and belongs to the technical field of multi-energy coordinated control, and the system comprises the steps: firstly collecting environment and operation parameters of wind power, photovoltaic and hydroelectric equipment, and carrying out the preprocessing of the environment and operation parameters to form a structured data set with a space-time label and a dynamic sampling identifier; performing space-time correlation analysis on the data set, constructing a wind power fluctuation and hydropower regulation margin real-time response matrix and a photovoltaic output attenuation and hydropower storage capacity compensation time sequence correlation model, and quantifying the multi-energy dynamic complementation degree and grading the data credibility through a two-dimensional coupling algorithm; then combining with a historical meteorological scene association rule base, constructing a water-wind-light combined power supply capability prediction model containing an energy characteristic mutual compensation coefficient, and generating a hierarchical regulation and control strategy with a space-time priority; and finally, executing a regulation and control strategy to complete parameter adjustment, continuously monitoring through closed-loop feedback, and triggering multi-energy collaborative complementary regulation when the single energy regulation capability is saturated, thereby realizing water-wind-light efficient collaborative control.

An electrical line selection system comprising a circuit module configured to connect energy sources with multiple line outputs. The circuit module has a number of inputs configured to connect to energy sources, including rechargeable battery systems, and a number of outputs configured to connect with other electrical systems such as other battery systems, loads, charging sources, and various AC or DC power supplies. A switching circuit is contained by the circuit module and a controller manages the switching circuit based on desired connections and strategies for managing power supplies and current sinks.

The invention discloses a fuel cell hybrid electric vehicle power distribution method based on heuristic action planning deep reinforcement learning. The method comprises the following steps: establishing a power distribution system model of a fuel cell hybrid electric vehicle equipped with a lithium battery and a super capacitor; a power layered structure is provided, a deep reinforcement learning model of the fuel cell hybrid electric vehicle is designed, a probability transfer matrix of required power is constructed, and model training is performed in a data driving mode; designing a reward function by adopting an equivalent consumption minimum strategy, and guiding optimization of an energy management strategy by fuel economy; the motion space of deep reinforcement learning is improved by adopting heuristic planning, and smooth output of the fuel cell is kept on the premise of reducing equivalent hydrogen consumption. According to the method, power distribution of the three-energy-source fuel cell hybrid electric vehicle can be achieved in a complex and random driving environment, hydrogen consumption is reduced, dynamic adaptability to different driving conditions is improved, and meanwhile the method has the potential of real-time application.

The invention relates to the technical field of nuclear reactor safety, and particularly discloses a reactor waste heat export, recovery and comprehensive utilization system and method based on a heat pipe, and the system comprises a nuclear energy generation system, a secondary loop energy conversion system, a primary loop waste heat discharge system, a secondary loop waste heat discharge system, and a waste heat recovery and comprehensive utilization system. According to the waste heat recycling system, the heat pipe can be used for heat transfer and storage under the peak regulation operation condition, the nuclear heat use efficiency is remarkably improved, the requirements of various types of energy sources such as electricity and heat are met, and passive export of reactor core waste heat can be achieved through multi-natural-circulation coupling cooperative operation under the condition of a whole-field outage accident. By means of the efficient heat transfer characteristic and the modularization characteristic of the heat pipes, independent operation of the heat pipes can be achieved, the problem of single-point failure of the system can be avoided, meanwhile, separation of a reactor coolant and a cooling medium of a waste heat removal system can be achieved, the inherent safety of a nuclear reactor is remarkably improved, and the requirements of multi-purpose scenes are met; and the purpose of fully utilizing resources is achieved.

The invention relates to an integrated energy system optimization method considering a carbon emission reward and punishment mechanism and shared electrochemical energy storage, and the method comprises the following steps: carrying out the modeling of an integrated energy system which comprises energy supply, energy conversion, load and shared electrochemical energy storage; constructing a peak-flat-valley period stepped carbon emission mechanism considering the carbon emission difference of different energies and a dynamic carbon price factor, and determining a corresponding carbon transaction cost / reward according to the total carbon emission of the integrated energy system in a scheduling period; based on a capacity leasing and power service mechanism, modeling is carried out on the cost of the shared electrochemical energy storage mode; an optimization scheduling problem is constructed by taking system operation cost minimization and clean energy utilization rate improvement as targets; and solving the optimization scheduling problem to obtain an optimal output scheme and an energy storage charging and discharging strategy of each energy device in the integrated energy system, thereby realizing optimization of the integrated energy system.

The invention belongs to the technical field of multi-energy micro-grid system optimization scheduling, and particularly relates to a multi-energy micro-grid distribution robust low-carbon economic scheduling method based on deep learning, electronic equipment and a medium. According to the method, a mathematical model of a multi-energy micro-grid system is established according to coupling characteristics of various energy sources among power systems. In order to improve the economical efficiency and the low-carbon property of the system, a load demand response mechanism and a carbon transaction mechanism are adopted, and an electric heating load demand response model and a reward and punishment type stepped carbon transaction model are constructed. In order to solve the wind and light uncertainty of the integrated energy system and improve the robustness of the system, a scene set of uncertain variables is generated by using a conditional generative adversarial network in deep learning, and the generated scenes are clustered by using a K-means clustering method to obtain typical scenes. In order to obtain more real probability distribution, a fluctuation range of a typical scene is constrained by using a comprehensive norm, and a probability distribution fuzzy set of uncertain variables is obtained. And based on the constructed fuzzy set, the demand response model and the reward and punishment type stepped carbon transaction model, a two-stage distribution robust low-carbon economic optimization model of the multi-energy microgrid is established, in the first stage, an energy storage equipment start-stop plan of the system is determined, and in the second stage, an initial plan is adjusted and supplemented after uncertainties are revealed. And finally, carrying out iterative solution on the established model by utilizing a column and constraint generation method to obtain an optimal scheduling scheme, thereby ensuring the low-carbon property, the economical efficiency and the robustness of the system.

The invention discloses an energy control method and device for a flying vehicle, electronic equipment and a readable storage medium. A solar cell layer, a heat insulation layer and a thermoelectric power generation layer are sequentially integrated on the surface of the flying vehicle from top to bottom, and the method comprises the steps of obtaining first electric energy converted by the solar cell layer in response to the fact that the flying vehicle is located in a light environment, and obtaining second electric energy converted by the heat insulation layer in response to the fact that the temperature difference between the flying vehicle and the external environment is larger than a first preset temperature difference threshold value; acquiring second electric energy converted by the thermoelectric power generation layer; performing voltage conversion on the first electric energy to obtain first target electric energy, and performing voltage conversion on the second electric energy to obtain second target electric energy; charging a battery of the flying vehicle based on the first target electric energy and the second target electric energy; the electrical energy stored in the battery is distributed to the electrical load based on an energy consumption demand of the electrical load of the flying vehicle. The technical problem that the energy source of the flying vehicle is single is solved.

The invention discloses an active power distribution network power flow optimization method based on a large language model, and belongs to the field of power system optimization. The method comprises the following steps: firstly, realizing optimal power flow problem modeling according to topology and equipment parameter data of an active power distribution network to be subjected to power flow optimization; designing structured cue words through an optimal power flow problem, and driving a large language model zero sample to generate a diversified heuristic algorithm initial population; and then a thinking chain evolutionary strategy is adopted, calculation errors serve as judgment criteria, another large language model is guided to simulate selection, intersection and mutation operation to achieve heuristic algorithm iterative optimization, output needed by all distributed energy sources of the active power distribution network is obtained based on the heuristic algorithm with the minimum calculation error, and power flow optimization of the active power distribution network is completed. According to the method, the core problems of low design efficiency and high dependence on expert experience of a heuristic algorithm in the complex optimal power flow problem of the active power distribution network are solved, and automatic generation of a high-quality algorithm can be realized for a user-defined problem scene.

The invention relates to an electric power energy labeling method and system, and the method comprises the steps: carrying out the preprocessing of multi-mode original data in an electric power system, obtaining the cleaned preprocessing data, and enabling the preprocessing data to comprise text data, image data, time sequence signal data and audio data; the preprocessed data is dynamically bound based on a space-time-event three-dimensional rule, a structured multi-modal data card is generated, and the multi-modal data card takes a device ID-timestamp-event type as a unique identifier and comprises a text abstract, an image thumbnail, a time sequence curve fragment and an audio waveform; based on the multi-modal data card, intelligent labeling is carried out in a man-machine cooperation mode, and an initial label set is obtained; the initial label set is dynamically optimized, label errors are corrected, a high-quality labeling result is obtained, and the high-quality labeling result is stored in a structured mode and output to a downstream application system through an API interface.

The present specification proposes a method and an apparatus for managing energy information in a next-generation wireless communication system. A next-generation wireless communication system including a 5G system may have defined therein an energy information repository function (EIRP) having a new network function capable of: exposing energy information to an AF; collecting information regarding energy of the AF; and storing and managing the energy information. The EIRF may provide energy information of a UE to the AF of a third party, and the AF may acquire energy information from the 5G system and monitor the acquired energy information. In addition, the AF may perform a system configuration based on energy efficiency, such as charging or restricting a service according to the energy information. Also, by the function, the AF may adjust service provision such as video playback by checking energy source information or carbon emission information.

The invention relates to the field of electrical energy, and discloses an intelligent anomaly identification and recovery method for electrical energy time sequence data. Comprising the steps of collecting and preprocessing multi-dimensional time sequence data of a power terminal; local and long-term features are extracted by combining a periodic attention mechanism through a feature extraction module fusing a time convolutional network and a Transform; a residual self-supervised classifier is used for identifying multiple types of anomalies such as missing, jumping, drifting and sudden rising; the abnormal segments are repaired in a context interpolation and period fitting combined mode, and dynamic weighted reconstruction is achieved through a deformable time window; after restoration, a credibility scoring mechanism based on residual amplitude, period consistency and classification confidence is introduced, high-risk marking is carried out on low-confidence fragments, and manual rechecking or system correction is triggered; and self-adaptive updating of the model is realized through historical feedback.

The invention relates to the technical field of hybrid electric vehicle energy management, in particular to a hybrid electric vehicle layered reinforcement learning energy management method considering energy source life and energy consumption optimization. The method comprises the following steps: establishing an energy management system model and an energy source degradation model; energy source physical characteristics are analyzed, demanded power is processed in a layered mode, and an energy management learning strategy based on historical data is constructed; and energy management is implemented by combining the demand power change, the lithium battery, the super capacitor SOC and the degeneration degree of the energy source. Fuzzy filtering is adopted to shunt required power, a high-frequency peak value is borne by a super capacitor, and low-and-medium-frequency power is proportionally distributed by a lithium battery and a fuel battery according to the degradation degree; energy source degradation and deep reinforcement learning are fused, related parameter weighting is introduced into the ECMS, and lithium battery charging and discharging current is restrained. According to the method, comprehensive energy consumption can be reduced, energy source degradation is slowed down, the working condition application range is widened, overcharge and overdischarge of the lithium battery are avoided, the service life of the lithium battery is prolonged, and the SOC of the energy storage element is stabilized in a reasonable interval.

The present disclosure relates to an apparatus for powering an implant for a human patient and a method for powering an implant for a human patient. Wherein said apparatus comprises an implantable energy source for providing energy to the implant, an energy provider connected to the implantable energy source and connected to an energy consuming part of the implant, the energy provider being configured to store energy to provide a burst of energy to the energy consuming part, wherein the energy provider is configured to be charged by the implantable energy source and to provide the energy consuming part with electrical power during startup of the energy consuming part.

A method for charging a battery pack via an offboard energy source uses an interleaved boost converter and closed-loop control. The energy source outputs a charging current via a DC charge port during a direct current fast-charging (DCFC) process. A controller detects a voltage disparity condition in which a voltage capability of the battery pack exceeds a voltage capability of the energy source. In response to this condition, a rise of the charging current over time is recorded as a current trajectory and an open-loop equivalent time constant is extracted from the current trajectory. A time constant of the PI control block is set substantially equal to the equivalent time constant. The PIM is controlled in closed-loop using proportional-integral control. The charging current is controlled in a continuous current conduction mode during the DCFC process.

The invention discloses a new energy high-voltage direct current protection device comprehensive test platform, and relates to the technical field of new energy high-voltage direct current system core protection device test, and the platform comprises a power supply and energy storage module which is used for converting a 380V alternating current into a stable and adjustable direct current and storing the stable and adjustable direct current as an energy source required by a high-voltage large-current test, different test voltage requirements are met through series-parallel topology switching; and the power control and load simulation module is used for controlling on-off and adjustment of current in the test loop. By adopting the modular combination design of the super-capacitor energy storage unit, the adjustable pulse inductor and the load module, the comprehensive compatibility of high-voltage direct-current protection devices such as a relay and a fuse in various test scenes such as short circuit resistance, electric service life and limit on-off is realized, meanwhile, the system can work only by being powered by a conventional 380Vac laboratory, and the test efficiency is greatly improved. The method does not depend on an industrial high-voltage power grid or a special transformer, greatly reduces the equipment deployment threshold, and improves the test response efficiency.

Described are devices and methods for administering targeted ultrasound therapy. The device consists of a wearable housing designed to conform to a part of the user's body, with an array of ultrasound transducer units on the skin-facing side. These transducers can generate ultrasound therapy to a target therapy area of the user, with frequency, intensity, treatment area, and duration parameters optimized for a therapeutic application. Incorporated within the device is a communication system, an energy source, and a processor. The processor's role is to execute instructions, including assessing the user's health status based on received data, processing and analyzing ultrasound data to gauge transmission quality, determining if the current transmission quality is within thresholds, initiating ultrasound therapy when the conditions are right, and adjusting ultrasound therapy parameters real-time or near real-time if needed during treatment. The real-time or near real-time adjustment is made through various parameters like pulsing frequency, pulse train frequency, the number of treated spots, duration, and treatment zone area. This device provides a personalized, adaptive approach to ultrasound therapy, optimizing the treatment process for each individual user.

Methods, vehicle systems, and vehicles are provided that are capable of managing communication between a vehicle and a portable energy source (PES) coupled to the vehicle. The vehicle systems include a vehicle battery configured to provide electrical power to a propulsion system of the vehicle and a vehicle controller that is configured to establish two-way data communication between the vehicle controller and a PES controller of the PES, determine an energy transfer mode for transferring electrical power between the vehicle battery and a PES battery of the PES, initiate electrical power transfer between the vehicle battery and the PES battery in accordance with the energy transfer mode while the vehicle is being propelled by the propulsion system, receive a status of the PES battery from the PES controller, and adjust the electrical power transfer between the vehicle battery and the PES battery based on the status.

Embodiments that provide advanced charging of energy source arrangements for energy storage applications are disclosed. The embodiments can be used within energy storage systems having a cascaded arrangement of converter modules. The embodiments can include the application of pulses to an energy source of each module of the system. The pulses can be applied for a duration sufficient to initiate an electrochemical reaction. Feedback based pulse control embodiments are also disclosed.

Disclosed is a method for constructing an optimal scheduling model of an integrated energy system considering virtual thermal storage, which relates to the technical field of electric power systems. The method includes: establishing an operation model of an apparatus, a demand response model of an energy load, a charging model of an electric vehicle, and an energy flow model of a heat supply network of the virtual thermal storage in the integrated energy system; processing, according to a second-order cone relaxation method, a direct current power flow model of a power distribution network, and constructing the optimal scheduling model of the integrated energy system by taking minimization of total cost of an energy operator as an objective, thereby coordinately and optimally scheduling a plurality of energy sources.

The invention provides a rural micro energy grid optimization scheduling system and method based on self-adaptive dynamic planning, and belongs to the field of distributed energy management and intelligent power grid scheduling. A multi-period optimization model is established for the state of the rural micro energy network by using a Markov decision process, a multi-period optimization scheduling scheme is obtained by using an adaptive dynamic programming algorithm and combining a piecewise linear function approximation value function, and a distributed energy unit, an energy storage unit and an electric vehicle unit are scheduled by using the multi-period optimization scheduling scheme. According to the method provided by the invention, real-time online optimization of the state of the micro energy network is realized, dependence on short-term prediction information is reduced, the problem of dimension disaster in traditional dynamic planning is avoided, and global coordinated optimization scheduling of each distributed energy source, each electric vehicle unit and each energy storage unit in the micro energy network is realized.

An example operation may include one or more of training at least one of an AI model using a neural network training capability with at least one of charging data of energy sources, vehicle location data, and energy availability data, to determine an amount of energy to be stored, determining energy-related data of an EV associated with a location and of an energy storage system at the location, determining an amount of energy to be store in at least one of the EV and the energy storage system at the location and a future point in time to store the energy based on execution of the at least one AI model on the energy-related data, and instructing at least one of the EV and the energy storage system to perform a charging operation based on the amount of energy and the future point in time.

The invention belongs to the field of power electronic technology and new energy grid-connected control, and particularly relates to a cooperative control system and method for parallel operation of multiple new energy inverters. The method comprises the following steps: firstly, establishing a small signal model of an inverter parallel system, and analyzing dynamic characteristics of the system under power disturbance; secondly, realizing power decoupling and current sharing control based on a frequency-power droop characteristic; furthermore, coordinated operation of multiple energy sources such as photovoltaic energy and energy storage is realized by monitoring the phase of the direct-current bus voltage and the alternating-current side voltage in real time; the method has high engineering applicability, and high-speed real-time communication between parallel units is not needed; the virtual impedance parameters Rv and Lv have clear physical significance and are easy to preliminarily set according to line parameters; the calculation of the dynamic matching self-adjusting module is linear operation, the requirement for the computing power of a processor is low, and integration and implementation on an existing inverter control platform are facilitated.

A resilient on-site microgrid system includes a multiport power router directly connected to various energy sources, including batteries, renewable energy sources, and broader grid power, as well as various loads, including electric vehicle chargers. The multiport power router dynamically adjusts power provided from the various power sources and to the various loads, especially to power devices in a nearby facility. The microgrid system includes various bypass systems allowing for powering of critical loads in the event of failure of individual components or pathways within the microgrid system.

Methods and systems for processing semiconductor workpieces are provided. In one example, a system includes one or more laser source(s) having emission parameters configured to induce a nonthermal lattice modification in a semiconductor workpiece and one or more energy source(s) having different emission parameters relative to the laser source(s). The system is configured to induce a treatment region in the semiconductor workpiece with a laser emission from the laser source(s). The system is further configured to induce a damage region at the treatment region with an energy exposure from the energy source(s). In some examples, the system is further configured to perform a pre-separation treatment process on the damage region and, subsequent to the pre-separation treatment process, separate the semiconductor workpiece along the damage region using a removal process to produce one or more semiconductor die.

A hybrid aerial hydro drone includes a body with a plurality of hydraulic thrusters supported on an outer surface of the body and configured to propel the body in a marine environment. The drone also includes a plurality of rotor arms arranged on the body, each rotor arm comprising a rotor system configured to propel the body in an aerial environment. Each rotor arm is deployably configured between a deployed position in which the rotor systems are extended from the body for aerial traversal, and a folded position in which the arms are hydrodynamically folded behind the body for marine traversal. The body also includes a controller, an energy source, a main ballast chamber and a pump with snorkel for operation of the drone.

The invention belongs to the technical field of comprehensive energy system optimization and intelligent control, and particularly relates to a comprehensive energy system demand response self-adaptive control method for multi-energy coordinated regulation, which comprises the following steps: identifying multi-energy response resources; performing multi-energy demand response collaborative decomposition; and closed-loop adaptive adjustment and excitation correction: in the instruction execution process, monitoring the deviation between the actual response and the expected response of each energy source in real time, dynamically generating a compensation control instruction based on the deviation and carrying out online correction on excitation parameters so as to realize the closed-loop adaptive control of the response. According to the method, the sensitivity and prediction precision of the system to load change can be remarkably improved, and the flexible regulation and control capability and response stability of the integrated energy system are enhanced from the source.

The invention discloses an optical storage diesel energy management system and method. The system comprises a photovoltaic power generation system, an energy storage system, a diesel power generation system, an alternating current bus, a load and an energy management controller. The photovoltaic power generation system, the energy storage system, the diesel power generation system and the load are all electrically connected with the alternating current bus, and the photovoltaic power generation system, the energy storage system and the diesel power generation system are all in communication connection with the energy management controller; and the energy management controller controls the operation states of the photovoltaic power generation system, the energy storage system and the diesel power generation system according to the photovoltaic power generation power of the photovoltaic power generation system, the total load power of the load, the energy storage charge state of the energy storage system and a priority control strategy. According to the invention, the photovoltaic power generation system is directly and electrically connected to the AC bus, so that the photovoltaic power loss can be avoided, the system operation efficiency is improved, and the real-time cooperative control of three paths of energy sources of the photovoltaic power generation system, the energy storage system and the diesel power generation system is realized through the photovoltaic power generation power, the total load power and the energy storage charge state.

The invention relates to the technical field of resource recovery, and provides a novel method for efficiently extracting gold. The method provided by the invention comprises the following steps: mixing tridecane and a gold-containing solution, forming micro-droplets under the ultrasonic action, and extracting Au (III) in the gold-containing solution. Au (III) in water is reduced through superoxide free radicals and electrons generated on the micro-liquid drop-oil interface under the ultrasonic action to generate Au (0) precipitates, and therefore efficient extraction of Au (III) is achieved. The method provided by the invention only needs to use commercially available tridecane and ultrasound as unique energy sources, and has the remarkable advantages of simplicity and convenience in operation, low cost and no secondary pollution. Results of the embodiment show that the method provided by the invention has a good removal effect on gold-containing solutions with the concentration of 0.01-1 mM and the pH value of 1-10, and the removal rate of gold can reach 95% or above.