491 results about "Energy regulation" patented technology

The present disclosure relates to the technical field of intelligent monitoring and management of power systems, and specifically relates to an intelligent collaborative power consumption regulation and control method, apparatus and system for source-grid-load-storage, an electronic device and a storage medium. Said system comprises an energy regulation and control center and energy regulation and control units provided in microgrids; the energy regulation and control units use a temporal attention mechanism-based LRCN dual-layer network combined model to predict power consumption amounts, so as to generate power consumption surpluses and shortages within a future preset time; and on the basis of the power consumption surpluses and shortages and latest current electricity prices of the microgrids, the energy regulation and control center uses a fusion multi-objective algorithm based on a Pareto front curve and a fuzzy algorithm to generate a microgrid collaborative power consumption regulation and control solution, and sends the regulation and control solution to the energy regulation and control units for execution, so as to ensure the balance of energy supply and demand of the microgrids. Therefore, the present disclosure achieves efficient, intelligent and refined energy management for microgrid clusters, reducing energy consumption and costs, and providing solid support for sustainable development of microgrids.

The present application relates to a multi-terminal linkage energy scheduling method and apparatus. The method comprises: acquiring multi-terminal data, wherein the multi-terminal data comprises power supply side data, power grid side data, load side data, and energy storage side data; on the basis of the acquired multi-terminal data, predicting multi-terminal electricity amount related information within a future preset time period by means of a prediction algorithm, wherein the multi-terminal electricity amount related information comprises photovoltaic power generation related information, power grid power generation related information, power consumption information of a load side device, and electricity charging and discharging related information of an energy storage device; on the basis of an energy efficiency target, acquiring energy regulation information by means of the multi-terminal electricity amount related information; and controlling the energy storage device and / or the load side device on the basis of the energy regulation information. According to the solution of the present application, by means of a multi-party linkage mechanism, a scheduling plan formed on the basis of a preset scheduling target is more suitable for actual requirements and more accurate, and the energy storage device and the load side device can be automatically controlled on the basis of the scheduling plan.

The invention discloses a hybrid energy storage system charging prediction and energy regulation and control method, and relates to the technical field of power systems and energy management, and the method comprises the following steps: obtaining the real-time operation data of an optical storage charging system; by adopting the dynamic regulation and control algorithm and the self-adaptive learning mechanism, the light storage charging system can predict and correct the power change of photovoltaic power generation in real time, the photovoltaic power is utilized to the maximum extent, the power consumption of a power grid is reduced, and the energy utilization efficiency and the economic benefit are improved. Meanwhile, the dynamic charging and discharging strategy based on error correction effectively avoids the problems of overcharging and deep discharging of the battery, prolongs the service life of the battery, and improves the long-term stability and safety of the system. The system optimizes the charging and discharging plan according to the power grid electricity price fluctuation, and combines an early warning mechanism to monitor the battery state in real time, thereby reducing the operation cost, reducing the potential safety hazard, and guaranteeing the efficient and reliable operation in the whole life cycle.

An energy regulation and control method for a hybrid vehicle, comprising: on the basis of real-time driving data and a driving condition standard library corresponding to the hybrid vehicle, determining a current driving condition and a current condition category (S31); on the basis of the current driving condition, the current condition category and road condition information, performing driving condition prediction on the hybrid vehicle to obtain a condition prediction result, the road condition information comprising at least one of the following: real-time road condition data, and predicted road condition data (S32); on the basis of the condition prediction result and a current battery level corresponding to the hybrid vehicle, determining a target energy regulation and control strategy corresponding to a current operation mode of the hybrid vehicle (S33); and, according to the target energy regulation and control strategy, performing real-time regulation and control on an engine output power and a driving motor output power of the hybrid vehicle (S34). The method improves an intelligent level and accuracy of the energy regulation and control method of the hybrid vehicle. Further provided is a vehicle.

The invention provides a distributed energy regulation and control method and system based on 5G network and block chain collaboration, and the method comprises the steps: building an energy block chain-based IES power transaction architecture which comprises a block chain node; docking the regulation and control object with a block chain node in an IES power transaction architecture, wherein the block chain node is used for storing the smart contract subjected to security verification; constructing a distributed energy optimization scheduling model considering the 5G network and a mathematical model of a cooperative scheduling mechanism; and the intelligent contract generates a scheduling instruction according to the distributed energy optimization scheduling model and the mathematical model of the cooperative scheduling mechanism, and the scheduling instruction value is issued to the power generation and utilization unit after passing constraint condition check.

The invention relates to the technical field of energy regulation and control, in particular to an inter-building energy regulation and control method based on the Internet of Things. The method comprises the following steps: predicting and judging whether the actual energy consumption of a building is abnormal or not; when the actual energy consumption is predicted and judged to be abnormal and the maximum energy consumption deviation value is positive, external climate data is associated to determine an execution mode of power dispatching; when the maximum energy consumption deviation value is negative, obtaining an identification type result of the current time period; and determining whether to execute power dispatching control based on the identification type result. By monitoring the energy consumption deviation value of each building in real time, the energy consumption deviation condition of the building in the to-be-monitored range is determined, energy consumption abnormity is found in time, power distribution is optimized, energy waste is reduced, external climate data and building types are associated to dynamically adjust a power dispatching strategy, the energy consumption requirement of the building is judged more accurately, and the energy consumption of the building is improved. Therefore, different environment and energy scheduling requirements can be met, power distribution can be rapidly adjusted, and the stability of energy supply can be ensured.

The invention relates to the technical field of medical equipment, in particular to an ultrasonic soft tissue operation accessory intelligent recognition and energy regulation and control system and method.The ultrasonic soft tissue operation accessory intelligent recognition and energy regulation and control system comprises an intelligent recognition module used for recognizing the type, specification and real-time use state of an operation accessory to serve as an output result; the energy regulation and control module is connected with the intelligent identification module and dynamically adjusts the output parameters of the ultrasonic energy according to the output result of the intelligent identification module; and the man-machine interaction module is respectively connected with the intelligent identification module and the energy regulation and control module and is used for displaying the identification result, the energy parameters and the early warning information. According to the result of the intelligent recognition module, dynamic adjustment of ultrasonic energy output parameters is achieved through the energy regulation and control module, and smooth operation is ensured; when it is detected that the accessory temperature exceeds the preset threshold value or the impedance abnormally and suddenly rises, energy supply is rapidly cut off, the surgical risk caused by energy abnormity is effectively prevented, and the safety of a patient is guaranteed.

The invention discloses an energy regulation and control method for a digital intelligent low-carbon building, and relates to the technical field of energy intelligent control, and the method comprises the following steps: constructing a multi-source feed-forward sensing link, unifying data collection timestamps, fusing people counting data, access control record data and wireless local area network probe data, and obtaining a multi-source feedback sensing link; passenger flow step fingerprints capable of reflecting instantaneous passenger flow change characteristics are generated and used for feedforward input of follow-up dynamic response; and performing crowded wave dynamic tracking based on passenger flow step fingerprints, analyzing a crowd movement track in combination with feedforward input, positioning a high-concentration air quality risk area, outputting a risk arrival time and intensity curve, and generating a feedforward ventilation time history input prediction link. According to the method, people flow changes are sensed and predicted through multi-source feedforward, a ventilation strategy is actively deployed, self-optimization is achieved in combination with feedback correction and closed-loop evaluation, and energy consumption is reduced and the service life of equipment is prolonged while air health and safety are guaranteed.

The invention provides a deep-buried soft rock tunnel supporting structure design method based on energy regulation and control, and belongs to the technical field of tunnel engineering. Comprising the following steps: obtaining components of crustal stress in a large principal stress direction, a middle principal stress direction and a small principal stress direction; manufacturing a rock cylinder test piece and a cube test piece; carrying out a conventional uniaxial compression test on the cylindrical test piece to obtain basic strength parameters of the surrounding rock; carrying out a true triaxial loading and unloading test on the cubic test piece to obtain the ultimate dissipated energy of the surrounding rock; drawing up a tunnel anchor rod supporting structure design scheme; establishing a deep-buried soft rock tunnel calculation model considering the synergistic effect of the surrounding rock and the anchor rod, and calculating the dissipated energy density of the surrounding rock and the absorbed energy of the supporting structure; the instability energy judgment basis of the surrounding rock and the instability energy judgment basis of the anchor rod are calculated; and judging the stability of the surrounding rock and the stability of the anchor rod. The method is suitable for the tunnel in a deep high-energy geological environment, and can reflect the energy driving essence of the instability failure of the high-ground-stress deeply-buried soft rock tunnel.

The invention relates to the technical field of intelligent charging and discharging adjustment, in particular to an intelligent charging and discharging adjustment method and system for an energy storage device based on multiple regions, and the method comprises the following steps: based on the data of energy users in each region, analyzing the power trend of a time period, recognizing and marking abnormal nodes, judging the deviation of a load trend in combination with monitoring and early warning, and optimizing an adjustment sequence; and dynamically balancing capacity distribution, and generating a charging and discharging instruction. According to the invention, real-time data fusion is carried out based on periodic factors and holiday correction, so that abnormal fluctuation and energy consumption trend change in each time period have dynamic identification capability, and advanced identification and linkage of load abnormal omen are realized through trend monitoring and early warning feature construction for load differences among nodes. The energy support distribution is ranked according to the energy storage state and the output capacity, fine matching of task objects and instruction schemes is promoted, the participation sequence of the energy storage units and an energy release window are dynamically optimized, and regional energy adjustment action collaboration is achieved.

The invention discloses an urban carbon emission peak prediction method, and particularly relates to the technical field of carbon emission prediction. A carbon emission data set with high time resolution is constructed, and first K influence factors with the highest contribution degree to a carbon emission peak value are screened based on an adaptive weight attribution mechanism, including extraction of heating system response time and energy scheduling hysteresis characteristics, construction of a carbon emission peak value prediction model, and when a prediction value exceeds a set threshold value, calculation of the carbon emission peak value prediction model is carried out. The method comprises the following steps: automatically adjusting the influence weight of a key factor, calculating a peak confidence interval on a test set, evaluating and optimizing the model performance, finally deploying an optimized model to an urban carbon emission monitoring system, and dynamically updating in combination with a real-time data stream to ensure the accuracy and stability of prediction; according to the method, the accuracy of urban carbon emission peak prediction is remarkably improved, the capability of responding to sudden energy demand increase in extreme weather is enhanced, and scientific support is provided for carbon neutralization policies, energy regulation and control and environment management.

The invention belongs to the technical field of comprehensive utilization of ocean renewable energy sources, and particularly relates to a pilot frequency coupling-based wind wave energy multi-degree-of-freedom broadband control method, which comprises the following steps of: performing frequency domain identification on wind wave environment characteristics, and constructing a wind wave pilot frequency energy coupling model; based on the motion response characteristics of the multi-degree-of-freedom floating platform, designing a pilot frequency energy regulation and conversion mechanism; a full-working-condition dynamic optimization control strategy is adopted, and cooperative operation and energy flow self-adaptive distribution of the wind energy conversion unit and the wave energy conversion unit are achieved. Aiming at the significant difference and relevance of wind energy and wave energy in frequency characteristics, time scale and spatial distribution, a pilot frequency wind wave coupling dynamic model is established, and broadband capture of low-frequency wind-induced and high-frequency wave-induced coupling energy is realized under complex sea conditions through multi-degree-of-freedom motion decoupling and state observation, so that the wind-induced and high-frequency wave-induced coupling energy is obtained. The energy utilization rate, the attitude stability and the structural safety of the system are effectively improved, and good robustness and engineering adaptability are achieved.

The invention discloses a smart community new energy grid management and analysis system, and belongs to the technical field of smart power grid and energy management, and the system comprises a data collection module which is used for collecting photovoltaic power generation, energy storage equipment and user power utilization data in real time; the dynamic modeling module is used for dynamically generating a multi-level energy grid division scheme according to the collected data; the optimization decision module is used for outputting energy regulation and control parameters according to the grid division scheme; and the iterative feedback module is used for monitoring the regulation and control effect and triggering online updating of the model parameters. According to the method, a dynamic grid topology adaptive division mechanism, a multi-source adaptive collaborative optimization algorithm and a pre-verification type network splitting simulation technology are adopted, so that real-time dynamic reconstruction, multi-target joint optimization and millisecond-level security risk prevention and control of a community energy network can be realized; the problems of high transmission loss, response delay, equipment service life reduction and the like caused by traditional static division are effectively solved.

The invention discloses an underground building space interface energy regulation and control method and system based on data processing, and the method comprises the steps: generating an initial design scheme of an underground building space interface according to design parameters including the type of the underground building space interface; calculating underground building space performance indexes of the initial design scheme, and performing underground building space performance evaluation on the initial design scheme by referring to preset underground building space performance indexes; performing multi-target space performance-oriented space interface optimization design on the initial design scheme which does not reach the standard to generate an optimization design scheme of the underground building space interface; and performing underground building space performance evaluation on the optimal design scheme, and outputting the optimal design scheme of the underground building space interface which is evaluated to reach the standard. Optimization design of an underground building space interface is achieved, natural lighting, natural ventilation, energy consumption performance and the like of the underground building are comprehensively optimized, and the environment quality and the energy utilization efficiency of the underground space are improved.

The invention relates to the technical field of monitoring control, and discloses a comprehensive energy management method and system, and the method comprises the steps: obtaining historical energy data, equipment operation parameters and internal and external environment data of a target smart entity, the internal and external environment data comprising building characteristic data, season data, building internal temperature data and building internal humidity data; inputting the historical energy data, the equipment operation parameters and the internal and external environment data into a trained first adjustment model, and outputting a first energy demand result; inputting the building characteristic data and the first energy demand result into a trained second adjustment model, and outputting a second energy demand result; and formulating an energy adjustment strategy based on the second energy demand result. By implementing the method and the system, response and adjustment can be quickly made when environment and energy demand changes, challenges brought by changes of operating environment and building characteristics are effectively handled, and efficient energy utilization and sustainable development of the smart entity are realized.

The invention discloses a welding seam detection and self-adaptive welding gun energy adjusting system and method, and relates to the technical field of welding control. The system comprises an image acquisition module, an image data processing module, a machine learning model, an energy detection module, a welding gun control module and a display interface, wherein the image acquisition module is responsible for acquiring a welding seam image in a welding process; the data processing module preprocesses the acquired image, such as de-noising and filtering; the machine learning model adopts a neural network to perform feature extraction and classification on the weld seam image; the welding gun control module adjusts energy output of a welding gun in real time according to an output result of the machine learning model; the display interface displays the welding seam detection result and the welding gun energy adjusting condition in real time. According to the system and the method, the welding seam defect can be automatically identified by analyzing the welding seam characteristic data in real time so as to improve the welding seam detection accuracy and efficiency, and the energy parameters of the welding gun are dynamically adjusted according to the detection result, so that the welding quality and efficiency are improved.

The invention discloses a method and system for adjusting energy consumption of a machine room based on AI, and relates to the technical field of energy consumption adjusting.The method comprises the steps that all energy consumption devices in the machine room are collected, the importance degree of each energy consumption device to work of the machine room is calculated, and main devices and secondary devices are screened out; training the preprocessed data by using deep learning, capturing the change trend of the energy consumption data along with the time sequence, and constructing an energy consumption prediction model; training the preprocessed data by using a convolutional neural network, performing feature learning on the equipment state data, and constructing a fault early warning model; calculating the correlation between the equipment fault and the energy consumption change, and analyzing the influence degree of the fault on the energy consumption to obtain a fault energy consumption function; constructing a fault propagation map in the machine room; and the energy consumption prediction model and the fault early warning model are combined to monitor the energy consumption data in the machine room in real time, and energy adjustment strategies are formulated for different monitoring results.

The invention discloses a linkage control system and method for cold energy storage and release in an energy storage low-temperature interval, belongs to the technical field of energy storage system temperature control, and aims to solve the problems that traditional energy storage cold energy regulation is lagged, cold energy waste is serious, and dynamic changes of working conditions are difficult to adapt. According to the system and method, cold release judgment is triggered based on the environment temperature and the temperature of an energy storage module, a cold release interval is defined by predicting the environment temperature and the temperature of the energy storage module in a fitting mode, a temperature prediction curve is dynamically corrected in combination with real-time working conditions, cold release subintervals are divided, and a cold release control instruction is generated; and meanwhile, the temperature of the energy storage module is monitored in real time to correct the cooling capacity release control instruction, and a cooling capacity recovery instruction is generated by monitoring the temperature of the cooling liquid. Accurate steady-state control over the temperature of the energy storage module and efficient circulation of the cooling capacity are achieved, and the operation economical efficiency and safety of the energy storage system are remarkably improved.

The invention discloses a self-stabilization system of an exterior wall robot, and relates to the technical field of engineering construction robots, and the self-stabilization system comprises a phase reference module, a frequency spectrum coupling module, a playback prediction module, a gap evolution module, a feedforward compensation module and an energy regulation and control module, constructing a millisecond-level phase comb index based on the wind vibration phase reference field, and locking a zero-phase anchor point in the phase comb index to form an initial constraint condition of attitude perception; according to the method, the closed-loop control of the outer wall robot from disturbance sensing to fine control is realized by constructing a six-stage self-stabilization process. The system introduces millisecond-level phase anchor point locking, cross-frequency information fusion, disturbance trend prediction, adhesion gap dynamic mapping, multi-channel compensation control and energy reverse regulation and control mechanisms, and can significantly improve the operation stability, adaptability and safety in a high-rise complex outer wall environment without depending on a mechanical redundant structure.

The invention discloses a system energy-saving structure optimization control method based on a dynamic balance strategy, and particularly relates to the technical field of energy management systems, which comprises the steps of dynamic model construction, LASSO regression decoupling, transient compensation, multi-machine system coordination control, power distribution network parameter optimization, multi-target control model construction and improved sparrow algorithm. And source-load-storage coordinated control of the new energy microgrid is realized, and short-term and long-term electric quantity balance is optimized. According to the system energy-saving structure optimization control method based on the dynamic balance strategy, through the optimization control method, the adaptive capacity of the system to rapid changes is enhanced, stable operation of a power grid under various changes is ensured, the stability and economical efficiency of the system are improved, a user is effectively guided to carry out energy adjustment, and the user experience is improved. The energy utilization efficiency is improved, the global optimization capability of the system is enhanced, the efficient and stable operation of the micro-grid is realized, the energy consumption is reduced, and the energy-saving optimization is realized.

The invention discloses a multifunctional broadband metamaterial structure with a polarization independent characteristic and a control method. The structure has a switchable tri-state function and a complete polarization operation capability irrelevant to polarization. By introducing the guide circuit design, three different electromagnetic energy regulation and control modes of second-order filtering, broadband absorption and multi-reflection shielding are efficiently integrated in the same structure, the real broadband performance in the band is realized, and meanwhile, the higher reflection efficiency outside the band is kept. Different from a traditional method which depends on a broadband lossless reflecting layer to expand the transmission bandwidth of an absorption structure, the three arrays are considered as an integral operating system, support three-state switching operation and have real broadband and efficient behaviors.

The invention relates to the technical field of photovoltaic energy regulation and control, in particular to a photovoltaic energy supply method and system driven by load sensing of a bridge structure. The method comprises the following steps: acquiring load response data through sensors arranged at key parts of a bridge; carrying out load sensing feature extraction according to the load response data to obtain load sensing feature data; performing load energy regulation and control mapping on the load sensing characteristic data to obtain photovoltaic regulation and control data; acquiring historical traffic flow data, and performing digital twinborn body construction according to the historical traffic flow data and a preset bridge-vehicle coupling model to obtain bridge-vehicle twinborn body data; and performing energy regulation and control response according to the photovoltaic regulation and control data and the bridge vehicle twinborn body data to obtain photovoltaic regulation and control response data. According to the invention, response control is carried out by combining twinborn body data and photovoltaic regulation and control data, so that the timeliness and execution precision of energy allocation are effectively improved, and the operation safety of a bridge structure and the utilization efficiency of renewable energy sources are enhanced.

The invention discloses a double-pulse system and method for improving depth resolution of laser ionization mass spectrometry, and relates to the technical field of mass spectrometers, the system comprises a control system for controlling femtosecond laser parameters generated by a femtosecond laser and nanosecond laser parameters of a nanosecond laser; the laser energy regulation and control module is used for carrying out phase adjustment and detection on the input femtosecond laser and outputting the femtosecond laser meeting set parameters based on the femtosecond laser parameters; the light beam shaping and light beam morphology analysis module is used for shaping femtosecond laser and focusing the femtosecond laser on the surface of the sample for laser denudation; the nanosecond laser performs off-resonance multi-photon ionization on the denudated neutral particles to generate ionized ions for mass spectrometry. According to the invention, the depth resolution of the laser ionization mass spectrum can be improved to nanoscale, the ionization efficiency of ions is improved under the condition of reducing the sampling amount, and meanwhile, the sensitivity of an instrument and the accuracy of quantitative analysis are improved.

The invention provides an ion beam energy adaptive regulation and control method and system for FIB equipment, and the method comprises the steps: obtaining an energy distribution parameter of an ion beam in a focusing region, and determining a target energy adjustment range according to the energy distribution parameter and a preset ion beam energy reference model, generating a multi-stage energy adjustment instruction based on the target energy adjustment range, controlling an output parameter of an ion beam energy adjuster through the multi-stage energy adjustment instruction, enabling the current energy distribution of the ion beam to enter the target energy adjustment range, and detecting the energy fluctuation data of the adjusted ion beam on the surface of the sample in real time, and according to the energy fluctuation data and a preset adaptive compensation algorithm, adjusting feedback control parameters of the ion beam energy regulator, so that the energy distribution of the ion beam is maintained within the target energy regulation range. By means of the method, better machining surface quality and process consistency of industrial machining can be achieved.

The invention discloses an aggregation regulation and control method and system for multiple virtual power plants, and relates to the technical field of intelligent power grid regulation and control, and the method comprises the steps: enabling a trust anchor to synchronize a link health abstract and preset a safe operation envelope and an autonomous rule when the communication is normal; after link disconnection is detected, an autonomous mode is immediately switched to generate power setting; during the autonomous period, recording power deviation and events and generating a hash track; after the link is recovered, two-way identity verification is completed through quantum key handshake, then a fingerprint set and sparse differences are uploaded, and latest global constraints are received; an aggregation composer reconstructs a system model based on a constraint relaxation matrix and a compensation weight vector, generates an optimized power instruction, smoothly replaces an autonomous instruction with a slip coefficient, recursively allocates spare capacity, and finally realizes the transition from autonomous smooth transition to unified scheduling of each virtual power plant; the method gives consideration to toughness, integrity, fairness and safety, and significantly and integrally improves the distributed energy regulation and control reliability and recovery efficiency.

The invention provides a laser additive manufacturing device and method cooperating with light spot shape control and energy regulation and control, and belongs to the field of additive manufacturing. A wire feeding mechanism conveys a wire and limits the wire to be perpendicular to the surface of a substrate; a plurality of laser beams are arranged around the wire material, the laser beams comprise first light beams and second light beams, the irradiation directions of the first light beams intersect at the same point on the substrate at the same time and form a first light spot, and the first light beams fuse the wire material and form a molten pool at the position of the first light spot on the substrate; and the second light beams irradiate the substrate to form second light spots, the second light spots are arranged around the first light spot, the second light spots move around the first light spot or are coupled with the first light spot, and the shapes and energy distribution of the light spots are cooperatively regulated and controlled. Coaxial laser cooperative scanning is adopted, dynamic adjustment and cooperative coupling of the light spot shape and energy distribution in the additive manufacturing process are achieved, the shape, size, depth and other characteristics of a molten pool are accurately controlled, and the high-efficiency and high-precision additive manufacturing requirements of complex components are met.

The invention belongs to the technical field of physical thermal ablation, and relates to a physical thermal ablation energy regulation and control method based on intelligent feedback, and the method comprises the steps: collecting point-shaped temperature data, impedance data and ultrasonic data, eliminating the asynchronization and heterogeneity problems through space-time alignment, and combining with focus region segmentation, thereby achieving the energy regulation and control of the physical thermal ablation. Discrete data and continuous images are integrated into a voxelization data cube containing space coordinates, physical attributes and semantic tags, then the temperature change rate and the impedance change rate are calculated based on the voxelization data cube, and then a morphological prediction network is fused with multi-modal features to output a voxel-level ablation probability graph. The method comprises the following steps: realizing prospective prediction of an ablation range, ensuring ablation accuracy by morphological deviation through a three-layer parallel regulation and control strategy, preventing and controlling local overheating by temperature gradient, avoiding tissue carbonization by an impedance change rate, and cooperatively deciding through multi-dimensional indexes to solve the contradiction that single regulation and control cannot give consideration to accurate coverage of a focus and protection of normal tissues; and misjudgment caused by abnormity of single data is avoided.

The invention relates to the technical field of medical instruments, in particular to an electromagnetic focusing extracorporeal shock wave pancreatic lithotripsy device and method.The electromagnetic focusing extracorporeal shock wave pancreatic lithotripsy device comprises a device body, a bed body is installed on one side of the device body through a supporting frame, and a lithotripsy notch is formed in the side, close to the device body, of the bed body; a large C-shaped arm and a small C-shaped arm installed on the inner side of the large C-shaped arm are installed at the position of the notch of the device body, an X camera imager is installed at the upper end of the large C-shaped arm, and a shock wave generator and an ultrasonic probe installed on one side of the shock wave generator are installed on the small C-shaped arm. An energy adjusting module used for controlling the shock wave generator and a safety detection module used for detecting the skin temperature are arranged in the device body, and a displayer and a human-computer interaction interface are arranged on one side of the device body. The technical scheme in the prior art has limitations on shock wave generation, positioning precision, energy regulation and control and treatment strategies.

The invention discloses an energy regulation and control method and system of a virtual power plant based on a prediction model, and relates to the field of virtual power plant operation control, and the method comprises the following steps: collecting energy data in the virtual power plant; integrating the wind power data and the load data, and performing feature extraction on the integrated data; based on the predicted power generation data of the distributed energy and the predicted demand data of the load side resources, constructing a preliminary energy dynamic balance prediction model; performing day-ahead load demand and distributed energy prediction by using the preliminary energy dynamic balance prediction model; according to the preliminary scheduling strategy, using a niche grey wolf optimization algorithm to adjust the operation state of each distributed energy and load side resource in real time; dynamically adjusting and optimizing the energy dynamic balance prediction model; and carrying out load demand and distributed energy prediction again by using the optimized energy dynamic balance prediction model. According to the method, the change of the power system can be responded in advance, and more efficient energy scheduling is realized.

The invention discloses a galvanometer scanning-based curved surface self-adaptive dynamic light spot laser quenching method, which has the following beneficial effects: (1) dynamic regulation and control of a light spot energy field: a traditional uniform light spot is reconstructed into a self-defined light spot with an adjustable energy gradient according to a curvature value of a workpiece, so that the energy of each section of the light spot is dynamically distributed according to the curvature; and the energy density deviation caused by geometric deformation is compensated. And (2) scanning-energy cooperative control: through coupling optimization of a light spot form and a scanning path, galvanometer high-frequency galvanometer micro-swing scanning and laser output energy adjustment are adopted in a curvature sudden change area, so that accurate regulation and control of heat input are realized, a heat accumulation effect is inhibited, and depth uniformity (fluctuation is less than or equal to 10%) of a hardening layer is ensured. And (3) online feedback and closed-loop correction: an infrared thermal imager and a surface topography sensor are integrated, a quenching point temperature field and a hardened layer topography are monitored in real time, a light spot energy ratio and a scanning strategy are dynamically corrected through an AI algorithm, and the dynamic characteristics of material phase change in the machining process are adapted.