2961 results about "Frequency modulation" patented technology

The invention relates to the technical field of power system operation and control, and discloses a primary and secondary frequency modulation cooperative control system of a hybrid energy storage coupling wind generating set, which comprises a wind power generation unit, a hybrid energy storage unit and a central cooperative controller. A total power demand including inertia response and primary and secondary frequency modulation is synthesized, a primary and secondary frequency modulation cooperative distribution module generates a dynamic adjustment weight by using an S-type nonlinear function based on a frequency change rate and frequency deviation coupling relationship, and an energy relay compensation mechanism is introduced to fill a power gap in a switching process. And the SOC adaptive constraint and execution module applies direction selective boundary constraint to the state of charge, and controls hybrid energy storage to perform internal energy self-balancing in a frequency modulation dead zone. According to the invention, seamless connection of multi-time scale frequency modulation is realized, frequency secondary drop is effectively prevented, and the frequency support capability and the self-recovery capability of the system are improved.

The invention discloses a remote sensing image segmentation method fusing frequency modulation and spatial perception, and the method comprises the steps: obtaining and preprocessing an original remote sensing image, and generating a standardized input image; the image is input into a multi-scale frequency domain enhanced feature extraction network, features are extracted step by step according to a plurality of feature levels, each level realizes frequency adaptive semantic enhancement through frequency domain modulation transformation and spatial feature fusion, and deep feature expression is enhanced through feedforward neural network modeling and residual connection output and cross-level residual fusion introduction; the final multi-scale features are decoded through a decoding module, the spatial resolution is recovered, and a pixel-level segmentation result is generated; and constructing a composite loss function containing classification errors, boundary perception and frequency consistency items, and carrying out optimization training on the network. According to the method, semantic complementarity of a remote sensing image in a frequency domain and a space domain is fully mined, so that segmentation precision and robustness of a ground object target in a complex scene are improved, and the method has good generalization ability and engineering practicability.

The invention discloses a flood disaster monitoring and early warning system and a flood disaster monitoring and early warning method. A cloud, rain, water and I integrated sensing network is constructed through a full-chain monitoring capability; a hybrid prediction model coupled with HEC-HMS and SWMM physical models and an LSTM-Transformer deep learning architecture is established, parameter deviation is dynamically corrected through NSGA-II and a symbolic regression multi-objective optimization algorithm, the flood prediction period is prolonged to 10 days (the precision of the southern watershed is larger than or equal to 90%, and the precision of the northern watershed is larger than or equal to 70%), the flood peak time error is compressed to be within 30 minutes, and compared with a scheme based on a static flood risk model, the method has the advantage that the flood prediction efficiency is greatly improved. The false alarm rate is reduced from 20% to 5% through the dynamic threshold calibration technology; hierarchical response and survivability communication are adopted, Beidou satellite and NB-IoT dual-channel redundant transmission is deployed, and a Mesh ad hoc network and frequency modulation subcarrier technology are combined, so that the direct rate of early warning information in extreme weather is ensured to be greater than or equal to 99%; and three-dimensional GIS platform dynamic rendering is supported, and collaborative visualization of a submerging thermodynamic diagram, a material scheduling path and ecological flow monitoring is realized.

The invention discloses a network construction type energy storage capacity optimal matching method based on a frequency response model, and belongs to the technical field of gas turbine power plant financial supervision and artificial intelligence, and the method comprises the steps: S1, quantifying the power vacancy of a typical station under an extreme short-circuit fault, determining a virtual inertia constant and a virtual droop coefficient of network construction type energy storage, and carrying out the calculation of the virtual inertia constant and the virtual droop coefficient; setting an initial output coefficient and adjusting a step length; s2, constructing and integrating a system frequency response model based on the inertia and frequency modulation characteristics of the conventional unit, the wind turbine generator and the network construction type energy storage; s3, applying power disturbance to the system, gradually increasing an initial output coefficient and performing simulation, and recording the maximum frequency deviation, the maximum frequency change rate and the quasi-steady-state frequency deviation; and S4, when the maximum frequency deviation, the maximum frequency change rate and the quasi-steady-state frequency deviation are respectively smaller than or equal to set threshold values, the energy storage capacity proportion corresponding to the current initial output coefficient is the optimal proportion. According to the method, the problem of accurately measuring the optimal configuration proportion of the network construction type energy storage in the new energy station is solved.

The invention discloses an energy storage system cooperative control method and system for power grid frequency modulation, belongs to the field of power grid control, and particularly relates to power grid frequency control, and the method comprises the steps: collecting power output time sequence data of each energy storage system in a target power grid in response to a power grid frequency modulation instruction through data monitoring equipment, to identify a timing misalignment event due to communication delay or response difference; acquiring output power data of each time sequence dislocation event so as to judge whether a cooperative failure condition occurs among the energy storage systems or not; if it is determined that a cooperative failure condition occurs, generating a frequency modulation power task redistribution instruction with smooth power grid power fluctuation as a target according to the output power data, and obtaining delay data to generate a communication time sequence adjustment instruction synchronized with power distribution, so as to adjust the frequency modulation power task according to the communication time sequence adjustment instruction; and cooperative control of each energy storage system in the target power grid is realized. The stability of power frequency modulation of the power grid can be improved through cooperative control of the energy storage system in the power grid.

The invention relates to the technical field of energy storage cooperative control, and discloses an improved energy storage converter grid following control algorithm, which comprises the following steps of: 1, extracting positive sequence and negative sequence components of three-phase voltage of a power grid through a double-sequence decoupling phase-locked loop, and acquiring a positive sequence axis component signal by adopting forward rotation coordinate transformation; and 2, when frequency locking is carried out based on the positive sequence axis component signal, extracting a voltage amplitude corresponding to the positive sequence axis component signal, and inputting the voltage amplitude to a feed-forward passivation module. An active power regulation technical scheme based on a frequency deviation threshold value is adopted, the technical effect of simulating the primary frequency modulation characteristic of a network-forming converter is achieved by detecting the power grid frequency deviation in real time and generating an active power compensation signal, and the defect that traditional network-following control lacks frequency active supporting capacity is overcome. And the converter can spontaneously increase the active power to stabilize the power grid frequency when the power grid frequency drops.

The invention relates to the field of power system automatic control and new energy grid-connected operation, and provides an energy storage-containing new energy field station frequency modulation optimization method based on deep reinforcement learning. The method comprises the following steps: firstly, establishing a frequency response model containing an energy storage new energy field station, constructing a frequency modulation problem into a Markov decision process, and defining a state space containing a charge state and frequency deviation, an action space taking a charge and discharge power instruction as an element, and a multi-target reward function fusing a frequency regulation effect and charge state management; and then designing an intelligent agent network based on a long short-term memory network and an improved soft actor-commentator algorithm, constructing an online training framework with priority experience playback and a sliding time window, and realizing adaptive optimization of the strategy. And finally, generating a robust frequency modulation instruction in real time based on the trained model. Simulation shows that the frequency long-term regulation and control capability and the intelligent level can be remarkably improved, and the frequency modulation performance and the frequency modulation margin are effectively coordinated.

The invention discloses a distributed new energy and energy storage primary frequency modulation multi-agent cooperative control method and system, and belongs to the technical field of power system frequency modulation. The method comprises the following steps: constructing a multi-agent power distribution network simulation environment based on power grid topology and integrated wind power / photovoltaic / energy storage models and constraints; distributing an independent intelligent agent for each unit, and defining an observation space containing information such as frequency deviation and an output adjustment action space; an MADDPG framework containing a shared Critic network and an independent Actor network is built, and cooperative training is achieved through experience playback; designing a comprehensive reward function fusing the frequency, the voltage, the energy storage SOC and the electricity abandoning rate; and outputting a real-time output instruction by using the trained model to realize primary frequency modulation cooperative control. The method can significantly improve the response speed and precision of the distributed energy participating in the primary frequency modulation, guarantees the system safety, reduces the power abandonment rate of the new energy, and meets the power grid safety requirements of the high-permeability new energy.

The invention discloses a wind power plant energy management system and a dispatching optimization system, and belongs to the field of wind power generation. The system comprises a data acquisition module, a wind speed prediction module, a wake effect analysis module, a power prediction and distribution module, an optimization scheduling module, a dynamic adjustment module, an energy efficiency evaluation module and a communication control module which work cooperatively. Through multi-source data fusion and dynamic collaborative optimization, the comprehensive performance of the wind power plant is remarkably improved, on the operating efficiency level, the system combines the space-time convolutional neural network and the multi-target optimization algorithm, high-precision prediction of minute-level wind speed and optimal distribution of whole-field power are achieved, energy loss caused by the wake effect is effectively reduced, and the wind power generation efficiency is improved. The output strategy is dynamically adjusted according to the health state of the fan, and the fatigue loss of the equipment is delayed while the generating capacity is maximized; on the power grid adaptability level, a self-learning mechanism based on the frequency disturbance qualified rate is introduced, and frequency modulation response parameters are optimized in real time.

The invention discloses a hybrid energy storage capacity configuration method based on an energy storage characteristic and instruction difference dynamic matching strategy and a related device, and relates to the technical field of power system energy storage, and the method comprises the steps: carrying out the mode division according to the amplitude of a total power instruction signal of a hybrid energy storage system, and carrying out the configuration of the hybrid energy storage capacity based on the dynamic matching strategy; distributing the total power instruction signal to a super capacitor and a lithium battery, and calculating the charge states of the super capacitor and the lithium battery; constructing a control configuration integrated model by taking the total power command signal as input and the charge state as feedback; determining value range constraints of the configuration parameters and the control parameters; and under constraint conditions, solving the comprehensive multi-objective optimization function of the control and configuration integrated model by adopting a traversal algorithm to obtain an optimal configuration parameter and control parameter combination, and determining a hybrid energy storage capacity configuration scheme of the hybrid energy storage system. The problems of insufficient energy storage utilization and insufficient frequency modulation precision in a traditional method can be solved.

The invention provides an electric energy storage power station virtual inertia optimization method considering inertia space-time distribution characteristics, and the method comprises the steps: carrying out the virtual inertia optimization of an electric energy storage power station under the scene of considering the non-uniform inertia distribution of an electric power system under the high-proportion new energy access; constructing a source measurement frequency response characteristic model considering load power mapping and a load node frequency response characteristic model considering source measurement frequency mapping; the system small interference stability based on the characteristic root method is used as a frequency safety constraint condition; taking the minimum inertia and frequency modulation energy of the energy storage power station as a target, considering the physical constraint, the frequency security constraint and the system stability constraint of the energy storage power station, and proposing a network tracking / constructing energy storage power station inertia coordination optimization strategy considering the frequency dynamic space-time distribution; wherein the objective function is that the sum of the integral quantity of the load node frequency deviation and the inertia kinetic energy of the following / constructing network energy storage power station is minimum. According to the method, aiming at the characteristic of frequency space distribution differentiation in a novel power system, it is ensured that all nodes can meet double security constraints of frequency deviation and frequency change rate.

The invention provides a low-power-consumption control method of a GPS module. Through data fusion of the gyroscope and the GPS, accurate perception of the motion state of the equipment is realized, and in combination with a dynamic frequency modulation technology and hardware-level power supply control, the power consumption of the system is remarkably reduced on the premise of ensuring the positioning accuracy and the real-time performance. The angular velocity change of the equipment is detected in real time through the gyroscope, and in combination with GPS position information, the equipment is judged to be in a moving, low-speed moving or static state. And dynamically adjusting the GPS sampling period according to the state division result. A sliding window algorithm is adopted to smooth rate fluctuation, a multi-threshold hysteresis mechanism is combined to avoid state misjudgment, a mathematical optimization model is constructed to carry out iterative optimization on control parameters, and balance between power consumption and performance is achieved. Through hardware-level power supply control, zero power consumption in a static state is realized, the average power consumption of the GPS module can be greatly reduced in long-endurance demand scenes such as Internet of Things equipment, wearable equipment, field animal research and the like, and meanwhile, relatively high positioning precision is maintained.

The invention discloses an adjustable resource unified data external characteristic modeling, regulation and control method and system oriented to various transaction scenes. The method comprises the following steps: collecting real-time data of an internal adjustable resource of a virtual power plant; the climbing time, the duration, the response capacity and the responsible frequency are quantized and defined as a group of external characteristic parameters, an adjustable resource data external characteristic model is constructed, adjustable resources are classified according to the external characteristic parameters of the model, and an adjustable resource characteristic library is established; in combination with the response characteristic and the load state of each adjustable resource, generating an optimal regulation and control strategy meeting the regulation and control requirements, and allocating a corresponding regulation and control instruction to each adjustable resource; each adjustable resource adjusts power output according to the regulation and control instruction, and meanwhile, the calling cost of each adjustable resource is calculated; in combination with the real-time state and the adjustment cost minimization target, the regulation sequence and proportion are optimized; according to the method, the economy and flexibility of the virtual power plant in multi-scene regulation can be effectively improved, and meanwhile, the accuracy of power grid frequency modulation response and the system stability are enhanced.

The invention relates to the technical field of power transmission line safety monitoring, and particularly discloses a self-adaptive calibration method for an ultrasonic wind speed sensor, which comprises the following steps of: arranging an orthogonal ultrasonic probe array at the top of a tower, and compensating probe offset caused by swinging of a tower body in real time through GNSS / IMU (Global Navigation Satellite System / Inertial Measurement Unit) fusion positioning; integrating a temperature, humidity and pressure sensor and vibration spectrum analysis to construct an environmental parameter compensation model; double-frequency ultrasonic waves are adopted to detect the ice accumulation thickness of the protective cover and correct the sound path distance; deploying a lightweight LSTM model at an edge computing unit to realize minute-level dynamic parameter adjustment; electromagnetic interference is suppressed by combining linear frequency modulation spread spectrum and beam forming technologies; and establishing a three-height-layer wind speed gradient model to generate a galloping early warning. The problem of measurement distortion caused by tower deformation, icing and parameter solidification of a traditional sensor is solved, all-working-condition operation from-40 DEG C to 60 DEG C is supported, and the monitoring reliability in a strong electromagnetic environment is remarkably improved.

The invention belongs to the technical field of metal crack detection, and discloses a metal microcrack ultrasonic detection method, which comprises the following modules: an ultrahigh frequency composite array probe with a center frequency dynamic adjustable range of 5-50 MHz; the dual-mode excitation and receiving module is used for independently generating a pulse reflection mode excitation signal and a diffraction mode chirp frequency modulation signal; the phase-controlled synthetic aperture dynamic focusing module is used for realizing + / -60-degree deflection and sub-wavelength level focusing of acoustic beams; the nonlinear harmonic enhancement module is used for exciting a crack nonlinear effect by superposing 1-2MHz fundamental waves; and a time-space-frequency three-domain data fusion module. According to the method, signal-to-noise ratio collapse caused by the diffraction effect in a traditional method is overcome, more importantly, the system has low-frequency penetrability and high-frequency resolution at the same time due to 80%-120% of broadband coverage of chirp frequency modulation signals, the diffraction signal gain is increased by 20 dB or above, a near-surface blind area is compressed to be within 0.2 mm, and the system can be applied to the field of radar imaging. And the core pain point of missing detection of the near-surface microcracks of the thin-wall component is solved.

The invention relates to a system inertia boundary backstepping method based on frequency dynamic indexes and distributed node equivalent inertia analysis, and belongs to the field of power optimization. The method comprises the following steps: dividing a frequency response process into an inertia response stage, a primary frequency modulation stage and a secondary frequency modulation stage; constructing a multi-source frequency response unified equivalent model; an equivalent inertia boundary inversion method based on RoCoF and Nadr dual constraints is provided, a frequency safety boundary is converted into a constraint expression for the equivalent total inertia of a system, and an inertia boundary required under given power disturbance is reversely deduced; the method further comprises the steps of introducing static load voltage characteristic correction during inertia boundary inversion; the method further comprises the step of constructing a frequency support-oriented regionalization control strategy. According to the method, the safety support boundary of the low-inertia emergency power supply system is researched from the overall level and the regional level, and a theoretical basis is provided for refined frequency control and resource optimization layout.

The invention discloses a wind power plant inertia damping adaptive regulation and control method and system fused with a deep Q network, and belongs to the technical field of power systems. The method comprises the following steps: establishing a doubly-fed wind turbine generator, a converter mathematical model and an interaction model of a wind power system connected to a power grid, and analyzing the grid-connected stability of the wind power system; the dynamic response characteristic of providing inertia support by the VSG system under different conditions is researched, and the primary frequency modulation capability is improved; a depth Q network is adopted to select rotational inertia and a damping coefficient, a damping inertia adaptive control strategy is improved, cooperation of inertia support and frequency response capability improvement of a wind turbine generator and continuous and smooth adjustment of active power is realized, the stability of a power grid is improved, and the operation performance of a wind power plant is optimized. According to the method, dynamic optimal matching of inertia response, primary frequency modulation and the running state of a unit is achieved, auxiliary services are provided, meanwhile, the running safety and service life of a draught fan are guaranteed, and smooth and impact-free adjustment of active power is achieved.

The invention provides a dynamic optimization method and system for steam turbine valve flow characteristics and a medium, and relates to the technical field of steam turbine valve flow control. The method comprises the steps that a historical curve of valve flow is acquired based on a target steam turbine cabinet; calculating an actual curve of the actual flow through a characteristic flow area identifier, and comparing the actual curve with a historical curve for judgment to obtain a curve deviation; the curve deviation is optimized according to the dual modes, and valve management parameters are obtained; and dynamically correcting the valve flow characteristics based on the valve management parameters. The technical problems that in the prior art, due to the fact that valve flow characteristic optimization depends on an off-line test and lacks the dynamic adjustment capacity, the unit operation condition adaptability is poor, the control precision is insufficient, and the frequency modulation performance and economic operation of the unit are further affected can be solved. The technical target of online real-time dynamic optimization of the valve flow characteristics of the steam turbine is achieved, and the technical effect of improving the frequency modulation response speed and the operation stability of a unit is achieved.

The invention discloses a communication-detection integrated sonar signal design method and device based on multi-pulse composite modulation, and the method comprises the steps: dividing a total frame period into a detection sub-frame and a communication sub-frame, enabling the detection sub-frame to achieve the high-resolution distance measurement through employing a bidirectional linear frequency modulation (BILFM) signal, a communication sub-frame adopts a multi-frequency multi-phase composite modulation (MTPM) signal to realize high-bit-rate data transmission; after band filtering, orthogonal demodulation, low-pass filtering and down-sampling preprocessing are carried out on detection sub-frame echoes, distance and speed information is extracted by adopting fast-time low-sampling two-dimensional fast Fourier transform (2D-FFT), unambiguous Doppler frequency is recovered by utilizing the Chinese remainder theorem (CRT), and accurate speed measurement of long-distance and high-speed targets is realized; a communication subframe receiving signal is subjected to IQ demodulation after down-conversion, Costas loop carrier synchronization and matched filtering, and multi-frequency multi-phase coded data are extracted. According to the method, the time-frequency collaborative design of detection and communication is realized, the distance resolution and the speed measurement range are considered, and the signal bandwidth utilization rate and the underwater information transmission reliability are remarkably improved while the system complexity is kept low. The device comprises a processor and a memory, and an executable program for implementing the method is stored in the memory. The technology can be widely applied to the fields of unmanned underwater vehicles, ocean monitoring, underwater sensing networks and the like.

The invention relates to the technical field of detection of toner cartridge powder, and discloses a method and a system for improving the uniformity of toner cartridge powder, which are used for continuously sampling powder flow to obtain a real-time weight distribution matrix. And when abnormal flow is detected, noise is eliminated, processed data are input into a fuzzy PID controller, and feeding parameters are dynamically adjusted. Meanwhile, powder is promoted to be uniformly dispersed in combination with a vibration frequency modulation technology, and a weight change trend is predicted by utilizing a long-short-term memory network algorithm. In addition, the method further comprises an anomaly detection and fault diagnosis mechanism, control parameters are continuously adjusted through closed-loop optimization, and finally a batch quality tracing system is established. By means of the method, the precision and consistency of toner cartridge powder conveying can be effectively improved, and intelligent control and quality management in the production process are achieved.

The invention discloses a super capacitor energy storage life evaluation method under a fire storage frequency modulation working condition, relates to the technical field of power system energy storage, and can at least partially solve the problems that an existing super capacitor life evaluation method is poor in adaptability to the frequency modulation working condition, insufficient in multi-factor coupling quantization and lack of engineering criteria. The method comprises the steps of simulating a fire storage frequency modulation working condition and collecting multi-dimensional operation data of a super capacitor; preprocessing the collected data and extracting life characteristic parameters such as capacity attenuation rate, equivalent C rate, average temperature rise, frequency modulation load factor and the like; key influence factors are screened through correlation analysis, weight coefficients are trained through a machine learning algorithm, and a coupling influence coefficient model is constructed; establishing a capacity attenuation equation, an equivalent series resistance growth equation and a response delay growth equation, and fusing three criteria to determine a life end point; and dynamically correcting model parameters based on the real-time frequency modulation data and calculating the residual life. Accurate evaluation and dynamic prediction of the service life of the super capacitor under the fire storage frequency modulation working condition are achieved.

The invention relates to the technical field of energy storage frequency modulation prediction, in particular to an AFGRU-based energy storage frequency modulation instruction prediction method and related equipment. The method comprises the following steps: decomposing an obtained original frequency modulation sequence by using a variational mode decomposition method to obtain a plurality of sub-sequences; fusing the plurality of sub-sequences into a set number of comprehensive components through a multi-scale entropy-dynamic alignment fusion method; and inputting the comprehensive component into the trained AFGRU network model, and predicting a next energy storage frequency modulation instruction to obtain an energy storage frequency modulation instruction prediction result. According to the method, by accurately predicting the energy storage frequency modulation instruction, the stability and reliability of the power grid are improved, and the influence of frequency fluctuation on power equipment and users is reduced.

A microgrid island division method based on a cumulative foreground theory and a transfer learning thought comprises the following steps: step 1, aiming at a day-ahead decision-making scene, taking income maximization in a scheduling period as a core target, integrating short-term renewable energy output prediction and electricity price fluctuation data, and constructing a capacity optimization configuration model; 2, constructing a double-layer model, constructing a transaction decision model by the upper-layer model by taking energy storage power station revenue maximization as a target, and determining a power station quotation strategy; the lower layer model takes the sum of the electric energy cost and the frequency modulation service cost as the target to construct a combined clearing model of the electric energy and the frequency modulation market; and 3, solving the double-layer model constructed in the step 2. According to the method, energy storage can participate in an electric energy and frequency modulation market through strategic quotation under a reasonable market mechanism, and an energy storage power station is stimulated to optimize resource allocation, so that the frequency modulation pressure of a power system is reduced, the energy storage economic benefit is improved, and the stability and resource utilization efficiency of the power market are further improved.

The invention discloses a novel power system primary frequency modulation optimization method based on deep learning, and relates to the technical field of power optimization. The method comprises the following steps: collecting state data of a hydroelectric generating set running in a power grid, constructing a three-dimensional feature tensor, and extracting spatio-temporal features through a TCN-GRU hybrid network; constructing a deep reinforcement learning decision layer, and defining an action space and a reward function; constructing a PID neural network with a time-varying forgetting factor, and outputting a dynamic weight; establishing a dual-time scale updating mechanism; a safety verification module is arranged, and when the system frequency deviation value is larger than a threshold value, the traditional PID mode is switched. Characteristics are extracted from state data of operation of a hydroelectric generating set in a power grid, the time sequence dependency relation of the characteristics is processed through deep learning, the frequency change trend of the power grid is captured, the optimal control strategy is explored by applying the DRL technology, PID controller parameters are adjusted in a dynamic environment, and the optimal control strategy is obtained. And the primary frequency modulation response speed and the control precision of the hydroelectric generating set during power grid frequency fluctuation are improved through self-adaptive control.

The invention discloses a frequency stability control method for accessing new energy to an offshore energy platform, and the method comprises the steps: firstly carrying out the state recognition and parameter extraction of frequency modulation resources, building a frequency-power response model of the frequency modulation resources, carrying out the superposition construction of a system frequency response total model, and carrying out the packaging of a dictionary structure; based on a frequency safety index, disturbance occurrence and grade are judged in real time, and a frequency change trend is dynamically estimated; according to the disturbance level and the response characteristics of various resources, a fast-medium-slow layered frequency modulation control strategy is constructed, different types of resources are scheduled in stages for cooperative adjustment, the frequency state is monitored, and control parameters are dynamically corrected; constructing a fuzzy logic controller to process nonlinear disturbance, and introducing a whale optimization algorithm to set and optimize parameters of the fuzzy controller; and finally, dynamically correcting the control strategy according to the frequency control result and the resource utilization rate index. The method can guarantee the frequency stability, reduces the frequency modulation cost, and improves the frequency control precision, the response speed and the overall operation toughness.

The invention relates to the technical field of power electronics, in particular to a network construction type STATCOM topological structure with a super-capacitor and a control method thereof, the topological structure is a star-shaped chain network construction type STATCOM system with a super-capacitor module power unit, the power unit comprises a super-capacitor module and an H-bridge module, and the super-capacitor module is connected with the H-bridge module in parallel; the super-capacitance module is formed by cascading three sub-modules, and each sub-module comprises a super-capacitor, a filter inductor and a DCDC circuit; the control method comprises the steps of voltage feed-forward unit phasor calculation, reactive voltage control and virtual internal potential angle calculation, virtual impedance amplitude limiting logic, bridge arm current reference instruction calculation and modulation wave instruction calculation. According to the invention, the applicability of the super capacitor module is enhanced, the design cost is saved, mutual interference between the frequency modulation characteristic and the inertia damping characteristic is avoided, the active power steady state control precision is improved, and the product safety is improved.

The invention provides a cascade AGC (Automatic Gain Control) frequency modulation regulation control optimization method, which comprises the following steps: acquiring frequency deviation and tie line power deviation in a power system in real time, calculating a regional control error ACE based on the two deviations, and decomposing the ACE into a frequency deviation component and a tie line power deviation component; calculating a ratio coefficient of the frequency deviation component in the ACE and a ratio coefficient of the tie line power deviation component in the ACE; acquiring a climbing rate and an adjustable capacity of each frequency modulation unit, and performing normalization processing on the climbing rate and the adjustable capacity; calculating the rate-capacity double weight of each unit through a dynamic weight formula in combination with the ratio coefficient, the normalized climbing rate and the normalized adjustable capacity, and distributing frequency modulation power to each unit according to the normalized weight; in the operation process, on-line self-adaptive adjustment is carried out on dynamic weight calculation and unit adjustment related parameters according to system performance indexes.

The invention discloses a wide-dynamic-range diamond NV color center magnetic sensing method and system, and the method comprises the steps: (1) calibrating the initial resonant frequency and magnetic sensing coefficient of a diamond NV color center in an initial magnetic field environment; (2) in a to-be-measured magnetic field environment, a microwave generator applies frequency-modulated microwaves to the diamond NV color center with the current resonant frequency as the center frequency; demodulating the fluorescence signal in real time by using a phase-locked detection technology to obtain an error signal; calculating the detuning amount of the center frequency in real time according to the error signal and the magnetic sensing coefficient, and further calculating the variable quantity of the magnetic field intensity; meanwhile, the detuning amount is fed back to a microwave generator to track the resonance frequency of the diamond NV color center; and (3) continuously and repeatedly executing the step (2) to realize wide-dynamic-range magnetic field measurement. The method has the advantages of wide dynamic range, high detection capability on strong and weak field mixed signals in a complex application scene and the like while giving consideration to the magnetic sensing sensitivity.

The invention discloses a force control joint dynamic error compensation method based on Kalman filtering, and the method comprises the steps: collecting and preprocessing multi-source signal data, and forming a force control joint input data set; constructing an energy hierarchical Kalman filtering model, executing energy constraint correction and outputting state estimation; calculating a prediction residual error, carrying out time-frequency analysis, adjusting a compensation gain, and generating residual error information; torque and angular velocity signals are extracted, a semantic state is recognized, and semantic gating parameters are output; fusing the state estimation, the residual information and the semantic parameters to generate a dynamic compensation instruction signal; energy layer and residual information changes are monitored, self-calibration is triggered, and a feedback closed loop is formed. According to the invention, by introducing energy hierarchical Kalman filtering, time-frequency modulation compensation and a semantic gating feedback mechanism, dynamic error self-adaptive accurate compensation of the force control joint in a complex multi-disturbance environment is realized.

The invention relates to the technical field of power system frequency modulation control, in particular to a thermal power generating unit collaborative frequency modulation method and system based on block chain federated learning. According to the method, a decentralized P2P network is constructed through a block chain technology, and model parameters are initialized based on a secret sharing mechanism; carrying out local training by adopting an adaptive federal near-end optimization algorithm, measuring data isomerism through KL divergence and dynamically adjusting a regular coefficient; carrying out noise addition on a sample by adopting differential privacy, and carrying out homomorphic encryption to realize parameter encrypted transmission; selecting representative nodes based on a block chain consensus mechanism to execute parameter aggregation in the encryption domain; and multi-unit collaborative frequency modulation is realized through model prediction control. According to the method, the problems of data privacy protection, heterogeneous data adaptation and decentralized cooperative training are solved, and the stability of power grid frequency regulation and control is improved.