988 results about "Frequency deviation" patented technology

The invention relates to the technical field of semiconductors, and discloses a full-temperature-zone polynomial digital temperature compensation method and system based on an SOI chip, and the method comprises the steps: obtaining the temperature frequency data of a preset temperature zone of a target SOI chip, fitting a full-temperature-zone curve, extracting a critical point of the temperature zone, dividing a segmented compensation interval according to the critical point, and obtaining the temperature frequency data of the preset temperature zone of the target SOI chip; the method comprises the following steps: calculating frequency drift amounts under different voltages to construct a full-automatic test framework, acquiring an environment temperature parameter and an instantaneous temperature value by using the framework, analyzing a temperature compensation vector of a segmented compensation interval, further monitoring a signal frequency interval output by a chip, extracting a phase noise parameter, calculating a frequency offset error amount with a preset value, and calculating the frequency offset error amount. And analyzing an error source, optimizing a polynomial compensation order, and collecting temperature drift suppression data to generate a full temperature region compensation report. According to the invention, the performance stability of the chip in a complex environment can be improved.

The invention belongs to the field of data processing, and particularly relates to a dynamic cooperative control system and method for a gas turbine and a micro-grid, and the method comprises the steps: constructing a micro-grid real-time monitoring module, continuously collecting distributed energy real-time output, controllable load demands, bus voltage frequency and equipment state parameters, and carrying out the filtering and noise reduction through a preprocessing unit, thereby guaranteeing the data precision; calculating a real-time power difference value based on the preprocessed data, calling an adaptive neural fuzzy inference system, taking the power difference value, the bus voltage deviation and the frequency deviation as input, and judging whether the power difference value, the bus voltage deviation and the frequency deviation exceed a preset threshold value by means of a fuzzy rule base and a neural network model; if the threshold values are not exceeded, the current states of the gas turbine and the energy storage system are maintained; if any one exceeds the threshold value, a dynamic cooperative control instruction is triggered, precise cooperative control of the gas turbine and the micro-grid is achieved, and the operation stability, the operation efficiency and the reliability of the micro-grid are improved.

This invention pertains to an intelligent electronic device designed for sophisticated monitoring and analysis of electrical power distribution. The device integrates at least one sensor for detecting electrical parameters from a distribution system to a load, coupled with an analog-to-digital converter to transform sensed analog signals into digital data. A processing module, linked to the converter, employs customized moving average filters to calculate the frequency of electrical power distribution, enhancing measurement accuracy by adjusting for transient fluctuations. It retrieves frequency threshold settings from memory to define operational bounds, logging frequency data around identified deviation events when measurements surpass these thresholds. This system facilitates precise frequency analysis and robust event logging, providing a comprehensive solution for maintaining electrical power distribution within defined standards.

The invention relates to the field of power systems, in particular to a multi-energy complementary power supply network cooperative control method and system. The method comprises the following steps: collecting dynamic characteristic data of wind power, photovoltaic power, energy storage and load through a sensor group, and generating a multi-energy state characteristic matrix with a timestamp; and matching the feature matrix with a dynamic response feature library, and outputting a dynamic feature parameter set. Based on the set, a multi-objective optimization model is constructed, second-level frequency deviation suppression, minute-level tie line power stabilization and hour-level economic dispatching are covered, and a cooperative control parameter set is generated. And generating a thermal power generating unit compensation amount, an energy storage charging and discharging sequence and an interruptible load priority list. After execution, power grid deviation data are collected, a dynamic deviation value is calculated, and when a threshold value is exceeded, feature library parameters are corrected and loop optimization is carried out. According to the invention, the problem of insufficient cooperative control of the multi-energy system in the prior art is solved, and the stability and economy of the power grid are improved.

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 provides a medical equipment fault detection method and system based on machine learning, and relates to the technical field of fault detection. The method comprises the steps of monitoring motor start-stop division operation cycles, synchronously collecting and processing vibration, frequency difference and voltage signals, calculating characteristic difference to generate a dynamic sequence, extracting a non-convergence trend and phase deviation, fusing voltage and frequency fluctuation characteristics, constructing a threshold rule to judge abnormity, and outputting a light fault early warning signal. According to the invention, through precise monitoring of motor start-stop nodes, period division, collection of vibration, frequency and voltage signals, combination of time alignment and noise filtering, improvement of signal quality, cross-period calculation of characteristic difference, and extraction of non-convergence trend and phase offset, the ability of capturing tiny anomalies is enhanced; according to the method, multi-dimensional indexes such as voltage fluctuation and frequency deviation are fused, a threshold judgment mechanism in a continuous window is constructed, stable identification and early warning of equipment light faults are achieved, and the detection accuracy and response timeliness are improved.

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 asynchronous motor energy-saving monitoring and dynamic early warning method based on situation awareness, and relates to the technical field of asynchronous motor energy-saving monitoring. The method comprises the steps that S1, multi-source heterogeneous data are synchronously collected, power supply parameters and operation parameters are obtained in real time, and a frequency conversion working condition self-adaptive deviation value and a current stability coefficient are obtained; s2, generating four-dimensional situation factors including an overtemperature danger value, a current stability coefficient, a voltage stability coefficient and a frequency deviation value; s3, constructing a fourth-order transmission network, and generating a primary early warning signal based on the path mark combination; s4, calculating the motor efficiency in real time, triggering an efficiency abnormity mark, fusing the efficiency abnormity mark with the primary early warning signal, and reconstructing a final early warning instruction; and S5, executing hierarchical control according to the final early warning instruction. Through multi-parameter coupling and dynamic early warning transmission, the early-stage capture capability of the composite fault is improved, the early warning response delay is shortened, energy-saving optimization and fault protection of the motor are realized, and the method has a remarkable practical value.

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 technical field of power systems, in particular to a UPQC harmonic compensation method and system based on repetitive control, and the method comprises the steps: obtaining a load current signal and a voltage signal of a power distribution network, and extracting a harmonic instruction current based on the load current signal; and inputting the harmonic instruction current into a feed-forward channel constructed based on an adaptive filter, and generating a feed-forward control quantity. The phase and frequency of the voltage signal of the power distribution network are tracked in real time through a digital phase-locked loop, the fundamental frequency of the power grid is accurately solved, and the power distribution network can be accurately controlled. The internal model period and the phase lead compensation amount of the frequency adaptive repetitive controller are dynamically calculated, and the internal model structure of the repetitive controller is always matched with the current power grid frequency by updating the two core parameters in real time, so that the compensation precision decline caused by frequency deviation is avoided; and high-precision suppression of the periodic harmonic waves can be realized in a normal fluctuation range of the fundamental wave frequency of the power grid.

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 power grid broadband oscillation suppression method and device based on adaptive robust control, terminal equipment and a storage medium, and belongs to the field of power systems. The method comprises the following steps: performing fuzzy disturbance classification according to an oscillation mode, an oscillation mode characteristic parameter and a state parameter obtained according to a power grid operation parameter to obtain a disturbance type label and a disturbance degree; the disturbance degree serves as a weighting factor, the initial control parameters are corrected according to the power grid operation parameters, the initial control parameters of the controller and the disturbance type label, and a self-adaptive control strategy is generated after correction; when the disturbance degree is smaller than a disturbance threshold value, the state parameters are regulated and controlled according to a self-adaptive control strategy to update power grid operation parameters; and when the disturbance degree is not less than a disturbance threshold value, taking the minimum sum of the system gain, the frequency deviation and the voltage fluctuation as a target, and regulating and controlling the state parameters under the H infinite robust constraint to update the power grid operation parameters. The problem that in the prior art, broadband oscillation suppression is difficult to adapt to sudden change working conditions is solved.

The invention provides a power distribution network single-high-frequency resonance rapid tracking and adaptive suppression method, a multi-mode dynamic cooperative adaptive suppression system is established based on a PCCVF adaptive method, and the damping characteristics of a power distribution network are remodeled by injecting compensation current into a power distribution network system so as to realize broadband resonance suppression of the power distribution network. The compensation current injection method comprises the following steps: step 1, detecting resonant frequency deviation of a power distribution network through real-time FFT (Fast Fourier Transform); 2, performing dynamic phase angle correction based on a phase prediction residual error of real-time frequency deviation; step 3, constructing a layered impedance remodeling module, and ensuring stable power transmission; 4, establishing a frequency-variable impedance model of the power distribution network based on resonance energy spectral density analysis, dynamically optimizing parameters through fuzzy logic of a bell-shaped membership function, and feeding harmonic compensation current into the power distribution network by using a space vector pulse width modulation technology; according to the invention, single high-frequency resonance can be effectively suppressed, the response and tracking performance of the system is improved, and the spectrum analysis efficiency and bandwidth occupation are optimized.

The invention relates to the technical field of wind power control, in particular to a wind power frequency modulation optimization method and system based on dynamic feedback. Comprising the following steps: constructing a three-layer optimization control model; the method comprises the following steps: optimizing frequency modulation capacity configuration of wind power and energy storage on the basis of a multi-disturbance scene in a planning layer, and outputting a capacity configuration scheme and a wind power adjustment depth constraint by taking minimization of the whole life cycle cost of a system as a target; a capacity configuration scheme and constraints of the planning layer are received at the scheduling layer, power distribution is optimized in real time based on a disturbance scene, and a power distribution instruction is output by taking minimization of frequency deviation and energy storage energy consumption as targets; optimizing a dynamic control strategy of energy storage in an execution layer to minimize the deviation between the actual output of the energy storage and a power distribution instruction, and maintaining the energy storage state in a safe interval; in the system operation process, frequency deviation and energy storage state information are collected in real time and fed back to the planning layer and the scheduling layer, and capacity configuration and power distribution decisions are dynamically corrected. The precision of wind power frequency modulation is improved.

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 relates to the technical field of power electronics and power system control, and discloses an intelligent control method and system for a multi-network converter, and the method comprises the steps: collecting the frequency deviation, the power change rate and the voltage amplitude of a power grid in real time, carrying out the filtering and feature extraction, and analyzing the coupling relation, thereby obtaining the parameter coupling strength. And if the intensity exceeds the threshold value, an inertia adjusting signal is generated through a fuzzy logic controller. And calculating a deviation correction value by combining the state evaluation response performance of the converter, and generating an optimization instruction by fusing the frequency deviation. And solving a voltage stability threshold based on the instruction, updating a coupling index, and issuing and executing after verification. And finally, updating the fuzzy rule base by adopting neural network iterative learning according to feedback data, and forming an inertia support frame with self-learning capability. According to the method, the inertia response speed and the operation stability of the multi-network converter system under high-proportion new energy access can be effectively improved, and adaptive cooperative control is realized.

The invention provides a current transformer dielectric loss anti-interference measurement method based on a variable frequency power supply, and relates to the technical field of power detection, and the method comprises the steps: constructing an excitation channel, collecting a background response signal, recognizing a main interference frequency through combining a frequency tracking algorithm, and dynamically constructing a frequency deviation parameter; generating a pair of non-power-frequency excitation frequency control variable-frequency power supplies to output sine wave excitation signals; excitation voltage and response current signals are synchronously collected to form sampling signals, notch frequency is set according to frequency deviation parameters, main interference is filtered out, and first processing signals are obtained; performing weighting processing by constructing a window function matched with the frequency band characteristic to generate a second processing signal; the complex amplitude and phase information at the target frequency is extracted, the complex impedance is calculated based on the complex current method, the dielectric loss value of the current transformer is finally output, and the anti-interference capability and precision of measurement are effectively improved. According to the invention, the interference in the dielectric loss measurement of the current transformer can be processed, so that the measurement precision is improved.

The invention discloses a data reading method and system based on an RFID reader-writer, particularly relates to the technical field of radio frequency identification data acquisition, and is used for solving the problem that the communication reliability of an existing RFID system is reduced due to carrier frequency deviation and multipath interference in a high-speed mobile environment. A phase change characteristic and an error rate index are obtained through double-antenna receiving signal analysis, when the error rate exceeds a limit, spatial correlation and error rate distribution difference are jointly analyzed to determine a multipath interference level, and meanwhile, a relative motion state is detected and judged through a phase track curvature characteristic. And dynamically selecting an optimal modulation coding mode to read data again according to the calculated motion speed estimated value and the interference level, thereby realizing the optimal balance between the communication rate and the reliability in the mobile environment.

The invention relates to the technical field of micro-grid control, and provides an island micro-grid distributed control method, system and device and a storage medium. Comprising the following steps: performing voltage compensation gain and frequency compensation gain calculation based on droop control output of each distributed power generation unit, droop control output of all neighbor distributed power generation units, and a voltage dynamic tracking error and a frequency dynamic tracking error which are obtained by calculating a microgrid global recovery target to obtain secondary adjustment output; and after corresponding items in the droop control output and the secondary regulation output are summed to generate comprehensive reference output, voltage synthesis is carried out according to the comprehensive reference output to obtain voltage regulation output for output control of a corresponding inverter. Based on a distributed regulation and control mechanism for cooperatively calculating the compensation amount of each power generation unit by using neighbor information and a global recovery target, the dynamic response speed and the power distribution precision can be improved, voltage drop and frequency deviation caused by load disturbance are effectively eliminated, and rapid recovery is realized.

The invention discloses a hybrid energy storage optimization configuration method based on a multi-time scale regulation and control demand, and the method comprises the steps: collecting the operation data of a power system, and obtaining the power fluctuation and the frequency deviation of the power system under a short time scale through a preset high-proportion renewable energy power system model; on the basis of power fluctuation and frequency deviation, the regulation and control requirements of the power system are divided according to different time scales, different energy storage modules are correspondingly configured, and a multi-level collaborative energy storage regulation and control structure matched with the time scales is formed; based on the power system model and the mathematical model of each energy storage module, constructing a hierarchical nested optimization model oriented to multiple time scales; and selecting a typical scene from the operation data by adopting a time sequence clustering method, and obtaining the optimal capacity and power configuration of each energy storage module based on a hierarchical nested optimization model, and obtaining a cross-time-scale collaborative operation strategy. The global optimal configuration is realized by establishing a multi-time-scale collaborative hierarchical nested optimization architecture.

The invention discloses a power system frequency risk quantification and coordination control method and system, and belongs to the technical field of power systems and automation thereof. The method comprises the following steps: collecting power grid online operation data and system working conditions; frequency response curves of the system after different faults are obtained through fault simulation; dividing the frequency into different frequency bands according to a binary criterion formed by a plurality of frequency threshold values and corresponding duration time, and distributing an initial weight coefficient for each frequency band; obtaining a dynamic weight coefficient of each frequency band by combining the frequency change rate in the frequency band and a preset weight gain coefficient; based on the dynamic weight coefficient of each frequency band, performing time integration on the frequency deviation value in each frequency band to obtain a transient frequency risk assessment value; and judging the system stability and the risk level, and giving a corresponding frequency control strategy according to the risk level so as to coordinate and control resources. According to the method, the short-time power disturbance and the permanent power disturbance can be effectively distinguished, and a basis is provided for on-line and off-line safe and stable control.

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 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 relates to the technical field of power dispatching, in particular to an energy storage combined frequency modulation control method and system in a source-network-load-storage integrated regional power grid, and the method comprises the steps: dynamically calculating the adjustable capacity of each resource, dynamically aggregating the total adjustable capacity of the system, sensing the multi-dimensional frequency situation and calculating the adjusting power, and selecting a frequency modulation mode and generating a power distribution strategy. And generating a splitting and isolated network frequency modulation stability control strategy and performing system grid-connected resynchronous operation. The method is suitable for guiding power supply, energy storage and load all-resource collaborative frequency modulation strategy generation in a regional power grid. For consistency of frequency deviation, frequency change rate and active power flow direction, multi-dimensional frequency situation awareness is constructed, power distribution strategies in different modes are generated based on a total adjustable capacity interval of a system, and a frequency stability control and grid-connected resynchronization strategy after splitting is given when the frequency and the adjustable interval exceed limits. Accurate matching of all-resource collaborative frequency modulation and strategies in a regional power grid is realized, and the frequency modulation response speed of the system is improved.

The invention discloses a photovoltaic power generation frequency response control method considering different time scales, and relates to the field of power system automation control, and the method comprises the steps: integrating a frequency deviation feature and an illumination load disturbance feature to obtain a state feature vector, and determining a disturbance type according to the state feature vector; adaptively selecting a frequency response control mode based on the judgment result of the disturbance type, and reasoning and outputting an optimal control parameter combination in the frequency response control mode by using a pre-constructed disturbance-response causal atlas; a four-state progressive switching control strategy is generated in combination with a spectrum analysis technology, and smooth switching between frequency response control modes is realized through the four-state progressive switching control strategy. According to the invention, the response capability and the adjustment precision of the photovoltaic system under the power grid frequency disturbance can be improved, the dynamic coordination of fast frequency response and slow frequency response and parameter self-optimization control are realized, and the whole-process supporting capability of the photovoltaic system to the frequency disturbance is effectively improved.

The invention discloses an active power and frequency coordination control method for a wind storage combined system, and belongs to the technical field of electric power system operation and control. The problems that in the prior art, due to wind power and load uncertainty, the frequency control effect is poor, energy storage life management is insufficient, and long-term and short-term control instructions are disjointed are solved. The problem is solved by constructing a three-layer collaborative architecture of a predictive optimization layer, a real-time coordination control layer and an execution layer: the predictive optimization layer randomly optimizes and generates a reference state track and a frequency modulation capacity instruction of an energy storage unit based on a scene method; the real-time coordination control layer utilizes a deep reinforcement learning coordination controller, synthesizes frequency deviation, SOC compensation signals and frequency modulation capacity reservation instructions, and dynamically distributes active power of a fan and energy storage; and the execution layer realizes rapid issuing of the instruction. The method is mainly used for active power coordination and frequency support of a wind storage combined system in a high-proportion new energy power system, and can effectively delay energy storage life attenuation while stabilizing frequency fluctuation.

The invention relates to the technical field of supervision control, in particular to a new energy storage optimization control method and system, and the method comprises the following steps: collecting a grid-connected point voltage amplitude deviation, a frequency deviation and a voltage total harmonic distortion rate, and generating a power grid stress index; according to the method, the multi-dimensional state vector is constructed by collecting the grid-connected point voltage amplitude deviation, the frequency deviation and the total harmonic distortion rate to generate the stress index reflecting the power grid operation pressure, accurate quantitative sensing of the power grid state is achieved, the power grid supporting gain coefficient is dynamically generated according to comparison of the index and the preset threshold value, and the power grid supporting effect is improved. And the total required power to be responded by the energy storage system is adjusted and determined, so that the power support strength is matched with the actual demand of the power grid, and insufficient response or excessive response is avoided.

The invention provides a VCO digital circuit control method and system with temperature compensation, and relates to the technical field of circuit control, and the method comprises the steps: obtaining VCO output frequency and real-time temperature, and calculating an initial frequency deviation; correcting the frequency deviation based on the temperature compensation coefficient, and generating a temperature-frequency deviation characteristic curve; an optimal compensation factor is determined through Monte Carlo sampling; calculating a compensation parameter adaptive weight by using Bayesian iteration, and dynamically adjusting a compensation factor; and a control signal is generated through the digital integrator to realize frequency calibration. According to the invention, the high-precision frequency stability of the VCO under the temperature change condition is realized, and the circuit reliability is improved.

The invention relates to the technical field of distributed energy and micro-grids, in particular to a distributed energy output high-precision prediction model, which comprises the steps of collecting data and generating a power fluctuation probability envelope; constructing a complementary voltage-stabilizing virtual subgroup with a negative correlation compensation characteristic through a sequential sequence comparison algorithm; based on a power grid agent model and a kernel function SHAP algorithm, quantizing marginal contribution values of residual disturbance power of each subgroup to frequency deviation of the common connection point; performing a non-linear mapping on the contribution value to generate a virtual impedance correction parameter; and finally, through a layered decoupling closed-loop correction architecture, determining predicted power regulation and control vacancy and generating a compensation instruction. According to the method, the complementarity and the disturbance contribution of each heterogeneous power supply are quantified, so that the high-precision prediction of the distributed energy grid-connected stability influence is realized.