1892 results about "Frequency deviation" patented technology

The invention relates to the technical field of devices for adjusting, controlling or stabilizing power or frequency in a power grid, in particular to a rapid frequency modulation method for a wind turbine generator based on disturbance adaptive compensation, which comprises the following steps of: constructing a dynamic disturbance sensing data set by collecting frequency deviation, a frequency deviation change rate and fan state parameters; a window length and a weight coefficient of a short-time window sliding mean algorithm are dynamically optimized by adopting a genetic algorithm, background noise interference of a power grid is suppressed, and high-precision disturbance characteristics are extracted. And reducing frequency interference of inertia identification by using a reverse test signal. And updating boundary layer parameters of the sliding mode control model through an online incremental learning algorithm, dynamically adjusting the output priority based on the disturbance energy entropy, and eliminating power conflicts. A multi-island genetic algorithm is introduced to optimize a mode switching threshold value, and frequency modulation safe exit is realized in combination with adaptive power ramp rate limitation. According to the method, the frequency response speed and the multi-source cooperation efficiency in the dynamic multi-disturbance and inertia time-varying scene are remarkably improved, and the frequency secondary drop risk is reduced.

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 provides a multi-power-supply cooperative frequency modulation control method, and relates to the field of power grid dispatching, and the method comprises the steps: obtaining the real-time operation data of a power grid, the real-time operation data of the power grid comprises system frequency deviation, load prediction information, and the real-time output and adjustment capability data of multiple power supplies such as wind power, photovoltaic, hydroelectric and thermal power; according to the real-time operation data of the power grid, through a mixed integer linear programming algorithm, taking power generation cost minimization as a target function, and taking multi-power output upper and lower limits, a climbing rate, a system frequency deviation limit value and the like as constraint conditions, calculating an optimal output distribution scheme of multiple power supplies; and converting the optimal output distribution scheme into a power supply output adjustment instruction. Cooperative frequency modulation of multiple power supplies is realized, the system frequency stability and economical efficiency are improved, the renewable energy source grid connection and consumption capability is enhanced, and an effective solution is provided for large-scale new energy source access to a power grid.

The invention discloses a time scale algorithm based on Kalman filtering and fusion weight. The time scale algorithm comprises the following steps: acquiring time deviation data and frequency deviation data of an atomic clock; calculating a time deviation optimal estimation value and a frequency deviation optimal estimation value of the atomic clocks in the clock group by adopting a Kalman filter, and calculating a time deviation optimal estimation value residual error and a frequency deviation optimal estimation value residual error of the atomic clocks in the clock group; calculating a fusion weight according to the time optimal estimation value residual error and the frequency optimal estimation value residual error of the atomic clocks in the clock group; and calculating a time scale through a time scale basic equation based on the fusion weight. According to the method, prediction values of time deviation and frequency deviation are improved through introduction of a Kalman filtering process, the noise influence of an atomic clock is reduced, and the real-time performance of a time scale is improved; and the time deviation residual error and the frequency deviation residual error are fused to calculate the weight of the atomic clock, so that the time scale with higher stability is established, and the medium and short term stability of the time scale is effectively improved.

The invention relates to an ore crushing equipment operation monitoring method. Comprising the following steps: establishing a physical field distribution equation including a vibration wave propagation path and sound wave attenuation characteristics in a crushing cavity in the ore crushing process; collecting multi-physical field data in real time by using a sensor, and converting the data into a characteristic field distribution diagram comprising a vibration intensity distribution diagram; calculating a real-time change rate of a working load through historical data and current data of equipment operation; the vibration intensity and the sound wave energy are combined, and three working conditions of a low-load area, a normal-load area and an overload area are defined in a partitioned mode; on the time scale, the signals are divided into short-time fluctuation and long-time trend, and two types of tracks are extracted through wavelet decomposition and a sliding window method; on the characteristic scale, analyzing the main frequency deviation of the vibration signal, the high-frequency energy peak value distribution of the sound wave signal and the gradient of temperature change; and combining a working condition partitioning result with a dynamic characteristic track, and establishing a working condition and characteristic linkage matrix.

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.

The invention relates to the technical field of electrical fault detection, in particular to a photovoltaic inverter fault detection system based on an electric signal, and the system comprises a signal collection module which continuously collects the output electric signal of an inverter, records the amplitude, frequency and phase of the electric signal, and generates an original signal record; and based on the original signal record, screening the electric signal, eliminating noise and non-characteristic data, and generating screened signal data. According to the method, the time frequency characteristics of the signals are extracted in real time through continuous wavelet transform, and the sensitivity and accuracy of fault detection are improved. According to the detailed feature recognition method, even tiny abnormal waveforms or frequency deviations can be captured, and therefore early warning of potential faults is achieved. Meanwhile, the fault detection threshold value is dynamically adjusted through the environmental parameters, flexible response is allowed according to the actual operation environment change, the false alarm and missing alarm conditions are reduced, and the adaptability and the reliability are improved.

The invention discloses a distributed wind set virtual inertia active support control method suitable for a weak power grid, and the method comprises the steps: dynamically adjusting the inertia support strength according to the frequency disturbance of a power grid through adaptive virtual inertia adjustment; multi-mode cooperative control is adopted, and an operation mode is switched according to the frequency deviation and the change rate so as to provide an optimal response; by means of dynamic damping compensation, frequency oscillation is suppressed in combination with multiple factors and an optimization algorithm, and system damping is improved; multi-time-scale cooperative control is implemented, and inertia support, power adjustment and rotating speed recovery are coordinated at a millisecond level, a second level and a minute level; and rotor kinetic energy graded release is adopted, kinetic energy release is accurately controlled according to the frequency drop degree, and sudden rotation speed drop is avoided. In addition, additional frequency damping control is introduced to enhance suppression of frequency fluctuation. The method can significantly improve the response speed and adaptability of the wind turbine generator to the frequency fluctuation of the weak power grid, ensures the frequency stability of the power grid, and provides key technical support for stable grid connection of wind power in the weak power grid.

The invention relates to the technical field of power supply, in particular to a new energy station power prediction method and system based on a weather forecast large model, and the method comprises the following steps: detecting a weather forecast difference value and output fluctuation, marking an abnormal time period, calculating a voltage and frequency deviation to generate a correction threshold value, and matching phase deviation to generate a smooth reference. And analyzing inertia and response rate, applying dynamic attenuation, and collecting tie line power to adjust, predict and generate an output result. According to the method, abnormal time periods are screened through reverse correlation of meteorological difference and output fluctuation, error conduction is blocked, irradiance prediction is corrected through a voltage frequency integral quantity closed loop, power grid response is improved, actually measured wind speed rolling mean value is matched with AGC phase offset, output smoothness is optimized, inertia time delay and frequency modulation rate dynamic matching is performed, and attenuation constraints are adjusted. The frequency risk is reduced, the tie line fluctuation and deviation superimposed effect is quantified, the attenuation range is dynamically adjusted, the power transmission robustness is enhanced, and wind and light curtailment is reduced.

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 belongs to the technical field of power systems and automation thereof, and relates to a virtual inertia fuzzy self-adaptive new energy inverter frequency active support method. Aiming at the problem of power grid frequency stability caused by new energy power generation intermittency and volatility, the method comprises the following steps: simulating inertia characteristics of a synchronous generator through a direct current side capacitance control strategy; detecting the frequency of the power grid by using a power synchronous ring, and converting a power difference value into a frequency deviation; designing a fuzzy control module, and adjusting the coefficient of the virtual inertia controller in real time according to the frequency deviation to optimize the frequency response; an inverter current given value is adjusted according to the output of the fuzzy control module, and active and reactive power output is calculated and controlled; relevant parameters are monitored in real time, the performance of the self-adaptive control module is evaluated, and parameter optimization response of the fuzzy controller is adjusted. The frequency stability and reliability of the power grid can be effectively improved, the control flexibility and precision of the inverter are improved, and new energy efficient grid-connected power generation is promoted.

The invention discloses an intelligent mine management and control platform for mine management, and relates to the technical field of mine management, a mine is divided into different monitoring areas, detailed classification is carried out according to the personnel density, and the personnel density of the monitoring areas is improved. Key data such as ground stress fluctuation amplitude and communication channel electromagnetic interference index are acquired in real time by using a preset sensor, and a data test model is constructed to evaluate the stability of the intelligent mine management and control platform in combination with a sensor acquisition frequency deviation proportion; according to the evaluation result, the area is divided into different out-of-control risk levels, in-depth stability prediction is carried out on the high-out-of-control risk area, and a corresponding emergency management plan is made; the monitoring precision and the emergency response efficiency of mine operation under complex and extreme environment conditions are remarkably improved, and the possibility of safety accidents and operation interruption caused by out-of-control risks is reduced.

The invention relates to the technical field of noise filtering, in particular to a communication line noise filtering system and method, and the system comprises a temperature coupling module, a voltage response module, a parameter joint debugging module and a link checking module. According to the method, inductance and capacitance node temperature data are collected and input into a piecewise linear regression model, the temperature-to-resonant frequency deviation gradient is calculated, a noise suppression bandwidth threshold value is dynamically matched in combination with a reference table, the frequency stability under temperature fluctuation is improved, Kalman filtering is used for processing voltage sampling, and a fluctuation predicted value is generated. According to the method, interval indexes are extracted based on a parameter mapping table, instant inductance and capacitance parameters are generated through least square fitting, voltage transient fluctuation self-adaption is achieved, noise power spectrum density is calculated through fast Fourier transform, a 3dB attenuation point is compared with a threshold value difference value to trigger parameter rollback, closed-loop control is formed, it is ensured that suppression bandwidth is continuously matched with a noise frequency band, and noise suppression is achieved. The bandwidth offset is reduced to be within 1.2%, and the optimization response time is shortened to 200 ms level.

A frequency regulation control method and apparatus, a device, and a storage medium. The method comprises: according to the frequency at a current moment and the calibration frequency of a wind / photovoltaic grid-connected system, determining the frequency deviation value at the current moment and, according to the frequency at the current moment and the frequency at the previous moment, obtaining a frequency deviation change rate (S110); if the absolute value of the frequency deviation value is greater than the absolute value of a preset frequency regulation threshold value, then, according to the frequency deviation value and the frequency deviation change rate, determining inertia response power (S120); according to the frequency deviation value, the preset frequency regulation threshold value, and a preset system maximum frequency deviation, determining droop response power (S130); according to the state of charge of battery energy storage, the inertia response power, and the droop response power, determining battery energy storage target charging and discharging power (S140); and, according to the battery energy storage target charging and discharging power, regulating the frequency of the system (S150).

The invention relates to the technical field of fault diagnosis, in particular to an automatic anomaly detection method for a high-speed rotating transmission device, which comprises the following steps of: acquiring angular acceleration, rotating inertia and strain data of the high-speed rotating transmission device, calculating a transient strain gradient and matching a rotating speed change rate, adjusting a strain deviation range according to the change of the rotating inertia, and detecting the anomaly of the high-speed rotating transmission device. And screening strain abrupt change points to obtain a rotation strain matching result. According to the method, the dynamic strain response interval is set, the strain deviation range is adjusted, the strain abrupt change points are screened, the frequency response of the equipment is monitored in real time and compared with the normal frequency, so that continuous monitoring of the frequency deviation rate is more accurate, the frequency deviation rate jointly acts on identification and clustering of abnormal characteristics, the accuracy and the real-time performance of fault diagnosis are improved, and the fault diagnosis efficiency is improved. By calculating the deviation degree of the abnormal characteristics and the normal track, the abnormal detection threshold can be adjusted, potential faults can be identified and processed more effectively, the maintenance cost of the high-speed rotating transmission device is reduced, and the operation efficiency is improved.

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 discloses a frequency modulation control method of a network-building type energy storage converter for improving frequency intensity, and the method comprises the steps: building a frequency deviation maximum value expression based on a frequency response model of the network-building type energy storage converter; when the frequency modulation of the network construction type energy storage converter is not considered, calculating a power grid system frequency intensity coefficient according to a given power grid system frequency deviation maximum value and a frequency deviation maximum value expression; when the frequency intensity coefficient of the power grid system is smaller than a preset threshold value, calculating a control parameter of the network-forming type energy storage converter; and performing frequency modulation control on the power grid system according to the control parameters and a pre-constructed adaptive inertia and damping parameter optimization control strategy.

The invention relates to the technical field of power system frequency, and discloses a thermal power generating unit-energy storage coupling frequency modulation system for improving power grid frequency stability, which comprises a thermal power generating unit module, an energy storage system module, an energy management and distribution control module and a communication and monitoring module. The thermal power generating unit provides a frequency stabilization basis through inertia response and power regulation, and the energy storage system compensates frequency deviation in a quick response mode. And the energy management module dynamically adjusts the power distribution proportion between the thermal power generating unit and the energy storage system based on the optimized objective function to realize efficient collaborative frequency modulation. The output power and the state of charge of the energy storage system are controlled by constraint conditions. The communication and monitoring module collects power grid frequency, load fluctuation and energy storage state data in real time, generates frequency modulation control signals and issues the frequency modulation control signals to each module. By combining the stability of the thermal power generating unit and the quick response characteristic of the energy storage system, the response speed and the adjustment precision of power grid frequency adjustment are remarkably improved, and meanwhile the frequency adjustment cost is reduced.

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 roadway surrounding rock deformation monitoring method based on an optical fiber sensor, and the method comprises the steps: laying on the surface of roadway surrounding rock through employing a distributed optical fiber sensing technology, and obtaining original optical signal data; processing backscattered light data in the original optical signal data through a Brillouin optical time domain analysis algorithm, extracting frequency deviation of an optical signal, and obtaining strain distribution data; according to the strain distribution data, in combination with a pre-established surrounding rock mechanical model, performing initial inversion calculation by adopting a finite element method to obtain initial three-dimensional deformation distribution; on the basis of the initial three-dimensional deformation distribution, updating dynamic boundary conditions of the surrounding rock mechanical model by acquiring real-time geological parameter data to obtain an optimized mechanical model; carrying out inversion calculation on the strain distribution data again by adopting an optimized mechanical model to generate final three-dimensional deformation distribution; and based on the final three-dimensional deformation distribution, performing comparison judgment through a preset deformation threshold, determining the stability state of the surrounding rock, and generating an early warning signal.

The invention discloses a frequency switching method and device of an embedded power terminal. The method comprises the steps that frequency switching is triggered by predicting frequency deviation and comparing the predicted frequency deviation with a preset frequency synchronization threshold value, and the transmitting power and the modulation mode in the switching process are optimized through a fuzzy control algorithm so as to suppress transient interference. During switching execution, the node synchronization state is monitored in real time, and an interruption mechanism is triggered when abnormity occurs. And after the switching is completed, calibrating the frequency parameter of each node, and updating the frequency drift compensation model. And dynamically optimizing the compensation model and the switching strategy by utilizing historical data and adopting a reinforcement learning algorithm, and synchronously updating the compensation model and the switching strategy to each node. By means of predictive triggering, intelligent parameter optimization, real-time monitoring and the like, the problems of transient interference, exception handling, model optimization and the like in the power terminal node frequency synchronization process are effectively solved. According to the method, the reliability and stability of power terminal node frequency synchronization are remarkably improved, and a powerful guarantee is provided for safe and stable operation of a power system.

The invention discloses a primary frequency modulation control method and system based on a collaborative optimization strategy, and the method comprises the steps: obtaining a system frequency deviation value of a power system, and triggering frequency modulation control when the system frequency deviation value exceeds a preset frequency deviation threshold value; obtaining and classifying various frequency modulation resources, and determining frequency modulation priorities of the various frequency modulation resources; based on the classified frequency modulation resources, a multi-target optimization model is constructed and solved, and the optimal output adjustment amount of each type of frequency modulation resources is obtained; converting the optimal output adjustment amount of each frequency modulation resource into a corresponding frequency modulation control instruction, and sending the frequency modulation control instruction to a corresponding control device; the system frequency is monitored in real time, and when the system frequency deviation value obtained in real time is within a preset frequency deviation threshold value, frequency modulation control is completed. The frequency of the power system is intelligently and accurately regulated and controlled, the frequency modulation response speed and the control effect are improved, the frequency modulation cost is reduced, and the stability and the reliability of the system are enhanced.

The invention relates to an active and reactive collaborative optimization control method for a photovoltaic energy storage system based on a network-forming inverter, and the method achieves the effective control of active and reactive power through simulating the characteristics of a synchronous generator. And then collaborative optimization of active and reactive power control parameters is carried out. A system frequency response model is utilized to describe dynamic response of system frequency, and a dynamic equation of the system is converted into a discrete form in combination with the dynamic equation of the energy storage unit. Meanwhile, the optimization model is solved by considering system capacity limitation, so that transient frequency characteristics are improved, and frequency deviation after system disturbance is reduced. In addition, the minimum active power loss is taken as an optimization target, the voltage deviation is taken as a penalty term to be substituted into a target function, and a reactive power optimization target function is established. A PSO algorithm is adopted to solve a reactive power optimization function, and reactive power output of photovoltaic and energy storage is adjusted by adjusting VSG control parameters, so that the economical efficiency of a power grid is improved on the premise of ensuring qualified voltage.

The invention relates to the technical field of wind storage combined system frequency modulation, in particular to a parameter setting and adaptive optimization-based wind storage combined system frequency modulation method, system and device and a medium, and the method comprises the steps of obtaining wind storage combined system data in real time; setting an initial value and an adjustment range of a frequency modulation parameter according to the wind storage combined system data; taking the adjustment range of the frequency modulation parameter as a constraint, inputting the wind turbine generator output distribution weight, the energy storage output distribution weight and the frequency modulation parameter as optimization variables into an improved particle swarm algorithm, and generating optimal values of the frequency modulation parameter, the wind turbine generator output distribution weight and the energy storage output distribution weight; generating a combined frequency modulation instruction, and controlling the wind turbine generator and the energy storage system to output frequency modulation power; and monitoring the parameters after frequency modulation in real time and updating the particle swarm algorithm output of the next period to form closed-loop control. According to the invention, the improved particle swarm optimization algorithm is used for dynamically setting the frequency modulation parameters and cooperatively optimizing the wind storage output weight, so that the targets of frequency deviation minimization and safe operation of equipment can be achieved.

The invention discloses a tracking-networking type new energy sending end system scheduling method considering dynamic frequency constraint, and belongs to the technical field of power system operation and planning. The method comprises the following steps: establishing a multi-resource collaborative frequency response model of a high-proportion new energy sending end system, establishing a maximum frequency deviation, an initial frequency change rate and a steady-state frequency difference dynamic index, and converting the dynamic indexes into constraint conditions in optimal scheduling; and combining an energy storage refinement model, conventional unit operation constraint and fuzzy opportunity constraint to process wind and light load uncertainty, and constructing an optimization framework with the lowest total operation cost as a target function. Through deep fusion of dynamic frequency security constraint and resource collaborative scheduling, new energy output fluctuation is effectively stabilized, the system frequency stability and economy are improved, and the technical defect that a traditional scheduling model neglects a dynamic frequency security index in a high-proportion new energy scene is solved.

The invention relates to the field of power system frequency stability control, and discloses a virtual synchronous machine energy storage frequency modulation method and system based on model prediction and adaptive control, and the method comprises the steps: constructing a prediction model of a virtual synchronous machine, wherein a virtual inertia coefficient and a virtual damping coefficient are included; designing a cost function, wherein the cost function is a weighted sum of squares of the frequency increment and the input power increment; solving the optimal control sequence by using quadratic programming, and further correcting the input power of the VSG in real time; and in combination with the dynamic characteristics of the energy storage device, the virtual inertia coefficient and the damping coefficient are adaptively adjusted according to the frequency deviation and the frequency change rate. The method focuses on the combination of model prediction control and adaptive control, is applied to the energy storage frequency modulation of the virtual synchronous machine, and aims to effectively solve the problem of frequency stability caused by the access of high-proportion renewable energy to a power system.

The invention discloses a control system and method for a thermal power generating unit and flywheel energy storage to cooperatively participate in power grid frequency modulation and a power grid frequency modulation method. According to the method, a low-pass filtering algorithm is abandoned, a tracking differentiator is used for decomposing a primary frequency modulation instruction of the thermal power generating unit, and decomposed low-frequency power components are distributed to the thermal power generating unit; high-frequency power components are distributed to the flywheel for energy storage, action times and output abrasion of the thermal power generating unit are reduced, and the service life of the unit is prolonged. A gain coefficient which adaptively changes along with the state of charge (SOC) and frequency deviation is introduced into the decomposed high-frequency power component, so that accurate matching requirements are facilitated, the energy utilization efficiency is improved, the frequency fluctuation of a power grid is better stabilized, and the quality of the power grid is improved; and meanwhile, a Logistic function for preventing the flywheel from being overcharged and overdischarged is introduced to restrain the theoretical response power of flywheel energy storage, deep charging and discharging of the flywheel are avoided, and therefore the loss of the flywheel is reduced.

The invention belongs to the technical field of inertia evaluation, and discloses a direct current delivery system minimum inertia demand evaluation method considering multi-frequency modulation resource support characteristic difference, and the method comprises the steps: firstly analyzing the frequency response characteristics of each frequency modulation resource in a direct current delivery system in a typical control mode; a system frequency response model considering wind power, photovoltaic and extra-high voltage direct current frequency response characteristic differences is established, and an influence mechanism of different frequency modulation resources on system frequency characteristics is disclosed. Secondly, constructing a system equivalent inertia calculation model considering a wind power and photovoltaic inertia support effect, and providing a minimum inertia demand evaluation method based on an initial frequency change rate as a constraint; and then, considering the influence of a direct current frequency limit controller on the maximum frequency deviation, designing a direct current delivery system minimum inertia evaluation scheme considering the frequency dynamic safety constraint so as to support efficient, stable and continuous delivery of new energy power generation.

The invention provides an underwater ultrasonic Doppler real-time analysis method and device based on a digital transducer, and relates to the technical field of data analys.The method comprises the steps that 1, multiple beams of directional ultrasonic waves are emitted into drilling fluid through a digital transducer array on the outer wall of a marine riser, echo signals reflected by gas-liquid two-phase flow are received, and the digital transducer array is used for receiving the echo signals; performing real-time digital conversion on the echo signal to generate an original digital signal containing phase and amplitude information; 2, Doppler frequency shift feature extraction is conducted on the original digital signals, and the real-time movement speed and direction of bubbles in the drilling fluid are determined by calculating the frequency deviation of reflected ultrasonic waves and transmitted ultrasonic waves. Through the digital transducer array and the ultrasonic Doppler technology, accurate measurement of motion parameters of bubbles in drilling fluid, real-time calculation of local gas content and early warning and grading response of gas cut are achieved, and the safety and the intelligent level of drilling operation are improved.