7163 results about "Frequency modulation" patented technology

The invention provides a method for participating in primary frequency modulation control of a power system based on a modular large-scale hydrogen production power supply, and the method comprises the steps: obtaining an original data flow from a high-precision synchronous phasor measurement unit, an electrolytic cell and a submodule, and carrying out the multi-scale decomposition and noise reduction processing after time synchronization and anomaly detection restoration; performing state estimation by using unscented Kalman filtering, extracting frequency disturbance characteristics in combination with empirical mode decomposition and Hilbert transform, and estimating the inertia of the power grid; an electrolytic cell dynamic model is established, and parameter identification and optimization are carried out through a recursive least square method; a control strategy is designed based on a multi-time scale control framework, virtual synchronous generator parameters are optimized through online Gaussian process regression, and frequency modulation control is realized in combination with scene tree random model predictive control and minimum-maximum regret learning; and finally, carrying out coordination control through a distributed consistency algorithm and carrying out multi-target performance evaluation optimization. And the frequency modulation performance and the operation efficiency of the system are improved.

A method for diagnosing rotor rub-impact in a rotating machinery based on vibration signal deconstruction and frequency modulation characteristic anti-noise enhancement, including: converting, based on two-stage integration transformation and high-pass filtering, vibratory acceleration signals from a rotating machinery device into vibratory displacement signals; performing targeted extraction on a rotating frequency component therein based on an improved variational mode decomposition method; calculating and estimating instantaneous fluctuation characteristics of a fundamental frequency of the extracted rotating frequency component using a quadrature-derivative-based normalized Hilbert transform to obtain an instantaneous frequency; inputting a calculated instantaneous frequency sequence into an optimum stochastic resonance system for anti-noise enhancement of intrawave frequency modulation characteristics; and processing FFT on an instantaneous frequency of intrawave frequency modulation characteristics after anti-noise enhancement, and diagnosing and identifying a rotor rub-impact fault of the rotating machinery based on a distribution characteristic of harmonic amplitudes related to a rotor rotating frequency.

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 discloses a virtual power plant collaborative optimization operation method based on distributed energy, and the method achieves the real-time monitoring of the operation state of a distributed energy resource through the precise modeling of the distributed energy resource, and predicts the change of the power load demand. A multi-objective optimization model and an advanced optimization algorithm, such as a genetic algorithm or a particle swarm algorithm, are utilized, so that the virtual power plant can dynamically adjust energy supply and load demands, and economic benefit maximization, energy efficiency optimization and carbon emission minimization are realized. The method also considers the energy efficiency and economic benefits of the virtual power plant, and improves the comprehensive benefits of the system through comprehensive analysis and optimization. Through effective interaction with the power grid, the virtual power plant can provide peak regulation, frequency modulation and standby services, a demand response mechanism is implemented, and operation of the power grid is further optimized. The method has the beneficial effects of improving the energy utilization efficiency, enhancing the stability of a power grid, optimizing economic benefits, promoting environmental protection, improving the flexibility and adaptability of the system and supporting policies and market mechanisms.

The invention relates to the technical field of communication optimization, in particular to a wireless communication method and system of a vehicle diagnosis system. The method comprises the following steps: identifying a plurality of signal sources in an environment and three-dimensional space data of a current position of a vehicle; performing scene interference intensity comprehensive evaluation on the plurality of signal sources in the environment to obtain a current scene interference intensity evaluation value of the vehicle; environment obstacle space layout analysis is carried out on the three-dimensional space data of the current position of the vehicle, environment three-dimensional modeling is carried out, and a vehicle environment three-dimensional point cloud model is constructed; signal multi-path propagation evolution is carried out according to the current scene interference intensity evaluation value of the vehicle and the vehicle environment three-dimensional point cloud model, and optimal signal frequency band analysis is carried out, so that optimal signal frequency band parameters are extracted; and carrying out dynamic transmission frequency modulation and signal adaptive coding based on the optimal signal frequency band parameter, and constructing a dynamic signal transmission strategy. According to the invention, efficient and stable wireless communication is realized, and the vehicle-mounted communication performance is improved.

The invention provides an optical energy storage regulation and control method and system based on multi-time scale rolling optimization in the technical field of energy storage regulation and control, and the method comprises the steps: S1, inputting a 24-hour electricity price prediction curve, a 24-hour photovoltaic output prediction curve, a 24-hour load prediction curve and an initial SOC into a day-ahead prediction model, a 24-hour SOC reference trajectory and a standard charging and discharging plan are obtained; s2, collecting feedback data, and inputting the 24-hour SOC reference trajectory, the standard charging and discharging plan and the feedback data into the intra-day prediction model to obtain a corrected charging and discharging plan; and S3, setting an SOC dynamic limit value, collecting a real-time electricity price and real-time photovoltaic output, and inputting the corrected charging and discharging plan, the SOC dynamic limit value, the real-time electricity price, the real-time photovoltaic output and the actual SOC into the real-time prediction model to obtain a charging and discharging instruction and frequency modulation output power. The method has the advantages that the precision, economical efficiency and power grid adaptability of energy storage regulation and control are greatly improved, and the attenuation speed of the service life of the battery is greatly delayed.

The invention discloses a wind-light-hydrogen multi-energy complementary system cooperative operation optimization and comprehensive benefit evaluation method, which relates to the technical field of electric energy storage, and comprises the following steps: constructing a hybrid power flow model containing electricity, hydrogen and heat coupling, taking whole life cycle cost and new energy consumption as double targets, introducing grid-connected and off-grid risk constraints, and optimizing equipment capacity configuration; a scheduling baseline and an intra-day dynamic correction strategy are formulated in the day-ahead stage, and hybrid energy storage cooperative control is combined to improve the response speed and flexibility of the system to wind and light fluctuation; a peak regulation and frequency modulation mode is switched according to the power grid state, a power response model is established, fluctuation is stabilized through hydrogen energy storage, the stability of the power grid is enhanced, and auxiliary service benefits are created; the performance of the system is evaluated from the three dimensions of efficiency, economy and interactivity, dynamic weight and Monte Carlo simulation optimization are utilized, system parameters are continuously optimized through a feedback mechanism, and the self-evolution ability is formed. The problem that system instability and economy are difficult to take into account due to wind and light fluctuation is solved.

A method for actuating a DC-to-DC converter, in particular a clocked buck-boost converter that includes at least two switch elements and an inductor or throttle and via which an input voltage is converted into a regulated output voltage, wherein the switch elements are actuated with a variable switch frequency using pulse- and frequency-modulated control signals, where the pulse- and frequency-modulated control signals are derived from a manipulated variable from a regulator, a voltage curve on the switch elements is continuously ascertained or monitored to determine the activation time of the switch elements and to start a new switch cycle, the switch elements are activated if a specified minimum period duration has been exceeded upon detecting a voltage minimum of the ascertained voltage curve on the switch elements.

The invention discloses a super-capacity energy storage frequency modulation instruction prediction method and system, a medium and equipment, and belongs to the technical field of power grid frequency modulation, and the method comprises the steps: obtaining a historical frequency modulation instruction sequence and a current frequency modulation instruction; an error sequence corresponding to the historical frequency modulation instruction sequence is a historical error sequence, and an error corresponding to the current frequency modulation instruction is a current error; based on the current error, the iteration weight of the prediction model is adjusted according to the historical error sequence until the current error is smaller than a preset value, and the prediction model after weight adjustment and a new current error are obtained; performing error trend analysis on the new current error and the historical error sequence to obtain an error acceleration; setting a fine tuning coefficient for the frequency modulation instruction sequence according to the magnitude of the error acceleration; inputting the frequency modulation instruction sequence with the fine tuning coefficient into the prediction model after weight adjustment to obtain a predicted frequency modulation instruction at a future moment; the prediction precision of the frequency modulation instruction is effectively improved, and the operation efficiency and stability of the energy storage system are guaranteed.

An optical storage system designed to compensate for the water hammer effect in hydropower turbines and its cooperative frequency modulation method are provided. The method involves detecting the water hammer effect and utilizing a pre-established system model integrating a hydropower unit, photovoltaic system, and hybrid energy storage system. Through model predictive control combined with a whale optimization algorithm, the governor parameters of the hydropower unit are optimized. The system then obtains the photovoltaic active power output and the battery's state of charge (SOC) within the hybrid energy storage system. Based on these parameters, a collaborative control strategy for the photovoltaic and hybrid energy storage systems is determined and executed. This strategy enables effective control of the photovoltaic system and / or hybrid energy storage to compensate for reverse power adjustments in the hydropower unit, addressing the water hammer effect and ensuring stable power grid operation.

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 relates to a self-adaptive intelligent power control method for an electric energy router in a photovoltaic power generation system. According to the method, key parameters of photovoltaic, energy storage and load are monitored in real time, a virtual power pool is constructed to quantify a multi-source power margin and dynamically distribute a priority sequence, energy storage output is dynamically adjusted in combination with a feed-forward compensation control strategy, frequency modulation deviation is periodically checked, weight optimization redistribution is triggered, and energy storage output is dynamically adjusted. Cooperative control of photovoltaic load reduction frequency modulation and DC bus voltage stability is realized, the multi-source cooperative frequency modulation response capability and the energy utilization rate are effectively improved, voltage fluctuation caused by power abrupt change is suppressed, and both the system operation economy and the power supply reliability are considered.

The invention relates to the technical field of participation of a wind storage system in power grid frequency modulation, and particularly provides an active regulation power quantitative evaluation method and device for self-adaptive frequency modulation of a wind storage system, and the method comprises the steps: constructing an energy storage system frequency response model, and calculating the active power of energy storage participating in frequency modulation; constructing a wind turbine generator wind speed fluctuation model, simulating the wind speed fluctuation condition in the same wind power plant according to the wind speed probability distribution, and generating a section of random wind speed disturbance; constructing a frequency response model of the wind turbine generator, and calculating active power participating in frequency modulation; a wind storage system adaptive distribution model is constructed based on a depth deterministic strategy gradient algorithm, and optimal distribution of a virtual droop control coefficient and a virtual inertia control coefficient of the wind storage system is realized; and calculating the active regulation power of the wind storage system after self-adaptive frequency modulation. And calculating the adjustable active power of the wind turbine generator and the energy storage equipment participating in the frequency modulation strategy when the optimal frequency modulation effect is achieved and the service life of the equipment is balanced.

The invention discloses an energy storage frequency modulation instruction prediction method and system based on a signal sequence folding rate. An original frequency modulation instruction signal sequence is obtained; obtaining optimization parameters for each signal in the original frequency modulation instruction signal sequence, wherein the optimization parameters comprise a first folding rate Z1, a first average value Q1 and a first variance C1; generating an auxiliary signal sequence based on the optimization parameters, and obtaining a combined signal sequence; predicting by using a neural network based on the auxiliary signal sequence and the combined signal sequence to obtain an intermediate prediction result; performing decoupling operation on the intermediate prediction result to obtain a final prediction result; the prediction result of the frequency modulation instruction is more accurate, the size of the frequency modulation instruction is predicted in advance for energy storage regulation, and the response accuracy and the frequency modulation income are improved.

The invention provides a power grid frequency modulation power energy coordination control method and system based on a super capacitor, and relates to the technical field of power grid frequency modulation, and the method comprises the steps: carrying out the time-frequency analysis of a collected power grid frequency signal, obtaining a frequency disturbance characteristic value, and determining power control data through combining with an electrical parameter value of a super capacitor group; and performing nonlinear programming calculation based on the power control data to obtain a power distribution sequence, dividing the power distribution sequence into a quick response section, a dynamic transition section and a steady state maintenance section according to a preset threshold value, and solving a control value by adopting an augmented Lagrange equation, recursive least square operation and a Lyapunov function respectively. Obtaining a power control instruction; and inputting a power control instruction into the disturbance observer, calculating a dynamic error value, constructing a nonsingular terminal equation, and outputting a power regulation signal in combination with recursive minimum entropy calculation and a superhelix algorithm.

The invention relates to the technical field of signal parameter measurement, and provides a parameter measurement method for a frequency modulation monitoring antenna, which realizes self-adaptive monitoring and accurate measurement of a complex electromagnetic environment through multi-dimensional data acquisition, intelligent analysis and dynamic optimization, and deeply integrates environment perception, signal processing and parameter optimization. A complete technical chain is formed, so that the parameter measurement method can have self-learning and self-adjusting capabilities, can cope with environmental changes and interference challenges in real time, remarkably improves the monitoring efficiency and the measurement precision, and provides a systematic solution for the application of a frequency modulation monitoring antenna in a complex scene.

The invention relates to the field of energy storage frequency modulation prediction, and discloses an energy storage frequency modulation instruction prediction method and system based on a two-stage method, and the method comprises the steps: obtaining an energy storage frequency modulation instruction, and carrying out the variational mode decomposition; judging mutual attraction or mutual repulsion of the subsequences according to a variation mode decomposition result; if it is judged that the two subsequences attract each other, sequence fusion operation is carried out, and if it is judged that the two subsequences repel each other, sequence generation operation is carried out; obtaining a new sub-sequence set through sequence fusion operation and sequence generation operation; and respectively inputting the sequences in the new sub-sequence set into the recurrent neural network to obtain a final prediction result of the energy storage frequency modulation instruction. By optimizing the frequency modulation instruction in advance, the energy storage system can respond to the frequency change requirement more quickly and accurately, the frequency modulation efficiency and economic benefits of the power system are remarkably improved, and meanwhile the stability of the system and the operation efficiency of the power plant are enhanced.

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.

The invention relates to the technical field of steam turbine testing, in particular to a testing system for mismatch correction of a wide-load-interval thermal power generating unit speed regulation model, which comprises a thermodynamic system component, a speed regulation system device, a dynamic signal acquisition device and a control device, a dynamic signal processing module analyzes the relevance between main steam pressure sudden change and control valve opening oscillation in real time, a dynamic response database including a time sequence is constructed, and a control valve opening feed-forward compensation instruction and a combustor fuel distribution gradient adjustment signal are generated according to correction parameters. Power over-modulation wave crests caused by sudden load change are suppressed, and primary frequency modulation action delay is reduced; and the simulation verification module compares measured data with model output through an error feedback mechanism, dynamically adjusts high-pressure cylinder flow characteristic curve calibration parameters, optimizes a control strategy in combination with a network-related safety margin evaluation result, and realizes improvement of dynamic response precision in a full peak regulation interval and enhancement of power grid frequency stability.

The invention discloses an energy storage frequency modulation instruction prediction method and system based on a gravitational method, and relates to the technical field of energy storage frequency modulation prediction. Optimal parameter optimization is carried out on the VMD through an improved sparrow search algorithm; and outputting each optimal sub-sequence to obtain a final prediction result. According to the energy storage frequency modulation instruction prediction method based on the gravitational method provided by the invention, the independence of each sub-sequence after sequence decomposition is improved by evaluating the similarity between the sub-sequences, the decomposition effect is improved through the improved sparrow search algorithm and adaptive optimization of VMD decomposition parameters, each IMF sub-sequence is independently predicted through the GRU network, and the prediction efficiency is improved. The method improves the reliability and accuracy of overall prediction, and achieves better effects in the aspects of decomposition effect, reliability and accuracy.

The invention discloses an energy storage power station state evaluation method and system based on real-time demand analysis, and relates to the technical field of power station state evaluation, and the method comprises the steps: obtaining the real-time operation data of an energy storage power station; the real-time operation data comprises voltage data, current data, temperature data and power data; based on the real-time operation data, establishing an energy storage power station real-time evaluation index system under the demand of a power grid system; and based on the energy storage power station real-time evaluation index system, establishing an energy storage power station performance comprehensive evaluation model, and performing energy storage power station state evaluation according to the energy storage power station performance comprehensive evaluation model. According to the method, operation data are acquired from multiple dimensions of a PCS converter, a battery body and a PCC point, a systematic evaluation index system of four requirements of power grid frequency modulation, peak regulation, voltage regulation and power oscillation suppression is combined, and an evaluation method of combining dynamic fuzzy comprehensive evaluation and adaptive weight dynamic adjustment is adopted; and comprehensive and accurate evaluation of the state of the energy storage power station is realized.

The invention relates to the technical field of instruction prediction, and discloses a frequency modulation instruction prediction method and system for super capacitor coupling lithium battery energy storage. The method comprises the following steps: performing decomposition processing on a standardized frequency modulation sequence through a smoothing function to obtain an approximate integratable amount and an inintegratable amount; performing trigonometric function periodic conversion processing on the approximate integrable quantity to obtain a periodic characteristic sequence which is composed of a plurality of sine and cosine functions with different frequencies; carrying out linear merging transformation processing on the periodic feature sequence and the non-integrable quantity to obtain a combined feature sequence; performing training processing on the combined feature sequence through a deep neural network to obtain a frequency modulation instruction prediction model; and performing prediction processing on the real-time frequency modulation instruction data through the frequency modulation instruction prediction model to obtain a prediction result, and performing reverse normalization processing on the prediction result to obtain a frequency modulation instruction prediction value. According to the invention, the efficiency and accuracy of frequency modulation instruction prediction for super capacitor coupling lithium battery energy storage are improved.

The invention belongs to the technical field of power systems, and particularly relates to a cooperative control evaluation method and system for a new energy station and shared energy storage, and the method comprises the steps: obtaining the dynamic operation parameters of the new energy station; based on the obtained dynamic operation parameters, considering peak and frequency regulation requirements of the power grid, and constructing a comprehensive evaluation index system of the new energy station and the shared energy storage; according to the constructed comprehensive evaluation index system, constructing a multi-time-scale collaborative optimization model of the new energy station and the energy storage system; based on the constructed multi-time-scale collaborative optimization model, performing collaborative multi-target optimization operation scheduling of the new energy station and the shared energy storage by taking the maximum total benefit of peak regulation and frequency modulation of the power grid as a target; and according to the obtained cooperative multi-objective optimization operation scheduling result, considering multi-station control adjustment margin fusion perception, and completing cooperative control evaluation of the new energy station and the shared energy storage.

The invention provides a temperature compensation method and device for a silicon carbide MOS drive control chip, and the method comprises the steps: obtaining a junction temperature-electrical parameter set of a silicon carbide MOS, and carrying out the thermoelectric coupling simulation modeling processing of a junction temperature-electrical parameter mapping data set, and obtaining three-dimensional temperature-efficiency characteristic data; performing real-time parameter analysis and dynamic execution on the three-dimensional temperature-efficiency characteristic data to obtain an optimized switching characteristic waveform; extracting the optimized switching characteristic waveform frequency domain characteristics, and generating a dynamic frequency modulation parameter; and performing dead time iterative optimization on the dynamic frequency modulation parameters to obtain a control parameter combination of the silicon carbide MOS.

The invention discloses an unmanned surface ship cluster trajectory prediction method and system in an uncertain environment, and the method comprises the steps: 1, employing a self-adaptive linear frequency modulation mode decomposition algorithm, decomposing original trajectory data into Q signal components, employing the first k signal components, including the kth signal component, in the Q signal components as useful signal components, and employing the first k signal components as the first k signal components; taking the residual signal components as noise of the ship trajectory data, and filtering the residual signal components; step 2, constructing a model for the time correlation of the ship trajectory based on Mama, and extracting a motion mode of the ship through the constructed model; step 3, constructing an interaction diagram according to the spatial positions of each ship and the surrounding ships in each time step, updating information of each node and edge of the interaction diagram, and obtaining interaction characteristics of the ships; and 4, fusing the motion mode in the step 2 and the interaction characteristics in the step 3, and predicting the future trajectory of the ship. According to the method, the influence of noise on ship trajectory prediction can be reduced, and the prediction precision is improved.

The invention relates to the technical field of signal analysis, and discloses a primary frequency modulation large disturbance signal peak value analysis method, which comprises the following steps: collecting a primary frequency modulation large disturbance signal and carrying out filtering processing of multi-band noise separation; performing multi-scale decomposition on the filtered disturbance signal, extracting a dynamic entropy of a multi-scale signal sequence, and performing dynamic entropy denoising on the disturbance signal to obtain a denoised disturbance signal; and calculating a potential peak position of the denoised disturbance signal, and carrying out multi-condition verification on the potential peak position to obtain peak information for frequency modulation disturbance analysis. Based on spectrum energy distribution, specific wavelet bases are selected for different noise frequency bands for noise reduction, the wavelet noise reduction performance is improved, the energy distribution complexity and the structure complexity of the disturbance signals on different scales are extracted, the dynamic characteristics of the disturbance signals are captured more comprehensively, the noise reduction precision is improved, and the noise reduction efficiency is improved. And the accuracy of wind power integration fault identification and equipment life monitoring in the peak value analysis process is improved.

The invention discloses an AI computing power equipment intelligent energy consumption management system and method based on big data, and relates to the technical field of data center energy consumption management, the method comprises the following steps: obtaining real-time operation data of AI computing power equipment, the real-time operation data comprising load characteristic parameters, energy consumption characteristic parameters, environment characteristic parameters and equipment state parameters; obtaining a load discrimination value according to the load characteristic parameter; obtaining an energy consumption discriminant value according to the energy consumption characteristic parameters; acquiring an environment discrimination value according to the environment characteristic parameters; acquiring a state discrimination value according to the equipment state parameter; fusing the load discriminant value, the energy consumption discriminant value, the environment discriminant value and the state discriminant value to generate a comprehensive energy efficiency index; judging whether the comprehensive energy efficiency index exceeds a preset dual-threshold decision interval or not; if the upper limit threshold value is exceeded, triggering graded consumption reduction response, including dynamic frequency modulation, task migration or equipment dormancy; and if so, determining that the current operation mode is in a high-energy-efficiency state and maintaining the current operation mode.

The invention discloses a collaborative optimization scheduling method and system considering energy storage frequency modulation reserve. The method comprises the following steps: acquiring basic data of a power system; based on the basic data, a collaborative optimization scheduling model considering energy storage frequency modulation reserve is established, and the collaborative optimization scheduling model takes the minimum sum of the coal consumption cost, the unit start-stop cost and the wind curtailment cost of the thermal power generating unit as a scheduling target under multiple constraint conditions; the multiple constraint conditions comprise a lithium battery power constraint, a charging and discharging state constraint, an SOC constraint, a frequency modulation response constraint, a frequency safety constraint, a frequency modulation standby constraint, a flywheel energy recovery constraint, a thermal power generating unit operation constraint and a power balance constraint; solving the collaborative optimization scheduling model to obtain an optimal scheduling scheme of the power system; by comprehensively utilizing the advantages of a traditional unit, flywheel energy storage and lithium battery energy storage, the safety and operation economy of the system during frequency disturbance are improved.

The invention relates to the technical field of mechanical fault diagnosis, and discloses a gearbox fault diagnosis method and system based on lightweight variational Bayesian learning, and the method comprises the steps: collecting a to-be-diagnosed vibration signal of a gearbox, carrying out the preprocessing of the to-be-diagnosed vibration signal, and obtaining an original vibration signal and the fault feature frequency of the original vibration signal; determining amplitude modulation-frequency modulation sparse combination representation of the original vibration signal according to the fault characteristic frequency of the original vibration signal, and constructing a joint probability model according to classification distribution containing sparse vectors and the amplitude modulation-frequency modulation sparse combination representation of the original vibration signal; performing variational Bayesian inference solution on the joint probability model by using the non-overlapping sub-sequence of the original vibration signal and natural gradient optimization to obtain posterior probability estimation of a sparse coefficient; and determining an activation component according to the posterior probability estimation of the sparse coefficient and the sparse precision parameter, and matching the activation component with a pre-established multi-scale amplitude modulation-frequency modulation sparse dictionary to obtain a fault type and a confidence coefficient thereof.

The invention belongs to the technical field of stable operation of a power system, and discloses a wind turbine generator primary frequency modulation adaptive control method considering active regulation capability, which comprises the following steps: firstly, establishing a wind speed model, and designing a wind turbine generator active load reduction control scheme according to different wind speed intervals; proposing active load reduction of the wind turbine to provide standby down-modulation potential evaluation indexes, carrying out weight calculation by adopting a normal cloud combination in combination with a subjective and objective weighting method, and carrying out comprehensive evaluation on the power regulation and control capability of the wind turbine generator; and when the power system encounters active power shortage, the wind power plant regulation and control center calculates the power regulation quantity of the wind turbine generator according to the comprehensive evaluation result, issues an adaptive power regulation instruction, and cooperates with the conventional unit to suppress the drop of the power grid frequency. According to the method, comprehensive evaluation of normal cloud combination is adopted as the making basis of the wind turbine generator set power adjusting instruction, the standby power reserved by active load reduction of the generator set is effectively utilized, active power output of a wind power plant grid-connected point under disturbance is optimized, and the stability of a power grid is improved.