167 results about "Electrical network frequency" patented technology

The invention discloses a safety control method and system for an emerging control main body, and belongs to the technical field of power system active control, and the method comprises the steps: carrying out the bidirectional data interaction through a master station AGC and a field station AGC, and carrying out the bidirectional data interaction based on a bidirectional data interaction result and a cooperative anti-error parameter; whether the emerging control main body is in a controllable state or not is judged in real time through collaborative security locking logic; if the control main body is in the controllable state, active measurement data of the emerging control main body are obtained, and jump detection and multi-source checking are carried out on the active measurement data; after verification is passed, a pre-control instruction is generated based on the control strategy, and reasonability verification and control effect simulation verification are carried out; and after the control effect simulation verification is passed, the pre-control instruction is taken as a final control instruction to be issued to the emerging control main body for execution. The method can greatly improve the safety control capability of AGC on an emerging control main body, guarantees the frequency operation safety of a power grid, and improves the safe and reliable power supply capability of the power grid.

The invention discloses a frequency response modeling method, system and device based on power grid planning and a storage medium, and relates to the field of power system planning operation, and the method comprises the steps: employing an improved K-means algorithm based on data intensity, and carrying out the clustering of water, fire, wind and light units according to characteristic parameters; predicting a long-sequence meteorological scene based on historical meteorological data by using a three-layer BP neural network and reducing the long-sequence meteorological scene to obtain a typical operation scene; establishing an optimization model to obtain a power supply total output plan by combining unit clustering, a typical scene and a power grid boundary condition; a mixed integer optimization model is constructed to determine a synchronous unit starting scheme, equivalent inertia is calculated, new energy and stored energy equivalent inertia is calculated, and system frequency response model identification parameters are established and simplified; the method can improve the frequency stability of the power grid, reduce the operation risk caused by new energy access, optimize the power supply and net rack configuration in the planning stage, reduce the frequency out-of-limit and load loss during a fault, and enhance the safety and economy of the power grid.

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

The invention belongs to the technical field of source network load storage monitoring, and particularly provides a source network load storage real-time monitoring cooperation system based on edge calculation, and the system mainly comprises a data collection and standardization module which obtains the collected output power of a photovoltaic inverter, the frequency deviation of a power grid, the switching state of an important load, and the charging and discharging rate data of an energy storage system, performing multi-source data fusion to obtain a system monitoring data set; the dynamic characteristic evaluation module is used for carrying out multi-dimensional characteristic analysis based on the system monitoring data set and obtaining a system adjustment parameter set through dynamic characteristic evaluation; and the coordination control construction module is used for constructing control logic according to the system adjustment parameter set and outputting a coordination control task scheme through a coordination control generation process. According to the method, the multi-source data fusion precision is improved, the dynamic characteristic matching capability of the system is enhanced, the source-network load-storage collaborative response efficiency is improved, the coping capability for power mutation is enhanced, and stable operation of the power grid frequency is effectively guaranteed.

The invention discloses a hydroelectric generating set power active control method, system and device based on frequency prediction and a medium, and belongs to the technical field of power control, and the method comprises the steps: collecting basic operation data of a hydroelectric generating set adjusting system in real time, and carrying out the preprocessing of the basic operation data; time sequence characteristics of the power grid frequency data are extracted, and a neural network is adopted to generate a power grid frequency prediction sequence in a future time window; the power grid frequency prediction sequence is converted into a dynamic power feed-forward compensation amount, feed-forward compensation amount optimization calculation is carried out, the feed-forward compensation amount is superposed to the output end of a feedback controller, and a composite power instruction input value hydroelectric generating set is formed; and updating a neural network input sequence in each control period by adopting a rolling time domain prediction strategy, dynamically correcting a future prediction result, and realizing controlled quantity updating based on actual frequency deviation. According to the method, the compensation weight is dynamically updated by using the online adaptive algorithm, the prediction error and the system performance target are considered, and the compensation amount distribution is optimized.

The invention provides a method for improving source network load storage integrated adjustment capability, and belongs to the technical field of power system automation and energy management. Multi-side data acquisition terminals are deployed to acquire power grid operation parameters in real time and perform adaptive extended Kalman filtering noise elimination; a source-load-storage dynamic coupling matrix is constructed based on historical data, adjustment weight coefficients of all links are calculated, and an adaptive prediction fusion model is used for energy storage state estimation and new energy output prediction. An energy storage power compensation instruction, an adjustable load starting instruction and a source load storage scheduling instruction are generated in a grading manner according to the magnitude of power grid frequency deviation by adopting a hierarchical cooperative regulation and control strategy, and an adjustment weight coefficient and a control instruction are iteratively optimized according to an adjustment effect, so that the technical problem of insufficient source network load storage multi-link cooperative adjustment capability is solved.

The invention discloses a method, device and equipment for determining parameters of a proportional resonance controller and a medium, the proportional resonance controller is applied to a current controller of a three-phase grid-connected inverter, the parameters of the proportional resonance controller comprise a proportionality coefficient, a first damping coefficient and a second damping coefficient, the first damping coefficient is greater than the second damping coefficient, and the second damping coefficient is greater than the first damping coefficient. The three-phase grid-connected inverter further comprises a filter. The proportional resonance controller is low in parameter coupling, can be independently designed, and is simple in engineering implementation; in the target open-loop transfer function, the proportionality coefficient determines the basic proportional gain, the damping coefficient controls the attenuation speed of the corresponding resonance factor, the difference between the first damping coefficient and the second damping coefficient can influence the gain bandwidth, and the larger the difference between the first damping coefficient and the second damping coefficient is, the more significant the attenuation speed difference between the second resonance factor and the first resonance factor is. The wider the high gain interval at the specific frequency of the power grid is, the higher gain is still kept even if the frequency of the power grid fluctuates, and the adaptability and robustness to the frequency deviation of the power grid are improved.

The invention provides an optimal primary frequency control method based on reinforcement learning. The method comprises the following steps: establishing a dynamic model of a power system; designing a frequency control strategy based on a deep reinforcement learning algorithm; the system frequency deviation is used as a reward signal, and a control strategy is trained through interaction with a power system; lyapunov function stability constraints are introduced into the reinforcement learning algorithm; a neural network is adopted to carry out parameterization design on the controller; discretizing the frequency dynamic equation, and proposing a multi-node collaborative optimization target; and deploying the trained control strategy to an actual power system, and adjusting control parameters in real time through an online optimization technology to adapt to the dynamic change of the system operation state. By means of the method, the frequency control accuracy and stability of the power system are improved, and the global optimal performance of frequency control of the whole power grid is achieved in actual deployment.

The invention discloses a VSG grid-connected system control method based on an improved three-parameter wave trap, and belongs to the technical field of power system control, and the method comprises the steps: firstly building a single-input single-output small signal model based on a VSG grid-connected system containing power coupling, and calculating an active open-loop transfer function; an improved active damping resonance suppression method is introduced, so that the transient stability of the system is improved; the expected system stability margin under the system oscillation frequency is obtained, and the parameter design of the three-parameter wave trap is completed based on the subsynchronous frequency oscillation characteristics; the three-parameter wave trap is remodeled, and active steady-state deviation caused by the virtual damping coefficient under power grid frequency disturbance is eliminated. According to the method, the stability of the system is improved, the system is ensured to have a relatively good stability margin, and active steady-state deviation caused by power grid frequency disturbance of the grid-connected system can be completely eliminated.

The invention provides a performance simulation test method and system for a pumped storage power station. The method comprises the following steps: acquiring characteristic data of the pumped storage unit, and performing characteristic line method analysis and dynamic impedance modeling to obtain a nonlinear hydraulic system mathematical model; constructing a synchronous generator model and an excitation system model, and constructing an AGC control model and a primary frequency modulation control model; generating a simulation system; generating a coordination control strategy by using a variable gain PID control algorithm based on a fuzzy control theory, and a dynamic weight distribution mechanism and a feed-forward compensation mechanism of an AGC instruction and a primary frequency modulation response; and executing a simulation test of a normal operation condition, a large disturbance condition and a condition switching process, and generating a performance test result. Through accurate modeling and coordinated control strategies, the problem of mutual interference between AGC and primary frequency modulation is solved, the stability and response speed of the pumped storage power station in power grid frequency regulation are improved, and the frequency modulation performance of a unit under different working conditions can be comprehensively evaluated.

The invention discloses a network-source collaborative primary frequency modulation optimization method and system based on reinforcement learning, and relates to the technical field of power dispatching and power generation, and the method comprises the steps: constructing a hierarchical reinforcement learning framework, and based on a high-level strategy network, taking system frequency deviation, frequency modulation demand prediction and a unit operation state as input, and outputting a dynamic frequency modulation weight vector; based on an underlying strategy network, taking the dynamic frequency modulation weight vector and the real-time frequency deviation as input, outputting an output adjustment instruction of each frequency modulation unit, and performing real-time verification on the output adjustment instruction; and if the verification is not passed, triggering a strategy re-planning mechanism to iteratively calculate a new instruction. The technical problems that an existing frequency modulation method cannot effectively cope with frequency fluctuation caused by large-scale renewable energy access, the response speed is low, and the frequency modulation precision is low are solved, efficient power grid frequency adjustment under renewable energy access is achieved through hierarchical reinforcement learning optimization, and the frequency modulation efficiency is improved. And the primary frequency modulation efficiency and precision are improved.

The invention discloses a power grid frequency coordinated regulation and control method and device based on coordination of three defense lines, and the method comprises the steps: carrying out the control cost analysis, constructing an interconnected power grid active frequency response model based on the control cost analysis, and building an active frequency response control strategy of coordination of the three defense lines on this basis, wherein the three defensive lines comprise prevention control, emergency control and correction control, and finally, a target function is constructed by taking the minimum total cost of the three stages of prevention control, emergency control and correction control as a target, so that the optimization space for coordinated operation of the three defensive lines for power system frequency stability is improved, and the control target of safety and economy coordination is further realized. The relationship between the control cost and the system frequency safety is coordinated, and the purpose of safe and economic cooperative control of the alternating-current and direct-current hybrid system for the frequency stability problem is achieved.

The invention discloses a frequency-locked loop of a self-adaptive delay signal elimination filter, which comprises a first filter, a second filter, a Park transformation module, a low-pass filter, an amplitude normalization module, an inverse Park transformation module, a frequency estimation module and a low-pass filter, and is characterized in that the first filter is used for eliminating higher harmonics, the second filter is used for eliminating low-order single harmonics, and the amplitude normalization module is used for normalizing the amplitude of the inverse Park transformation module. A signal passing through the filter is converted into a direct current component under a dq coordinate system through the Park conversion module, high-frequency clutter is filtered out through the low-pass filter, then the signal enters the amplitude normalization module, the signal amplitude is standardized to be 1, the signal is recovered into an alternating current signal through the reverse Park conversion module, the alternating current signal is input into the frequency estimation module, and the frequency estimation module estimates the frequency of the signal. And finally, a stable power grid frequency estimation value is obtained after processing by a low-pass filter. The invention aims to eliminate rounding errors and introduce a novel prefilter with relatively small time delay, so that the dynamic and steady-state performance of the first-order frequency-locked loop is improved.

The invention discloses a new energy power grid optimization scheduling method considering AGC frequency base value adjustment, which belongs to the technical field of new energy power grid optimization, realizes source and load collaborative optimization by dynamically adjusting a system frequency base value, and comprises the following steps: establishing a load and frequency dynamic response model; setting a safety boundary of frequency base value adjustment; constructing an optimization model taking a frequency base value as a core; and solving a dynamic optimization result. According to the method, firstly, the incidence relation between the load power and the frequency is quantitatively analyzed, meanwhile, the frequency safety constraint is considered, and a power grid frequency base value active adjustment model is established; and then, establishing a power balance constraint of interaction of thermal power, wind power and load, taking the sum of the thermal power cost and the wind curtailment penalty as a target, providing a power grid optimization scheduling method, reducing the wind curtailment rate, and improving the effectiveness and feasibility in the aspects of operation economy.

The invention relates to a new energy frequency support remote measurement and control device and method, and the device comprises an acquisition assembly which is used for collecting three-phase voltage and current analog quantity signals, and calculating the real-time active power and power grid frequency; the logic component is used for processing the analog quantity data acquired by the acquisition component and carrying out dynamic performance evaluation calculation of one-time frequency modulation and inertia response; the communication component is used for receiving a test instruction issued by a remote scheduling master station and remote signaling and telemetering data sent by the primary frequency modulation device, forwarding the test instruction and the remote signaling and telemetering data to the logic component, receiving a control instruction of the logic component and sending the control instruction to the frequency generator; the frequency generator is a programmable frequency signal source, and the output end of the frequency generator is connected to a frequency measurement loop of a primary frequency modulation device in the new energy station; the man-machine assembly is used for outputting alarm state data and working state information of each assembly; and the power supply assembly is used for providing a working power supply for each assembly. The method can be widely applied to the technical field of new energy power generation grid-connected control.

The application provides a wind power frequency modulation droop coefficient correction method and system considering the influence of delay characteristics, establishes a system frequency response model considering wind power frequency modulation delay characteristics and speed recovery control, obtains a system transfer function through the system frequency response model, and obtains system frequency key indexes through analytical solution; analyzes the influence mechanism of the delay characteristics on the power grid frequency dynamics, determines the relationship between each key index and the delay; on the basis of the relationship result, the droop control coefficient is corrected, so that the system frequency minimum point meets the preset requirement. The application can effectively improve the system frequency minimum point, so that the system frequency minimum point is consistent with that when the delay characteristics are not considered.

The application discloses a flywheel energy storage-based active quick-response frequency stabilization method and system for an isolated network, and relates to the field of power grid control.The method comprises the following steps: collecting a frequency signal of an isolated power grid in real time, fitting the frequency signal, and obtaining a smooth frequency value and a frequency change rate; when the absolute value of the frequency change rate exceeds a dynamic starting threshold, acquiring frequency deviation time series data of a preset time length to generate a disturbance event analysis window; extracting a frequency deviation signal in the disturbance event analysis window, performing time-frequency conversion on the frequency deviation signal, and generating a time-frequency spectrum diagram; based on the time-frequency spectrum diagram, decomposing the frequency deviation signal into a fundamental component and at least one overtone component, extracting a morphological feature parameter, and generating a disturbance image; setting a target state and a constraint condition of frequency recovery according to the disturbance image, determining a frequency recovery trajectory; and based on the frequency recovery trajectory, cyclically executing a control strategy until the power grid frequency is stabilized in a preset frequency range.

The invention discloses a multi-dimensional optimization method and system for improving the primary frequency modulation capability of a thermal power generating unit. The multi-dimensional optimization method comprises the steps that an annular data cache region is constructed by collecting power grid frequency signals, and the maximum frequency difference in a time window is dynamically extracted; in combination with cooperative judgment of an AGC instruction direction and a primary frequency modulation action direction, a load reference is intelligently selected, and a frequency difference function related to a maximum frequency difference is superposed to generate a real-time frequency modulation target value; constructing a primary frequency modulation performance comprehensive evaluation index based on the primary frequency modulation response speed and the electric quantity contribution degree; dynamically correcting a primary frequency modulation feedforward coefficient; establishing a valve opening-flow characteristic function model based on historical operation data, and dynamically generating an adaptive compensation amount according to a real-time working condition; and resetting parameters by adopting a gradient attenuation model. According to the method, full-chain optimization from frequency difference sensing to valve execution is realized, and the primary frequency modulation response quality of the thermal power generating unit and the qualification rate of power grid examination are remarkably improved.

This application relates to the field of artificial bee colony algorithm technology, providing a method and system for optimizing energy storage frequency regulation strategies based on the artificial bee colony algorithm, addressing the problems of slow suppression speed and low stability of power grid frequency fluctuations. The method includes: acquiring power grid frequency deviation data under load abrupt changes, extracting frequency change characteristics through sliding time window processing, and performing extreme value normalization to form a standard fluctuation sequence characterizing the dynamic characteristics of the frequency. After converting this sequence into an initial power compensation demand signal, phase compensation preprocessing is performed to obtain an optimized power compensation signal. A parameter optimization model is established with virtual inertial control parameters as optimization variables, and the optimal parameter combination is obtained by iteratively solving using the artificial bee colony algorithm, thereby constructing a frequency-power mapping function. Based on the mapping function, an adaptive virtual inertial control strategy is formed, and after processing the power compensation signal, an energy storage output command is generated. This application improves the suppression speed and stability of power grid frequency fluctuations.

The invention discloses an optimal frequency control method and device for improving an extreme weather power supply level. The method comprises the following steps: constructing an island power grid frequency response model containing thermal power generating unit frequency modulation and network construction type energy storage frequency modulation; constructing a frequency security constraint according to the island power grid frequency response model; the frequency security constraints comprise constraints of maximum frequency deviation, steady-state frequency deviation and maximum frequency change rate; determining an out-of-limit condition according to the frequency safety constraint during load disturbance; when the maximum frequency deviation or the steady-state frequency deviation exceeds the limit, obtaining an equivalent droop coefficient range of the network-forming energy storage according to the constraint of the steady-state frequency deviation, and starting droop control; when the maximum frequency change rate exceeds the limit, obtaining an equivalent inertia coefficient range of the network-forming energy storage according to the constraint of the maximum frequency change rate, and starting inertia control; and performing frequency control according to the equivalent droop coefficient range and the equivalent inertia coefficient range in combination with an island power grid frequency response model.

The invention provides an automatic test method and device for a low-cycle load shedding device. The method comprises the following steps: analyzing a configuration file of a to-be-tested device, extracting key parameter information, establishing station level communication with the to-be-tested device, reading a current constant value parameter on line, and automatically matching test configuration; generating a test strategy covering the whole scene according to a preset multi-dimensional test model; and finally, realizing automatic checking of the low-cycle load shedding logic by stoping an outlet signal of the device to be tested. According to the invention, through the modularized test architecture, the construction of a test scene covered by a full frequency band is realized, and the test efficiency is improved; a multi-round constant value closed-loop verification mechanism reduces manual intervention errors, ensures that a protection device cuts off corresponding loads according to a set low-cycle load shedding strategy when the power grid frequency is abnormal, and improves the stability of a power system.

The invention discloses a power grid frequency prediction method based on LSTM and time feature attention. The power grid frequency prediction method comprises the following steps: step 1, collecting multi-dimensional time sequence feature data of a power system before and after disturbance; 2, preprocessing the multi-dimensional time sequence feature data, and extracting high-dimensional time sequence features in the feature data obtained in the step 1 by using a time convolutional neural network T-CNN; 3, inputting the high-dimensional time sequence features extracted by the time convolutional neural network T-CNN into the time-feature attention module to obtain a focusing key feature and a weighted feature sequence of a key moment; 4, taking the weighted feature sequence obtained in the step 3 as input, mining a time sequence dependency relationship through a frequency prediction model of a long short-term memory (LSTM) network, and outputting a prediction curve of the inertia center frequency of the power system; and step 5, according to the predicted frequency curve, calculating a frequency lowest point deviation and a frequency change rate, and according to a preset frequency response danger level standard, outputting a frequency safety evaluation result of the power system.

The invention discloses a sending-end power grid frequency characteristic analysis method, system and device considering multiple dead zones and multiple control modes and a medium, and belongs to the technical field of power system planning operation. Constructing a droop control model of the new energy, a virtual inertia control model, rotor motion models under a plurality of synchronous units, a second-order speed regulation system model, a frequency regulation model of a load, a set value of a primary frequency modulation dead zone of the synchronous units, a direct current frequency limit control model, a dead zone set value and virtual inertia control of a direct current sending part; identifying parameters of the synchronous unit speed regulation system through a time domain simulation method; establishing a power grid frequency response model; and analyzing frequency characteristics and influence factors of the sending-end power grid by adopting a Routh criterion and a root locus method. The auxiliary sending end power grid planning operation provides decision support for a new energy control mode and a control mode of a direct current power transmission system.

The application relates to the technical field of power grid frequency modulation and discloses a power grid frequency dynamic analysis method containing a wind power diversification frequency modulation strategy and a dominant frequency modulation method, which is used for solving the problem of the lack of a dominant mode in the frequency response mode of the existing multiple wind power generators participating in system frequency modulation. The application establishes a time domain analysis model based on an SFR model, analyzes the section points caused by power changes and parameter changes, solves the boundary conditions of the section points, and further obtains an analytical expression; secondly, based on the analytical solution, a parameter replacement setting method between the frequency modulation modes is given respectively with the equal frequency minimum point as an index, and the frequency modulation energy contribution of each frequency modulation mode is compared, so that a theoretical basis is provided for determining the new energy dominant frequency modulation mode at the power grid level. It is concluded that, under a strong power grid environment, the inertia control and the variable coefficient droop control are both used as the dominant frequency modulation modes of the wind power generators; and under a weak power grid environment, the variable coefficient droop control is used as the dominant frequency modulation mode of the wind power generators in the weak power grid environment.

The invention relates to the technical field of power grid inertia evaluation, in particular to a power grid inertia comprehensive evaluation method under multi-type disturbance, which comprises the following steps: periodically acquiring power grid frequency and power data, identifying disturbance types and calculating an initial inertia evaluation value; based on the disturbance physical characteristics, calculating the confidence coefficient of each moment through a unified quantization formula; constructing a time sequence window and an LSTM-AE model, and fusing confidence weighting, time sequence smooth constraint and inertia fluctuation physical constraint to perform offline training; during online evaluation, a real-time timing window is constructed by adopting a sliding window mechanism, out-of-limit calibration is performed on the confidence coefficient after model reasoning, and final evaluation results are output in a classified manner. According to the method, full-coverage adaptation of multi-type disturbance is realized, the precision, consistency and physical credibility of an evaluation result are improved through a unified confidence system and multi-constraint modeling, the real-time operation state change of the power grid can be quickly responded, and powerful support is provided for stable frequency control of a high-proportion new energy power grid.

The application discloses a kind of digital video tampering detection method and system based on power grid frequency, the method of the application includes deleting visual content in digital video to obtain the noise component of power grid frequency to be embedded in digital video in optical form, average processing is carried out in column direction to obtain line signal;The line signal of each frame idle time period is filled to zero, and all frames are spliced to construct one-dimensional time sequence, and the power grid frequency signal estimate value is tracked by S transform;The obtained power grid frequency signal estimate value is matched with reference frequency, and whether digital video is tampered with is determined by frequency mutation.The application aims to solve the problem of incomplete and distorted power grid frequency signal caused by time distortion in existing video power grid frequency estimation, and the problem of high-precision extraction of power grid frequency signal restricted by complex background interference in video recording process, accurately extract the power grid frequency signal, realize high-precision detection and stable discrimination on video tampering behavior.

The application discloses a noise monitoring digital audio tampering detection method based on a power grid frequency signal, and steps include: obtaining a noise monitoring digital audio and extracting a power grid frequency signal; signal pretreatment is performed on the extracted power grid frequency signal; the pretreated power grid frequency signal is input into a trained deep learning model to obtain the two-classification probability of each data in the power grid frequency signal being normal or tampered; the model output is normalized to calculate the tampering probability of each data in the power grid frequency signal, compared with a preset threshold, and a tampering mark is set to obtain a prediction sequence; the prediction sequence is subjected to connected domain analysis to identify continuous tampering segments, and the sample index of the tampering segments is mapped back to the timestamp of the original noise monitoring digital audio to output a corresponding detection report. The application automatically learns a tampering feature mode through a deep neural network, realizes point-by-point labeling of a tampering position, and realizes high-precision tampering detection while keeping lightweight.

The invention relates to the technical field of large-scale power grid safety guarantee, in particular to a thermal power generating unit primary frequency modulation performance index real-time monitoring method and system, and the method comprises the steps: obtaining a power grid frequency signal and a unit main steam pressure signal, mapping the power grid frequency signal and the unit main steam pressure signal to the same physical time axis based on a unified time service reference, and generating a frequency-pressure time domain data sequence; when it is judged that the power grid frequency deviates from the frequency modulation dead zone, time domain integration is conducted on the pressure drop track of the main steam pressure signal within the deviation duration, and unit heat storage release energy is obtained; combining the actual active power of the unit, integrating the increment relative to the frequency modulation initial power reference to obtain the electric energy increment, completing energy conservation closed-loop verification through an energy conversion model, determining the effective frequency modulation contribution or outputting an abnormal state bit and performing linkage regulation and control, and realizing the real-time monitoring of the primary frequency modulation performance index. According to the invention, indexes can be accurately monitored and abnormity can be timely fed back.

The embodiment of the invention relates to the field of data processing, and provides a power grid frequency control method of a small hydroelectric generating set and a related device, and the method comprises the steps: obtaining the current frequency of the small hydroelectric generating set, and obtaining a reference network access frequency interval of a small hydroelectric generating set microgrid where the small hydroelectric generating set is located; if the current frequency is not in the reference network access frequency interval, acquiring current water inflow and environment water quantity information of the small hydropower generating set; determining a reference frequency adjustment parameter according to the frequency offset between the current frequency and the reference network access frequency interval and the operation state information of the micro-grid of the small hydroelectric generating set; frequency adjustment correction parameters are determined according to the current water inflow and the environment water quantity information; performing correction processing on the reference frequency adjustment parameter by adopting the frequency adjustment correction parameter to obtain a target frequency adjustment parameter; and performing frequency adjustment on the small hydroelectric generating set by using the target frequency adjustment parameter, thereby improving the accuracy of determining the frequency adjustment parameter.

The present application relates to the technical field of automatic control of hydropower station, disclose a kind of adaptive control method of hydropower station governor primary frequency modulation based on network source cooperation, including obtaining grid frequency rate of change, active power fluctuation and bottom physical data;According to physical data, calculate dynamic water flow inertia time, combine active power fluctuation and frequency rate of change to calculate grid equivalent inertia, reconstruct anti-reverse regulation threshold boundary;Calculate the real-time module length and phase angle of the trajectory vector of frequency difference and frequency rate of change;When satisfying the threshold boundary condition of frequency drop, generate feedforward differential negative compensation based on frequency rate of change;When determining that water flow establishes positive acceleration, generate dynamic clamping coefficient using vortex belt pressure fluctuation derivative, limit the recovery trajectory of main loop proportional gain;Finally, generate comprehensive guide vane opening degree instruction by fusing each control quantity and issue execution.The present application inhibits the water hammer reverse regulation effect in the initial stage of primary frequency modulation, reduces the pressure fluctuation risk in the later stage of regulation, and guarantees the stable operation of unit.