2897results about "Reactive power adjustment/elimination/compensation" patented technology

The invention discloses a power distribution management system of an intelligent charging pile, and belongs to the technical field of electric vehicle charging facilities and intelligent power grids. The load prediction module carries out space-time alignment fusion on historical data and real-time monitoring data to generate a power distribution demand prediction value, and the edge calculation controller executes a model prediction control algorithm based on multi-source data to generate a real-time control strategy containing relay time sequence parameters and a capacitance compensation scheme. And the dynamic power distribution adjustment module executes strategy parameters through the solid-state relay array and the parallel compensation capacitor bank. Self-adaptive adjustment of the power distribution network is achieved through a real-time monitoring-prediction-optimization closed-loop control mechanism, the harmonic content of the power grid is effectively reduced, the energy distribution efficiency of the charging pile group is improved, and the method is suitable for intelligent electric energy management of public charging stations and other scenes.

The invention relates to the technical field of energy storage control, in particular to a grid-connected type light storage and charging energy storage control system which comprises a power bearing capacity monitoring module, a light storage power adjusting module, a grid-connected power feedback module, a power grid stability margin calculation module and an energy storage power dynamic control module. According to the method, the voltage and current data of the grid-connected point are acquired in real time, the power transmission capacity is calculated in combination with the rated voltage range and the safety power upper limit, the power adaptation precision of the grid-connected point is improved, the photovoltaic power generation grid-connected proportion is dynamically optimized on the basis of comparison between load growth rate calculation and the power adjustment range, and photovoltaic power output curve change rate analysis is combined. Power output fine control, calculation of the load change rate and combination of power grid power factor data are achieved, a charging and discharging mode adjustment strategy is optimized, the frequency change rate and fluctuation degree are monitored, the stability margin of the power grid is enhanced, frequency deviation of the power grid caused by load fluctuation is avoided, and the new energy consumption rate and the operation reliability of the power grid are improved.

The invention belongs to the technical field of power distribution network voltage regulation and control, and discloses a distributed photovoltaic complex power prediction-cluster-cooperation-based power distribution network voltage regulation and control method, which integrates photovoltaic historical data, inputs an improved back propagation neural network model and outputs predicted photovoltaic active power output. Estimating the reactive capacity boundary of each node in real time based on the running state of the network-following inverter; dividing a distributed photovoltaic cluster by establishing a two-dimensional modularity function of a net load index and an equivalent electrical distance; a multi-device differential cooperative control strategy is provided for the voltage out-of-limit risk in the cluster; and constructing an optimization function with minimum network loss and voltage offset as a target, and optimizing and solving the function by using an improved multi-organization particle swarm optimization algorithm to obtain a multi-device adjustment sequence and a device action amount. According to the method, the renewable energy consumption capacity is improved and the network loss is reduced while the voltage stability of the power distribution network is ensured, and the comprehensive adjustment cost is optimized.

The invention discloses a power supply real-time compensation technology and application based on digital signal processing, and relates to the technical field of power electronics, and the power supply real-time compensation technology comprises a split-phase parallel processing architecture: a three-phase independently configured DSP core, each core integration comprises a real-time harmonic detection module, a dynamic sliding window FFT-RT algorithm is adopted, and the window length is adjustable in a set range; the bandwidth of the self-adaptive variable parameter filter can be dynamically adjusted in a set range; the FPGA coprocessor is specially used for PWM generation; an input stage of the harmonic prediction and decomposition module is synchronously acquired by a multi-source sensor; the processing layer comprises an improved VMD decomposition unit and a variational mode decomposition order; the edge prediction network is used for deploying a lightweight LSTM model, embedding a DSP core and predicting a harmonic spectrum in a future short period; and the multi-target dynamic optimization layer is used for setting a dynamic weight distributor and performing real-time adjustment according to the load sudden change rate. According to the invention, through split-phase parallel architecture, harmonic prediction and dynamic optimization, the response speed, multi-target cooperation and reliability improvement in the field of power supply real-time compensation are realized.

The invention provides a graphene super-capacitor capacity energy-saving control method based on an intelligent algorithm, and the method comprises the steps: obtaining the harmonic content data of a power grid, carrying out the spectrum analysis of the harmonic content through a Fourier transform algorithm, and obtaining the change trend of the harmonic content; acquiring historical capacitor bank impedance characteristic data and a corresponding harmonic content change trend, and calculating impedance matching degrees of the graphene super capacitor under different load conditions; according to the impedance matching degree of the graphene super capacitor, generating a capacitor bank switching sequence by adopting a dynamic programming algorithm, and determining a target switching sequence of the graphene super capacitor; switching of the graphene super capacitor according to the target switching sequence is executed through an edge calculation unit, the access state of the graphene super capacitor is adjusted in real time, and harmonic wave changes of a power grid are dynamically matched; the method comprises the following steps: acquiring transient current data of a system, and decomposing the transient current data by adopting a wavelet transform algorithm to obtain a frequency component of transient current;

The invention discloses a power distribution network intelligent scheduling method and system based on data enhancement and topology awareness dynamic partitioning. The method comprises the steps of performing data enhancement by using an improved Wasserstein generative adversarial network model based on photovoltaic historical feature data; constructing a dynamic partition evaluation index system, and realizing self-adaptive partition of the power distribution network topology based on an improved genetic algorithm; and constructing a mixed attention mechanism and fusing the mixed attention mechanism into a graph convolutional network for solving optimal scheduling of the power distribution network, realizing partition autonomous optimization through local attention, coordinating power interaction among regions through global attention, and outputting an optimal scheduling scheme meeting network constraints. According to the method, dynamic partitioning and optimal scheduling are combined, historical data limitation is broken through by improving the generative adversarial network, an intelligent model with topology perception capability is constructed, the problem of model adaptation in scale difference and meteorological diversity scenes is solved, and the consumption capability of a power distribution network on high-permeability distributed photovoltaic power is remarkably improved.

The invention provides a micro-grid group-containing AI active distribution network scheduling optimization method, a medium and a system, and belongs to the technical field of power grid scheduling. The method comprises the following steps: firstly, constructing a micro-grid group and main and distribution network interaction model, and determining boundary constraints; predicting key parameters of the micro-grid group by using deep reinforcement learning; constructing an active distribution network power balance equation and topology constraint conditions; solving by adopting mixed integer programming to obtain power flow distribution of the distribution network; constructing a power grid dispatching optimization objective function based on a quantum evolutionary algorithm; processing multi-source data by using an MGPN deep neural network to output an optimal scheduling strategy; monitoring a running state verification effect in real time through a state estimation technology; updating the strategy in real time by applying a rolling optimization mechanism; and establishing an evaluation system to dynamically optimize neural network model parameters, realizing efficient collaborative scheduling of the micro-grid group and the active power distribution network, and solving the technical problem of low distributed energy consumption rate in the collaborative scheduling optimization process of the micro-grid group and the active power distribution network.

The invention relates to the technical field of power electronics, in particular to a control method for a low-voltage intelligent reactive compensation system of a submerged arc furnace. Comprising the following steps: acquiring three-phase voltage, current, power factor, harmonic content and temperature parameters of the low-voltage side of the submerged arc furnace through a sensor network; the load fluctuation of the submerged arc furnace in the future 1-5 minutes is predicted based on a deep learning algorithm, and a compensation demand pre-judgment value is generated; according to a load prediction result and a real-time working condition, performing dynamic switching from three modes of fixed compensation, grouped switching and continuous adjustment; harmonic component dynamic tracking compensation is carried out by combining an active power filter (APF) and a static var generator (SVG); the system overvoltage, overcurrent and temperature parameters are monitored in real time, and a grading protection mechanism is triggered and fed back to the compensation strategy adjusting module. The invention provides a control method for a low-voltage intelligent reactive compensation system of a submerged arc furnace so as to improve the response speed of the system, prolong the service life of equipment and guarantee the electric energy quality of a power grid.

The invention relates to the technical field of power grid operation and maintenance, and discloses an AI-based reactive compensation optimization method and system, and the method comprises the following steps: integrating the four-dimensional characteristics of traffic flow, power grid load, user preference and equipment health degree, constructing a space-time correlation graph model, achieving the adaptive evolution of a topological structure through dynamic graph convolution and an attention mechanism, and obtaining a reactive compensation optimization model. The method comprises the following steps: fusing spatial-temporal features of a graph neural network with a BiGRU time sequence for modeling, injecting an equipment health degree attenuation factor, generating a charging demand prediction result with uncertainty quantification, expanding an intelligent agent state space, improving a reward function, and embedding equipment health degree constraints in a strategy network and near-end optimization. By sensing the degradation state of the equipment in real time and intelligently adjusting the reactive compensation strategy, the service life of the old equipment is prolonged while the voltage stability is guaranteed, the deviation accumulation effect is effectively inhibited through feedforward-feedback composite control and dynamic rescheduling, and accurate matching of a scheduling instruction and actual output is ensured.

The invention relates to the technical field of electric power reactive power compensation, in particular to a novel static dynamic reactive power compensation device and a control method thereof, and the device comprises a power grid state monitoring module, a reactive power demand calculation module, a compensation control execution module, a harmonic suppression module and a dynamic energy storage support module. According to the method, through real-time extraction and segmented analysis of the dynamic operation parameters of the power grid, accurate perception of the state of the power grid is realized, the transient characteristics of operation are represented, an accurate basis is provided for subsequent compensation, decomposition and classified accumulation of reactive power requirements are realized, inductive and capacitive power differences are accurately identified, the calculation accuracy and efficiency are improved, and load adaptation is optimized; in harmonic suppression, resolution and response speed are enhanced through signal separation and frequency correction, energy storage and compensation linkage is improved through dynamic energy storage optimization, dynamic response capability is enhanced, loss is reduced, voltage stability and power factors are improved, stable guarantee is provided for complex fluctuation scenes, and electric energy is saved.

The invention relates to the technical field of hybrid inverters, and discloses a hybrid inverter supporting reactive compensation and a control method thereof, and the hybrid inverter comprises a DC input unit, a three-phase full-bridge inversion unit, a grid-connected switching unit, a signal acquisition unit and a digital control unit. The direct current input unit comprises a photovoltaic interface, a battery interface and a direct current bus and is used for converging photovoltaic and energy storage electric energy; the three-phase full-bridge inversion unit is composed of a power device and an LCL filter and converts direct current into alternating current. The grid-connected switching unit comprises a static switch and an isolation transformer and is used for controlling power grid connection; the signal acquisition unit detects voltage and current signals; and the digital control unit judges a grid-connected mode or an off-grid mode according to the signal, calculates a reactive current reference value and generates a PWM (Pulse Width Modulation) control signal so as to realize reactive compensation control in the grid-connected mode and the off-grid mode. According to the invention, reactive power compensation capability is provided in both grid-connected and off-grid operation modes, and stable operation of the inverter in various working conditions is ensured.

The invention provides an intelligent management method and system for photovoltaic energy storage equipment, and the method comprises the steps: analyzing the power fluctuation trend through monitoring the output power and environment parameters of the photovoltaic energy storage equipment in real time, and pre-judging the power fluctuation characteristics; according to the operation state parameters of the supercapacitor and the vanadium redox flow battery and the power fluctuation pre-judgment result, the power distribution proportion and the cooperative working mode of the energy storage element are determined; based on industrial load demand characteristics, an energy storage element is controlled to be flexibly switched between an active adjustment mode and a reactive compensation mode; and voltage regulation and harmonic compensation are realized by monitoring electric energy quality indexes of parallel connection points. According to the invention, the rapid response capability of the photovoltaic energy storage system to the industrial load can be effectively improved, the power supply stability and the electric energy quality are remarkably improved, the system power fluctuation is reduced, the utilization efficiency of the energy storage equipment is improved, and reliable clean energy support is provided for industrial users.

The invention discloses a high-photovoltaic-permeability power distribution network voltage control method and system. The method comprises the following steps: constructing a high-photovoltaic-permeability power distribution network voltage control strategy; constructing a dynamic degradation cost function of the energy storage system; constructing a power distribution network node voltage approximate value calculation model; constructing a CVaR function for evaluating the voltage out-of-limit risk and the inverter capacity out-of-limit risk; constructing a centralized optimization model of high photovoltaic permeability power distribution network voltage control considering photovoltaic uncertainty, calculating a weighted sum of a node voltage upper limit exceeding risk and a power distribution network voltage control cost in a limited time domain, constructing a target function by taking minimization of the weighted sum as a target, and constructing a global optimal voltage control strategy; solving the centralized optimization model based on a distributed robust model predictive control algorithm, and outputting a voltage-reactive droop control curve; and adjusting reactive power output of the photovoltaic inverter based on the voltage-reactive droop control curve to realize voltage control. The voltage deviation can be reduced in real time, and the voltage control cost can be reduced.

The invention relates to the technical field of generator control, and particularly discloses an SVG static var generator control method and system, and the method comprises the steps: constructing a reactive-voltage sensitivity matrix containing a node sensitivity weight based on the real-time measurement data of a power grid, and obtaining a node sensitivity matrix; a dynamic sorting strategy of device priority grading is generated, a distributed compensation priority queue of all devices is obtained, and the devices comprise an SVG cluster and a photovoltaic inverter cluster; executing reactive power distribution under a capacity constraint condition based on the distributed compensation priority queue, and generating a target reactive power compensation amount with the capacity constraint condition; generating a hierarchical coordination control instruction of the SVG and the inverter according to the target reactive compensation amount, and obtaining a hierarchical control instruction set; executing the distributed cooperative compensation driven by the hierarchical control instruction set, and completing the dynamic regulation of the power grid voltage; the reactive power regulation capability of different devices in a power grid can be fully utilized, the accuracy and response speed of reactive power distribution are improved, and resource waste and excessive compensation are avoided.

The invention discloses a wind and light storage adjustment inertia and frequency coordination control method, and belongs to the technical field of new energy grid-connected power generation. The method is used for inertia support and frequency cooperative control of a new energy power station containing wind power generation, photovoltaic power generation, energy storage and a phase modifier, and comprises the steps of system minimum inertia demand evaluation, wind and light storage and adjustment inertia time constant evaluation, calculation of minimum inertia support time needed by the system and a wind and light storage and adjustment inertia distribution strategy. According to the wind and light storage and adjustment inertia and frequency coordination control method, the inertia supporting capacity of a new energy grid-connected system is effectively improved, wind, storage, photovoltaic and phase modifier inertia supporting tasks are effectively distributed, and the system frequency safety setting requirement is flexibly met. By calculating the minimum inertial supporting time, inertial supporting and exiting are carried out in time, power back-filling in the frequency recovery stage is avoided, and the frequency modulation burden of the system is relieved.

The present application relates to the field of power electronics. Disclosed are an operation control method, apparatus and device for multiple grid-forming converters, and a storage medium, which are used for improving the control efficiency. The method comprises: constructing a multi-grid-forming-converter simulation system having a steady-state operating point, wherein the multi-grid-forming-converter simulation system is controlled on the basis of a virtual synchronous generator; on the basis of a first simulated operating condition, determining a virtual synchronous generator control category for each grid-forming converter in the multi-grid-forming-converter simulation system; on the basis of a second simulated operating condition, determining accumulated acceleration energy and accumulated deceleration energy for each grid-forming converter in the multi-grid-forming-converter simulation system; and controlling multiple grid-forming converters on the basis of the accumulated acceleration energy, the accumulated deceleration energy and the virtual synchronous generator control category that correspond to each grid-forming converter.

The invention provides an electric energy quality compensation method and system based on power electronics, and relates to the technical field of power grid dispatching, and the method comprises the steps: collecting the voltage, current, harmonic content, reactive power, three-phase unbalance degree and other real-time multi-mode data of a power grid, and extracting key frequency spectrum features through wavelet transform denoising and windowing interpolation Fourier transform; and constructing a power quality feature vector. A self-adaptive fuzzy logic algorithm and power grid operation parameters are combined, a threshold value of a power quality index is dynamically adjusted, a multi-stage optimization strategy is divided based on the number of standard-exceeding indexes and importance analysis, and a dynamic compensation priority and a compensation strategy are generated. An improved particle swarm optimization algorithm is introduced, an inertia weight is dynamically adjusted, a constraint penalty function is introduced, output parameters of a power electronic compensation device are optimized, and effective compensation of power quality is realized by taking minimization of total active loss as a target.

The invention relates to the technical field of photovoltaic power generation, and discloses a zero-carbon factory intelligent operation and maintenance central control system and an electric energy quality optimization method and device. According to the method, a central control platform is arranged in a preset zero-carbon factory and comprises a photovoltaic monitoring module and an electric energy quality analysis module; constructing a factory energy digital twinborn model according to the characteristics of the photovoltaic module, the parameters of the load equipment and the characteristics of the power grid access point; acquiring real-time meteorological data and historical power generation data corresponding to the zero-carbon factory; inputting the power generation data, the electric energy quality parameters, the real-time meteorological data and the historical power generation data into a factory energy digital twinborn model to generate a future power generation power curve; matching an optimal treatment scheme in a preset fault mode self-learning database according to the power generation data of the zero-carbon factory and a future power generation power curve; and adjusting the three-phase unbalance degree of the power supply network of the zero-carbon factory according to the optimal treatment scheme, and completing the power quality optimization of the zero-carbon factory. And the problem of power quality control of grid connection of the distributed photovoltaic system is effectively solved.

A method for configuring reactive power capacity of a power grid to which offshore wind power is connected on a large scale includes the following steps. Static voltage stability index of substations in a regional power grid to which the offshore wind power is connected on the large scale and at multiple points and relative dynamic voltage drop area index for an N-2 fault are calculated. Thus, weak nodes in voltage stability are located, thereby implementing a prediction of a risk to the voltage stability of the regional power grid. These nodes are used as candidate reactive power compensation configuration nodes. An objective function is established as the minimum total cost of reactive power compensation devices at the candidate reactive power compensation configuration nodes. A multi-type reactive power optimization configuration model including static voltage stability constraints, voltage stability constraints under faulty state, and other constraints is solved.

The invention discloses an electric energy quality comprehensive treatment method and device based on multilevel collaborative optimization, and belongs to the technical field of electric energy quality treatment of an electric power system. According to the method, voltage and current data of a power grid are collected in real time and multi-parameter monitoring is performed; processing the data by using an adaptive wavelet transform and singular value decomposition combined algorithm, extracting disturbance characteristics and identifying the type and position of a disturbance source; a multi-objective optimization function including harmonic suppression, voltage stabilization, three-phase balance and power factor improvement is constructed, a Pareto optimal solution set is solved, and an optimal solution is selected; and according to an optimization result, generating and executing a cooperative control strategy of each type of electric energy quality treatment equipment. Cooperative treatment of various electric energy quality problems and cooperative control of various treatment devices are realized, the accuracy, self-adaptability and economical efficiency of electric energy quality treatment are improved, and the reliability and stability of an electric power system are enhanced.

The invention belongs to the technical field of virtual power plants, and particularly relates to a distribution network virtual power plant aggregation control method based on a disperse complex adaptive system, which comprises the following steps: constructing a distribution network disperse complex adaptive system architecture comprising a tail end resource layer, a local autonomy layer and a global collaboration layer; setting a dynamic aggregation index of the virtual power plant, and calculating the dynamic aggregation index of the virtual power plant based on the operation data of the distributed resources in the local autonomous layer; a virtual power plant dynamic aggregation algorithm based on a greedy strategy is adopted, and a virtual power plant is formed through aggregation; a virtual power plant voltage control strategy based on key node selection is constructed, in the local autonomy layer, each virtual power plant preferentially controls internal resources to realize autonomy, and in the global collaboration layer, key node voltage in each virtual power plant is adjusted to realize collaboration control among the virtual power plants. According to the method, the adjustment potential of the distributed resources can be fully mined, so that the distributed resources can better participate in power grid adjustment, and resource utilization and power grid benefit maximization are realized.

The invention discloses a virtual power plant capacity configuration and regulation operation optimization method, which comprises the following steps: constructing an aggregation model and physically consistent digital twinning, establishing a linearized power distribution network model containing voltage and power flow constraints, and depicting resource efficiency and time delay characteristics; forming a time-varying uncertainty set through quantile calibration and set drift constraint; establishing a capacity-operation joint double-layer optimization model, realizing capacity configuration under the constraint of the whole life cycle cost, and obtaining a rolling scheduling strategy through distributed robust optimization; before issuing, control shielding and formalized constraint are adopted to ensure the safety of the power grid; a multi-variety collaborative quotation is generated on the market side through opportunity constraint and risk measurement; hierarchical adaptive re-optimization is realized based on a trigger criterion, and a twin model is continuously calibrated by using a hardware-in-the-loop experiment; model updating is realized by adopting federated learning and differential privacy; executing degradation control under an abnormal condition, and performing smooth rollback after recovery; and finally, the capacity and operation parameters are evaluated and corrected through performance and service life linkage.

The invention discloses an electric energy quality optimal compensation control method and device based on a photovoltaic converter, and the method and device achieve the optimal compensation control of the electric energy quality of the photovoltaic converter by exploring the self-regulation potential of the photovoltaic converter and carrying out the autonomous adjustment of the electric energy quality while having the renewable energy consumption capability. According to the basic principle of the control method, reactive, negative sequence and harmonic current components are detected from a compensation object, and a compensation current reference value of the photovoltaic converter is generated by combining the output condition of the current photovoltaic converter and through instruction optimization of electric energy quality treatment current; therefore, the purpose of maximally utilizing the capacity of the photovoltaic converter to treat the electric energy quality is achieved.

The invention provides a power system voltage control method and device based on dynamic steady state collaborative correction, and the method comprises the steps: building an electromagnetic transient model for a preset voltage node in electromagnetic transient simulation software PSCAD, simplifying a power grid with the electrical distance to a target region exceeding a preset distance into a dynamic Thevenin equivalent model, initializing load flow calculation in the BPA to obtain a dynamic-steady state hybrid model; updating dynamic Thevenin equivalent parameters of the power system in real time according to the data of the phasor measurement unit of the power system, and synchronizing the dynamic Thevenin equivalent parameters to the BPA; based on the dynamic-steady state hybrid model, the transient overvoltage of the power system is suppressed within the time shorter than the first preset duration, and the steady state voltage of the power system is optimized within the time shorter than the second preset duration in combination with wide-area coordination control, so that the parameter bidirectional correction of the dynamic and steady state models is realized, and the head end voltage prediction error is reduced. And the voltage control robustness is improved.

The invention relates to the technical field of reactive compensation, in particular to a reactive compensation control system and method based on artificial intelligence autonomous learning, the reactive compensation control system comprises a data acquisition layer, an AI decision layer, a compensation execution layer and a feedback optimization layer, the data acquisition layer comprises a sensor module and a data acquisition module, the sensor module is used for collecting current and voltage data in the circuit. According to the method, firstly, a reactive power prediction model can be established through AI autonomous learning, and dynamic optimization of a compensation strategy is achieved; secondly, production load types are matched in real time, that is, products of the same kind are judged when the deviation is smaller than 0.05, the accuracy of a compensation strategy is ensured, in addition, instantaneous reactive power pre-judgment of the SVG and steady-state compensation cooperative control of the TBB / TSC can be achieved, and the response speed and accuracy of hybrid compensation are improved; and finally, through verification after compensation and a model updating mechanism, the adaptability and stability of long-term operation of the system are ensured.

The invention discloses a phase modifier unit state monitoring and load control method and system for reactive power compensation of a power grid, belongs to the technical field of automatic control of power systems, and mainly solves the problem that service life loss is aggravated or a control target is single due to the fact that the health state of equipment is not fully considered when an existing phase modifier unit responds to reactive power requirements of the power grid. The method comprises the following steps of: calculating reactive vacancy and extracting vibration frequency band energy characteristics by acquiring voltage and frequency of a power grid as well as vibration, temperature and exciting current signals of a unit in real time, and constructing a health state index HSI in combination with self-adaptive wavelet basis selection; taking minimum equipment life loss and optimal power grid voltage stability as multiple objectives, dynamically generating a load control instruction by adopting a particle swarm algorithm, realizing weight adaptive adjustment based on HSI, and introducing an online life loss model as a constraint condition; finally, reactive power output is adjusted through an excitation system, and cooperative control of power grid stability and equipment life extension is achieved.

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

The invention discloses an optimized reactive power control and fault ride-through method and system for a hybrid commutation converter, and the method comprises the steps: introducing reactive power control and considering the constant voltage control of negative turn-off angle limitation, achieving the control of an extremely low turn-off angle through the active turn-off of a full-control device in the converter under a steady-state working condition, and further meeting the demands of a high power factor; the investment of passive filter equipment is reduced; under the alternating current fault working condition, forced commutation and negative turn-off angle operation are achieved through active turn-off of a full-control device, the receiving end power grid voltage is effectively supported while commutation failure of a half-control thyristor in the hybrid commutation converter is avoided, and the active power transmission level during the fault period is improved. The full-control characteristic of the reverse blocking type integrated gate commutation thyristor in the hybrid commutation converter is fully utilized, reactive power control under the steady-state working condition and stable power transmission under the alternating-current fault are achieved by optimizing active turn-off control, and the method has wide applicability and good application prospects.

The invention relates to a medium-voltage expansion ice melting device and an ice melting expansion system. The medium-voltage expansion ice melting device comprises an ice melting transformer and a reactive compensation unit, the primary side of the ice-melting transformer is electrically connected with the power supply end of the medium-voltage power supply, and the secondary side of the ice-melting transformer and the input end of the reactive compensation unit are electrically connected with the ice-melting output end; wherein the ice melting transformer is a double-winding ice melting transformer of which the primary side is subjected to on-load voltage regulation and the secondary side is subjected to no-load gear regulation, and the medium-voltage power supply comprises a medium-voltage emergency power supply vehicle or a power grid; the deicing transformer is used for adjusting the alternating current of the medium-voltage power supply into the adjustable alternating current of the line section to be deiced, and the reactive compensation unit is used for regulating and controlling the reactive compensation current and the reactive compensation power. According to the technical scheme of the invention, the medium-voltage emergency generator car can be fully utilized to quickly expand the ice melting function of the medium-voltage emergency generator car, and meanwhile, the ice melting technical equipment of power grid power supply can be considered, and the economy of distribution network ice melting is improved.

The invention discloses a power grid voltage fluctuation suppression method and system based on dynamic voltage regulation, and the method comprises the steps: synchronously collecting a three-phase voltage signal through a sensor array, generating a multi-dimensional feature vector through Park transformation, and extracting a time-frequency joint feature through a mixed multi-scale decomposition algorithm, and inputting a model fusing fuzzy reasoning and a space-time diagram neural network, generating a cooperative adjustment strategy in combination with power grid topology and equipment constraints, and optimizing model parameters through a closed-loop correction mechanism driven by a dynamic forgetting factor. The system comprises a signal acquisition module, a characteristic decomposition module, an intelligent decision module and a closed loop correction module. According to the method, high-precision suppression of power grid voltage fluctuation is realized, the multi-node cooperative adjustment capability is improved, the method can be adaptive to power grid operation state changes, technical feasibility and economic rationality are considered, and an effective scheme is provided for modern power grid voltage stable control.