529 results about "Virtual inertia" patented technology

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

The invention discloses a fan inertia support evaluation and control method considering power grid inertia space-time distribution. Based on wide area measurement system data, a power grid inertia space-time distribution model is constructed, inertia contribution characteristics of different areas are analyzed, and the influence of extra-high voltage direct current transmission on inertia distribution is considered. And calculating the inertia response power of the fan, quantifying the support contribution of the virtual inertia of the fan based on the frequency change rate and the regional equivalent inertia, and establishing an inertia support efficiency evaluation index system. A dynamic feedback control strategy is put forward, a reinforcement learning or adaptive gain adjustment method is adopted in combination with the real-time distribution condition of the inertia of the power grid, the virtual inertia control parameters of the fan are optimized, and the response accuracy is improved. Based on a wide-area coordination optimization method, a fan inertia support scheduling strategy is optimized, and the system frequency stability is improved. The method can effectively improve the frequency supporting capability of the new energy power grid, improves the new energy consumption level, enhances the operation safety of the power grid, and is suitable for a high-proportion new energy grid-connected smart power grid.

The invention relates to the technical field of intelligent control of a power system, in particular to a photovoltaic power generation-energy storage-power grid intelligent scheduling method and system based on multi-mode energy management, and the method comprises the steps: 1, collecting and fusing multi-source operation data in real time; 2, establishing a multi-modal feature fusion model; 3, according to the photovoltaic fluctuation amplitude and the frequency deviation component, the energy storage adjusting capacity is formed; 4, constructing a differential control strategy for each mode, and achieving the dynamic matching of the virtual inertia and the power grid demand in the power grid supporting mode; and step 5, executing multi-time scale rolling optimization control, triggering strategy reconstruction according to mode switching, and maintaining power continuity among different modes through a transition process. According to different modal requirements, differentiated control strategies are adopted, so that the service life loss of the energy storage system can be reduced and the service cycle of the energy storage equipment can be prolonged while the energy storage system is ensured to quickly respond to the power grid requirement.

The invention discloses a network construction type energy storage capacity optimal matching method based on a frequency response model, and belongs to the technical field of gas turbine power plant financial supervision and artificial intelligence, and the method comprises the steps: S1, quantifying the power vacancy of a typical station under an extreme short-circuit fault, determining a virtual inertia constant and a virtual droop coefficient of network construction type energy storage, and carrying out the calculation of the virtual inertia constant and the virtual droop coefficient; setting an initial output coefficient and adjusting a step length; s2, constructing and integrating a system frequency response model based on the inertia and frequency modulation characteristics of the conventional unit, the wind turbine generator and the network construction type energy storage; s3, applying power disturbance to the system, gradually increasing an initial output coefficient and performing simulation, and recording the maximum frequency deviation, the maximum frequency change rate and the quasi-steady-state frequency deviation; and S4, when the maximum frequency deviation, the maximum frequency change rate and the quasi-steady-state frequency deviation are respectively smaller than or equal to set threshold values, the energy storage capacity proportion corresponding to the current initial output coefficient is the optimal proportion. According to the method, the problem of accurately measuring the optimal configuration proportion of the network construction type energy storage in the new energy station is solved.

The invention discloses a network construction type inverter for a photovoltaic energy storage system and a virtual synchronous machine control method. The network construction type inverter comprises an inverter power module and a central controller. The central controller is used for collecting power grid operation data in real time and generating a power grid impedance state vector through online impedance identification; and dynamically adjusting virtual inertia and damping parameters of the inverter power module according to the impedance state vector by using an adaptive mapping function so as to realize cooperative control and circulating current suppression between the modules. Performing stability boundary evaluation based on the adjusted parameters, then performing intelligent early warning of the photovoltaic energy storage system, and smoothly switching the operation mode of the inverter power module; according to the invention, through deep integration of a modular hardware architecture and intelligent adaptive control, the inverter has strong autonomous network construction capability, the problems of weak power grid adaptability and transient stability are effectively solved, and the dynamic response and reliability of a photovoltaic energy storage system are improved.

The invention relates to the technical field of photovoltaic power generation management systems, in particular to a photovoltaic power generation management, control and regulation system, which realizes multi-target collaborative optimization by fusing AGC active dynamic distribution, AVC reactive collaborative compensation, virtual inertia frequency response and reverse power rapid protection technologies. The system adopts a priority regulation and control strategy, a hybrid reactive power distribution algorithm and a multi-stage interlocking protection mechanism, the stability and the regulation precision of the power grid are remarkably improved, and the grid-connected requirement of a large-scale photovoltaic power station is met.

The invention discloses a wind and light storage coordination control method and system for a virtual synchronous machine, and the method comprises the steps: building a wind power plant-energy storage power station double-layer response mechanism at a first stage, and employing a multi-time scale coordination control strategy for a second-stage energy storage system; and in combination with the virtual synchronous control characteristics of the optical storage power station, establishing a multi-scene optimization model of a wind and light storage multi-source collaborative double-layer coupling mechanism, and realizing dynamic optimization of output of each unit among inertia support, frequency modulation capacity and energy storage health state. According to the method, wind power plant rotor kinetic energy release combined overspeed load shedding control, a fuzzy control means based on an energy storage charge state and a VSG control means based on a virtual inertia and damping coefficient self-adaption photovoltaic system are considered, then wind and light energy storage frequency modulation coordination is optimized, and the system inertia safety is effectively improved on various working conditions and different time scales.

The invention discloses a regional fan virtual inertia support scheduling method considering a wind power plant group synergistic effect, and aims to solve the problems of non-uniform inertia distribution, response conflict and economy in wind power plant group scheduling. By introducing a hybrid multi-level cooperative control architecture, the inertia vacancy of the power grid is calculated in real time, the inertia demand of each wind power plant is allocated, and the scheduling strategy of the wind power plant group is optimized. And a time-varying inertia demand curve is generated by adopting a hybrid algorithm, the future inertia demand is accurately predicted, and the fan rotating speed recovery cost, the equipment loss and the wind curtailment amount are minimized in combination with a multi-target optimization model. A model predictive control framework and a Nash equilibrium theory are introduced, the game problem between wind power plants is solved, collaborative scheduling of a wind power plant group is optimized, and timeliness and stability of a scheduling instruction are ensured by embedding a time delay compensation algorithm. According to the method, the inertia supporting efficiency of the power grid can be remarkably improved, the equipment loss and the wind curtailment amount are reduced, the robustness of the system is improved, and the method has high application value and prospect.

The invention discloses a method for preventing power reverse peak regulation by coupling primary frequency modulation and virtual inertia of a network-forming type fan, and the method effectively prevents power reverse peak regulation by dynamically decoupling the coupling effect of primary frequency modulation and virtual inertia and adjusting an amplitude limiting threshold value based on a real-time working condition. The adaptive amplitude limiting control strategy adjusts an amplitude limiting threshold value in real time according to parameters such as power grid frequency deviation, frequency change rate and fan operation state, optimizes fan power output, and avoids excessive power fluctuation. The virtual inertia compensation module simulates inertia response of a traditional generator set, provides extra inertia support and stabilizes frequency fluctuation of a power grid. The hierarchical control architecture realizes the balance of virtual inertia and frequency modulation control through the synergistic effect of an upper decision layer and a bottom execution layer, and avoids the phenomenon of reverse peak regulation of power. The control strategy not only improves the frequency modulation response speed and precision, but also enhances the adaptive capacity of the fan to the frequency fluctuation of the power grid, and has important application value and wide market prospect.

The invention provides a new energy station control parameter dynamic evaluation method, which comprises the following steps: according to a frequency dynamic response process after a system is disturbed, retaining a nonlinear link corresponding to an influence frequency in each unit of multivariate heterogeneous frequency modulation resources and corresponding parameters, and constructing a system multi-machine frequency response model; based on a system multi-machine frequency response model, determining the frequency change rate of the system at the disturbed moment; determining a virtual inertia control parameter of the new energy station based on the frequency change rate; based on the virtual inertia control parameters and a system multi-machine frequency response model, determining the maximum frequency deviation after the system is disturbed; and determining a primary frequency modulation control parameter of the new energy station based on the maximum frequency deviation and the virtual inertia control parameter. The evaluation result can provide engineering guidance for new energy station control parameter configuration, support controller optimization and active support strategy landing, improve frequency response under various working conditions, and improve the safety and stability level of the system.

The present disclosure discloses a method for controlling coordinated operation of multiple wind generators to avoid secondary frequency drop. The method includes the following steps: first, the Doubly Fed Induction Generator (DFIG) required for frequency support is dynamically selected based on a real-time disturbance power of a power grid and the rotating speed level of each DFIG; second, the virtual inertial control parameters are adaptively regulated according to the system frequency and the change in the rotating speed of the DFIG participating in frequency support, ensuring that the frequency support requirements are satisfied; and finally, the remaining DFIGs are controlled to release the rotor kinetic energy to support the rotating speed recovery of the selected DFIG, so as to reduce the extra energy absorbed from the power grid in the process.

The invention provides an electric energy storage power station virtual inertia optimization method considering inertia space-time distribution characteristics, and the method comprises the steps: carrying out the virtual inertia optimization of an electric energy storage power station under the scene of considering the non-uniform inertia distribution of an electric power system under the high-proportion new energy access; constructing a source measurement frequency response characteristic model considering load power mapping and a load node frequency response characteristic model considering source measurement frequency mapping; the system small interference stability based on the characteristic root method is used as a frequency safety constraint condition; taking the minimum inertia and frequency modulation energy of the energy storage power station as a target, considering the physical constraint, the frequency security constraint and the system stability constraint of the energy storage power station, and proposing a network tracking / constructing energy storage power station inertia coordination optimization strategy considering the frequency dynamic space-time distribution; wherein the objective function is that the sum of the integral quantity of the load node frequency deviation and the inertia kinetic energy of the following / constructing network energy storage power station is minimum. According to the method, aiming at the characteristic of frequency space distribution differentiation in a novel power system, it is ensured that all nodes can meet double security constraints of frequency deviation and frequency change rate.

A device, method, and non-transitory computer readable medium for controlling a power distribution system includes an islanded microgrid and a control system. The islanded microgrid includes battery energy storage systems (BESSs) that operate as a primary energy source, and a decentralized consensus-based virtual synchronous generator (VSG). The control system simultaneously, emulates inertial response of a synchronous generator by the virtual synchronous generator during grid disruptions to regulate and stabilizes frequency of the islanded microgrid, and maintain consensus among the plurality of battery energy storage systems (BESSs).

The invention discloses an electric energy and inertia combined clearing method and system considering new energy virtual inertia, and relates to the technical field of electric power system dispatching automation, and the method comprises the steps: obtaining data, forming a calculation scene, evaluating a system inertia demand and a droop factor demand based on the calculation scene, and obtaining a clearing result according to an evaluation result. The method comprises the following steps: constructing an all-time electric energy and inertia combined clearing model, solving electric energy bid-winning output and inertia bid-winning quantity of each time period, dynamically adjusting a demand value, establishing a single-time electric energy and inertia combined pricing model based on a solving result of the all-time combined clearing model, and solving node prices of electric energy and inertia of each time period. And outputting the unit output, the on-off state, the inertia standard, the line blocking condition and the node price of each time period. According to the invention, by acquiring multi-source data to form a calculation scene, evaluating inertia and droop factor requirements, constructing a full-time joint clearing model and establishing a single-time pricing model, collaborative optimization configuration and pricing of electric energy and inertia resources are realized.

The invention discloses a power grid frequency regulation and control method for a low-inertia power system, and the method comprises the steps: taking the minimum lowest point of the power grid frequency in fluctuation as a first regulation and control target based on frequency response models constructed by frequency modulation resources in the low-inertia power system, taking the lowest total frequency modulation cost of the frequency modulation resources as a second regulation and control target, taking the condition that the lowest point of the fluctuating power grid frequency meets the security constraint as a first constraint condition, and taking the condition that the generated power output by each frequency modulation resource meets the power limit as a second constraint condition; taking a third constraint condition that the total amount of the generated power output by each frequency modulation resource meets the total power requirement of the low-inertia power system, solving to eliminate the frequency deviation and the generated power output by each frequency modulation resource, and the frequency modulation resources comprise a synchronous generator set, a network construction type virtual inertia device and a network following type virtual inertia device. Collaborative optimization of various frequency modulation resources can be realized, and complex dynamic power system requirements can be met.

The invention relates to a multi-energy collaborative intelligent micro-grid control method, device and equipment and a medium. According to the method, a micro-grid frequency signal is collected in real time, the change rate of the micro-grid frequency signal is calculated, the inertia requirement of a system is accurately evaluated, the maximum virtual inertia capable of being provided by each unit is dynamically calculated in combination with the physical characteristics and operation constraints of each energy unit, and the system requirement and the unit capacity are dynamically matched through grey correlation analysis to generate an optimal distribution scheme. And then the special control models of all the units are driven to generate differentiated power regulation instructions, and finally power support is cooperatively executed through the power electronic converter, so that accurate matching and efficient cooperation of multi-energy virtual inertia capability are realized, the frequency stability of a high-proportion new energy power grid is remarkably enhanced, and the system performance is improved. The problems of resource allocation mismatch, poor control adaptability and the like in a traditional method are effectively avoided, and the dynamic safety of the system is guaranteed under the complex operation working condition.

The invention relates to a micro-grid frequency control system with hybrid energy storage. The system comprises an input power decomposition module for performing adaptive wavelet packet decomposition on wind power generation output power to obtain an optimal low-frequency component and an optimal high-frequency component; the initial power distribution module is used for decomposing the high-frequency component into a sub-high-frequency component and an ultrahigh-frequency component and respectively distributing the sub-high-frequency component and the ultrahigh-frequency component to a storage battery and a super capacitor to obtain a primary power distribution instruction; the correction power distribution module is used for correcting the primary power distribution instruction through a Logistic regression function to obtain an optimized output instruction; and the power grid primary frequency modulation module inputs the frequency deviation and the frequency change rate of the micro-grid into a hybrid energy storage model based on virtual inertia control and virtual droop control to obtain a total frequency modulation output demand and generate a total frequency modulation output instruction. According to the system, through the adaptive wavelet packet decomposition and hybrid energy storage technology and in combination with virtual inertia and virtual droop control, the fluctuation of the distributed power supply can be effectively stabilized, and the frequency stability of the micro-grid is improved.

The invention discloses a wind power inertia analysis method considering fan inertia support, and relates to the technical field of wind power system control, and the method comprises the following steps: collecting dynamic response data of a target generator set under a preset disturbance condition, and building a double-loop dynamic model based on the dynamic response data; performing closed-loop coupling on the double-loop dynamic model and a preset power grid model, and constructing a unit-power grid joint dynamic simulation model; based on the joint dynamic simulation model, acquiring a multi-dimensional inertia response characteristic matrix; based on the inertia response characteristic matrix, obtaining a contribution value of a virtual inertia control layer to power grid frequency support; and dynamically adjusting control parameters of a virtual inertia controller in the target generator set according to the quantized contribution value. According to the method, the response characteristics of the wind turbine generator under different disturbances are simulated through the double-loop dynamic model and unit-power grid joint simulation, the inertia response characteristics are analyzed based on real-time data, the capability of efficiently and accurately adjusting the virtual inertia control layer is achieved, and the stability of the power grid is enhanced.

The invention discloses a networking type energy storage semi-physical simulation test platform and method, and particularly relates to the field of simulation testing, and the platform comprises a digital twin collaborative modeling module, an impedance adaptive hardware coupling module, a networking control depth verification module, a multi-dimensional performance evaluation module, and an iterative optimization module. According to the method, a dynamic impedance network model and a virtual energy storage unit are integrated by constructing a power grid-energy storage digital twin; the dynamic impedance network is generated by adopting a frequency-dependent parameter transmission line equation and combining actual measurement impedance scanning data in a fitting manner; in the loop test, a full-band disturbance injection method is adopted to monitor impedance characteristics, and virtual inertia and physical droop control parameters are coordinated under a preset weak power grid working condition; the multi-dimensional performance evaluation system quantifies the system performance from three dimensions of dynamic response, stability margin and transient energy function, and when the phase margin deviation is greater than 15 degrees, triggers an iterative optimization mechanism, reconstructs a virtual inertia coefficient and repeatedly verifies the virtual inertia coefficient until a stability threshold is met.

The invention discloses a cooperative autonomous synchronous networking method for a multi-networking type energy storage converter without communication interconnection. The method comprises the following steps: S1, state perception and estimation based on local measurement: acquiring local electrical parameters in real time by using a sensor, and performing state estimation through an improved Kalman filtering algorithm and a local dynamic model; s2, a cooperation mechanism of the virtual synchronous machine and droop control: combining the virtual synchronous machine with the droop control mechanism, and realizing automatic power adjustment and cooperation work by setting a virtual inertia, a damping coefficient and a droop coefficient; s3, self-adaptive synchronization algorithm: based on the local state estimation and the output of the virtual synchronous machine, adjusting the phase and frequency of the output voltage, and dynamically adjusting synchronization parameters according to the state of the power grid; and S4, detecting a fault by monitoring local electrical parameters and a self state in real time, and automatically adjusting a control strategy and realizing system fault tolerance when the fault occurs.

The invention relates to the technical field of power systems, and discloses a flywheel energy storage assisted thermal power generating unit collaborative frequency modulation control method, which comprises the following steps: extracting dominant dynamic characteristics based on state matrix eigenvalue analysis through a joint dynamic model, and setting layered optimization time granularity according to the dominant dynamic characteristics; aiming at the difference between the thermal power slow dynamic characteristic and the flywheel fast dynamic characteristic, optimization objective functions of a thermal power layer and a flywheel layer are respectively designed, robust consistency constraint is introduced, and multi-time scale optimization instruction iteration generation is realized through an asynchronous coordination algorithm. The system monitors the frequency change rate of a power grid in real time, dynamically adjusts virtual inertia parameters of the flywheel and generates dynamic compensation power, and finally fuses the coordinated reference instruction and the dynamic compensation amount to form an execution instruction. According to the scheme, the frequency dynamic stability in the new energy power grid frequency modulation process can be remarkably improved, and meanwhile, the frequency modulation equipment loss and the sustainable operation capability of the energy storage system are balanced.

The invention belongs to the field of robots, and particularly discloses a mechanical arm man-machine cooperation self-adaptive admittance control method and device, a terminal and a medium, a man-machine interaction model omitting virtual stiffness is constructed, and admittance parameters in the man-machine interaction model comprise virtual inertia and virtual damping; designing a stability observer of the physical man-machine interaction system, monitoring an external force applied by an operator by the stability observer, and performing spectral analysis on a force signal to obtain a system instability index; constructing an admittance parameter adaptive controller through a system instability index, wherein the admittance parameter adaptive controller comprises a virtual inertia adaptive controller and a virtual damping adaptive controller; and the virtual inertia and the virtual damping are adjusted based on the admittance parameter self-adaptive controller, so that the physical man-machine interaction system returns to a stable state. The method realizes self-adaptive adjustment of controller parameters, adapts to a complex environment, and keeps stability of physical man-machine interaction.

The invention relates to the technical field of power system control, in particular to a direct-current capacitor self-synchronizing grid-connected control strategy method, system, equipment and medium, a direct-current capacitor energy dynamic model is established based on an actual energy balance relation, a direct-current voltage signal is acquired in real time, and a synchronous compensation signal is calculated based on the acquired direct-current voltage signal; performing phase compensation and gain adjustment on the synchronous compensation signal through a correction link based on the calculated synchronous compensation signal, adjusting the internal frequency of the inverter based on the synchronous compensation signal after phase compensation and gain adjustment, controlling the DC voltage through the internal frequency of the inverter, and establishing a self-synchronization control model; and based on the self-synchronization control model, establishing an adaptive control algorithm, generating a damping coefficient and a virtual inertia coefficient through the adaptive control algorithm, and dynamically adjusting control parameters according to the damping coefficient and the virtual inertia coefficient.

The invention provides a wind power plant equipment modeling and operation and maintenance management and control method and device based on digital twinning, and the method comprises the steps: restoring a fan entity based on a 1: 1 three-dimensional modeling technology, integrating multi-source data, including equipment sensor, video monitoring and GIS topographic data, and achieving the real-time mapping of a physical field and a virtual field through the construction of a high-precision digital twinning model. And the intelligent decision support module predicts wind resource distribution by using a dynamic boundary layer model, optimizes a grid-connected control strategy in combination with a virtual inertia simulation technology, and guarantees the transient stability of the power grid in a new energy fluctuation scene. And the full-life-cycle management platform supports full-process management from site selection planning, operation monitoring to fault diagnosis, and realizes multi-service data fusion display and interactive operation and maintenance strategy verification through a three-dimensional visual large screen.

The invention relates to a wind turbine generator active power control method and system based on the lowest inertia demand of a power system, and belongs to the technical field of wind turbine generator power control methods. The method comprises the following steps: (1) estimating the minimum inertia demand of the power system under the transient frequency security constraint of the system; (2) hierarchical adaptive virtual inertia control strategies including wind power plant virtual inertia demand calculation, a wind power plant virtual inertia hierarchical control strategy and a single machine virtual inertia control strategy; and (3) applying the strategy in the step (2) to power system control. Coordinated frequency modulation among the wind power station, the traditional thermal power plant and multiple machines in the wind power station is realized, and the problem of secondary frequency disturbance caused by group modulation and group control rolling optimization and frequency modulation quitting is solved.

The invention discloses a grid-connected inverter control method, system and device and a medium. The method comprises the steps of obtaining a power grid operation parameter, a system power instruction and a direct current bus voltage provided by a photovoltaic side hybrid energy storage system; a virtual inertia parameter is dynamically adjusted through an active-frequency control loop of the virtual synchronous machine in combination with an adaptive inertia algorithm, and a virtual rotor angular speed and an active power reference value are obtained through calculation according to a second-order motion equation of the synchronous generator; in combination with a reactive power instruction, a virtual internal potential amplitude is calculated according to a reactive-voltage droop relation through a reactive-voltage control loop of the virtual synchronous machine; and generating a three-phase voltage reference signal of the grid-connected inverter through synchronous rotation coordinate transformation. According to the invention, the dynamic performance, the operation efficiency and the grid-connected stability of the system under complex working conditions are obviously improved.

The invention discloses an action recognition method based on a virtual inertial measurement signal generation model, and relates to the technical field of action recognition, and the method comprises the steps: collecting a surface electromyogram signal and an inertial measurement signal, and carrying out the preprocessing of the collected signals; constructing and training a generator to convert the surface electromyogram signals into virtual inertial measurement signals; inputting the generated virtual inertial measurement signal and the original surface electromyogram signal into an action recognition model, and training to obtain a classification module; the performance of an action recognition model is evaluated by using a test data set, the accuracy rate, the recall rate and the F1 score index are calculated, the recognition effect of the model is measured, a classification model and a generator are optimized according to the recognition effect, and the advantages of two modal signals can be fully utilized by fusing surface electromyogram signals and virtual inertial measurement signals, so that the accuracy of the action recognition model is improved. And the motion information of the fingers, the wrist, the forearm and other parts is analyzed, so that the complex limb motion is identified more accurately, and the performance of the limb motion identification system in practical application is improved.

The invention discloses a hydrogen fuel cell ship electric propulsion inertia self-adaptive optimization control method, which relates to the technical field of hydrogen fuel cell ship electric propulsion control, and comprises the following steps of: acquiring ship operation state data and ship internal power network fluctuation data in real time, preprocessing, extracting features, calculating a virtual inertia coefficient and a virtual damping coefficient, and calculating an inertia coefficient and a damping coefficient; generating a virtual torque instruction; obtaining a total power demand of the ship by using a torque rotating speed calculation method, and dividing the total power demand into high-frequency, intermediate-frequency and low-frequency ship power distribution instructions; through a virtual synchronous machine model, the actual power of the ship is output, the voltage of a direct-current bus and the power of a hydrogen fuel cell are monitored in real time, a dynamic compensation power fluctuation method is utilized, the operation state of the ship is regulated and controlled, and a voltage stability index is obtained; the ship propulsion inertia is adaptively optimized through a power regulation algorithm, so that the ship can better adapt to different working conditions, and the stability and safety of the ship are enhanced.

The invention discloses a micro-grid parallel-separation operation switching method, which relates to the technical field of micro-grids and comprises the following steps: S1, collecting real-time state data of a micro-grid, calculating system instability and generating a stability state label; s2, generating an ultra-short-term prediction result, and calculating an energy buffer potential well parameter set and a virtual inertia coefficient in combination with a stability label; s3, triggering a mode switching instruction based on the stability state label, executing the energy buffer potential well parameter set and the virtual inertia coefficient to control the output of the energy storage system, and completing grid-connected and off-grid mode switching; s4, the harmonic content of the power grid is collected, and a protection constant value and reactive power output are dynamically adjusted according to the instability degree of the system; and S5, constructing a system support framework by constructing a hierarchical communication network, deploying a redundancy mechanism and adopting a staged implementation strategy. And through real-time stability evaluation, virtual inertia adjustment and ultra-short-term prediction optimization, the stability, the electric energy quality and the adaptive capacity in the grid-connected and off-grid switching process of the micro-grid are improved, and high reliability and flexibility of the system are ensured.

The invention relates to a new energy power plant black-start capability evaluation method, which comprises the steps of determining evaluation indexes for evaluating the black-start capability of a new energy power plant, including a continuous output capability index, a black-start voltage regulation capability index, a frequency modulation capability index, a frequency modulation time index and a virtual inertia index; obtaining the value of each evaluation index of the new energy power plant to be evaluated, and constructing a standardized evaluation matrix; and based on the standardized evaluation matrix, adopting an entropy weight fuzzy comprehensive evaluation method to evaluate the black-start capability of the to-be-evaluated new energy power plants, and realizing sorting of the black-start capabilities of the plurality of to-be-evaluated new energy power plants. According to the invention, on the basis of seasonal historical data of the new energy power plant, a black-start capability evaluation index system based on seasonal characteristics of the new energy power plant is constructed. And the lack of research on the black-start capability evaluation scheme of the new energy power plant in the prior art is made up. The method can meet the demand of off-line evaluation, and is suitable for industrial application.