1759results about "Flicker reduction in ac network" patented technology

According to the optical storage direct flexible system scheduling method based on multi-objective optimization and an adaptive scheduling strategy, monitoring devices are installed on a photovoltaic array, an energy storage unit and a load side, a data sensing network covering the whole link of'source-storage-load-network 'is constructed, and key data are collected in real time. A multi-objective optimization model with maximization of economical efficiency, reliability and clean energy consumption rate as objectives is established, and a hybrid optimization mechanism of a genetic algorithm and particle swarm optimization is adopted to generate a day-ahead scheduling reference scheme. And designing an adaptive scheduling algorithm and a dynamic parameter adjustment mechanism based on fuzzy logic, and combining a rolling optimization window to realize real-time optical storage coordination control and power real-time balance. According to the invention, the operation efficiency, stability and flexibility of the optical storage direct-flexible system are effectively improved, the capability of coping with emergencies is enhanced, and the optimization of the overall performance of the system is realized.

The invention relates to an optical storage cooperative control optimization method, electronic equipment and a medium. The method comprises the steps of collecting historical energy consumption and photovoltaic data of a park, constructing a photovoltaic electronic model based on the data, performing day-ahead prediction by adopting CNN-BiGRU, and generating a load power and photovoltaic generation power sequence; calculating the electricity consumption and the photovoltaic generating capacity of each time period; setting the capacity of an energy storage module, and calculating the energy storage charging and discharging capacity based on an SOC formula; according to the electricity consumption, the generating capacity and the energy storage capacity, determining a peak section discharge demand; photovoltaic fluctuation constraint is combined, and energy storage charging and discharging power is adjusted to stabilize fluctuation; optimizing load power utilization, photovoltaic power generation and energy storage power scheduling based on the power balance relation; and constructing a revenue maximization objective function, establishing a light storage collaborative optimization model in combination with constraints, and solving an optimal operation scheme of a prediction day. According to the method, photovoltaic power generation errors are reduced, power output is balanced, power grid requirements are met, the photovoltaic consumption rate is improved, healthy operation of the system is guaranteed, and operation benefits are improved.

The invention discloses a sequence impedance remodeling-based grid-forming converter system resonance suppression method and system, and the method comprises the steps: obtaining linearized grid-side voltage, grid-side current and converter-side current small signals based on the active and reactive power control strategy of a grid-forming converter and the voltage and current double-closed-loop control principle; establishing a sequence impedance model of the output impedance of the network construction type converter system based on the virtual synchronous generator; based on the sequence impedance model, combining a passivity theory to determine a system stability condition; in combination with the condition of system stability, an active damping feedback loop is introduced in a voltage control link of the grid-forming converter, equivalent output impedance of converter resonance control is remodeled, a non-passive area for outputting positive and negative sequence impedance is reduced, and grid-connected current harmonic resonance suppression of the grid-forming converter is realized. According to the method, a sequence impedance model is used for performing impedance remodeling of a grid-connected system for the first time, equivalent series virtual damping and a feedback control ring of an equivalent wave trap are specifically introduced into a converter system to perform sequence impedance waveform remodeling, and then the stability and robustness of the system are controlled.

The invention relates to the technical field of power system stability control, in particular to a broadband oscillation suppression method and system for an offshore wind power flexible direct current grid-connected system and a medium, and the method comprises the steps: sequentially injecting positive and negative sequence perturbation sine harmonic signals at a grid-connected point of a wind turbine generator, constructing a multi-input multi-output impedance matrix, reducing the order of the multi-input and multi-output impedance matrix into single-input and single-output equivalent positive sequence impedance; the stability margin of the offshore wind power flexible direct current grid-connected system is obtained based on equivalent positive sequence impedance quantification; when the stability margin is lower than a preset margin threshold value, reconstructing the fan grid-side converter into a matrix control structure by cascading a weighting coefficient matrix between the inner and outer ring control loops of the fan grid-side converter; and iteratively optimizing the matrix type control structure based on impedance sensitivity, and synchronously connecting a low-pass filter in series in a voltage and current feedback channel to carry out impedance remodeling so as to finish broadband oscillation risk suppression. According to the invention, broadband oscillation suppression of the offshore wind power flexible direct current grid-connected system is realized through impedance modeling and a matrix type control strategy.

The invention discloses a stability analysis method of a network tracking / constructing hybrid station based on an impedance model, and relates to a modeling and stability evaluation technology of a wind power plant grid-connected system. The method comprises the following steps: firstly, respectively establishing sequence impedance models of a following network type direct-driven fan and a construction network type direct-driven fan based on a harmonic linearization method, and verifying the accuracy of the established models in different frequency bands by combining an impedance sweep frequency method; secondly, on the basis of considering the influence of line impedance, deducing to form an impedance network structure of a hybrid wind power plant grid-connected system, and constructing a stability judgment condition suitable for system analysis; and finally, based on the established impedance stability criterion, identifying possible oscillation risks of the system in subsynchronous and supersynchronous frequency bands. The method is suitable for wind power system stability analysis in various hybrid access scenes, and provides theoretical basis and technical support for subsequent system parameter setting, control strategy optimization and oscillation suppression measures.

Disclosed in the present invention are a voltage control method and system for clusters of a power distribution network having a high proportion of photovoltaics. The method comprises: acquiring parameters of a power distribution network, and constructing a comprehensive electrical distance by means of adjustable active power and reactive power reserves of each node in the parameters of the power distribution network; forming an improved weight matrix by means of distributed photovoltaic reactive power and active power supporting capacities, a reactive power sensitivity matrix and an active power sensitivity matrix, and obtaining an optimal reactive power cluster and active power cluster division result by a community algorithm by means of a node coupling degree index in each cluster and the comprehensive electrical distance; and selecting, by means of a clustering algorithm on the basis of the division result, a key node in each cluster to act, to improve the cluster voltage regulation and control capability. Starting from the relationship between active power sensitivity and reactive power sensitivity, and considering the impact of different changes on other nodes, efficient utilization of the reactive power regulation capability of a grid-connected PV inverter can be achieved, the complexity of control strategy computation is greatly reduced, and the situation where there are too many adjustable distributed photovoltaics in clusters is avoided.

The invention relates to a shared energy storage virtual inertia compensation control method for wind power cluster collection, and belongs to the technical field of power system control. In order to solve the problem of insufficient cooperative control of a wind power system and an energy storage system in the prior art, a dynamic model is established by obtaining operation parameters, and the dynamic model comprises a wind turbine generator active power control model and an energy storage system charging and discharging model; designing a virtual inertia control strategy, and introducing virtual inertia control to simulate inertia response characteristics of the synchronous generator; shared energy storage coordination control is carried out, and a strategy is designed by using an MPC method according to an inertia demand and an SOC state; establishing a frequency dynamic response model and calculating inertia response time as a virtual inertia control start-stop condition; and optimizing controller parameters and designing locking logic by adopting an intelligent algorithm. The method can improve the system performance and efficiency, enhance the frequency stability, improve the energy utilization efficiency of the energy storage system, optimize the system performance, and improve the system stability and reliability.

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

The invention discloses a virtual power plant-based power distribution area collaborative governance system and method, and relates to the technical field of power system automation and intelligent power distribution networks, and the system comprises a dynamic autonomous partition governance unit which is used for dividing a power distribution area node into a plurality of subunits, correcting abnormal states in the subunits based on a power mutual aid strategy between adjacent subunits; the multi-time-scale collaborative optimization unit is used for constructing a second-level, minute-level and hour-level multi-time-scale collaborative mechanism and coordinating control targets of the power distribution area at different time scales; the edge-cloud collaborative decision-making unit is used for complementing the edge side real-time control strategy and the cloud global strategy; and the elastic resource pool unit is used for calculating the elastic contribution degree of the resources and formulating priorities, and calling the resources according to the priorities to meet load requirements. By integrating the virtual power plant technology, the edge calculation, the digital twinning and the multi-time scale optimization strategy, the intelligent and efficient treatment of the power distribution area is realized.

The invention relates to the technical field of hydrogen production, in particular to a micro-grid hydrogen production system based on dynamic optimization control and a multi-mode energy scheduling method. Comprising a renewable energy power generation unit which comprises at least two distributed power supplies with different power generation characteristics; the multi-stage hydrogen production device is configured to receive the electric energy output of the renewable energy power generation unit and perform proton exchange membrane water electrolysis hydrogen production; the hybrid energy storage system comprises a super capacitor bank and a lithium ion battery pack which are connected in parallel to the direct current bus through a bidirectional DC / DC converter; the dynamic optimization controller is internally provided with a multi-time-scale coordination algorithm and is used for acquiring meteorological prediction data, load demand data and an energy storage SOC state in real time; the multi-mode scheduling module comprises three working modes including an island operation mode, a grid-connected operation mode and an emergency standby mode; according to the scheme, hydrogen production economy, equipment durability and power supply reliability can be considered at the same time.

The invention provides a charging and discharging control strategy optimization method and system of V2G applied to a virtual power plant. The method comprises the steps of constructing a collaborative optimization strategy of comprehensive income data based on electricity price change prediction and peak regulation demand prediction; based on the user behavior mode and the user historical charging behavior data, constructing a collaborative optimization strategy matched with the user demand; constructing a collaborative optimization strategy of battery health degree management based on the health degree quantitative model of the battery; and based on a collaborative optimization strategy of comprehensive income data, user demand matching and battery health degree management, a multi-target dynamic optimization model is constructed, and charging and discharging control strategy optimization of the V2G application in the virtual power plant is realized. According to the method, full-process cooperation of strategy customization-dynamic invitation-user response is realized under the guidance of the virtual power plant, multi-mode charging and discharging control strategy combination is realized, load aggregation is carried out by effectively utilizing the distributed energy storage characteristic of the electric vehicle group, and the power grid regulation capability is maximized.

The invention discloses a low-voltage ride-through control method of a flywheel energy storage system, which is based on a low-voltage ride-through control strategy of model predictive current control (MPCC) so as to improve the low-voltage ride-through capability of the flywheel energy storage system when a power grid fails. A future current value is predicted through system modeling and a prediction algorithm, so that effective control is realized. The MPCC-based machine side-power grid side coordination control strategy can quickly respond to the voltage sag of the power grid, provide reactive power support, stabilize the voltage of the direct current bus, and ensure the safe and reliable operation of the flywheel energy storage system during the voltage sag period of the power grid. A traditional pulse width modulation (PWM) technology is abandoned, the optimal switching state is directly selected through a limited control set, and hardware implementation of a power grid side converter is simplified. A differential control strategy aiming at a power grid symmetric fault (three-phase voltage sudden drop) and an asymmetric fault (single-phase grounding) is provided, the method is suitable for a complex power grid fault scene, and the system universality is improved.

The invention provides a distributed energy storage output scheduling optimization method, medium and system, and belongs to the technical field of distributed energy storage output scheduling, and the method comprises the steps: firstly, collecting the electrical parameters, load parameters, renewable energy power generation parameters and energy storage equipment parameters of a transformer area, and building an energy storage grid-connected equation set which comprehensively considers the factors; and predicting a load, renewable energy output and energy storage demand curve in a period of time in the future according to historical data. Then, a multi-time-period energy storage scheduling optimization model is constructed, and objectives comprise operation cost minimization, renewable energy consumption maximization and power grid fluctuation minimization; and solving the multi-objective optimization problem by adopting an improved particle swarm optimization algorithm to obtain a plurality of candidate schemes. And finally, comprehensively evaluating the candidate schemes by using a multi-objective decision-making method, and selecting an optimal energy storage scheduling scheme. The technical problem that in the prior art, only parameters of an energy storage system are considered, and influences of power grid input electrical parameters and load parameters are ignored is solved.

The invention discloses a virtual power plant intelligent aggregation optimization control method for multi-type flexible resources, and the method comprises the steps: constructing a dynamic characteristic model of distributed resources, wherein the dynamic characteristic model comprises a photovoltaic output probability prediction model, an energy storage SOC-life coupling model, an electric vehicle behavior chain model, an adjustable load constraint model, and an industrial interruptible load model; an edge agent node calculates an adjustable potential interval of a resource cluster in real time and uploads the adjustable potential interval to a cloud end, a global optimization target is solved on the cloud end based on an improved sparrow search algorithm (ISSA), after a scheduling instruction is generated, model parameters are corrected in a rolling mode according to actual output deviation calculated in real time, and a scheduling result is obtained. And triggering a resource fault emergency strategy for prediction deviation and resource fault problems occurring in the operation process of the virtual power plant. Through an edge-cloud collaborative architecture and a multi-stage optimization strategy, accurate modeling, optimization aggregation and intelligent scheduling of distributed resources are realized.

The invention relates to the technical field of power system monitoring and control, and discloses a power grid oscillation monitoring system and method based on an intelligent sensor, and the system comprises an intelligent sensor module which is used for collecting the signal data of the operation of a power grid, is internally provided with a self-adaptive sampling mechanism, dynamically adjusts the sampling frequency to achieve the capturing of the signal change, and meanwhile, transmits the signal data to the intelligent sensor module; de-noising and preprocessing are carried out on the collected signal data, the processed signal data are transmitted to an edge calculation module, and high-quality input is provided for oscillation signal feature extraction; and the edge calculation module is used for receiving the preprocessed signal data from the intelligent sensor module. Through the intelligent sensor module, a self-adaptive sampling mechanism is combined with multi-mode signal acquisition, the rapid change characteristic of sampling frequency capture signals is dynamically adjusted, accurate capture of oscillation signals is ensured, the redundant calculation burden and energy consumption of the system can be reduced while the precision is ensured, and technical innovation is provided for real-time monitoring of a complex oscillation scene of a power grid.

The invention provides a virtual synchronous generator adaptive control method based on line impedance identification, and relates to the technical field of power system control. The line impedance identification-based adaptive control method for the virtual synchronous generator comprises the steps of dynamically adjusting the virtual inertia J, the damping coefficient D and the droop coefficient K of the virtual synchronous generator through a multivariable constraint optimization algorithm according to the impedance-frequency coupling model, and realizing real-time matching between the output power of the virtual synchronous generator and the impedance of a power grid. By collecting power grid signals in real time and extracting impedance characteristics, the dynamic change of power grid impedance can be timely and accurately mastered, and a reliable basis is provided for subsequent control strategy adjustment, so that real-time matching of the output power of the virtual synchronous generator and the power grid impedance is realized, power fluctuation is effectively reduced, and the stability of a power grid is improved; according to the invention, a self-adaptive modulation strategy and a multi-resonant controller are adopted, harmonic oscillation can be effectively suppressed, and the quality of output electric energy of the inverter is improved.

The invention provides an electricity-hydrogen coupling intelligent regulation and control method and system considering a wind-solar prediction error, and relates to the technical field of electric power, and the method comprises the steps: collecting wind-solar historical power generation data, and obtaining prediction error probability distribution based on adaptive combination kernel density estimation; the distribution serves as an uncertainty constraint, a dual neural network is adopted to execute deep reinforcement learning, an action value network dynamically adjusts a decision space, and a target network evaluates risks and restrains decisions based on conditional risks and state values; a distributed collaborative network is constructed, and hydrogen production power and hydrogen desorption power are controlled in real time based on a dynamic consistency theory and a synchronous potential function. The operation stability and economical efficiency of the electricity-hydrogen coupling system are improved, and the uncertainty of wind and light power generation is effectively dealt with.

The invention discloses a wind power grid-connected oscillation suppression method and system based on a self-adaptive damping controller, and relates to the technical field of oscillation suppression of a power system. According to the method, a self-adaptive damping controller structure is designed, and parameter setting is completed; then building a wind power grid-connected system simulation model; after voltage signals are collected, an FFT processing method is used for identifying oscillation frequency, and whether an unstable oscillation mode exists in the system or not is judged; if unstable oscillation exists, a self-adaptive damping controller is connected between the wind power plant side and the power grid side; the self-adaptive damping controller filters out signal components causing system oscillation and performs phase modulation; a signal component generated by the self-adaptive damping controller is injected into the power grid and counteracts with an original signal, and oscillation suppression is achieved. According to the self-adaptive damping controller designed by the invention, the oscillation frequency identification module and the phase shift parameter calculation module are introduced, so that measured data can be fully utilized, control link parameters are adjusted according to vibration frequency changes, and oscillation is effectively suppressed.

The present application relates to an energy-storage power-conversion series compensation system and a stability analysis method therefor, a damping controller, and an energy storage system, wherein a voltage signal on a capacitor arranged between an energy storage battery pack and a converter of the energy-storage power-conversion series compensation system can be collected, and whether an activation condition is met is determined based on the voltage signal; when the activation condition is met, an adaptive adjustment filter is activated to bring the damping controller into operation within the energy-storage power-conversion series compensation system. A voltage synchronization controller determines, on the basis of a sub-synchronous frequency band voltage signal output by the adaptive adjustment filter and an initial voltage signal, a required output phase angle signal corresponding to a pulse width modulation signal for controlling operation of the converter.

The invention discloses a harbor shore power system oscillation damping suppression method based on heuristic probability optimization. According to the method, sliding window preprocessing is carried out on an alternating current bus side current time domain oscillation signal, modal decomposition is carried out based on a Prony algorithm, and modal energy is calculated to judge an oscillation mode; the discriminated oscillation modes are aggregated and mapped into equivalent circuit elements, a corresponding three-order circuit state matrix is constructed, and the damping ratio of each mode is determined according to the characteristic value of the matrix; taking a damping ratio as an evaluation index, introducing an influence factor to construct a multi-objective optimization function, parameterizing the parallel adjustable impedance, and limiting an adjustable range; and searching the control parameters by adopting a heuristic probability optimization strategy to obtain final damping control parameters, and downloading the final damping control parameters to the parallel adjustable impedance device to realize online dynamic adjustment. According to the method, multi-modal identification, physical magnitude mapping and online adaptive optimization can be realized, and the suppression capability and the operation stability of the shore power system on sub / super synchronous oscillation are improved.

The invention relates to the field of voltage regulation and control, in particular to a real-time voltage regulation method for a new energy automobile. Initializing a power distribution network voltage measurement module, and collecting voltage data of each node of the power distribution network; setting a voltage deviation threshold value, and judging whether the voltage is in a normal range or not; collected voltage is compared with a set voltage deviation threshold value, a result obtained after preliminary voltage regulation of an on-load voltage regulation transformer is compared with the set voltage deviation threshold value, and a result obtained after cooperative voltage regulation of an electric vehicle charging pile is compared with the set voltage deviation threshold value. According to a comparison result, tap adjustment of an on-load voltage regulation transformer, cooperative voltage regulation of an electric vehicle charging pile and voltage regulation participated by a distributed photovoltaic system are carried out in sequence; and formulating an optimization strategy based on historical data and results of three times of voltage regulation. By means of cooperative voltage regulation, optimal control, intelligent management and the like, the voltage stability is effectively improved, and the adaptability and flexibility of the system are enhanced.

A passivity-based dual-mode integrated control method for a grid-connected inverter (GCI) is provided. In view of the insufficient robustness of the conventional single-mode GCI in a high-impedance and low-inertia weak grid, and the problem of wideband oscillation of the grid voltage and grid current or even system instability in nonlinear application scenarios such as grid structure / parameter variation, and plug-and-play of the inverter, the dual-mode integrated control method performs modeling on the GCI based on a port-controlled Hamiltonian (PCH) model, thereby obtaining integrated control with a weighted passivity-based feedback control law for the GCI based on a grid-following (GFL) mode and a grid-forming (GFM) mode. Based on the dual-mode integrated control method, the stable operation of the GCI in severe grid conditions with large fluctuation of the impedance, and desirable robustness of the GCI in nonlinear working scenarios can be ensured.

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 discloses a load control method based on a charging pile ad hoc network, and relates to the technical field of charging pile ad hoc network load control, and the method comprises the following steps: firstly, carrying out the real-time collection of various parameters in the operation process of a charging pile, guaranteeing the obtaining of high-quality original data, and providing a solid data basis for the subsequent analysis and model evaluation; according to the invention, through real-time data acquisition, intelligent feature extraction, deep learning evaluation and adaptive dynamic regulation and control, the problems of harmonic resonance, power distribution imbalance and power grid instability in the operation of the charging pile are solved. Charging pile parameters are collected in a high-precision mode, harmonic key features are extracted through a detection window mechanism, intelligent evaluation is conducted through a deep learning model, and the harmonic abnormal trend is predicted. When the resonance risk is detected, the power of the charging pile and the reactive compensation strategy are intelligently adjusted, the load distribution is optimized, the harmonic resonance risk is reduced, the power supply quality of the power grid is improved, and the intelligent charging network has higher stability, reliability and scheduling capability.

The invention relates to the field of power systems, in particular to a multi-energy complementary power supply network cooperative control method and system. The method comprises the following steps: collecting dynamic characteristic data of wind power, photovoltaic power, energy storage and load through a sensor group, and generating a multi-energy state characteristic matrix with a timestamp; and matching the feature matrix with a dynamic response feature library, and outputting a dynamic feature parameter set. Based on the set, a multi-objective optimization model is constructed, second-level frequency deviation suppression, minute-level tie line power stabilization and hour-level economic dispatching are covered, and a cooperative control parameter set is generated. And generating a thermal power generating unit compensation amount, an energy storage charging and discharging sequence and an interruptible load priority list. After execution, power grid deviation data are collected, a dynamic deviation value is calculated, and when a threshold value is exceeded, feature library parameters are corrected and loop optimization is carried out. According to the invention, the problem of insufficient cooperative control of the multi-energy system in the prior art is solved, and the stability and economy of the power grid are improved.

The invention provides a network following type and network constructing type energy storage combined planning method and device, and belongs to the field of power system planning. The method comprises the following steps: in a to-be-planned grid following type energy storage and grid construction type energy storage power system, carrying out joint modeling on a grid following type converter, a grid construction type converter and a fed alternating current power grid, so as to obtain a closed loop transfer function of the power system; based on the closed-loop transfer function, constructing a small-interference stability security domain oriented to energy storage joint planning; and converting the small-interference stability security domain into a small-interference stability security constraint, and further establishing a multi-type energy storage joint planning model to obtain a joint planning scheme of following network type energy storage and constructing network type energy storage. According to the method, the influence of the operation condition of the converter on small interference stability can be considered, power system optimization targets such as new energy consumption and the like are considered, and combined optimization configuration of network following type and network construction type energy storage is realized.

The invention provides a smart power grid dispatching optimization method based on adaptive evolution control, which comprises the following steps: performing power network graph modeling and standardization processing on a power network to generate a standardized graph structure; constructing a Markov decision framework of power grid dispatching based on the standardized graph structure; performing interactive training under a Markov decision framework to generate a preliminary scheduling strategy meeting power balance constraints; taking the preliminary scheduling strategy as an initial population, and generating a global optimization scheduling scheme through fitness function evaluation and multi-mode crossover mutation operation; and deploying a global optimization scheduling scheme to an actual power grid, and dynamically updating strategy network parameters based on node loads, power generation output and frequency data acquired in real time. According to the method, the power grid dispatching strategy can be dynamically adjusted in real time, consumption and dispatching of new energy are optimized, and the adaptive capacity of the power grid to different loads and power generation fluctuations is improved.

The invention relates to the technical field of power distribution network analysis, in particular to a distributed energy storage cooperative control system and device for an intelligent power distribution network, in the distributed energy storage cooperative control system and device for the intelligent power distribution network, inverter phase angles and bus voltage fluctuation characteristics are collected in real time through a dynamic virtual impedance parameter library, and a virtual impedance parameter library reflecting a disturbance propagation path is constructed; a lower-layer region dynamic division unit of the double-layer decision control module dynamically divides cooperative control sub-regions based on a virtual impedance deviation value and a preset clustering interval, and improves local disturbance suppression precision in combination with power grid topology constraints, and an upper-layer weight distribution unit generates a dynamic power distribution weight coefficient according to an inverse proportion relation of an equivalent impedance ratio; the overload risk caused by traditional fixed weight distribution and impedance characteristic mismatch is solved; when the energy storage unit is off-network, the power disturbance buffer factor calculation module adjusts the upper limit of output of the remaining units according to the original weight proportion and the equivalent impedance ratio in an equal-ratio scaling mode, and output adjustment and the impedance attenuation direction are maintained to be synchronous.

The invention discloses a power grid subsynchronous oscillation suppression method based on a neural network prediction model, and particularly relates to the technical field of power grid control. The method comprises the following steps: extracting a high-dimensional feature vector of power grid measurement data and performing frequency domain decomposition to obtain feature distribution information of different frequency components; utilizing a sparse coding algorithm to realize mode separation, and identifying a running state abnormal region set; constructing a dynamic coupling model to evaluate the interaction relationship between the oscillation mode and the operation state in the abnormal region and the time evolution characteristic; analyzing modal distribution characteristics through adaptive filtering, and calculating a local modal separation degree; based on oscillation evolution information and a modal structure evaluation result, power grid operation parameters and suppression device configuration are dynamically adjusted, and the recognition and response capability of a neural network to a potential dangerous subsynchronous oscillation mode is effectively improved.