2543 results about "Power regulation" patented technology

The invention discloses a regional energy internet hierarchical control method considering flexible loads, which comprises the following steps of: constructing a global layer, dividing a regional energy internet into a plurality of electrically strongly coupled sub-regions by adopting a dynamic partitioning algorithm, aggregating equivalent adjustable capacities of the flexible loads in the sub-regions, and performing rolling optimization in an hour-level time scale, an improved Benders decomposition algorithm is adopted to accelerate solving and generate a partition-level power regulation instruction; constructing a regional layer, designing a thermodynamic-economic hybrid constraint model according to flexible load physical characteristics and user behavior elasticity, introducing a user comfort recovery time constraint and elastic electricity price response function, and decomposing an adjustment instruction issued by the global layer to each flexible load cluster in a minute-level time scale by adopting a parallel ADMM optimization algorithm; and constructing a load layer, constructing a millisecond-level adjustable load priority switching mechanism based on FPGA hardware acceleration and finite-state machine logic, calculating a load adjustable power boundary in real time, and dynamically adjusting a response queue in combination with system frequency deviation.

The invention discloses a game reinforcement learning-based reactive power dispatching method for an electric vehicle to participate in a power distribution network, and the method comprises the steps: collecting node voltage, line current, electric vehicle charging and discharging states and topological information, and constructing graph attention embedding; generating an initial reactive power regulation action in the multi-agent game reinforcement learning framework, and shaping and updating a strategy gradient through double rewards; the improved particle swarm is initialized according to the updating strategy gradient, and a self-adaptive inertia coefficient is set; iteratively searching according to the node voltage sensitivity, the line reactive margin and the expected convergence step number to obtain an optimized particle swarm; the particle speed is mapped to a main strategy network through online cooperative training, the inertia coefficient is synchronously adjusted, a cooperative optimization strategy is output, a reactive power dispatching instruction is generated, and the algorithm is updated in a closed-loop mode according to real-time feedback. According to the invention, rapid and cooperative reactive dynamic scheduling of an electric vehicle group is realized, and the voltage stability and the electric energy quality are remarkably improved.

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 DC bus voltage fluctuation suppression method of a renewable energy hydrogen production system, and relates to the technical field of renewable energy electrolysis hydrogen production. The method comprises the following steps: collecting system operation parameters in real time; bus voltage disturbance power is estimated based on a disturbance observer, and frequency decomposition is carried out; fusing the ARIMA model and the LSTM model to predict the load power, and calculating a prediction deviation; dynamically setting upper and lower limits of a bus voltage control interval according to the predicted deviation and the operation state; a multi-objective optimization function is constructed, bus voltage disturbance power, prediction deviation and a control limit value are comprehensively considered, and power regulation instructions of battery energy storage, a fuel cell and an electrolytic cell are solved; and executing power regulation control to realize bus voltage stabilization. The method can improve the grading response capability of voltage disturbance, the prediction accuracy of load power change, the adaptability of the control boundary and the overall operation stability of the system, and is suitable for the electric energy quality control of the hydrogen production system in a multi-source fluctuation scene.

The invention discloses a micro-grid anti-countercurrent control method and system based on multi-objective optimization, and the method comprises the steps: generating a dynamic load prediction result according to the power grid side voltage, user side load power and energy storage system charge state data collected by an energy management system in real time; based on the dynamic load prediction result, obtaining a countercurrent risk quantitative index; generating a corresponding dynamic anti-reflux threshold curve according to the reflux risk quantitative index; the dynamic anti-reflux threshold curve is corrected through a real-time collaborative verification module, and an anti-disturbance optimization threshold is generated; and converting the anti-disturbance optimization threshold value into a PCS power regulation and control instruction, synchronously displaying a threshold value execution state and reverse feed early warning information on an energy management interface, and triggering adaptive power clamping protection when detecting that the voltage is out of limit or the power is reverse. According to the embodiment of the invention, the intelligent level of countercurrent prevention and control of the micro-grid can be improved, and safe and stable operation of the grid is guaranteed.

The invention relates to a self-adaptive pressure regulation vacuum pump closed-loop control system and method. The system comprises a model building module which is used for acquiring real-time data flow of a vacuum pump and building a nonlinear dynamic model to obtain a pressure-flow-power feature mapping relation; the predictive analysis module calculates a pressure-flow predictive value based on the relationship and compares the pressure-flow predictive value with the real-time power data for analysis. And generating a parameter adjustment instruction once the deviation value exceeds a preset threshold value. And the control scheme generation module corrects the control parameters according to the parameter adjustment instruction and generates an optimized power adjustment scheme. And if the data is abnormal, generating a state update value. And the control scheme updating module fuses the state updating value and the pressure-flow prediction value to obtain an optimized model parameter so as to adjust a weight coefficient of an adaptive control strategy and generate a control scheme. The system effectively improves the accuracy of vacuum pump pressure control, greatly enhances the ability of the system to deal with abnormal conditions and equipment performance changes, and ensures long-term stable operation of the vacuum pump.

The invention relates to the technical field of new energy power systems, and discloses an energy storage coordination system and control method based on meteorological prediction and multi-energy complementation, and the system comprises a power generation end module which carries out the dynamic adjustment according to a power adjustment instruction of a power generation end; the meteorological prediction and data acquisition module is used for acquiring meteorological data in a future time period in real time and sending the meteorological data to the intelligent control and scheduling platform; the energy storage end module sends data including lithium battery SOC and hydrogen storage tank pressure to the intelligent control and scheduling platform and performs charging and discharging according to an energy storage end charging and discharging priority strategy; and the intelligent control and scheduling platform receives the electricity price data of the weather prediction and data acquisition module, the energy storage end module and the power grid in real time, generates a power generation end power regulation instruction and an energy storage end charging and discharging priority strategy, and meanwhile, improves the income and maximizes the hydrogen energy use proportion through electricity price peak-valley arbitrage and green electricity transaction premium. The power grid stability and the energy utilization rate are greatly improved, the energy storage life is prolonged, and the investment payback period is shortened.

The invention relates to the technical field of power management, and provides a power distribution method based on BMS power control and related equipment thereof. The method comprises the following steps of: performing multi-mode synchronous acquisition and self-adaptive preprocessing on detected battery pack global state data to obtain a battery state tensor, and performing unsteady-state signal decomposition and time-space feature extraction on a received load power demand signal to obtain a power component matrix; performing multi-constraint dynamic planning on the battery state tensor and the power component matrix to obtain an initial power distribution strategy, performing dynamic correction in combination with a deep reinforcement learning model to obtain an adaptive distribution strategy, and performing multi-layer circuit equalization optimization on the adaptive distribution strategy to obtain a power regulation instruction set; and finally, performing multi-physics field coupling verification and fault-tolerant reconstruction on the power regulation instruction set to obtain an execution signal sequence. According to the invention, through data fusion, demand prediction, strategy optimization and deep learning, power distribution is accurately regulated and controlled according to the battery state and the load power demand.

The invention relates to a dynamic power regulation and control method and system for an electric vehicle charging pile, and the method comprises the following steps: S1, based on the real-time operation data of a charging pile cluster, employing a multi-source information fusion technology, collecting a power grid voltage fluctuation signal through a Hall sensor disposed at a charging pile end, and combining with the battery charge state data transmitted by a vehicle-mounted BMS, and eliminating noise interference by using an improved Kalman filtering algorithm, and realizing multi-dimensional data fusion by using a D-S evidence theory to generate a multi-source working condition feature set. The method has the advantages that the power grid voltage fluctuation signal and the battery charge state data are integrated through the multi-source information fusion technology, the improved Kalman filtering algorithm is adopted to eliminate noise interference, multi-dimensional data fusion is achieved in combination with the D-S evidence theory, the integrity and reliability of working condition feature extraction are remarkably improved, and the working condition feature extraction efficiency is improved. And the LSTM-ARIMA hybrid prediction model is utilized to synchronously process the nonlinear features and the periodic rules.

The invention is suitable for the technical field of power grid control, and provides a virtual power plant cooperative control scheduling method and system, and the method comprises the following steps: constructing a multi-dimensional resource library, each resource node in the multi-dimensional resource library corresponding to real-time adjustable power, power adjustment cost, response delay time, a carbon emission coefficient and a resource availability coefficient; establishing a global optimization model at the cloud, wherein the global optimization model fuses economy, environmental benefits and system stability; solving the global optimization model by adopting an improved non-dominated sorting genetic algorithm to obtain an optimal scheduling strategy, and issuing the optimal scheduling strategy to a control center and an edge terminal; and determining a real-time state of the resource node based on the edge terminal, and adjusting the optimal scheduling strategy according to the real-time state. According to the method, the response precision and the system stability of the virtual power plant are remarkably improved by constructing the global optimization model and dynamic cooperative control and adopting the improved non-dominated sorting genetic algorithm for solving.

The invention relates to the technical field of network load prediction, and particularly discloses a power supply energy saving system and method based on a load prediction intelligent dormancy strategy, and the method comprises the steps: collecting base station service load and power supply power data, and employing a neural network to accurately fit the nonlinear relation between the two for adjusting the power; constructing a multi-mode service load prediction model, generating a power supply power adjustment instruction in advance, and adjusting the power in time when the load prediction deviation exceeds a threshold value; frequent power fluctuation is avoided through a dynamic threshold mechanism based on hysteresis comparison; a sleep and wake-up strategy and a buffer mechanism are established to ensure that the state of the power supply is switched only when the load changes continuously, so that the switching accuracy and stability are improved; self-adaptive sleep duration and progressive wake-up adjustment are introduced, so that smooth transition and intelligent energy conservation of power supply operation are realized; the method can improve the energy efficiency of the power supply and reduce the energy consumption.

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 relates to the technical field of communication base station energy-saving control, and discloses an energy-saving optimization control method and system for a communication base station. The method comprises the following steps: collecting and preprocessing traffic energy consumption data of a communication base station to obtain standardized characteristics; inputting the features into a double-flow space-time convolutional network, and carrying out parallel calculation through time and space branches to predict a load; performing hierarchical quantitative pruning on the network, and distributing bit width according to the influence degree to obtain a compression structure; and processing the real-time data based on the compression network, and generating an energy-saving control strategy for radio frequency resource configuration and power regulation. Based on accurate load prediction and differentiated resource scheduling strategies, the optimal balance between energy saving and service quality is realized, the problems of passive response and coarse-grained control in a traditional method are effectively solved, and the energy saving effect is maximized on the premise of ensuring communication quality.

The invention relates to the technical field of power plant data processing, in particular to a virtual power plant integrated management system, which comprises a data acquisition module for acquiring voltage fluctuation characteristics and power climbing rate parameters of energy equipment in real time; the equipment fingerprint database construction module generates an equipment fingerprint code comprising a dynamic response time-lag coefficient and an adjustment margin quantized value; the dynamic clustering module is used for dividing simulation sub-models of regional topology constraints based on the geographic position of the equipment and a power regulation threshold value; the multi-time scale prediction module is used for generating source load prediction data by fusing meteorological parameters through a space-time diagram convolutional network; the digital twin simulation module outputs an energy storage charging and discharging threshold value and a demand response priority strategy; and the cross-domain collaboration module adopts a double-chain block chain architecture to realize security verification and data integrity binding of federated learning feature parameters. According to the invention, through equipment characteristic digital modeling, regional co-simulation and multi-energy flow coupling regulation and control, the resource aggregation precision and response real-time performance in a new energy strong fluctuation scene are improved.

The invention provides a self-adaptive low-voltage ride-through control method for a network-building type converter considering virtual impedance, and the method comprises the steps: defining a reactive power adjustment coefficient and an active power adjustment coefficient, obtaining a power parameter, building an active-reactive power self-adaptive low-voltage ride-through control strategy formula when the influence of the virtual impedance is not considered, and carrying out the self-adaptive low-voltage ride-through control of the network-building type converter. The relation between the virtual impedance and the output reactive power is analyzed through the reactive power of the network-forming converter control system after the virtual impedance link is switched in, so that the enlightenment that the virtual impedance needs to be introduced to carry out linear correction on the reactive power regulation coefficient is obtained; a corrected value function can be obtained after linear correction is carried out on reactive adjustment parameters through virtual impedance, the corrected value function is finally substituted into a strategy formula, an active-reactive self-adaptive low-voltage ride-through control strategy formula considering the influence of the virtual impedance is obtained, the transient power angle stability of a grid-forming type converter system can be enhanced, and the stability of the grid-forming type converter system is improved. And meanwhile, the problem of over-current of the converter under large disturbance is solved.

The invention provides a voltage control method based on dynamic cluster division of a high-permeability photovoltaic power distribution network, and the method comprises the steps: carrying out the Newton-Raphson method load flow calculation of a power distribution network power system based on the topological structure data of the power distribution network, line parameters, the access position of a photovoltaic inverter and energy storage equipment, and equipment parameter information, and constructing a comprehensive modular function; based on the comprehensive modularization function, according to the load capacity of each moment, taking the average load capacity as a standard, utilizing an improved artificial hummingbird algorithm to dynamically divide time segments of the clusters and selecting dominant nodes of each cluster; based on the dominant node, taking the minimum node voltage deviation and the minimum system loss as objective functions, and constructing a second-order cone programming model when a preset constraint condition is satisfied; and solving the second-order cone programming model by using a solver CPLEX to obtain the reactive power regulation quantity of the distributed photovoltaic inverter and the active power regulation quantity of the energy storage equipment, thereby improving the power supply reliability and the electric energy quality of the photovoltaic power distribution network.

The invention discloses a grid-connected inverter control method based on second-order linear active disturbance rejection, and particularly relates to the field of grid-connected inverter control. Voltage and frequency error signals between the output side of the inverter and the power grid are obtained, a pre-synchronization control model is constructed, and voltage amplitude and frequency synchronization is achieved; a second-order linear active-disturbance-rejection controller is introduced in the frequency synchronization control process, an extended state observer is adopted to estimate the output frequency, the frequency change rate and a disturbance term, and a state error feedback control law is combined to generate a frequency regulation control quantity, so that accurate frequency control is realized; after grid connection, a dual-channel LADRC power regulation controller is constructed, and decoupling tracking control is carried out on active power and reactive power; meanwhile, on the basis of fast Fourier transform processing as a stable grid-connected state criterion, the method has the advantages of being high in control precision, high in anti-interference capability, good in current waveform quality, high in adaptability and the like, and is suitable for various grid-connected application scenes.

The invention relates to the technical field of energy storage cooperative control, and discloses an improved energy storage converter grid following control algorithm, which comprises the following steps of: 1, extracting positive sequence and negative sequence components of three-phase voltage of a power grid through a double-sequence decoupling phase-locked loop, and acquiring a positive sequence axis component signal by adopting forward rotation coordinate transformation; and 2, when frequency locking is carried out based on the positive sequence axis component signal, extracting a voltage amplitude corresponding to the positive sequence axis component signal, and inputting the voltage amplitude to a feed-forward passivation module. An active power regulation technical scheme based on a frequency deviation threshold value is adopted, the technical effect of simulating the primary frequency modulation characteristic of a network-forming converter is achieved by detecting the power grid frequency deviation in real time and generating an active power compensation signal, and the defect that traditional network-following control lacks frequency active supporting capacity is overcome. And the converter can spontaneously increase the active power to stabilize the power grid frequency when the power grid frequency drops.

The invention discloses a micro-grid automatic power regulation and control method, and relates to the technical field of micro-grid power regulation and control and resource management. In order to solve the defects of poor new energy consumption capability, high distributed resource management difficulty, poor power grid regulation and control flexibility, poor resource cooperation effect and poor power and load prediction accuracy of an existing micro-grid power regulation and control method, grid-connected and off-grid flexible switching of a power grid A and a power grid B is realized by constructing an integrated construction framework. And multi-source data are integrated, and new energy power generation and load demands are intelligently predicted through data center management. And during grid connection, the distribution and dispatching integrated system determines power dispatching, and the micro-grid management system B makes a dispatching plan. And during off-grid, power is supplied according to the user priority. And in the grid-connected and off-grid mode, power distribution, load regulation and control and resource optimization configuration are carried out, and distributed resources are regulated and controlled in real time through the coordination controller, so that stable operation of the power grid is ensured. The method is mainly used for flexibly regulating and controlling the micro-grid.

The invention discloses a photovoltaic energy storage cooperative control method and system, and the method comprises the steps: obtaining the real-time state data and environment information of distributed photovoltaic and energy storage equipment, and constructing a system network topology; constructing a hierarchical prediction model including photovoltaic power generation prediction, load demand prediction and electricity price prediction based on the system state data set; constructing a multi-objective function containing an economic benefit objective and a system stability objective based on a prediction result, and performing objective decomposition through recursive iteration; according to a local optimization target, generating a photovoltaic power adjustment strategy and an energy storage charging and discharging strategy by reducing a distributed maximum matching gap and reducing an order to break a distributed maximum independent set obstacle algorithm; and based on the distributed control strategy set, the system operation state is monitored in real time, and control parameters are dynamically adjusted by adopting an event triggering mechanism. According to the method, the problems of calculation complexity and communication dependence of traditional centralized control in a large-scale photovoltaic energy storage system are solved.

The invention discloses a source network load storage coordination control system and method for high-capacity multi-network energy storage combined transportation. The system comprises a master station layer which is responsible for receiving a superior scheduling instruction, issuing an emergency control instruction, and performing economic optimization scheduling and rapid coordination control on photovoltaic and energy storage resources; the substation layer is responsible for accessing photovoltaic, load and energy storage resource information and decomposing and issuing superior instructions to realize a local frequency voltage control function; and the terminal layer is used for receiving a generator tripping command or a power regulation command issued by the emergency state monitoring device. The system can effectively improve the network-related performance of a new energy station, enhance the stability and reliability of a power grid, improve the absorption capability of new energy, and optimize the economical efficiency of the system. Through combined operation of the network construction type energy storage equipment and the new energy, effective support for the power grid is realized, the problem of coordination control of parallel operation of multiple voltage sources is solved, oscillation and circulation are avoided, and the overall performance and the power supply guarantee capability of the system are improved.

The invention relates to the technical field of photovoltaic power adjustment, and discloses a photovoltaic power automatic adjustment method and system. The method comprises the steps of collecting real-time parameters of an inverter through distributed communication, performing multi-dimensional evaluation sorting based on equipment efficiency, load rate and operation time, executing adaptive power distribution fusing edge calculation and cloud optimization, generating standardized instruction time-sharing issuing, and storing control logic by using a block chain. And an encrypted link is established to realize bidirectional data interaction between the power station and the dispatching system to form a closed-loop control system. According to the invention, high-efficiency, precise and reliable dynamic power adjustment of the inverter level is realized.

The invention relates to the technical field of data center power supply, and discloses a transient voltage treatment control method based on a data center flywheel energy storage system. The method comprises the following steps: firstly, acquiring three-phase voltage, current and frequency signals of a power supply bus of a data center and rotating speed and energy storage power signals of a flywheel energy storage system, and calculating a transient voltage characteristic matrix; then, a dynamic threshold value is quantified, a multi-layer cascade evaluation network structure is constructed to carry out voltage transient evaluation, and energy storage control evaluation parameters are generated; then establishing a transient constraint function, and calculating a dynamic stability boundary of the flywheel energy storage system; and finally, iteratively optimizing energy storage control parameters according to the result to obtain a flywheel energy storage power regulation sequence. Through closed-loop adjustment, energy storage power is dynamically adjusted according to load requirements and voltage deviation, transient fluctuation of power supply bus voltage is effectively treated, and power supply stability and reliability of the data center are improved.

The invention discloses an intelligent silicon controlled rectifier voltage conversion circuit, which relates to the technical field of voltage conversion, and comprises a photovoltaic module, a micro-control module, a power regulation module, a first voltage threshold, a second voltage threshold, a second voltage threshold, a third voltage threshold, a fourth voltage threshold, a fifth voltage threshold and a sixth voltage threshold, when the converted electric energy is larger than a first voltage threshold value, the access control module transmits the electric energy output by power regulation, superposes the electric energy output by double-path electric energy coupling and stores the superposed electric energy by the energy storage module, and when the converted electric energy is smaller than the first voltage threshold value and larger than a second voltage threshold value, the access control module outputs the superposed electric energy. And when the voltage is smaller than a second voltage threshold value, electric energy coupling is stopped, the power regulation module is controlled to carry out power regulation on the electric energy released by the energy storage module, and power is supplied to the output module. According to the intelligent silicon controlled voltage conversion circuit, the utilization rate of photovoltaic electric energy can be improved, and the voltage gain and the power supply efficiency are improved.

An active-reactive voltage cooperative control method for multiple reactive compensation devices considering energy storage comprises the steps that 1, simulation analysis is conducted on time sequence voltage fluctuation characteristics of a high-permeability photovoltaic grid-connected system, and dynamic influences of photovoltaic output fluctuation in different time periods on system node voltage are quantitatively evaluated; 2, solving a non-dominated solution set of the model by adopting a multi-target particle swarm optimization algorithm, realizing collaborative optimization and trade-off analysis of multi-dimensional performance indexes, and establishing a reactive power regulation model and an energy storage active power support model; and organically coupling the reactive power regulation model and the energy storage active power support model. By means of the method, high photovoltaic area voltage treatment can be effectively carried out in real time, and the method has high engineering application value and wide popularization prospects.

The invention provides a dynamic power adaptive charging control system and method based on a W algorithm, and relates to the technical field of electric two-wheeled vehicle charging control. The system comprises a battery state sensing module, a charging power standard calculation module, a regulation and control model construction module, a model dynamic optimization module and a deviation early warning and regulation and control module. The battery state sensing module generates battery charging basic data; the charging power standard calculation module calculates a charging operation power standard value; the regulation and control model construction module generates an initial power regulation and control curve; the model dynamic optimization module calculates a self-adaptive charging power regulation and control curve; and the deviation early warning and regulation module realizes self-adaptive regulation of the charging power of the electric two-wheeled vehicle. According to the method, the power grid adaptability correction model is constructed and the regional differentiation parameters are introduced, so that power grid fluctuation is flexibly coped, wide-voltage stable operation is guaranteed, and the adaptability, the safety and the intelligent level of the electric two-wheeled vehicle charging system are comprehensively enhanced.

The invention provides a virtual power plant control method based on a multi-objective optimization algorithm. The virtual power plant control method comprises the steps of collecting real-time operation data of distributed energy equipment through a virtual power plant control center; establishing a dynamic prediction model, and predicting output fluctuation characteristics and load change characteristics of each distributed energy device in a future time period; constructing a multi-time scale collaborative optimization model; solving the multi-time-scale collaborative optimization model by adopting an improved chaotic particle swarm algorithm, and generating an equipment control parameter set; dynamically adjusting a weight coefficient matrix of the optimization model according to the deviation degree of the real-time operation data and the prediction data; the robustness of the control parameters is verified through Monte Carlo simulation, and the next step is executed when the verification passing rate is larger than or equal to 95%; and issuing a control instruction set including a time sequence control instruction and a power adjustment threshold to each distributed energy device. According to the invention, efficient scheduling and precise control of the virtual power plant can be realized, and the power tracking precision, economical efficiency and stability of distributed energy can be improved.

The invention relates to the field of transformer control, and discloses a solid-state distribution transformer control system and method for improving access of a distributed power supply, which are used for solving the problem that original controller parameters are not representative due to access change of the distributed power supply when the solid-state distribution transformer is controlled. The method comprises the following steps: constructing a solid-state distribution transformer with a multi-port power regulation capability, setting initial control parameters, obtaining equivalent impedance influenced data, evaluating according to the equivalent impedance influenced data to obtain an equivalent impedance change index, judging whether the equivalent impedance is changed according to the equivalent impedance change index, and if the equivalent impedance is judged to be changed, judging whether the equivalent impedance is changed or not. If yes, dynamically correcting the initial control parameter according to the equivalent impedance change index to obtain an actual control parameter, and adjusting the output of the solid-state transformer according to the actual control parameter, thereby effectively improving the accuracy of transformer control and the reliability of energy supply.

The invention relates to the technical field of energy storage equipment regulation and control, in particular to an energy storage frequency control method and device based on charge estimation and dynamic scheduling, and the method comprises the following steps: initializing an initial energy storage estimated value of an energy storage system; monitoring the power grid frequency in real time and identifying the frequency deviation event type; calculating a current-round global active power regulation target; constructing an energy storage unit response prediction model, and predicting the charge state change process of the energy storage unit under the current power; updating the residual energy storage estimated value of each energy storage system; judging whether a fault critical state of over-limit or under-limit state of charge exists or not; executing the control strategy to enable the charge state of the energy storage system to return to the safety interval; and circulating monitoring is carried out to realize energy storage frequency control. Through combination of charge state estimation, modeling prediction energy storage unit response and an automatic control strategy, self-adaptive and closed-loop frequency regulation control of the heterogeneous energy storage system in a complex power environment is realized.

The invention discloses a response control method for a charging station participating in a low-voltage treatment scene, and the method comprises the following steps: S1, collecting the voltage data of a charging pile, calculating a deviation, and judging a low-voltage grade; s2, when the deviation is in a light interval, outputting reactive power support voltage in proportion; s3, when the deviation exceeds a heavy threshold value, reducing active power and starting V2G feedback; s4, constructing a graph structure model, and extracting inter-node power coupling and user behavior factors; s5, inputting the model into an improved prediction controller, predicting a future voltage state, and optimizing and outputting a current period power control value; s6, power adjustment is executed, and feedback power is slowly output in the V2G stage; and S7, comparing the control deviation with the behavior factor change, updating the node control priority, and feeding back for rolling optimization of the next period. According to the invention, while the charging regulation and control precision is improved, the user experience and the voltage stability are effectively considered, and the method is suitable for various low-voltage treatment scenes.