3229 results about "Power regulation" patented technology

The invention discloses a charging pile power regulation and control method and system, and particularly relates to the technical field of charging pile management, data is collected from a multi-dimensional data source and summarized to form a preliminary information set, and a standard information set is obtained through format standardization processing; feature data of the charging pile are extracted based on the standard information set, and charging task analysis and resource occupation analysis are carried out respectively; inputting the analysis result into a pre-trained machine learning model to generate a charging priority coefficient; constructing a priority matrix, and dividing the charging piles into high priorities and low priorities according to the charging priority coefficients; and finally, dynamically adjusting a power distribution strategy according to the priority type, optimizing low-priority task power distribution while meeting high-priority task requirements, and improving the operation efficiency and the resource utilization rate of the charging station. According to the method, the real-time operation state and the charging task characteristics of the charging piles are combined, the power distribution strategy is dynamically adjusted, the priority division and power distribution proportion of the charging piles are adjusted in real time, and the self-adaptive capacity of operation of the charging station is improved.

The invention discloses an energy storage control and adjustment method and system for distributed photovoltaic consumption, and relates to the technical field of renewable energy sources, and the method comprises the steps: obtaining illumination intensity, temperature data and historical load data, and predicting the future photovoltaic power generation amount and load demand changes; analyzing the voltage fluctuation of the power grid and the charging demand of the energy storage system based on the prediction results of the photovoltaic generating capacity and the load demand; according to the health state of the energy storage battery, optimizing the charging and discharging depth, and outputting an energy storage adjustment plan; dynamically optimizing the charging and discharging plan and reactive power regulation of the energy storage system by using a multi-objective optimization algorithm, and generating an optimal reactive power regulation instruction; according to the reactive power adjustment instruction, performing transformer area self-adaptive cooperative control to obtain a cooperative control result; according to the invention, through an area adaptive cooperative control mechanism, the reactive power regulation capability of the adjacent areas can be automatically coordinated when the regulation capability of the local energy storage system is insufficient, and the stability of the power grid and the utilization efficiency of the energy storage system are further enhanced.

The invention relates to a V2G-based alternating current charging power adjusting method and device. The method comprises the following steps: carrying out multi-scale data acquisition and preprocessing on a V2G alternating current charging system to obtain a standardized system state data set; constructing a system dynamic model comprising a power grid voltage characteristic and a charging power characteristic; carrying out decomposition to obtain a power output mapping relation calculation, and obtaining a power modulation control parameter; establishing a fast and slow time scale coordination control framework, and designing a power regulation agent and a voltage regulation agent to obtain a coordination control strategy; checking a charging power limit value constraint, a voltage limit value constraint and a power factor constraint to obtain a constraint violation judgment result, and executing constraint projection calculation to obtain a target control instruction; and controlling a power conversion circuit of the charging pile to execute power regulation operation. According to the invention, a hierarchical control structure is adopted, the control complexity of the system is reduced, and the robustness and the adaptive ability of the control strategy are improved.

The invention discloses a charging pile intelligent control management platform, relates to the technical field of charging pile intelligent control, and can identify the peak and valley periods of the power grid load in advance by collecting and analyzing the power grid load data and the operation state of a charging pile in real time and combining a regression model of a load prediction and demand analysis module. The power output of each charging pile is dynamically adjusted through the charging pile scheduling and power adjusting module, the power grid resource distribution is optimized, the overload phenomenon is avoided, and the stability of power grid operation is improved. By monitoring and feeding back the charging behavior data of the user, the platform can reasonably plan the working state of the charging pile. Therefore, too fast loss of some charging piles due to continuous overload is avoided, resource waste of idle charging piles is reduced, the utilization efficiency of equipment is improved on the whole, and the service life of the charging piles is prolonged. By using the load prediction and demand analysis module, the platform can pre-judge the charging demand peak of the user and optimize the scheduling strategy in advance, thereby shortening the waiting time of the user.

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 an electromagnetic heating and heat preservation system for a wind power blade girder plate pultrusion die, and relates to the technical field of thermal field regulation and control, comprising the following steps: activating an electromagnetic coil array to generate an alternating magnetic field, synchronously starting a heat preservation layer device, and triggering a gradient heating mode when the temperature of the die reaches a preset threshold value; a mold temperature field is monitored in real time, the power of an electromagnetic coil and parameters of a heat preservation layer are dynamically adjusted, a target temperature gradient is established, an electromagnetic heating device and a mechanical traction device are linked in the pultrusion process, and heat dissipation control is triggered according to the material flowing state; and after heat dissipation control is completed, the main power source is cut off, the mode is switched to the waste heat recovery mode, mold waste heat is guided into the energy storage device, and the cooling rate is controlled. According to the method, accurate mode switching of electromagnetic heating from uniform temperature rise to gradient heating is achieved through cooperation of magnetic field activation and a gradient triggering mechanism, and the temperature gradient establishment speed and the morphological stability are effectively improved in cooperation with power regulation and control partition differentiation power instruction and thermal insulation layer parameter dynamic matching.

The invention belongs to the technical field of distributed resource control of a power distribution network, and particularly relates to a distributed resource cooperative control method based on layering and partitioning autonomy of the power distribution network. The method comprises the following steps: S100, proposing an active power grid layering and zoning control strategy oriented to feeder autonomy; s200, establishing a power distribution network area power regulation and control information model of hierarchical and distributed control; and S300, realizing distributed resource cooperative control based on layering and partitioning autonomy of the power distribution network. According to the distributed resource cooperative control method provided by the invention, the distributed photovoltaic, user load and distributed energy storage coordinated control in the transformer area is realized by combining a feeder-autonomous-oriented active power distribution network layered and partitioned control strategy and utilizing the edge computing capability of the transformer area intelligent fusion terminal, the distributed photovoltaic absorption capability is improved, and the distributed resource utilization rate is improved. Energy supply and demand imbalance caused by distributed photovoltaic randomness is stabilized, and the economic operation level of a power distribution area is improved.

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.

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 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 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 discloses an industrial park demand response potential assessment method and system. The method comprises the following steps: collecting basic data of each user in an industrial park; load characteristic key indexes are determined, and a typical daily load curve of each user is extracted through clustering analysis; the production characteristics of the user equipment are analyzed, and an interactive response model capable of translating, transferable and reducing loads is established; a multi-target optimization model with the minimum park load peak-valley difference and the minimum operation cost as targets is constructed; and carrying out statistics on the variable quantity of each user load in an optimization result, and evaluating the peak clipping and valley filling potential of the industrial park in different time periods. The method effectively improves the accuracy of industrial park demand response potential evaluation, can accurately describe the power regulation characteristics and time translation characteristics of the flexible load resources of industrial users in different periods of time within the day, fits the actual power consumption behaviors of the users, can accurately obtain the upper and lower adjustable potentials of the industrial park, and improves the evaluation accuracy of the industrial park demand response potential. And a powerful basis is provided for formulating a reasonable load interaction strategy for the industrial park.

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 discloses a power distribution network voltage control method based on distributed photovoltaic active-reactive cooperation, and the method comprises the steps: analyzing the influence of reactive / active injection on voltage stability through building a sensitivity matrix, deducing a critical control gain constraint condition, and guaranteeing the static stability of the voltage of a power distribution network; a photovoltaic inverter active / reactive cooperative control general model suitable for different scenes is constructed based on an intra-day scheduling and real-time control two-stage framework, and control curve parameters of each node photovoltaic inverter are optimized by taking minimization of network loss cost, active reduction cost, inverter voltage regulation cost and voltage deviation as targets in the intra-day scheduling stage; in the real-time control stage, active power reduction and reactive power regulation are dynamically coordinated based on an optimal control curve, reactive power margin is preferentially utilized to suppress voltage rise, and power flow distribution is directly regulated through active power reduction when reactive power capacity is saturated. According to the method, the safety and economy of the power grid are considered, and theoretical support and a practical solution are provided for voltage control of the high-permeability photovoltaic power distribution network.

The present invention discloses a method and system for intelligent control of generator output, which relates to the field of intelligent power control, including collecting generator operation data, sampling the generator output waveform, and extracting harmonic distortion data using fast Fourier transform; based on the generator operation data, predicting future changes through a long short-term memory network model to obtain load change trends; according to the load change trend, combined with harmonic distortion data, identifying the correlation between harmonic sources and loads, and generating a harmonic compensation scheme; based on the harmonic compensation scheme and the load change trend, generating a dual control strategy to adjust the generator operating parameters. The present invention generates a dual control strategy by combining the harmonic compensation scheme with the load change trend, thereby realizing dynamic adjustment of the generator output power, reactive power, excitation current and speed, and optimizing the generator operating parameters and energy efficiency.

The invention discloses a new energy sending section adjustment control system based on energy storage, and relates to the technical field of energy storage control, and the system comprises the steps: collecting and obtaining a new energy power generation data set, and building a new energy power generation prediction network; determining new energy power generation prediction parameters; obtaining new energy power generation fluctuation parameters; acquiring power regulation demand parameters of the power grid; performing charging and discharging analysis on the energy storage unit based on the new energy power generation fluctuation parameter and the power grid power regulation demand parameter, and determining an energy storage charging and discharging strategy parameter scheme; and dynamically adjusting and controlling the energy storage charging and discharging strategy parameter scheme through the power operation feedback parameters. The technical problems that in the prior art, new energy power output fluctuation is difficult to respond in time, so that charging and discharging control of an energy storage system is not efficient and accurate enough, and the energy storage utilization efficiency is low are solved, and the technical effects of improving the energy storage utilization efficiency, the charging and discharging control accuracy and the power output stability are achieved.

The invention belongs to the technical field of stable operation of a power system, and discloses a wind turbine generator primary frequency modulation adaptive control method considering active regulation capability, which comprises the following steps: firstly, establishing a wind speed model, and designing a wind turbine generator active load reduction control scheme according to different wind speed intervals; proposing active load reduction of the wind turbine to provide standby down-modulation potential evaluation indexes, carrying out weight calculation by adopting a normal cloud combination in combination with a subjective and objective weighting method, and carrying out comprehensive evaluation on the power regulation and control capability of the wind turbine generator; and when the power system encounters active power shortage, the wind power plant regulation and control center calculates the power regulation quantity of the wind turbine generator according to the comprehensive evaluation result, issues an adaptive power regulation instruction, and cooperates with the conventional unit to suppress the drop of the power grid frequency. According to the method, comprehensive evaluation of normal cloud combination is adopted as the making basis of the wind turbine generator set power adjusting instruction, the standby power reserved by active load reduction of the generator set is effectively utilized, active power output of a wind power plant grid-connected point under disturbance is optimized, and the stability of a power grid is improved.

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 discloses an alternating current charging pile ordered charging power regulation and control method, and relates to the technical field of alternating current charging pile charging power regulation and control, and the method specifically comprises the following steps: obtaining the operation state information of each alternating current charging pile in real time, and generating a voltage fluctuation influence index and a load dynamic response index of each alternating current charging pile; constructing a power influence evaluation model for the generated voltage fluctuation influence index and the load dynamic response index of each alternating current charging pile, generating a power influence evaluation coefficient of each alternating current charging pile, performing analysis after generation, and evaluating the influence degree of the three-phase voltage phase difference fluctuation on the charging power of each alternating current charging pile. And the alternating current charging piles are divided into low-influence charging piles, medium-influence charging piles and high-influence charging piles according to the evaluation result. According to the method, the problem that the charging power is influenced by three-phase voltage phase difference fluctuation is solved, and the efficient and stable effects of dynamic evaluation and accurate regulation and control of the power of the charging pile are achieved.

A method for dynamically adjusting transmit power of a first device that is in communication with a second device using a wireless communications protocol includes, in part, determining, by the second device, a received signal strength indication (RSSI) associated with a signal received from the first device; determining, by the second device, a first amount of power adjustment for the first device in accordance with the determined RSSI; transmitting the first amount of power adjustment from the second device to the first device; determining, by the first device, a second amount of power adjustment for the first device in accordance with the RSSI and the first amount of power adjustment; and changing a transmit power of the first device in accordance with the second amount of power adjustment.

The invention relates to the technical field of power system frequency, and discloses a thermal power generating unit-energy storage coupling frequency modulation system for improving power grid frequency stability, which comprises a thermal power generating unit module, an energy storage system module, an energy management and distribution control module and a communication and monitoring module. The thermal power generating unit provides a frequency stabilization basis through inertia response and power regulation, and the energy storage system compensates frequency deviation in a quick response mode. And the energy management module dynamically adjusts the power distribution proportion between the thermal power generating unit and the energy storage system based on the optimized objective function to realize efficient collaborative frequency modulation. The output power and the state of charge of the energy storage system are controlled by constraint conditions. The communication and monitoring module collects power grid frequency, load fluctuation and energy storage state data in real time, generates frequency modulation control signals and issues the frequency modulation control signals to each module. By combining the stability of the thermal power generating unit and the quick response characteristic of the energy storage system, the response speed and the adjustment precision of power grid frequency adjustment are remarkably improved, and meanwhile the frequency adjustment cost is reduced.

The invention relates to the technical field of emergency mobile power supplies, and discloses a control method of an emergency mobile power supply and the emergency mobile power supply, and the method comprises the steps: carrying out the operation parameter data collection and adaptive wavelet transform noise reduction of the emergency mobile power supply, and obtaining a standardized feature matrix; performing hierarchical feature extraction through an extended convolutional capsule network to obtain global power supply features and local power supply features; establishing a deep deterministic strategy network for power supply state scoring to obtain a state scoring result; inputting historical data in the experience playback pool into an action generation module, performing optimization iteration on the control action to obtain a first control strategy, and recording state transition data in a control process; and carrying out power loss compensation control analysis to obtain compensation control quantity, superposing the compensation control quantity to obtain a second control strategy, carrying out PWM (Pulse Width Modulation), and generating a charging and discharging control signal. According to the invention, accurate power regulation and energy storage unit control are realized, and stable operation of the system is ensured.

The invention discloses a distributed energy storage aggregation method and system based on the improved Minkowski sum, and relates to the technical field of power systems, and the method comprises the steps: constructing a single operation model; according to the operation model of each energy storage monomer, representing a power regulation feasible region of the energy storage monomer in a Polytopes semi-plane form; clustering the to-be-aggregated distributed energy storage cluster according to the model parameter of each distributed energy storage monomer in the to-be-aggregated distributed energy storage cluster, and determining a clustering result of the to-be-aggregated distributed energy storage cluster; and according to clustering results, aggregating the power regulation feasible regions of all monomer energy storage in each type of distributed energy storage by adopting an improved internal approximate Minkowski sum, and determining an aggregation feasible region of each clustering result of the energy storage cluster to be aggregated. According to the method, the aggregation efficiency of a large number of distributed flexible resources is improved, the flexibility lost in the aggregation process is reduced, the adjusting capacity of the power system is enhanced, and positive support is provided for sustainable development and economic operation of the power system.

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.

Embodiments of this invention discloses a split-phase output power adjustment system, adjustment method, and storage medium in a low voltage transformer area. The system includes adjustment power supplies, split-phase power adjustment modules, sub-controllers, a main controller. The adjustment power supplies connected to the split-phase power adjustment modules, and total power P of the adjustment power supplies complying with a relationship as follows: P=Pt=PG1+PG2+ . . . . PGn; wherein Pt is power required to comply with three-phase current unbalance adjustment of a distribution transformer, PG1, PG2, . . . PGn is power generated by each of the adjustment power supplies to compensate three-phase current unbalance in a transformer area; wherein the split-phase power adjustment modules are connected to lines of three phases A, B, and C and a neutral line N in the transformer area; wherein the sub-controllers are connected to the adjustment power supplies, and the sub-controllers communicate with the main controller to control power generated by each of the adjustment power supplies, so as to compensate the unbalanced three-phase current in the transformer area. Coordinated adjustment of multiple distributed power supplies realizes precise control of three-phase imbalance in the transformer area, which reduces line loss and improves power quality.

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.