1734results about "Polyphase network asymmetry elimination/reduction" patented technology

The invention provides a dynamic balance system for wind, light, fire and nuclear storage integrated regulation and control of a power grid in a cold region, which relates to the technical field of power grid regulation and control and comprises an energy data acquisition and preprocessing module, a multi-energy coordinated regulation and control module, an energy storage system optimization management module, an energy scheduling optimization module, an intelligent decision and monitoring module and a system communication and safety module. A multi-level, multi-module and intelligent comprehensive framework is constructed, collaborative management and optimal scheduling of various energy sources are achieved, stable operation, efficient energy utilization and sustainable development of a cold region power grid are ensured, global optimization is achieved through deep reinforcement learning, local precise control is conducted through fuzzy logic, and the energy utilization efficiency is improved. The system can intelligently distribute the generated power of each energy source of wind, light, fire and nuclear storage according to the real-time state and environmental conditions of the cold region power grid, gives full play to the advantages of different energy sources, realizes the complementary utilization of the energy sources, realizes the collaborative optimization of multiple energy sources, and improves the utilization efficiency and stability of the energy sources.

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

A distributed photovoltaic consumption-oriented energy storage planning method and system for a flexible distribution network. The method comprises: acquiring grid data, photovoltaic data and load data of a distribution network in a target area, preprocessing the data, screening the preprocessed data, and selecting fault data; on the basis of the selected fault data and a genetic algorithm, establishing a distribution network energy storage system capacity configuration model; and on the basis of the distribution network energy storage system capacity configuration model, performing distributed photovoltaic consumption-oriented flexible distribution network energy storage planning.

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

A distributionally robust optimization method and apparatus for an electric-hydrogen-thermal integrated energy system, relating to the field of power system optimization operation. The method comprises: establishing a multi-agent optimization scheduling model of an electric-hydrogen-thermal integrated energy system; using a data driving-based distributionally robust optimization model to describe the source-load bilateral uncertainty of a power grid system agent optimization scheduling model, establishing a three-layer two-stage power balance model of a power grid system, and using a column and constraint generation algorithm for solving; and using an alternating direction method of multipliers to alternately iterate the three-layer two-stage power balance model of the power grid system, a hydrogen network system agent optimization scheduling model, and a heat network system agent optimization scheduling model, to realize distributed parallel solving of the multi-agent optimization scheduling model of the electric-hydrogen-thermal integrated energy system. Compared with the prior art, each agent scheduling scheme is solved by means of interactive iteration in the present method, thereby protecting the information privacy of each agent while improving the operation economy and reliability of an interconnected power grid.

The invention discloses a charging and discharging control system and electronic equipment. The method comprises the following steps: S1, constructing a charging pile multi-target optimization model; s2, initializing a chaotic particle swarm optimization algorithm; s3, each particle in the particle swarm is optimized according to an objective function in the charging pile multi-objective optimization model; s4, carrying out loop iteration until the chaotic particle swarm optimization algorithm reaches a convergence condition; s5, generating a prediction result of the operating environment of the charging pile; s6, updating the current optimal particle and the global optimal particle; and S7, generating a multi-target charging and discharging optimization control strategy of the charging pile according to the optimized global optimal particle, applying the optimization control strategy to a charging pile charging and discharging control execution module, and executing multi-target charging and discharging control of the charging pile. According to the method, the globally optimal solution in a complex scene can be quickly solved, and the efficient operation requirement of the electric vehicle charging pile in a large-scale deployment scene is met.

The invention discloses an electric energy quality prediction and management platform based on a digital twin technology, which relates to the technical field of power system monitoring and comprises a physical space layer, a data space layer, a model space layer and an application space layer. The physical space layer is provided with an electric energy quality monitoring device and an electrical equipment state monitoring device, output multi-time-scale data are transmitted to the data space layer to be synchronously collected and preprocessed, the preprocessed data are input into the model space layer, a physical entity mapping relation is constructed through a digital twin basic model, and the physical entity mapping relation is obtained. The attribute expansion model constructs dynamic feature mapping, the multi-scale analysis model realizes dynamic analysis, and an analysis result is input into the application space layer to execute prediction, early warning and treatment. According to the method, a hierarchical digital twinborn system of'basic mapping-feature extension-dynamic analysis' is established, collaborative analysis of transient disturbance, short-term fluctuation and steady-state features is realized, and effective support is provided for optimal configuration of an electric energy quality management device.

The invention relates to the technical field of power generation, power transformation or power distribution, and discloses a control method for preventing overload of an energy storage system transformer, which comprises the following steps: monitoring the three-phase total power and the power of each phase of a power grid side ammeter in real time, and calculating the three-phase unbalance degree based on the three-phase total power when the three-phase unbalance phenomenon occurs; when the three-phase unbalance degree is greater than a preset unbalance degree threshold value, dynamically adjusting the charging power of the energy storage converter according to a starting threshold value, a charging limiting threshold value and a charging forbidding threshold value by adopting a multi-threshold value dynamic adjustment mechanism; the phase with the maximum deviation between the power of each phase and the average power of the three phases is calculated as an overload phase, load reduction is performed on the overload phase based on a load increasing and decreasing strategy, load increasing is performed on a non-overload phase, and the adjusted three-phase power is obtained; a power distribution instruction is calculated in real time in combination with a dynamic response mechanism, and the three-phase unbalance degree does not exceed a safety threshold value in cooperation with total power control. The problems of easy overload, three-phase imbalance and slow response of a transformer in the prior art are solved, and the purposes of accurate load control, high system stability and high response speed are achieved.

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

The present invention relates to the field of distribution network fault detection and analysis, and specifically to a distribution network fault impact range assessment method based on automatic generation of distribution network topology, automatic collection of fault information and intelligent quantitative analysis. The steps of the present invention are: 1. Automatic generation of distribution network topology; 2. Automatic collection of fault information; 3. Theoretical calculation of power flow; 4. Dynamic correction of calculation results; 5. Quantitative assessment of fault range. The present invention provides accurate fault propagation path analysis and quantitative assessment through automatic generation of topological structure, multi-source data fusion, theoretical calculation of power flow and intelligent correction technology. The intuitive quantitative results of node scoring and impact range provided provide a scientific basis for operation and maintenance decision-making, contribute to the rational allocation of operation and maintenance resources, and further improve the operation efficiency of the power grid.

The present invention relates to the technical field of parallel power supply, specifically to a tower coordinated power supply method and system, comprising the following steps: obtaining tower inverter power supply current, voltage, and total harmonic distortion rate data, calling a photovoltaic control module to record tower node load, using a sliding window to calculate communication load equipment fluctuations, and generating a tower load fluctuation trend value. In the present invention, through current, voltage, and load data analysis, combined with sliding windows to calculate load fluctuation trends, dynamic prediction of power supply demand is achieved, adjacent nodes are screened based on power supply margin and current monitoring, power distribution is optimized, overload or waste is avoided, low-loss solid-state relays are used to switch power supply paths, adjustment efficiency is improved, losses are reduced, load adaptation is optimized in combination with power adjustment, power supply coordination is ensured, current distribution is optimized according to topology, fluctuations are reduced, harmonic distortion rates are calculated for compensation, power quality is improved, harmonic interference is reduced, and power supply stability and energy utilization are improved.

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

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

The invention, which relates to the technical field of optical storage and charging, discloses an optical storage and charging cooperative control method for a transformer area, and the method comprises the steps: carrying out the intelligent and multivariate collection and prediction through intelligent equipment, constructing a function through collected data, solving an optimal solution, selecting an optimal optical storage and charging cooperative control strategy from the optimal solution, generating a corresponding control instruction, and carrying out the transmission of the corresponding control instruction. Cooperative regulation and control of a photovoltaic power generation system, an energy storage system and a charging pile system are achieved, a feedback and correction mechanism is further established, and it is ensured that the photovoltaic storage and charging system stably operates according to a preset strategy. According to the transformer area light storage and charging cooperative control method, a light storage and charging cooperative control mechanism is established by comprehensively considering photovoltaic power generation, an energy storage system and a charging pile system, power resource distribution in a transformer area is optimized, maximum consumption of photovoltaic power generation is achieved, the light abandoning phenomenon is reduced, meanwhile, unnecessary charging and discharging loss of the energy storage system is reduced, and the power utilization rate of the transformer area is improved. And the impact of disordered charging of the charging piles on a power grid system is relieved, so that the overall operation performance of a transformer area power system is improved.

The invention provides an impedance scanning device based on network side voltage dynamic compensation under a three-phase voltage imbalance working condition, and relates to the technical field of new energy station power electronic converter topology and control, the device comprises a three-phase rectifier, a direct current bus capacitor, an inverter, a voltage compensation device, a frequency sweeping device, a circuit breaker and a series transformer part, the three-phase rectifier is connected in series with inverters of the voltage compensation device and the frequency sweep device, a secondary side of a series transformer of the voltage compensation device is connected in series with a network side, a secondary side of a series transformer of the frequency sweep device is connected in series with a grid-connected point, and a primary side of the series transformer is connected to the inverters and is coupled to a secondary side of the series transformer; according to the device, the power grid side voltage is rectified through the voltage compensation unit and is compensated to the grid side after being subjected to single-stage inversion transformation, voltage compensation is achieved through the energy of a power grid when the voltage is unbalanced, and an external energy source or an interference source does not need to be introduced. After compensation, the accuracy of the frequency sweeping result is obviously improved.

The invention relates to the technical field of power dispatching management and control, and discloses a power distribution network power dispatching method based on a virtual power plant AI large model and demand response, and the method comprises the steps: collecting the operation data of a power distribution network, and constructing a feature vector; an AI large model is adopted to calculate and predict load output, and joint uncertainty information is output; calculating a system power unbalance amount, and generating a scheduling strategy; issuing a scheduling instruction corresponding to the scheduling strategy and executing the scheduling instruction; comprehensive performance evaluation indexes are calculated, and whether a performance reduction reason diagnosis mechanism is started or not is judged; according to the method, the AI large model is adopted, the load power, the photovoltaic output and the wind power output are predicted at the same time through a multi-task learning strategy, and the correlation among multiple variables is fully utilized; by constructing a multi-objective optimization model, comprehensively considering economy, safety and reliability and adopting an improved particle swarm optimization algorithm for solving, coordinated optimization configuration of demand response resources is realized, power grid fluctuation is effectively reduced, and power supply reliability is improved.

The invention discloses a flexible interconnected power distribution network active-reactive optimization method considering electric energy quality requirements, and belongs to the technical field of power distribution network optimization operation. The invention aims to provide the active-reactive optimization method for the flexible interconnected power distribution network considering the electric energy quality demand, which simultaneously optimizes the voltage deviation, feeder balance and network loss of the power distribution network through various control means such as soft switching power regulation participation response. The method comprises the following steps: proposing a flexible interconnection system power quality demand subjective and objective weighting evaluation method through calculation of a flexible interconnection system day-ahead index time sequence value, and proposing a flexible interconnection power distribution network active-reactive power optimization model considering a node comprehensive weight through coordinated operation of a traditional network side resource and an intelligent soft switch. According to the invention, the active-reactive optimization method of the flexible interconnection power distribution network considering the power quality demand is analyzed, the effective cooperation of the flexible interconnection device and the controllable network side resource regulation and control is explored, and the influence on the voltage deviation, feeder balance and network loss of the power distribution network is optimized by multiple control means at the same time; and reference is expected to be provided for guiding optimal scheduling of the flexible interconnected power distribution network.

The invention discloses a three-phase imbalance compensation method and system based on negative sequence current and a medium, and relates to the technical field related to power imbalance compensation, and the method comprises the steps: executing the three-phase current, voltage and reactive power data collection of a power distribution network, and carrying out the three-phase imbalance recognition through negative sequence current analysis; carrying out additional acquisition of a load mode and environment data on the power distribution network; taking the data acquisition result and the additional data set as input data to execute negative-sequence current change trend prediction; a double-layer compensation device is configured for cooperative control optimization; power distribution network balance compensation is executed through a time sequence compensation strategy, and time sequence window feedback is established; and carrying out adaptive strategy correction. The technical problems that in the prior art, a three-phase imbalance compensation strategy lacks perspectiveness and self-adaptive capacity and cannot cope with a dynamically-changing power grid scene, and consequently compensation precision and stability are poor are solved, and the technical effects that perspectiveness and predictive compensation is achieved, and three-phase imbalance compensation precision and stability are improved are achieved.

The invention discloses a virtual synchronization-based parallel optimization control method for a network energy storage system, and relates to the technical field of power system operation control. The virtual synchronization-based parallel optimization control method for the network energy storage system comprises the following steps of: based on an active-frequency droop characteristic and a reactive-voltage droop characteristic; setting a virtual synchronous generator control strategy of the energy storage unit; the virtual impedance is introduced into a virtual synchronous generator control strategy, and the output impedance of the virtual synchronous generator is set to be inductive; and selecting the optimal virtual inertia and damping value to optimize the dynamic response of the networking energy storage system. The dynamic virtual impedance is introduced into the parallel converter, the virtual impedance is adjusted, power decoupling of the VSG parallel control system is achieved, optimal system frequency and power dynamic response are comprehensively considered, optimal configuration of control parameters is completed through the particle swarm optimization, the system frequency and power dynamic response is improved, and the stability of the system is improved.

The invention provides a dynamic aggregation peak regulation method and system based on distributed photovoltaic power prediction and computing equipment, and is applied to the technical field of dispatching and control of a power system. The dynamic aggregation peak regulation method comprises the following steps: acquiring data of a photovoltaic power station through a photovoltaic power station monitoring system, a meteorological station and a geographic information system; performing photovoltaic power prediction by using the distributed photovoltaic power prediction model; load demand prediction is carried out on the load in the future time period; performing network division and dynamic aggregation on the photovoltaic area; and carrying out peak regulation strategy optimization based on the output of the dynamic aggregation. According to the method, the peak regulation pressure of power grid operation can be reduced, and the stability and economical efficiency of the system are improved.

The invention provides a dynamic scheduling method for new energy station loads, which relates to the technical field of new energy power generation, and comprises the steps of collecting power generation data and equipment operation state data, calling power grid load demand data and power grid operation parameters, building a comprehensive prediction model according to station historical data in combination with a neural network algorithm, and carrying out dynamic scheduling on the new energy station loads. The comprehensive prediction model comprises a power generation power prediction model and a load demand prediction model, inputting the power generation data, the equipment operation state data, the power grid load demand data and the power grid operation parameters into the comprehensive prediction model, performing power generation capacity prediction and load demand prediction, and performing dynamic scheduling based on a power generation capacity prediction result and a load demand prediction result. The technical problems of power grid power imbalance and resource waste caused by the fact that load scheduling is difficult to adapt to the power generation characteristics of the new energy station in the prior art are solved. The technical effects of realizing flexible scheduling of the load of the new energy station and effectively balancing the generated power of the new energy station and the load demand of the power grid are achieved.

The invention belongs to the field of power system control, and particularly discloses a power transformer, photovoltaic and energy storage integrated electric energy regulation and control system which comprises a power generation and energy storage optimization scheduling module, a load balance control module, a fault diagnosis and processing module cabinet and a communication module. The system can monitor the operation states of the power transformer, the photovoltaic power station and the energy storage device in real time, and controls the power directions of the photovoltaic inverter and the energy storage converter in real time according to the load condition of the power transformer in combination with the current power grid policy, the peak-valley time period and the electricity price policy, so as to solve the overload problem of the power transformer and improve the safety of the power transformer. And the most economical and environment-friendly electric energy distribution and utilization are realized.

Module-based energy systems are provided having multiple converter-source modules. The converter-source modules can each include an energy source and a converter. The systems can further include control circuitry for the modules. The modules can be arranged in various ways to provide single phase AC, multi-phase AC, and / or DC outputs. Each module can be independently monitored and controlled.

The invention discloses a virtual synchronous generator stability improving method and device, and the method comprises the steps: carrying out the impedance modeling of a VSG, and obtaining a VSG impedance model; generating a regulation voltage based on the variable transient virtual damping control scheme; superposing the current loop output voltage and the adjusting voltage, and applying the superposed voltage to a VSG impedance model to adjust the three-phase voltage output by the VSG; in the variable transient virtual damping control scheme, a VSG impedance model is compared with a synchronous motor operation principle according to a power system similarity principle, a transient virtual resistance is calculated by using an angular frequency change output by the VSG and a d-axis current change, and a steady-state virtual resistance and a virtual inductance are calculated by using a direct-current bus voltage fluctuation and a direct-current bus output current change of the VSG; a regulated voltage is determined using the transient virtual resistance, the steady state virtual resistance, and the virtual inductance. The stability of the virtual synchronous generator can be improved.

The invention relates to the technical field of power grid bearing capacity evaluation, in particular to a method and system for evaluating the bearing capacity of a power distribution network. The method comprises the following steps: obtaining a noise reduction power distribution network operation data set; performing three-phase imbalance index calculation based on the noise reduction power distribution network operation data set to obtain three-phase imbalance characteristic data; performing wavelet transform decomposition on the noise-reduced operation data set of the power distribution network to obtain photovoltaic output fluctuation characteristic data; associating the photovoltaic output fluctuation characteristic data with the three-phase imbalance characteristic data to obtain a photovoltaic-imbalance mapping relation model; performing electric-thermal coupling modeling on the distribution transformer winding based on the photovoltaic-unbalanced mapping relation model to obtain a thermodynamic response model of the distribution transformer; and performing finite element thermal field simulation on the thermodynamic response model of the distribution transformer to obtain winding temperature distribution data. By accurately quantifying the influence of the intermittent output of the photovoltaic inverter on the three-phase imbalance of the distribution transformer, the defect that the traditional method is difficult to accurately evaluate is overcome.

The invention discloses a grid-connected inverter complementary sliding mode control method based on a cascade generalized proportional-integral observer, and the method comprises the steps: firstly building a mathematical model of a grid-connected inverter, and enabling the mathematical model to be used for the design of a controller; and a cascade generalized proportional integral observer is introduced to estimate the lumped disturbance of the hyper-local model so as to improve the anti-disturbance capability and the noise suppression capability of the system. By introducing the complementary sliding mode controller, compared with a traditional sliding mode, the position tracking error is reduced by half. By introducing the improved reaching law, a large reaching speed can be kept when the system state is far away from the sliding mode surface, and the sliding mode reaching speed is weakened when the system state approaches the sliding mode surface, so that the chattering phenomenon of the sliding mode is reduced. According to the control method, the coupling influence of the d axis and the q axis can be obviously inhibited, the harmonic content of the three-phase current is reduced, and stable operation of the grid-connected inverter is facilitated.

The invention discloses an intelligent commutation type three-phase imbalance dynamic treatment method for a power distribution network, relates to the technical field of power distribution network treatment, and aims to solve the problem of poor treatment effect of three-phase imbalance. By using the data mining and analysis technology, not only can the cost minimization path be calculated according to the current state, but also the future change can be pre-judged in combination with the load dynamic trend, so that the formulated switching strategy is more prospective and accurate, the generated high-dimensional mapping vector fuses the node characteristics and the neighbor node characteristics, and the switching efficiency is improved. By combining the use of a nonlinear activation function, the model can adaptively learn a load change rule, sensor equipment integrates various sensors and chips, has the functions of environment monitoring, power management and the like, and is matched with structural components to ensure the reliable operation of the device, reduce the operation and maintenance cost and difficulty and prolong the service life of the equipment.

The invention relates to the technical field of power quality management of a power distribution network, in particular to a power quality management method and device with a rapid fault removal function, and the method specifically comprises the steps: obtaining the comprehensive weight of a three-phase imbalance degree, a reactive loss degree and a harmonic distortion degree through the data characteristics of each node in a power distribution network system; analyzing the operation cost when the power distribution network system is subjected to three-phase imbalance treatment, reactive treatment and harmonic treatment, and determining an optimization objective function; and based on the optimization objective function, combining a particle swarm optimization algorithm, dynamically adjusting the inertia weight during each iteration, obtaining an optimal configuration scheme, and performing power quality management of the power distribution network system. The probability that particles fall into a local optimal solution in the iteration process is effectively reduced, and a better optimal configuration scheme of the electric energy management equipment can be obtained to carry out electric energy quality management on the power distribution network system, so that electric power faults occurring in the power distribution network system can be rapidly removed.