143 results about "Voltage optimisation" patented technology

The invention relates to a source-containing power distribution network multi-target collaborative voltage optimization control method based on an FACMAC algorithm, and belongs to the technical field of photovoltaic inversion control. According to the technical scheme, a power distribution network physical system is composed of a plurality of feeder lines, a transformer, a line and a plurality of grid-connected photovoltaic inverters, and each inverter can measure operation information such as local voltage and current in real time; the data acquisition and communication system is used for acquiring node operation data and realizing low-delay communication; the multi-agent reinforcement learning control system is composed of a plurality of distributed agents and factorization centralized Critic modules, and whole-network voltage optimization decision can be carried out in training and execution stages. And the execution unit adjusts the reactive power output of the inverter in real time according to the control instruction. According to the method, the whole-network cooperative regulation and control capability is improved, the training efficiency bottleneck in a high-dimensional scene is relieved, the expression capability on a complex nonlinear coupling relationship is enhanced, and efficient, stable and extensible power distribution network voltage optimization control is realized.

The invention discloses a current coordinated distribution and voltage optimization control method of a multi-network converter considering nonlinearity and negative sequence load. The method comprises the following steps: carrying out harmonic separation on three-phase load side current and three-phase capacitor voltage through feedforward compensation to obtain a fundamental wave positive sequence component, a fundamental wave negative sequence component and an h-order harmonic component; fundamental wave positive sequence active and reactive power are solved, and angular frequency and output voltage are respectively obtained through an active frequency regulator and a reactive voltage regulator; virtual impedance of a fundamental wave positive sequence, a fundamental wave negative sequence and a harmonic component is set, a multi-frequency-point virtual impedance voltage drop instruction is calculated, and a voltage reference instruction value is obtained by subtracting the multi-frequency-point virtual impedance voltage drop instruction value from the output voltage of the constructed network type converter; calculating a three-phase modulation wave signal based on the voltage reference instruction value, the capacitor voltage, the load side current, the inductor current and the DC voltage; and calculating a pulse signal of the switching device based on the three-phase modulated wave signal. The virtual impedance of the networking converter is set to be a negative value, the harmonic voltage drop on a common coupling point can be reduced, the sum of the virtual impedance and the actual impedance is adjusted to be a certain proportion, and the harmonic current of each order of the multi-networking converter can be distributed according to the proportion.

The invention discloses a three-phase vehicle-mounted charger hierarchical control method and system based on a battery state, and the method comprises the steps: obtaining the battery state data of a vehicle-mounted power battery, the battery state data at least comprising a battery voltage and a battery charge state; determining a charging mode according to the battery voltage and / or the battery charge state; when the charging mode is a first charging mode, controlling the PFC converter to operate in a constant voltage output mode, and executing voltage following control on the bidirectional DC-DC converter based on the battery voltage; and when the charging mode is a second charging mode, executing voltage following control on the PFC converter based on the battery voltage, and controlling the bidirectional DC-DC converter to operate in a constant-frequency or constant-phase output mode at the same time. By setting hierarchical control strategies under different working conditions, the output voltage of the PFC converter is adaptively adjusted, the voltage regulation transformation ratio under different working conditions is optimized, the overall circuit structure is improved, and the charging efficiency of the vehicle-mounted charger within the full working condition range is improved.

A method for controlling a permanent magnet (PM) synchronous motor in an ESP application is provided. A load angle of the PM motor is estimated. A voltage adjustment value is determined for the PM motor based at least on the estimated load angle of the PM motor. A voltage to be applied to the PM motor is determined based on the voltage adjustment value.

The invention discloses a front-stage and back-stage collaborative optimization control method for a vehicle-mounted V2G bidirectional converter, and relates to the technical field of vehicle-mounted bidirectional converter control. According to the invention, a front-stage totem-pole bridgeless PFC double-closed-loop controller and a rear-stage CLLC resonant converter double-closed-loop controller are designed; secondly, establishing a system joint model, reflecting the dynamic behavior of the bus voltage in the charging and discharging process, designing a corresponding bus voltage optimization method, and adopting an improved particle swarm optimization (IPSO) algorithm to optimize the parameters of a front-stage controller and a rear-stage controller by using a comprehensive cost function in the bus voltage optimization method; and the prediction step length and the weight parameter of the MPC link and the gain of the PI link are optimized in real time, so that the front-stage and rear-stage double-closed-loop control strategy can be more flexible and reliable in application. Through the innovation, the system can adapt to different working conditions in real time, front-stage and back-stage collaborative optimization control is achieved, the overall energy transmission efficiency is improved, and energy loss is remarkably reduced.

A multi-time scale voltage control method for an active distribution network is provided. The method comprises: establishing a voltage optimization approach taking into account a large scale of distributed power supplies to realize cooperative dynamic control in case of a voltage violation generated when the distributed power supplies are incorporated into a distribution network; under a long time scale, establishing a voltage control model for controlling a capacitor bank based on voltage sensitivity analysis to realize drastic voltage regulation in case of the voltage violation by means of reactive power compensation; and under a short time scale, establishing a distributed voltage control model, and considering the problem of voltage violation, solving an optimal control strategy online by fully using active and reactive power outputs of the distributed power supplies to realize quick voltage regulation.

The invention discloses a multi-scale adjustment demand evaluation method and system adaptive to mountainous area load characteristics, and the method comprises the steps: obtaining the voltage data of a mountainous area power grid, carrying out the preprocessing of the voltage data through different time scales, and obtaining different types of load data samples under multiple time scales; constructing a load characteristic description model of each type of load unit based on the load data sample, and integrating power system data to establish a power distribution network structure topology model; and the load characteristic description model and the network structure topology model are combined to evaluate the power grid regulation requirements of different time scales. According to the method, the operation data of the power grid are accurately acquired, a load characteristic description model of multiple types of units is made based on historical load fluctuation information, the power loss and voltage optimization results of the power grid are comprehensively considered, node power adjustment demand evaluation results are given in different time scales, and reliable data support is provided for subsequent operation adjustment of the power grid.

The invention discloses a high-voltage distribution network reactive voltage optimization method, device, equipment and medium based on a time scale, and relates to the technical field of distribution network optimization, and the method comprises the following steps: obtaining the real-time operation state data and prediction information of a high-voltage distribution network, dividing the operation time of the high-voltage distribution network, obtaining the divided data, and calculating the real-time operation state data of the high-voltage distribution network; the division data comprises a long time scale and a short time scale; under a long time scale, based on load prediction and distributed power supply output prediction, a mixed integer programming model is established, and a capacitor bank switching scheme and a transformer tap reference position are obtained; under a short time scale, constructing an optimal power flow model with minimum voltage deviation as a target, and dynamically calling the reactive capacity of the distributed energy converter for real-time correction; and establishing a cross-time-scale coordination control mechanism, triggering advanced re-optimization of a long time scale when the accumulated reactive power regulation quantity under a short time scale reaches a preset reactive power capacity threshold value, and updating an equipment action constraint condition.

The micro-grid multi-time scale voltage optimization method based on deep reinforcement learning comprises the steps of providing a multi-time scale collaborative optimization framework based on deep reinforcement learning for a voltage out-of-limit problem caused by distributed photovoltaic access in a micro-grid; an improved hierarchical DQN (HRL-Dueling DQN) algorithm is adopted to carry out long-time scale optimization control on discrete capacitor equipment, so that the voltage out-of-limit risk is reduced; and performing short-time scale fine adjustment on reactive output of the continuous photovoltaic inverter by using a depth deterministic strategy gradient (DDPG) algorithm to suppress voltage deviation. According to the micro-grid multi-time scale voltage optimization method based on deep reinforcement learning, the real-time performance and robustness of voltage optimization are improved, the voltage out-of-limit risk is effectively restrained, voltage fluctuation is finely adjusted, and reliable guarantee is provided for safe and stable operation of a micro-grid with new energy access.

The invention relates to the technical field of electrochemistry and energy storage, and discloses a battery life and charging efficiency equalization optimization method and system, and the method comprises the steps: extracting the capacity fading rate, internal resistance change trend and temperature sensitivity of a target battery; analyzing the real-time health state of the target battery and the battery chemical model, and establishing a dynamic reference charging curve of the target battery; defining a charging efficiency threshold value and an IDR safety limit value of the target battery; monitoring battery charging data in the charging process of the target battery in real time so as to analyze the current charging efficiency and the instantaneous attenuation rate of the target battery, and establishing a dual-target optimization function of the target battery; and the charging efficiency equalization parameters of the target battery are generated by using the dual-objective optimization function, and the charging efficiency equalization parameters comprise the optimized charging voltage, the optimized charging current and the optimized charging pulse interval, so that the service life of the battery can be prolonged, and the equalization optimization effect of the charging efficiency can be improved.

The invention provides a 10kV feeder reactive voltage optimization control method based on reactive compensation optimization stationing, which relates to the technical field of reactive voltage control, and comprises the following steps: constructing a 10kV feeder reactive optimization configuration model by taking loss reduction and investment cost reduction as targets; solving the reactive power optimization configuration model to obtain a reactive power compensation device optimization stationing scheme of the 10kV feeder line; constructing a 10kV feeder reactive power optimization control model according to the reactive power compensation device optimization stationing scheme; solving the reactive power optimization control model to obtain a reactive power optimization control scheme of the 10kV feeder line; and controlling corresponding equipment of the 10kV feeder line according to the reactive power optimization control scheme. According to the scheme, the reactive voltage control capability of the 10kV feeder line can be improved, and the reliability of stable operation of a power grid is further improved.

The invention relates to the technical field of rare earth electrolytic metallurgy, and discloses a praseodymium-neodymium alloy low-temperature electrolysis cell voltage optimization method and system.The method comprises the steps that multi-parameter coupling analysis is conducted on an electrolytic cell low-temperature electrolysis initial parameter set, and key influence factors are obtained; carrying out correlation analysis on the key influence factors by combining fluctuation characteristics of the cell voltage to obtain an influence weight sequence; determining a collaborative adjustment scheme of the polar distance and the current density according to the weight sequence; the cell voltage is synchronously adjusted based on the collaborative adjustment scheme, and accurate control over the two is achieved; the operation parameters of the electrolytic cell are collected and integrated to obtain a feedback parameter set, the feedback parameter set is fed back to a correlation analysis link to optimize the key influence factor identification precision, and finally a cell voltage optimization scheme is obtained. The technology can accurately identify the key influence factors, dynamically adapt to the operation change of the electrolytic cell, improve the stability of the cell voltage, reduce energy consumption and cost, and improve the efficiency of cell voltage optimization. The production efficiency and the product quality are ensured.

The invention relates to the technical field of electric vehicle driving control, and particularly discloses a driving control system and method for intelligent transfer equipment. The driving control method is used for solving the driving control problems of large current tracking error, high torque ripple and noise vibration, unstable regeneration and poor low-speed micro-climbing and ramp restarting response caused by sampling and inverter time lag, parameter drift, bus fluctuation and degradation faults of a six-phase permanent magnet synchronous motor of intelligent transfer equipment under the complex working condition of a port. The system comprises an AT-AGV, a PMSM, a six-phase inverter, a DC bus, a controller and a planning module. Through midpoint sampling, two-beat equivalent time-delay modeling and limited deadbeat voltage optimization, and in combination with xy harmonic compensation, online parameter identification, three-section regeneration trajectory and fault-tolerant SVPWM, robust stability and high-efficiency recovery under low-overshoot rapid torque establishment, low ripple and low NVH, bus fluctuation and fault are realized; accurate current tracking and smooth traction are realized during micro-crawling and ramp restarting.

A power distribution network voltage cooperative control method considering a cluster division-optical storage all-in-one machine comprises the following steps: step 1, combining an electrical modularity index, a balance index and a membership index to construct a cluster comprehensive division index; 2, taking the comprehensive division index as a convergence condition for dividing a cluster region, and solving an optimal cluster division result of the power distribution network by utilizing an improved spectral clustering algorithm; 3, with the minimum power distribution network node voltage deviation punishment cost, the minimum network loss cost and the minimum power generation loss cost of the optical storage all-in-one machine as the target, a power distribution network voltage optimization model containing the optical storage all-in-one machine is constructed; and 4, based on the optimal cluster division result, solving the power distribution network voltage optimization model of the optical storage all-in-one machine through a cluster voltage optimization control strategy, optimizing active power, reactive power and voltage of the power distribution network, and improving power flow distribution of the whole network. The voltage regulation task sharing and power balance are realized, the voltage regulation effect is more reasonable, and the voltage out-of-limit problem under the random fluctuation of the source load power can be effectively solved.

The invention belongs to the technical field of voltage optimization, and particularly relates to a reactive voltage optimization control method suitable for a large-scale new energy collection area, and the method comprises the steps: constructing a node power distribution network topology based on a power system simulation platform, and obtaining a training label; mapping the power distribution network into a graph structure containing nodes and edges; executing graph convolution operation through a graph neural network, extracting single-moment spatial topological features, and arranging the single-moment spatial topological features according to a time sequence to form a spatial topological feature sequence; performing spatial-temporal dynamic modeling on the spatial topological feature sequence by using an improved Mamba model, and outputting a spatial-temporal time sequence feature sequence; introducing an attention mechanism, and outputting a reactive power prediction value of each controllable device as a control instruction of power distribution network dispatching; and outputting a control instruction of actual power distribution network dispatching by using the trained graph neural network and the improved Mama model. According to the invention, under the condition of ensuring voltage safety and reactive constraint, the voltage out-of-limit quantity is reduced, and the voltage qualification rate is improved.

The invention provides a whole-process reactive voltage optimization control method for a power distribution network. The method comprises the following steps: S1, optimizing a slowly-changing discrete control variable in the day; s2, reactive power output of a wind and light grid-connected unit is optimized on the time scale of 15 minutes in the day, and the voltage amplitude of a grid-connected point of the wind and light grid-connected unit is calculated through power flow; and S3, in a real-time control stage, according to a reactive voltage sensitivity criterion, taking a constant grid-connected point voltage amplitude as a target, and finely adjusting reactive power output of the wind and light grid-connected unit in real time. According to the method, the voltage stability and the voltage quality of the system are improved.

The invention relates to a self-adaptive bias voltage optimization method and related equipment based on an MOS (Metal Oxide Semiconductor) transistor, which are applied to a gate drive circuit and comprise the following steps of: monitoring a target MOS transistor in a working state of the gate drive circuit in real time to obtain a working parameter of the target MOS transistor; based on a preset bias voltage demand prediction model, performing bias voltage demand prediction on the target MOS tube based on the working parameters to obtain a bias voltage demand value; performing digital signal processing on the bias voltage demand value so as to convert the bias voltage demand value into a control signal; the control signal is applied to the grid electrode of the target MOS tube so as to dynamically adjust the working state of the target MOS tube, and the technical problem that under extreme conditions such as high temperature or heavy load, fixed bias voltage may cause overheating of the MOS tube or increase of switching loss is solved.

The invention discloses an LLC converter output voltage optimization method and device based on active disturbance rejection control. The method comprises the following steps: inputting an observed output voltage of a resonant converter to an extended state observer; inputting the reference output voltage into a tracking differentiator, outputting a smooth voltage tracking signal and a voltage change rate estimation value by the tracking differentiator, and subtracting from the output of the extended state observer to obtain a first error signal and a second error signal; inputting the first error signal and the second error signal into a nonlinear state error feedback controller, and outputting an error integral signal by the nonlinear state error feedback controller; subtracting the error integral signal and the output of the extended state observer, and dividing the difference by a stability coefficient to obtain a switching frequency control quantity; parameters in the extended state observer and the nonlinear state error feedback controller and a stability coefficient are obtained through a multi-objective optimization algorithm. By adopting the technical scheme, the anti-disturbance capability of the LLC resonant converter is effectively improved.

The invention discloses a flexible interconnection power distribution network voltage optimization control method considering flexible interconnection switch access, and belongs to the technical field of power system operation control, and the method comprises the steps: 1, building a target function considering the total voltage deviation, the total line loss, the total loss cost of a flexible interconnection switch and the net load deviation of a power distribution network; 2, establishing an overall model of the flexible interconnection power distribution network voltage optimization control method considering the flexible interconnection switch and the distributed photovoltaic access; and 3, solving the overall nonlinear optimization model by using a second-order cone programming algorithm to obtain a voltage optimization control result. According to the invention, the voltage of the power distribution network can be optimally controlled by accessing the flexible interconnection switch into the flexible interconnection power distribution network, and the problems and phenomena of instantaneous heavy load or overload of the power distribution network, insufficient existing capacity utilization rate, insufficient distributed power generation permeability and the like are obviously improved.

The invention discloses a low-carbon demand response and partition hierarchical scheduling system and method based on cloud side-end collaboration, and belongs to the technical field of carbon emission reduction resource response capability modeling and interaction mechanisms, and the system comprises a physical layer, a terminal layer and a platform layer. According to the method, firstly, a node carbon potential modeling method under a dynamic carbon emission factor is researched, multi-type flexible resource models of an electric vehicle, an air conditioner load, an electric hydrogen load, energy storage and the like are constructed, a multi-time-scale multi-element resource response capability evaluation method is formed, and a multi-target demand response interaction mechanism and a cluster regulation and control method considering low carbon and high reliability are provided; secondly, researching a supply and demand cooperation partition interaction low-carbon regulation and control technology in a steady state, and proposing a hierarchical partition cooperation active scheduling and reactive voltage optimization method; and finally, realizing low-carbon demand response and partitioned hierarchical scheduling of different dimensions by relying on a cloud side regulation and control framework.

The invention provides a reactive voltage optimization method and device, computer equipment and a storage medium, and belongs to the field of power grid optimizing.The method comprises the steps that a reactive voltage mathematical model of a regional power grid in each time period is established, and parameters are initialized; the improved Golden litsea rotundifolia algorithm comprises the step of introducing a self-adaptive decline factor for regulating and controlling escape energy and a mutation strategy based on a Cauchy distribution function for updating the positions of male Golden litsea rotundifolia individuals; obtaining an initial active power loss value, a node voltage deviation and investment cost data of each time period; and constructing an objective function, carrying out iterative optimization on the mathematical model through an improved Golden Litsea Algorithm to obtain an optimal solution of the objective function in each time period, and optimizing the operation of the power grid based on the optimal solution of the objective function in each time period. Therefore, through the synergistic effect of the adaptive energy factor and the Cauchy variation and the greedy strategy screening, the method has remarkable advantages in the aspects of reducing the active power loss, improving the voltage stability, controlling the investment cost and the like.

The invention relates to the technical field of power distribution network control, and discloses a whole county photovoltaic cluster voltage control method, system and device based on an improved differential evolution algorithm, and a medium, and the method comprises the steps: calculating electrical data between nodes in a power distribution network, and carrying out the preprocessing of the electrical data; performing cluster division through modularity optimization, and setting a target function of cluster division; and constructing a cluster voltage control model by improving a differential evolution algorithm in each cluster and taking photovoltaic inverter residual capacity reactive compensation and distributed photovoltaic active power reduction as control variables, and performing voltage optimization control of the power distribution network. According to the method, the influence of active power and reactive power is comprehensively considered, adaptive clustering of the power distribution network is realized, and the calculation speed is higher; the differential evolution algorithm is improved, so that better optimization precision and calculation stability are achieved; on the basis of cluster voltage control of the virtual balance nodes, the problem that calculation errors are too large due to the fact that global coordination is ignored by independent control is avoided to a certain extent.

The invention discloses a new energy station reactive power coordination control method and system, and relates to the technical field of station coordination, and the method comprises the steps: collecting the data of a new energy station, constructing a target function, and setting a penalty factor; layered and partitioned control is implemented, terminal voltage and power factors of substations are set, and reactive voltage is optimized; the grid-connected point voltage of the power station is pre-judged and regulated, and the maximum capacity of reactive power regulation equipment is exerted; establishing a master-slave station communication and data transmission system, and integrating a reactive voltage control platform to carry out global analysis; and dividing a voltage control area, and performing closed-loop control based on a whole-network reactive target function. According to the invention, the active loss of the system caused by unnecessary reactive power flow is reduced; data are collected in real time through the AVC system and are analyzed and calculated on line, all load voltage regulation devices and reactive compensation devices of all substations in a power grid are monitored in a centralized mode, managed in a unified mode and controlled on line, and reactive voltage optimization control closed-loop operation of the whole grid is achieved.

The invention discloses a short-time voltage fluctuation suppression method, device and equipment based on partition fluctuation evaluation, and relates to the technical field of power system control. The method comprises the following steps: under a minute-level time scale, taking the comprehensive minimization of active power loss, voltage fluctuation in adjacent time periods and reactive power regulation cost as a target, constructing a multi-period reactive power voltage optimization control model, and obtaining a reference voltage and a reference reactive power control quantity; a power system is partitioned through a modularity-based reactive voltage control robust partitioning algorithm, and influence areas which are mainly influenced by new energy fluctuation are identified on the basis of partitioning. And constructing a partition fluctuation evaluation index and setting a partition optimization event triggering mechanism. And under a short-time scale, constructing a subarea reactive voltage optimization control model based on quadratic programming by utilizing a subarea space decoupling technology, and executing subarea coordination optimization. And correcting the partition reactive voltage optimization control model through a model correction method based on multiple linear regression.

The invention discloses an electrical engineering automatic monitoring system and method, relates to the technical field of electrical engineering monitoring, and forms a core architecture of the electrical engineering automatic monitoring system through cooperation of three algorithm units. A plurality of influence factors such as the current fluctuation value, the total harmonic distortion rate and the humidity of air in the environment where the electrical equipment is located are comprehensively considered, the final output power P3 is obtained through calculation, the operation efficiency of the equipment in the actual environment can be accurately evaluated, efficiency reduction caused by equipment aging or load imbalance can be found, and the reliability of the equipment is improved. And the power output of the plurality of electrical devices is optimized by adjusting the load impedance Z or voltage V, so that the plurality of electrical devices in the monitored electrical engineering can maintain the maximum energy efficiency in different load states, the monitoring period of the plurality of electrical devices can be adjusted, and the energy efficiency of the plurality of electrical devices can be effectively improved under limited monitoring resources. The electrical equipment with low energy efficiency is emphatically monitored and maintained, and the monitoring efficiency of the automatic monitoring system of the electrical engineering is improved.

The invention discloses a voltage balance control method and system in a photovoltaic power distribution network based on a DDPG algorithm, and relates to the technical field of power system automation and optimization control, and the method comprises the steps: collecting operation data, and building a distributed photovoltaic power distribution network voltage control model; establishing a reactive voltage optimization model of the power distribution network; and generating a voltage balance control strategy based on the reactive voltage optimization model of the power distribution network. According to the invention, the reactive output of the photovoltaic inverter is dynamically adjusted through the power distribution network reactive voltage optimization model based on the DDPG algorithm, so that the voltage of the power distribution network is controlled. A reactive voltage optimization control strategy is provided for solving the power grid safety problem caused by high-permeability photovoltaic grid connection. According to the strategy, the voltage out-of-limit problem of all nodes of the power distribution network system is controlled by adjusting the reactive power output of the grid-connected photovoltaic inverter, and the voltage on each node in the system is ensured to be maintained in a safe range, so that the operation safety of the power distribution network after photovoltaic grid connection is improved.

The invention discloses a multi-reactive-power-source static and dynamic optimization control method and system based on source-network cooperation, and the method comprises the steps: S1, building and solving a unified optimization model for fusing multiple types of reactive power sources at a power grid side and a power supply side based on ultra-short-term prediction data, and generating a switching plan, a reference curve and a voltage optimization target interval in a future time period; s2, performing simulation check on the optimization plan by using a power grid digital twin model, and if a transient voltage safety standard is violated, triggering re-optimization taking transient safety as a constraint; s3, based on the optimization target and real-time measurement, a tracking adjustment mode or an emergency cooperative control mode is adaptively executed according to the disturbance level; and S4, equipment execution and feedback updating. Through static and dynamic closed-loop coordination and source network resource global optimization, the problems of static and dynamic separation and insufficient source network coordination in traditional control are solved, and the economical efficiency, the safety and the adaptive capacity of the high-proportion renewable energy power grid are remarkably improved.

The invention discloses a power distribution network disturbance self-healing voltage optimization control method, device and system based on multi-agent deep reinforcement learning. The power distribution network disturbance self-healing voltage optimization control method comprises the following steps: modeling a distributed power distribution network voltage optimization problem as a partition Markov decision model; the partition Markov decision model is solved through a deep reinforcement learning MGPER-MATD3 model, reactive power of each photovoltaic inverter in the distributed power distribution network is obtained, and voltage optimization of the power distribution network is completed; wherein the deep reinforcement learning MGPER-MATD3 model performs sampling according to the priority of each experience during experience sampling, and the priority of each experience is related to the TD error, the experience rare degree and the experience reward feature value. The method has the advantages of good voltage control effect, high experience utilization efficiency and the like, and is suitable for the field of distributed power distribution network reactive voltage control and the like.

The invention is suitable for the technical field of power system optimization, and provides a day-ahead and intra-day dual-time scale power system voltage regulation method and system combining a new energy station with energy storage, and the method comprises the steps: constructing a new energy station model and a power system network model respectively, respectively calculating predicted values of new energy generation power and load power according to the new energy station model and the power system network model, and obtaining predicted values of node voltage amplitude and phase angle of the day-ahead prospective dispatching power system based on the predicted values; constructing an optimization model of day-ahead look-ahead scheduling; according to the new energy station model and the power system network model, real-time values of new energy generation power and load power are calculated respectively, and predicted values of node voltage amplitude and phase angle of the intra-day rolling scheduling power system are obtained based on the real-time values; constructing an optimization model of intra-day rolling scheduling; and a day-ahead and intra-day dual-time scale voltage optimization scheme of the power system is determined, so that the problem of unstable pressure of the power system is effectively solved.

The present application relates to a multi-stage coordinated voltage optimization method for a power distribution network optical storage system, which divides the voltage regulation strategy into three stages: 1) using an analytical method for local reactive power compensation of a photovoltaic inverter; 2) selecting the reactive power output of the photovoltaic inverter as a consistency variable based on filter consistency, and performing distributed reactive power regulation of the photovoltaic inverter; 3) selecting the state of charge variation of the energy storage system as a consistency variable based on filter consistency, and performing distributed active power regulation of the energy storage system; this method can fully utilize the voltage regulation resources of the distributed photovoltaic-energy storage system to control the voltage, while solving the voltage out-of-limit problem, and as much as possible reducing the total active power output of the photovoltaic system due to participation in voltage control, and reducing the overall voltage regulation cost of the energy storage system, and at the same time, this method can well adapt to the normal changes of the information-physical topology of the power distribution system, and has better voltage regulation effect and adaptability compared with the traditional single control mode single-stage voltage regulation strategy.