73 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 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.

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 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 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 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 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 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 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.

The invention provides a power distribution network reactive voltage optimization method based on mathematical analysis, and relates to the technical field of power distribution network control, and the method comprises the steps: S1, building a control model of a distributed active power distribution network reactive power compensation device according to a physical model and control characteristics of the distributed active power distribution network reactive power compensation device; s2, establishing a multi-optimization objective function which takes the minimum network loss as a core and takes voltage quality into account, and establishing operation constraint conditions; s3, based on the obstacle function conversion constraint and gradient / Hessian matrix optimization, designing a solving algorithm model; and S4, integrating the control model, the multi-objective optimization function and the operation constraint condition into an active power distribution network reactive voltage coordination control optimization model, calling a solution algorithm model for solution, and outputting an optimization control scheme of the reactive power compensation device. According to the scheme, the problems that a traditional distribution network optimization model does not fully fuse the characteristics of the distributed active reactive power compensation device, and a multi-dimensional target and complete constraint are not designed for the active power distribution network can be solved.

The invention discloses a high-fidelity rapid ion transport device. The device comprises an upper computer module, an FPGA data processing module, a digital-analog voltage conversion module, a voltage amplification module, a low-pass filtering module and an ion trap module which are connected in sequence, the invention also discloses a voltage optimization method for high-fidelity rapid ion transport, the speed of ion movement is controlled through a sin2 function, and the method provided by the invention calculates the optimal voltage value of each transport electrode under the transport track of ions through a quadratic programming algorithm; the moving process of ions has the characteristics of slow start, constant-speed middle section and slow stop, and the smooth movement can effectively avoid excitation of a motion mode and reduce the heating effect; the optimal voltage value of each transport electrode avoids additional heating, improves the efficiency of quantum calculation, and meets the high fidelity requirement of the ion logic gate.

A supply voltage may be set using a local voltage regulator, such as a Digital Linear Voltage Regulators (DLVR). A DLVR may include a compensator, and the performance of the compensator may be affected by a dropout (DO) voltage. To improve the performance of a compensator, a number of compensator calculations may be pre-calculated to reduce the complexity of remaining real-time computations and enable compensator calculations to be completed within a single DLVR clock cycle. A DLVR may include a sense filter, and the DLVR transfer function (TF) may be modified using dynamic shaping of open loop gain and pole locations of a sense filter. The DO range associated with the DLVR TF may be changed according to a monitored DO(t) to reduce the sensitivity of a domain VMIN on dropout, which reduces power consumption, increases performance, and enables simplification of test flows.

The application discloses a kind of multi-energy distribution network voltage control methods, comprising the following steps, define local voltage control rule;Analysis distributed power output causes voltage fluctuation upper and lower limit;Build global voltage control function;Algorithm is solved to objective function, the local voltage control rule is acquisition control point voltage u, determine whether to satisfy the following constraint, set the reactive power output of voltage compensation device.The multi-energy distribution network voltage control method, considering the uncertainty fluctuation of distributed power supply, improve the accuracy of voltage fluctuation analysis, formulate the localized voltage adjustment rule and global voltage optimization function, realize passive control and active control combination, reduce fluctuation rate, using interval number to express the uncertainty of distributed power supply, less computing resource demand, control reaction speed is fast.

A GCIB apparatus that can change the energy of ions to be irradiated onto a substrate without changing the electrode arrangement of the GCIB apparatus that have an extraction electrode arrangement optimized for a specific voltage or a permanent magnet type magnet that effectively removes singly charged monomer ions at that voltage, or the magnetic field strength of the permanent magnet type magnet. A separated high voltage power supply that generates a positive or negative high voltage in addition to the first high voltage power supply, the second high voltage power supply and the third high voltage power supply, and a separated high voltage application circuit that applies a positive or a negative separated high voltage supplied from the separated high voltage power supply to the ground electrode of the extraction electrode and the ground electrode portions of the one or more electrostatic lenses.

This application relates to the field of power system technology, and in particular to a distributed optimization method for reactive power and voltage in a multi-zone flexible interconnected AC / DC hybrid distribution network based on cluster partitioning. By constructing distributed optimization models for reactive power and voltage within and between clusters, an improved particle swarm optimization algorithm (PSO) is used to enhance the global search capability of the model. Furthermore, the advantages of the alternating direction multiplier method (ADMM) for distributed solving are combined to improve solution efficiency and effectiveness, thereby effectively optimizing the reactive power and voltage of a multi-zone flexible interconnected AC / DC hybrid distribution network with a high proportion of distributed renewable energy. The aim is to solve the problem of reactive power and voltage optimization in such a network.

This invention discloses a hierarchical control method and system for a three-phase on-board charger based on battery state. The method includes: acquiring battery state data of the on-board power battery, the battery state data including at least battery voltage and battery state of charge; determining a charging mode based on the battery voltage and / or battery state of charge; controlling the PFC converter to operate in a constant voltage output mode when the charging mode is a first charging mode, while simultaneously performing voltage following control on the bidirectional DC-DC converter based on the battery voltage; and performing voltage following control on the PFC converter based on the battery voltage when the charging mode is a second charging mode, while simultaneously controlling the bidirectional DC-DC converter to operate in a constant frequency or constant phase output mode. This invention adaptively adjusts the output voltage of the PFC converter by setting hierarchical control strategies under different operating conditions, optimizes the voltage regulation ratio under different operating conditions, improves the overall circuit structure, and enhances the charging efficiency of the on-board charger across the entire operating range.

The application discloses a flexible on-load voltage regulating transformer multi-target cooperative control system and method based on hour-level load prediction, which comprises the following steps: a node parameter acquisition module acquires electrical parameters of each node of a power distribution network; a load prediction module outputs a load prediction sequence in the future time; a multi-target optimization module generates an optimal control optimization strategy according to a cooperative optimization model; an upper prediction optimization layer makes an hour-level optimization decision on tap position and capacitor group switching; a lower real-time adjustment layer outputs a voltage dynamic compensation amount and generates a minute-level equipment adjustment instruction; and an execution module coordinates and controls flexible on-load voltage regulating transformer (FOLTC) tap switching, capacitor group switching and converter action, so that multi-target optimization of voltage deviation, reactive power compensation and equipment loss is realized. The application is suitable for voltage optimization, reactive power compensation and loss control in a conventional load fluctuation scenario of a power distribution network.

The invention provides a voltage optimization control method and system for a multi-branch power distribution network based on moment difference analysis, and relates to the field of power distribution network voltage optimization control research. The method comprises the following steps: acquiring basic data and operation data of all typical daily power distribution networks; the upper limit and the lower limit of the critical moment difference of the distribution line are calculated for the typical day, and the real-time moment difference of each feeder line is obtained; the branch where the node with the most serious voltage out-of-limit is located is selected as a trunk line, and the multi-branch power distribution network is simplified and equivalent to a trunk line power distribution network; determining the regulation and control direction of the moment difference; determining the moment difference sensitivity of all regulation and control resources; and classifying all regulation and control resources according to the regulation and control cost, sorting according to the classification result and the moment difference sensitivity, and sequentially carrying out moment difference regulation and control according to the regulation and control direction of the moment difference until the moment difference of the main line is recovered to a normal range. According to the invention, the voltage optimization control of the multi-branch power distribution network is realized in the most economical and effective manner.

This invention relates to the field of power grid sensitive node identification technology, and discloses a method, system, device, and medium for identifying sensitive nodes in distribution networks based on sensitivity thresholds and topological electrical characteristics. The method includes: constructing a distribution network simulation model, performing power flow calculations, and obtaining a reactive power sensitivity matrix; performing a dual-threshold initial screening on the reactive power sensitivity matrix to obtain a theoretical set of sensitive nodes, and performing a second screening based on topology and electrical characteristics to obtain a final set of sensitive nodes; performing reactive power compensation and control simulation on the final set of sensitive nodes to verify the voltage optimization effect. This invention identifies high-impact nodes from a sensitivity perspective, and then uses degree centrality and electrical distance to exclude terminal and isolated nodes, ensuring that the selected points simultaneously possess strong control capabilities and feasibility; after configuring reactive power compensation at sensitive nodes, it can improve the overall network voltage qualification rate, reduce voltage deviation, and reduce network losses, and effectively suppress overvoltage problems caused by high-penetration distributed power sources.

This invention relates to a multi-timescale reactive power optimization method for unbalanced distribution networks based on an improved Golden Jackal algorithm. First, the Golden Jackal optimization algorithm is improved by combining low-difference sequence generation and chaotic mapping traversal enhancement to improve population initialization, ensuring the traversal characteristics of the population in space. A hyperbolic tangent-power-law hybrid attenuation model is designed to maintain global exploration and enhance local development. A leadership dynamic weighting mechanism is proposed to enhance the guiding role of optimal individuals and avoid getting trapped in local optima. Considering the three-phase voltage imbalance of the distribution network and the discrete characteristics of regulating equipment, a day-ahead reactive power-voltage optimization model is established and solved using the improved Golden Jackal optimization algorithm. Using the equipment action scheme obtained from the day-ahead optimization as the basis for intraday optimization, an intraday reactive power-voltage optimization model for a three-phase unbalanced distribution network considering continuous equipment is established to regulate reactive power and voltage. The improved Golden Jackal optimization algorithm is then used to solve the model, thus completing the second stage of optimization.

The present application relates to a kind of flexible interconnection ac-dc power distribution network multilayer collaborative voltage optimization method, comprising: the topological model of the mixed power distribution network including alternating current network, direct current network and voltage source converter interconnection device is established;Using the model conversion method based on second-order cone relaxation and linearization, the topological model is converted, and linearized topological model is obtained;Linearized topological model is used as foundation, and the system-level voltage optimization model considering dynamic network reconfiguration and the equipment-level voltage source converter droop control optimization model are constructed;In day-ahead stage, system-level voltage optimization model is solved, and in day-ahead stage, based on the real-time measurement data of power grid, the active power reference value of voltage source converter in day-ahead decision strategy is corrected on-line by equipment-level voltage source converter droop control optimization model.The present application can solve the problem of voltage fluctuation and regulation lag.

The invention belongs to but not limited to the technical field of power system operation control, and discloses a low-voltage distribution network voltage optimal compensation method and system. According to the method, a voltage drop mathematical model containing active power and reactive power of a power compensation device is established, the phase and amplitude relation of head and tail end voltages before and after compensation is analyzed, an optimization function with the minimum compensation current as the target is constructed, and a voltage phase angle optimal solution enabling the target function to obtain the minimum value is determined through derivation. And the minimum compensation current and the minimum apparent compensation power required by the power compensation device are calculated. On the premise of ensuring the voltage compensation effect, the current output of the compensation device can be effectively reduced, the energy efficiency is improved, and the method is suitable for voltage optimization control of a power distribution network and a micro-grid.

This invention discloses a method for noise reduction based on a high-precision voltage source matrix using an optical chip, comprising the following steps: S1, initializing the MCP23017 and configuring chip select and address select signals; S2, sending control signals via SPI to select the DAC8568 channel; S3, the DAC8568 converting the digital signal into an analog voltage signal; S4, amplifying the analog voltage signal; S5, adding noise-reducing capacitors for high-frequency noise filtering; S6, a regulated power supply module providing a stable voltage; S7, optimizing the PCB design, layering and shielding the wiring; S8, adjusting and calibrating the voltage output in real time. This invention, through a high-precision voltage source matrix control method based on the ESP32-S3 microcontroller and the DAC8568 chip, achieves precise adjustment, noise suppression, and voltage stability optimization of multi-channel voltage output, meeting the stringent requirements of high-precision equipment for voltage sources.

The invention discloses a flexible energy storage-oriented power distribution network multi-time-scale collaborative voltage optimization regulation and control method and system, and relates to the technical field of power grid voltage optimization regulation and control, and the method comprises the steps: on the basis of the day-ahead photovoltaic and load prediction power, taking the minimum power loss and voltage deviation of a power distribution network as an optimization target; solving and obtaining day-ahead scheduling result data of the slow-action equipment by considering a scheduling strategy that a beam condition adopts a first duration as a scheduling period and a first preset duration as a time resolution; and performing optimization decision based on day-ahead scheduling result data on the basis of intra-day photovoltaic and load prediction power, and solving and obtaining scheduling plan node data of real-time action equipment to dynamically correct a day-ahead scheduling result by adopting a rolling optimization scheduling strategy in which a second duration is a scheduling period and a second preset duration is a time resolution. According to the method provided by the invention, the technical problem that the adaptability of a voltage regulation and control system to complex working conditions is insufficient in the prior art is solved.

A supply voltage may be set using a local voltage regulator, such as a Digital Linear Voltage Regulators (DLVR). A DLVR may include a compensator, and the performance of the compensator may be affected by a dropout (DO) voltage. To improve the performance of a compensator, a number of compensator calculations may be pre-calculated to reduce the complexity of remaining real-time computations and enable compensator calculations to be completed within a single DLVR clock cycle. A DLVR may include a sense filter, and the DLVR transfer function (TF) may be modified using dynamic shaping of open loop gain and pole locations of a sense filter. The DO range associated with the DLVR TF may be changed according to a monitored DO(t) to reduce the sensitivity of a domain VMIN on dropout, which reduces power consumption, increases performance, and enables simplification of test flows.