288 results about "Energy balancing" patented technology

The invention discloses a source network load storage oriented regional collaborative scheduling method and system, and relates to the technical field related to power resource scheduling, and the method comprises the steps: traversing target region source network load storage to carry out real-time data collection, and constructing a source network load storage multi-dimensional data set to carry out multi-scale layered optimization; operation constraint conditions are set, limitation is carried out in combination with a power grid topological structure, a cooperative scheduling instruction set is determined, cooperative control feedback is carried out, and regional power scheduling feedback parameters are generated; and multi-channel dynamic correction is carried out, and a cooperative scheduling optimization strategy is generated to carry out energy balance cooperative scheduling on the source network load storage in the target area. The technical problems that in the prior art, intermittent fluctuation of new energy is difficult to consume, the collaboration of all links of source network load storage is poor, the dispatching flexibility of a power system is insufficient, and the resource configuration efficiency is low are solved. The technical effects of optimizing regional energy resource allocation and improving the clean energy consumption level, the power grid operation stability and the source grid load storage cooperative response capability are achieved.

The invention discloses a steam pipe network decoupling steady-state optimization method and device, a medium and a program product, and relates to the technical field of smart city guarantee. The method comprises the following steps: determining node pressure distribution data and flow distribution data when a mass and momentum balance condition is satisfied according to fluid distribution data of a pipe network simulation model corresponding to a physical structure and an actual working condition of a steam pipe network; and determining node enthalpy data meeting an energy balance condition. Determining a condensation phase change node according to the node pressure distribution data and the node enthalpy data, associating the steam enthalpy of the condensation phase change node to a saturation state under the current pressure, and updating a current fluid distribution parameter according to the determined condensation water volume, and taking the parameters of the pipe network simulation model finally reaching the dynamic balance state as the operation state parameters of the steam pipe network under the target operation condition. The problem that the steam pipe network parameters cannot be accurately determined in the prior art can be solved, and the running state parameters of the steam pipe network can be accurately determined.

The invention discloses a public building cold load short-time prediction method fusing physical information, and the method comprises the steps: collecting and preprocessing the historical cooling capacity, indoor environment, outdoor weather and equipment operation state data of a public building at a fixed time interval, and obtaining multi-dimensional input features; respectively establishing a workday sub-model and a holiday sub-model according to workday and holiday scene division; the workday sub-model and the holiday sub-model jointly form a cold load prediction model, the workday sub-model adopts a long short-term memory (LSTM) network, and the holiday sub-model adopts a light gradient elevator (Light GBM); a physical constraint loss function based on building energy balance and heat conduction residual error is introduced in the training process, and the physical constraint loss is fused into a total loss function according to a weighting coefficient so as to constrain that the output of each sub-model accords with the law of energy conservation and thermal inertia; monitoring the prediction error MAPE in real time and performing online calibration; and outputting a short-time cold load prediction result.

The invention relates to the technical field of power system control, in particular to a direct-current capacitor self-synchronizing grid-connected control strategy method, system, equipment and medium, a direct-current capacitor energy dynamic model is established based on an actual energy balance relation, a direct-current voltage signal is acquired in real time, and a synchronous compensation signal is calculated based on the acquired direct-current voltage signal; performing phase compensation and gain adjustment on the synchronous compensation signal through a correction link based on the calculated synchronous compensation signal, adjusting the internal frequency of the inverter based on the synchronous compensation signal after phase compensation and gain adjustment, controlling the DC voltage through the internal frequency of the inverter, and establishing a self-synchronization control model; and based on the self-synchronization control model, establishing an adaptive control algorithm, generating a damping coefficient and a virtual inertia coefficient through the adaptive control algorithm, and dynamically adjusting control parameters according to the damping coefficient and the virtual inertia coefficient.

The invention discloses an isolated high-voltage direct-hanging energy storage converter and energy balance integrated control method. The method comprises the following steps: S1, acquiring SOC and voltage of each battery cluster in an energy storage converter; s2, establishing a controlled energy channel between the battery clusters, and performing self-balancing transfer on energy between the adjacent battery clusters according to voltage and SOC differences between the battery clusters; s3, selecting an expansion phase shift mode according to the power flow direction between the battery clusters, and selecting a phase shift ratio under the constraint of transmission power to reduce current stress and backflow power; s4, generating a modulation coefficient of a shared bridge arm according to decoupling inductive current inner loop proportion tracking; performing PR current closed loop on the main bridge arm, and generating a switching sequence of each switching tube of the shared bridge arm by adopting unipolar carrier phase-shifting modulation; and S5, outputting the modulation coefficient of the shared bridge arm and the switching sequence of each switching tube, driving the isolated bidirectional DC-DC converter and each H-bridge module to work, and realizing grid-connected energy bidirectional flow and voltage and current index satisfaction.

The invention discloses an enterprise lease-oriented equipment credit evaluation system and method, relates to the technical field of equipment data processing, and aims to synchronously quantify the running temperature, power consumption and heat dissipation state of equipment by forming an original thermal state data set Hraw and avoid one-sided judgment caused by traditional single-parameter monitoring. Based on a thermal state feature set Hset of a temperature stability index Tstb, a power consumption fluctuation spectrum index Pspc and a heat dissipation anomaly integral Qint, a three-dimensional feature space reflecting equipment operation stability and energy balance can be constructed, a thermal state feature template set Htpl is further formed through clustering, and dynamic reference establishment in different operation modes is achieved. And comparing the real-time feature vector with the thermal state feature template set Htpl to calculate a thermal balance index Hc, and generating an equipment credit score Sc in combination with a historical credit mean value score Sh, so that quantitative credit of enterprise equipment use behaviors can be realized.

The invention relates to an industrial park-based comprehensive energy flow direction on-line monitoring system and method, and the system comprises an energy modeling module which is used for representing instrument information, carrying out the modeling of collection labels and collection frequencies of different types of instruments, constructing nodes of different energy layered structures, carrying out the modeling of a directed flow direction relation between the nodes, and carrying out the modeling of the directed flow direction relation between the nodes; binding the logic relationship between the node and the instrument; the data acquisition module is used for performing data acquisition through an instrument, performing edge processing and encrypted transmission through communication equipment, and storing the data in a database; the energy monitoring module is used for monitoring and counting the state of the instrument and monitoring the energy flow direction of the enterprise in real time according to the directed flow direction of the node; and the statistical analysis module is used for providing energy balance analysis for different links of the enterprise energy in the conversion and use process according to the nodes, evaluating the energy consumption loss degrees of the different links, visualizing the nodes with abnormal loss and giving an alarm. Through the real-time and accurate calculation of the energy loss among the nodes at all levels, the backtracking of the nodes with abnormal loss and the timely pushing of the alarm information, the enterprise can timely discover the problems occurring in the energy supply, and can quickly find out the corresponding solution, reduce the energy consumption loss and guarantee the robustness of the energy flow network.

The embodiment of the invention provides a thermal power plant waste heat gradient utilization management method and system, belongs to the field of energy and power engineering, and aims at solving the problems that in the prior art, waste heat gradient matching is unreasonable, the low-temperature waste heat recovery efficiency is low, and the system integration degree is insufficient. The method comprises the following steps: constructing a multi-physics field coupling digital twinborn model and performing real-time correction; establishing a dynamic matching matrix of the residual heat source and the heat consumption load based on balance analysis; solving a Pareto optimal operation scheme through a multi-objective optimization model; and generating and issuing a cooperative control instruction. The system comprises a panoramic data sensing module, a digital twin modeling module, a balance and optimization decision module and a cooperative control instruction generation module. Through global optimization and dynamic regulation and control, the waste heat utilization efficiency, the economical efficiency and the equipment reliability are remarkably improved.

The invention discloses a self-adaptive photovoltaic energy storage comprehensive optimization method and system, and belongs to the technical field of photovoltaic energy storage optimization control. According to the method, a system operation model is established based on historical and real-time operation data of a photovoltaic unit, an energy storage unit and a load side, a hybrid robust-stochastic optimization framework is introduced, a collaborative optimization model with energy balance and system stability as targets is constructed, and an initial control parameter set is solved; in the system operation process, a power fluctuation mode and energy storage response characteristics are identified through a multi-layer agent algorithm, and a dynamic energy storage control instruction is generated and corrected; and according to the cross-cycle change trend of the operation performance index, adaptively adjusting the weight and step length of the control parameter, and realizing strategy evolution and dynamic closed-loop optimization. According to the invention, cooperative operation of photovoltaic and energy storage can be realized under complex operation conditions, and the energy utilization rate and the operation stability are improved.

The invention relates to an anti-reflux control method based on time interval distribution. The method comprises the following steps: acquiring a multi-source fused operation data set; obtaining a trend prediction result set according to the operation data set; according to the trend prediction result set, dividing the prediction time window into a plurality of continuous control time periods, and based on the power generation prediction value, the load prediction value and the uncertainty index of each time period, calculating a corresponding time period countercurrent risk level, and generating a time period risk assessment result; obtaining a time period budget allocation table according to a time period risk assessment result; according to the time period budget distribution table, performing time-division power adjustment on the photovoltaic inverter, the energy storage unit and the controllable load, and realizing smooth transition between adjacent time periods through a cross-time period energy balance mechanism; and monitoring the grid-connected point power and the equipment operation state in real time, and when power deviation or load sudden change is detected, dynamically correcting the current output according to the residual capacity of the time period budget allocation table. According to the invention, the photovoltaic anti-reflux control effect can be improved.

The invention discloses a power control method, system, equipment and medium for a modular multilevel converter, and belongs to the technical field of power electronics and power system application, and the method comprises the steps: collecting the bridge arm current, the sub-module capacitor voltage, the DC bus voltage and the AC side power of the modular multilevel converter; calculating a power error according to the AC side power and a power reference value, and calculating a sub-module capacitor voltage error according to the sub-module capacitor voltage and a voltage reference value; constructing a Lyapunov function comprising a plurality of control targets, wherein the Lyapunov function comprises a power error term, a sub-module capacitor voltage error term, a circulating current suppression term and a total energy balance term; and determining a control law on the basis that the Lyapunov function meets a stability condition, and controlling the modular multilevel converter according to the control law. According to the method, the coupling control problem of multi-terminal direct current system power distribution and sub-module energy balance is considered and improved.

The invention provides a multi-microgrid energy collaborative optimization method and system. The method comprises the following steps: S1, establishing an energy collaborative network topology structure comprising a plurality of microgrid nodes; s2, constructing an energy balance model based on the real-time power demand, the new energy output prediction and the power grid dispatching instruction; s3, taking the minimization of the total operation cost of the multi-microgrid system as a target to form an optimization function; s4, an improved whale optimization algorithm is adopted to solve the optimization function, and an energy scheduling scheme of each microgrid in each time period is obtained; s5, regulating and controlling an energy storage device, a charging pile and an adjustable load in each micro-grid according to the energy scheduling scheme, and coordinating the energy flow direction and the transmission power between the micro-grids; and S6, monitoring the actual operation state and the energy interaction effect of each micro-grid, and when it is detected that the predicted deviation exceeds a preset threshold value, re-executing the steps S2 to S5 based on the real-time data. According to the invention, energy collaboration among multiple microgrids can be realized, the new energy consumption capability is improved, the operation cost is reduced, and the economy and stability of power grid operation are enhanced.

The invention discloses an electric power system resource scheduling method and device, and belongs to the technical field of electric power systems, and the method comprises the steps: obtaining the resource data of an electric power system when the natural climbing amount of the electric power system is not greater than the climbing demand of the electric power system, and taking the minimization of the total operation cost of the electric power system and the maximization of the climbing service demand response as targets; constructing an objective function, a system power balance constraint, a transmission capacity constraint, an energy storage charging and discharging constraint, an energy storage energy balance constraint, a climbing ability constraint and a climbing service demand constraint; and solving the target function under each constraint to obtain the output of each thermal power generating unit and each energy storage system in each scheduling period and the up-climbing demand quantity and the down-climbing demand quantity of each flexible climbing price interval in each scheduling period, and scheduling the resources of the power system according to the solving result. By implementing the invention, the problem that the power supply and demand of the power system are unbalanced when the natural climbing amount is not greater than the climbing demand in the prior art can be solved, and the operation stability of the power system is improved.

The invention discloses a grid-connected control method and system based on a three-port energy router. The grid-connected control system comprises a photovoltaic power generation system, an energy storage system and a grid-connected inverter system, the photovoltaic power generation system adopts a perturbation and observation method and is used for performing photovoltaic maximum power generation; the energy storage system comprises a storage battery, adopts direct current bus voltage stabilization control, and is used for performing peak load shifting of energy and maintaining the direct current bus voltage; the preceding stage of the grid-connected inverter system adopts fuzzy VSG + pre-synchronization control so as to realize grid-connected and off-grid seamless following and provide voltage support; the post-stage of the grid-connected inverter system adopts double closed-loop + optimization compensation control, performs power regulation and control through weighted cooperation with a VSG double closed-loop system, and is responsible for long-term energy balance. According to the invention, photovoltaic maximum power tracking, energy storage charging and discharging coordination and grid-connected and off-grid seamless switching are realized, and the method is suitable for distributed power supply grid connection, a DC micro-grid and a novel power distribution system.

The invention discloses a large-scale cruise ship water chilling unit pipe network cold storage intelligent energy-saving control method based on double-layer deep reinforcement learning, which comprises the following steps: 1, carrying out inherent cold storage engineering modeling on a chilled water pipe network of a water chilling unit to obtain an energy balance relationship between equivalent cold storage capacity and cold release sustainable time of the pipe network and bearable cold capacity; the relationship is used as a physical prior to introduce strategy learning and a security boundary; 2, constructing a double-layer deep reinforcement learning architecture; 3, a safety layer is additionally arranged in the double-layer deep reinforcement learning architecture, the safety layer cuts and projects output feasible regions of a target layer and a sublayer through a hard constraint and barrier mechanism, the water supply temperature, the temperature difference, the start-stop interval, the condensation temperature and the power change rate are ensured, and the maritime affair safety requirement is met; and 4, on the basis of a pipe network inherent cold storage model, a double-layer deep reinforcement learning framework and a safety layer, peak load shifting control of low-load cold charging-high-load cold discharging is achieved, and unit cold energy consumption of the water chilling unit is reduced.

The invention discloses a multi-sensor fusion target scoring system high-precision positioning method, and relates to the technical field of target scoring positioning, and the method comprises the following steps: building a transient interference recognition channel based on the electromagnetic response of a shock wave sensor, obtaining the electromagnetic disturbance of the bullet hit front edge, and generating an interference time sequence; performing delay triggering on the image sensor according to the interference time sequence, and avoiding an interference peak value to form a safe exposure time period; performing charge pre-release on the image acquisition chain before safe exposure; carrying out synchronous compensation on the shock wave signal based on energy distribution of charge pre-release, so that the shock wave signal and image energy response are symmetrical and mutually stable in a time domain; and dynamic shielding control is carried out on a space coupling path between the two types of sensors by utilizing an energy balance region formed in the mutual stable state. Through energy symmetric compensation and dynamic shielding control of shock waves and image signals, time-space separation and synchronous mutual stability of the signals are achieved, and high precision and stability of target scoring positioning under high-energy shooting are ensured.

The invention discloses an optical storage charging-UPQC multi-port cycle calendar life cost collaborative energy management method, and belongs to the technical field of electric energy quality management and optical energy storage collaborative control of a power distribution and utilization system. The invention aims to provide a light storage and charging-UPQC multi-port cycle calendar life cost collaborative energy management method which introduces a photovoltaic flexible power regulation and'cycle + calendar 'combined life modeling mechanism and embeds energy storage life cost into a model predictive control (MPC) framework on the premise that UPQC undertakes power quality compensation. According to the invention, a model predictive control (MPC) framework is adopted to carry out cooperative energy management on photovoltaic flexible output, energy storage power distribution and charging load limit, and when the SOC approaches a boundary, photovoltaic load reduction and power change rate limitation are automatically triggered. According to the method, energy storage deep circulation and excessive loss can be actively inhibited while the energy balance of the direct-current bus is maintained, and the comprehensive targets of electric energy quality treatment, energy stabilization and energy storage life protection are achieved.

The embodiment of the invention discloses a control system of a multi-voltage bus hybrid micro-grid. The control system comprises a control layer and a hardware layer, wherein the medium-voltage direct-current bus is used for being connected with a distributed energy module of which the power is higher than a first set power value; the low-voltage direct-current bus is used for connecting an equipment assembly of which the power is lower than a second set power value, and the equipment assembly at least comprises a direct-current load of which the power is lower than a set value and a data center load; the AC bus is compatible with a traditional power grid and an AC load; the main control layer is used for realizing closed-loop regulation of voltage and current; the auxiliary control layer realizes the consistency of multi-bus voltage and frequency based on state estimation, bus impedance identification and virtual inertia control; and the comprehensive power management layer realizes cross-bus energy balance and power sharing based on a model predictive control and optimal scheduling algorithm. The technical problems that in the prior art, a control layer and a hardware layer of the multi-voltage bus hybrid micro-grid are independent of each other, a cooperative relation is lacked, and the dynamic self-adaptive adjustment type is poor are solved.

The invention discloses an intelligent calibration method and system for the electric quantity of an instrument, and relates to the technical field of electric energy metering of an electric power system.The intelligent calibration method comprises the steps that an electric meter network diagram with a main meter and sub-meters as nodes is constructed, and robust composite correlation indexes are calculated on the basis of reading increments in a sliding time window; the interference of common background load and instantaneous noise is suppressed by using a threshold clipping and main table purification mechanism, so that the depiction capability of the correlation graph on a physical connection relationship is improved fundamentally, and the phase to which the sub-table belongs can be identified more accurately in a stock area with unknown phase or incomplete topology; a graph neural network model is introduced based on the network graph, electric meter embedding representation with physical meaning is obtained through neighborhood information aggregation, phase grouping is achieved in combination with unsupervised clustering, split-phase energy balance loss is designed in the training stage, and the difference between the reading of a main meter and the sum of the reading of sub-meters in each phase group is used as a constraint. Alignment of the embedding space and the energy conservation relation is pushed in a self-supervised mode.

The invention discloses an unmanned aerial vehicle network multipath selection and network coding redundancy transmission method. The method comprises the following steps that each unmanned aerial vehicle carries out node state perception and link prediction; the source node initiates a multi-path routing discovery process based on the extended AOMDV routing protocol, performs path quality measurement, and selects a plurality of paths with the highest path quality as active transmission paths; the source node divides an original data block to be sent into a plurality of original data packets and encodes the original data packets respectively; performing optimal distribution based on a water injection algorithm; data forwarding and decoding receiving are carried out according to an optimal distribution result; and continuously detecting that the link communication actively triggers the maintenance process before the link is actually broken. According to the method, high-reliability, low-delay and energy-balanced data transmission is realized in a highly dynamic unmanned aerial vehicle network through a rigorous evaluation and optimization system, and the overall survival time of the network is effectively prolonged; and predictive route maintenance and fast route switching are carried out through the extended routing table.

The invention provides a three-layer nested IES collaborative optimization method fusing semantic evolution and reinforcement learning, and belongs to the technical field of integrated energy system scheduling, and the method comprises the steps: constructing an IES mathematical model, an energy balance constraint and an optimization target, and abstracting a scheduling task into a Markov decision process MDP quintuple; building an ARDRL model containing a semantic knowledge layer, an evolutionary optimization layer and a distributed evaluation layer, generating a candidate reward function population through a large language model, and quantifying the fitness through Thompson sampling optimization and SAC intelligent agent distributed evaluation; and finally, carrying out iterative optimization by taking the fitness as feedback, and outputting an optimal reward function to guide IES collaborative scheduling. According to the method, a reward function does not need to be designed manually, the robustness and comprehensive performance of a scheduling strategy are improved, and economic, safe and low-carbon multi-target optimal balance is realized.

A multi-port flexible interconnection device for distribution networks, and a control method and system thereof are provided. The multi-port flexible interconnection device includes a bipolar output inverter and a multi-port flexible interconnection module connected in series therewith. The multi-port flexible interconnection module includes multiple unipolar output inverters which share the same common connection bus and are connected in parallel, and AC output ports of each unipolar output inverter are interconnected with different feeders. By adjusting an AC output voltage in series between the feeders, active and reactive power decoupling control for each feeder is achieved. Energy balance for the entire device and its components is maintained by controlling an internal circulating current of the bipolar output inverter. The provided introduces the multi-port flexible interconnection module to interconnect multiple feeders in a distribution network, enabling flexible power interchange between feeders and facilitating a flexible AC distribution network featuring multi-terminal interconnection.

The invention provides a hydrogen-electricity hybrid energy storage capacity optimization method and device applied to an integrated energy system, and belongs to the field of integrated energy configuration optimization. The method provided by the invention comprises the following steps: adopting a self-adaptive time sequence compression algorithm to perform self-adaptive grouping, weighted fusion and iterative updating processing on annual original time sequence data of the integrated energy system, and compressing to obtain representative time sequence data; based on the representative time sequence data, constructing a capacity planning model, and solving to obtain a capacity pre-planning value of the system core equipment; the capacity pre-planning value is substituted into the original time sequence data, the capacity planning model is reused, the hydrogen energy storage capacity is checked and corrected through full-time sequence energy balance simulation, and the final capacity configuration of the system core equipment is obtained; and based on the final capacity configuration, simulating system operation, extracting an electric and thermal power unbalance residual sequence, extracting a residual fluctuation scene and a corresponding probability, respectively constructing independent optimization models of electric energy storage and thermal energy storage, and solving to obtain the optimal capacity of the electric energy storage and the thermal energy storage.

The invention discloses a multi-energy balance margin adaptive regulation and control method and device, and relates to the technical field of quantum computing crossover, and the method comprises the steps: carrying out the optimization of a four-dimensional input matrix through a quantum encoder, executing quantum annealing calculation to generate a ground state solution, integrating an inertia demand increment with the ground state solution through quantum bit entanglement, and carrying out the optimization of a four-dimensional input matrix; calculating a comprehensive inertia gap value, and generating a hierarchical scheduling instruction by adopting a dynamic threshold hierarchical strategy; and according to the hierarchical scheduling instruction, a topology reconstruction instruction is generated through a virtual inertia dynamic algorithm, dynamic monitoring is performed by applying multi-agent collaborative game optimization, and an intelligent regulation and control report is generated. After three-dimensional fault features and space-time dimensions of a multi-energy fluctuation ratio are aligned based on a dynamic time warping-covariance matching method, dynamic fusion is carried out on standard field phase fiber bundles by adopting aged-Simons topology weaving, and self-adaptive regulation and control of a multi-energy balance margin are realized.

The invention relates to the technical field of photovoltaic power generation, in particular to a regional autonomous regulation and control method and system for distributed photovoltaic groups and user side energy storage. The method comprises the following steps: obtaining photovoltaic group output data and user side load data; performing energy balance evaluation according to the photovoltaic group output data and the user side load data to determine a regional energy gap; performing energy storage autonomous adjustment analysis based on the regional energy gap to obtain energy storage autonomous adjustment data; performing peak clipping and valley filling identification based on the energy storage autonomous adjustment data to obtain peak clipping and valley filling data; positioning an energy mutual aid path by using peak clipping and valley filling data; performing power grid stability detection based on the energy mutual aid path to obtain power grid stability data; predicting a critical instability state according to the power grid stability data; and adjusting energy storage parameters according to the critical instability state to obtain energy storage adjustment parameters. Based on the photovoltaic power generation technology, the energy dispatching precision and the power grid operation stability of the regional photovoltaic and energy storage system are improved.

The invention discloses a full-process control method and system for galvanization processing, and relates to the technical field of Internet of Things production control. The invention discloses a full-flow control system for galvanization processing. The full-flow control system comprises a data acquisition module, a micro-flow field observation module, a risk calculation module, a parameter decision module, a comprehensive optimization module and a data positioning module. According to the method, a physical information neural network containing electrochemical constraint and thermal-fluid conservation constraint is introduced into a CFD digital twinborn model, and assimilation is carried out on micro-flow field observation data, so that micro-flow field state and dynamic evolution prediction synchronous with a production line are obtained; on the premise of ensuring mass balance and energy balance, the physical consistency and precision of flow field reconstruction and prediction are improved, and credible flow field state representation is provided for defect risk assessment and control decision based on the micro-flow field.

The invention discloses a partition optimization scheduling control method and system for an energy storage power station, and relates to the technical field of power grid load prediction scheduling, and the method comprises the following steps: constructing a multi-scale dynamic baseline of load data, carrying out the phase calibration of a short-time fluctuation signal and a long-term trend signal under a unified time coordinate, and obtaining a multi-scale dynamic baseline; generating a cross-scale coupling mapping matrix by using a time embedding operator based on a calibration result; and establishing a gradient phase tracking network based on the cross-scale coupling mapping matrix. According to the method, time alignment and self-adaptive correction of short-time fluctuation and long-term trend signals are achieved through a multi-scale dynamic baseline and gradient phase tracking mechanism, weight energy balance is kept, and prediction continuity and accuracy are remarkably improved. Meanwhile, a causal residual error playback chain and time scale self-folding mapping enable the model to have self-correction and self-stabilization capabilities, sub-models can be automatically split during phase resonance, multi-scale response coordination is ensured, and the stability and operation efficiency of power grid load prediction scheduling are improved.

The invention relates to the technical field of scale regulation and control, and discloses a multi-time scale regulation and control method, device and equipment for an optical storage overcharge station, and the method comprises the steps: carrying out the feature analysis of the instantaneous power gradient of the historical load power data of a target optical storage overcharge station, screening out an initial threshold value, carrying out the nonlinear disturbance and constraint of the initial threshold value, and carrying out the nonlinear disturbance and constraint of the initial threshold value; the method comprises the following steps: obtaining a plurality of candidate thresholds, carrying out multi-time scale regulation and control on a target optical storage overcharge station, collecting fast layer trigger response data and slow layer energy balance data in a regulation and control process, constructing a threshold comprehensive evaluation function, calculating regulation and control comprehensive scores of the candidate thresholds, screening out a target load impact response threshold, and carrying out multi-time scale regulation and control on the target optical storage overcharge station. And performing performance analysis on the target optical storage overcharge station to obtain a target regulation and control result. According to the invention, the load impact response threshold can be effectively set, and the regulation and control precision, stability and energy efficiency utilization rate of the optical storage overcharge station in a complex load scene are improved.

An electric power and electric quantity balancing method for a clean energy base containing a high-energy load comprises the steps that firstly, the fluctuation rule of the high-energy load is recognized based on the historical operation condition of the high-energy load, and a high-energy load model is established; secondly, according to the operation mechanism of the clean energy base, establishing an output model for each new energy unit in the base, and predicting the output and load demand of the new energy units in combination with weather forecast and historical data; then, according to the characteristics of a high-energy load and a conventional load, establishing a load management system, introducing a demand response mechanism, constructing a flexible scheduling resource platform considering different time scales by relying on the load management system and an adjustable power supply in a base, and setting priorities and adjusting costs for all adjustable resources in the flexible scheduling resource platform; and different adjustment resources can be reasonably selected in the scheduling process of the power grid. And finally, establishing a high-energy load-containing optimal scheduling model considering electric power and electric quantity balance, and ensuring that the electric power and electric quantity balance on the two sides of the source load can be realized in the scheduling of the power grid on different time scales.