36887 results about "Bus" patented technology

The invention provides a prediction method and system for a rock stratum fracture disaster in tunnel engineering, and belongs to the field of tunnel engineering. Comprising the steps of multi-modal monitoring data acquisition and synchronization, data preprocessing and feature calculation, multi-modal information entropy evolution analysis, catastrophe point detection and precursor identification, risk assessment and early warning output and the like. Multiple types of sensors are arranged at key positions of a tunnel, an edge computing gateway is accessed through an industrial-grade field bus, and space-time reference unification of multi-source heterogeneous data is achieved; carrying out preprocessing and feature calculation on the collected original data; performing sliding window probability distribution modeling on each modal feature, calculating an information theory index, and analyzing non-linear relevance among the multi-modal features; judging whether a catastrophe precursor event exists or not by adopting multiple methods; and finally, based on a catastrophe point detection result, performing risk assessment on the tunnel region by using a multi-dimensional risk quantification model, and performing early warning output on high-risk and emergency states.

The invention relates to the technical field of data processing, in particular to a building light storage and charging integrated energy management system, which is used for solving the problems of data processing delay and resource coordination mismatch caused by insufficient multi-source heterogeneous data fusion in photovoltaic power generation, energy storage and grid connection links. The system comprises a data acquisition module, a protocol conversion module, a data fusion module, a scheduling optimization module, an instruction generation module and a feedback module. The protocol conversion module carries out Modbus, CAN bus and IEC 61850 protocol analysis on the photovoltaic output time sequence data, the energy storage charging and discharging state data and the power grid dispatching instruction to generate standardized data streams. And the safety verification module intercepts the overrun instruction and triggers an amplitude limiting strategy. Through protocol unification, dynamic fusion and closed-loop control, the system realizes improvement of photovoltaic consumption rate, reduction of energy storage circulation loss and optimization of power grid frequency modulation deviation, and significantly improves the efficiency and economy of light storage and charging cooperative operation.

The invention discloses a computing power load stabilizing and energy-saving management system based on a flywheel energy storage system, and belongs to the technical field of energy storage and management, and the system comprises a data collection module which is used for collecting and calculating a real-time current harmonic spectrum of a cluster and server rack vibration data to generate an electric energy quality characteristic spectrum; the prediction modeling module is used for establishing a prediction model output computing power demand dynamic distribution matrix based on multi-dimensional space-time correlation; the optimization control module is used for analyzing a peak load phase in the power demand dynamic distribution matrix to generate a dynamic coordination control strategy; and the power execution module is used for executing the dynamic coordination control strategy to adjust the phase parameter of the reverse electromotive force of the flywheel so as to offset the voltage harmonic component of the server bus. Harmonic phase compensation is realized through dynamic reverse electromotive force modulation, the calculation load prediction precision can be effectively improved, and the energy utilization efficiency and the equipment operation reliability are remarkably improved.

The invention provides a machine room overall electrical scheme configuration method and system for cabinet layout, and relates to the technical field of electrical design, and the method comprises the steps: building a machine room three-dimensional digital model, and carrying out the function partitioning; optimizing the cabinet layout and determining the maximum capacity; constructing an electricity load prediction model; uPS load balancing is carried out by adopting deep reinforcement learning; designing an intelligent bus duct wiring and circuit breaker access scheme; constructing an equipment topological graph and collecting operation parameters; extracting equipment association features based on the graph attention network; and identifying an abnormal power consumption mode and optimizing a regulation and control scheme.

The invention belongs to the technical field of intelligent traffic, and particularly relates to a commuting regular bus operation line intelligent early warning system, which comprises a data acquisition module, a data communication module, a processing analysis module, an early warning output module and a feedback module, and a commuting regular bus operation line intelligent early warning method comprises a risk prediction model training process, the specific process is as follows: step 1, a data preparation stage; 2, a model construction stage; 3, a model training stage; 4, a reinforcement learning optimization stage; 5, a verification and deployment stage; and step 6, a closed loop iteration stage. According to the invention, the limitation of a single data source can be broken through, the early warning precision is improved, and accidents such as sudden traffic congestion, vehicle faults, driver misoperation and dangerous behaviors of passengers can be timely handled; a processing feedback continuous iteration model is combined to adapt to a complex traffic scene; emergency resources are automatically matched based on the early warning level, and the operation loss is reduced.

The invention provides a heterogeneous acceleration pooling server system, a pooling resource allocation method and a medium, and relates to the technical field of computers, the heterogeneous acceleration pooling server system comprises a general computing resource pool, an internal bus switching module, an Ethernet switching module and a plurality of heterogeneous computing acceleration resource pools; the internal bus exchange module comprises a plurality of mutually connected high-speed data interconnection modules, each module is provided with a plurality of IO devices, the IO devices of the plurality of high-speed data interconnection modules overall allocate global unique codes, the general computing resource pool configures the required IO devices according to resource requirements after obtaining the resource requirements, and the required IO devices are distributed to the general computing resource pool according to the resource requirements. And establishing a heterogeneous computing resource allocation path to enable the general computing resource pool to be matched with one or more heterogeneous computing acceleration resource pools corresponding to the resource requirements, so that each general computing power unit can access any heterogeneous acceleration device, the system expansion capability is improved, and the resource utilization rate is improved when large-scale and diversified applications are dealt with. And the operation efficiency of the heterogeneous acceleration server is improved.

The invention relates to the technical field of liquid cooling servers, and discloses a liquid cooling server safety management system and method, and the method employs a multi-mode sensor network to synchronously collect the thermodynamic parameters of a liquid cooling system at 100 Hz, and constructs a three-dimensional thermal field digital twinborn model after the processing of an extended Kalman filtering algorithm. A distributed cooling strategy is designed based on a federated learning framework, and each node locally trains a thermal dynamic prediction model and is optimized by a central aggregator. A dynamic control instruction is generated by using a near-end strategy optimization algorithm, and cooling liquid flow distribution is optimized in combination with a quantum derivative simulated annealing algorithm. And designing a dual-threshold phase change control mechanism, establishing a block chain log to ensure traceability and tamper resistance of the instruction, and realizing closed-loop feedback control through a CAN bus. The system and the method can accurately monitor and intelligently control the liquid cooling system, improve the heat dissipation efficiency, reduce the power consumption, and guarantee the data safety and the system stability.

The invention provides a multilevel caching method and system based on CAN bus communication, and is applied to the field of data transmission. According to the method, the influence coefficient of the CAN bus is obtained by presetting load scenes (idle, low load and high load), whether the influence coefficient is limited by hardware is judged, the optimization direction is ensured to be accurate, data cache management is performed by adopting an annular buffer area, and the data transmission interval is dynamically adjusted and the data packaging strategy is optimized (small data merging, data alignment and filling byte reduction), so that the data transmission efficiency is improved. The CAN ID priority is dynamically adjusted by collecting communication data category information, it is ensured that high-priority data (such as ECU control signals) are transmitted in time, bandwidth occupation of low-priority data is reduced, in addition, the processing response speed of data frames is monitored, and if the processing response speed does not reach the standard, the data sending frequency is optimized, and the real-time performance is improved.

Certain examples described herein relate to at least a cryptographic system and a method of operating a cryptographic system. The cryptographic system may be implemented as a co-processor for performing post-quantum cryptographic functions. The cryptographic system has a set of bus interfaces for coupling to an external computing system, a cryptographic math unit and a control unit. The cryptographic math unit in certain examples is adapted to provide one or more masked modes of operation that secure the cryptographic operations against side-channel and non-invasive attacks. The method of operating a cryptographic system involves annotating secret data and tracking those annotations through one or more arithmetic operations.

The invention provides a public transportation network toughness evaluation method considering subway passenger evacuation and station failure propagation, and the evaluation method is used for an urban public transportation composite network, and comprises the steps: firstly obtaining urban public transportation network station map data, passenger flow OD data and vehicle operation related information; then, an urban bus composite network considering the one-to-many coupling relation between subway stations and conventional bus stations is constructed through a Space L method, and meanwhile, composite network performance indexes considering the structure and operation performance are defined in the propagation process of station cascade failure by considering the re-decision of the travel mode of blocked passengers in the urban bus composite network under sudden interruption; based on the network performance curve, the urban bus composite network toughness evaluation model is constructed to measure the toughness level of the urban bus composite network under sudden interruption; according to the method, the toughness of the urban bus composite network can be accurately evaluated, and the operation stability and safety of a bus system are improved.

The invention provides a BIM intelligent management platform oriented to a whole life cycle of project construction. A building information model, Internet of Things sensing data and a block chain evidence storage mechanism are integrated through a multi-source data fusion technology, and a whole-process data chain of association planning, design, construction, operation and maintenance is associated. The platform adopts space optimization Huffman coding to realize model lightweight, combines a constraint genetic algorithm to optimize a construction path, and applies a bidirectional long-short-term memory network to analyze an equipment state. A three-chain block chain system is reconstructed on the architecture, intelligent association of engineering quantity and payment nodes is realized through cooperation of a main chain, a calculation quantity side chain and an auditing side chain, and mobile terminal offline interaction is supported based on a digital-analog separation technology. The platform covers an intelligent design management unit, a block chain investment management unit, a dynamic correction management unit, a quality safety responsibility tracing unit, an NLP risk management unit and a digital twin operation and maintenance unit. The units achieve cross-system cooperation through a unified data bus, and a closed-loop management architecture covering the whole life cycle of project construction is formed.

The invention relates to a network real-time synchronization communication system, and relates to the technical field of computer network communication. The system comprises four core modules: a hardware optical IO synchronization module which integrates a multi-wavelength optical transceiver array and an anti-jitter circuit and provides a nanosecond global clock signal, and the synchronization precision is less than or equal to 15ns; the time sequence arrangement module is used for dividing a fixed time window and a dynamic buffer window based on a time sensitive network, supporting a priority preemption mechanism of the SRIO bus and realizing deterministic data transmission; the distributed RTDATA nodes replace a traditional single-board computer, a heterogeneous computing unit and an intelligent storage controller are integrated, and protocol stack processing delay is reduced through the zero copy technology; according to the dynamic multicast routing system, a safely isolated multicast tree is constructed as required, and link load distribution is optimized in combination with machine learning. Through collaborative design of hardware optical synchronization and dynamic data arrangement, the problem of real-time performance reduction caused by multi-node communication concurrence is solved.

Aspects of this disclosure relate to an acoustic wave resonator with a patterned conductive layer. The acoustic wave resonator can include a piezoelectric layer, an interdigital transducer electrode over the piezoelectric layer, and a temperature compensation layer over the interdigital transducer electrode. The interdigital transducer electrode can include a bus bar and fingers extending from the bus bar. The fingers can each include an edge portion and a body portion. The patterned conductive layer can overlap the edge portions of the fingers. The patterned conductive layer can conductive portions that are spaced apart from each other. A portion of the temperature compensation layer can be positioned between the patterned conductive layer and the interdigital transducer electrode.

The invention discloses a back contact electrode structure, a back contact solar cell and a photovoltaic module, and belongs to the technical field of solar cells. The electrode structure comprises current collection electrodes, current collection electrodes, current collection points and current collection areas, the current collection electrodes extend in the first direction, and the current collection electrodes with different polarities are alternately designed at intervals in the second direction; the bus electrodes are distributed on the two sides of the battery substrate in the second direction, the bus electrodes with the same polarity are distributed on one side of the edge of the battery substrate, the bus electrodes with the other polarity are distributed on the other side of the edge of the battery substrate, and the bus electrodes with different polarities are distributed in an array mode in the first direction and are coupled with the part, extending in the first direction, of the collector electrodes with the same polarity; the collector electrodes at least partially extending in the first direction have a segmented design, and the length of the collector electrodes on the two sides of the battery substrate in the first direction is W1lt; and the other collector electrodes are W2 in length.

A diagnostic system and method for identifying and resolving vehicle Controller Area Network (CAN) bus faults is disclosed. The system connects to a vehicle's data link connector (DLC) and automatically retrieves diagnostic trouble codes (DTCs) from multiple electronic control units (ECUs). It filters the DTCs to identify those related to CAN communication errors, groups repeated DTCs across ECUs to highlight systemic faults, and assigns repair priority based on status, scope, and criticality. A user interface displays prioritized DTCs with definitions, affected systems, possible causes, and repair guidance. Upon technician input, the system re-scans the network to confirm resolution and updates the display accordingly. The invention supports semantic and conceptual recognition of communication faults, enabling robust, language-agnostic analysis. This system reduces diagnostic time, improves repair accuracy, and supports multilingual or manufacturer-specific DTC definitions without requiring external infrastructure or advanced user expertise.

The invention discloses a server equipment location positioning method and device, a server and a medium, and relates to the technical field of server configuration. The method is applied to a server board card, and comprises the following steps: acquiring field replaceable unit information on external equipment to obtain corresponding silk-screen information lists when slots on the external equipment are connected with different channels of a switch, and determining case silk-screen positions of the slots on the equipment according to the silk-screen information lists; determining a communication bus interface correspondingly connected with each slot on the external equipment from a preset corresponding relation list according to connector identification information transmitted by the mainboard through the connector; equipment information of a processing device on a mainboard is obtained through in-band scanning, and then entity information of server equipment under current configuration is constructed by utilizing the equipment information, information of a case silk-screen position and information of a communication bus interface so as to position the server equipment. Through the technical scheme of the invention, various server configurations are compatible, and the server equipment can be automatically identified and positioned.

The invention discloses a storage battery capacity checking method for a parallel intelligent direct-current power supply system, and relates to the technical field of storage battery capacity checking, which comprises the following steps of: respectively deploying electromagnetic sensing modules with nanosecond-level response capability at a master control end and a slave node end of a communication bus, acquiring voltage disturbance waveform signals of the communication bus in an operation process, and performing feature extraction operation on the transient high-frequency interference pulse detected each time, and constructing a multi-dimensional feature sequence of the high-energy transient electromagnetic interference. By deploying the high-response electromagnetic sensing module and combining an active suppression mechanism of interference feature extraction and risk index driving, time alignment modeling and self-adaptive regulation and control of electromagnetic interference and communication performance are realized, the communication stability, the battery state recognition accuracy and the capacity accounting continuity of the system in a strong interference environment are effectively improved, and the system reliability is improved. And the anti-interference capability and the operation safety of the parallel direct-current power supply system are obviously enhanced.

A high-impedance fault positioning method and system based on synchronous Lissajous curve characteristics are provided. The method includes: acquiring a bus zero-sequence differential voltage and a feeder zero-sequence current of a faulty line; constructing a first Lissajous curve in a characteristic frequency band range based on the bus zero-sequence differential voltage and the feeder zero-sequence current; when the proportion of the faulty line is less than a set threshold value and the slope of the first Lissajous curve is negative, determining that high-impedance faults have occurred in the faulty line; constructing a second Lissajous curve based on the bus zero-sequence differential voltage and the section zero-sequence current, performing linear fitting on discrete data points of the second Lissajous curve to obtain a fitted curve; and when the slope of the fitted curve is negative for at least three consecutive periods, determining that high-impedance faults have occurred in the section.

The invention discloses an automatic identification and expansion communication method based on an RS485 interface, and relates to the technical field of industrial automation communication. The problems that an existing RS485 interface is complex in configuration, poor in protocol compatibility and high in data transmission delay are solved. According to the scheme, the terminal matched resistance and the bias current are adjusted in real time by dynamically measuring the bus equivalent distributed capacitance value, and signal attenuation caused by the capacitance effect is inhibited; a silicon controlled rectifier trigger type charge discharge mechanism is adopted to force bus residual charge to return to zero quickly, and an idle state is accurately judged in combination with a hysteresis comparator; dynamically compensating signal edge distortion and calibrating a sampling window time sequence based on a pre-emphasis filtering and Kalman filtering algorithm; multi-node stable communication is realized through capacitance value driven conflict detection threshold adaptive adjustment and a Poisson back-off model; according to the invention, the real-time performance, the anti-interference capability and the multi-node expansion reliability of RS485 communication in a complex industrial scene are obviously improved, and the debugging and maintenance cost of the system is reduced at the same time.

The invention discloses an IT asset fault propagation prediction method and system based on dynamic evolution of a knowledge graph, and relates to the technical field of cloud computing and large-scale IT operation and maintenance management. Through an asynchronous message bus and a logic clock, the knowledge graph is updated immediately when resources are abnormal and a scheduling event occurs; the knowledge graph uniformly integrates physical connection, logic dependence and multi-copy redundancy, so that the cross-machine-room asset relationship is clear at a glance. And then, based on a weighted logistic regression model, node features and relation weights in the knowledge graph are fused, the node fault probability is accurately calculated, the limitation of traditional single-dimensional analysis is solved, self-healing operation is supported, end-to-end intelligent operation and maintenance from fault detection to prediction and early warning to closed-loop self-healing are realized, and the fault detection efficiency is improved. The problems that in a cross-machine-room and multi-live-site environment, resource topology is split, real-time state and alarm information cannot be fused with an asset dependence model, and large-scale real-time deployment of a traditional single-dimensional fault analysis and high-complexity prediction algorithm is difficult are effectively solved.

The invention discloses a dynamic control method of a lithium battery module intelligent equalization management system, and relates to the field of lithium battery module equalization, and the method comprises the steps: constructing a hierarchical data fusion platform, and generating a battery state data set containing SOC, SOH and an inconsistency evaluation value; a credibility reasoning algorithm is adopted to calculate a single body imbalance credibility factor value to divide an equalization stage, and equalization current is dynamically adjusted; a charge and discharge curve health factor is extracted through an LAB health factor algorithm, SOH is updated online in combination with extended Kalman filtering, and an SOH attenuation rate is fed back to the battery model; in-module equalization is carried out through a bidirectional energy transfer circuit, inter-module equalization is carried out through a ring bus topology, and layered topology linkage control is formed. The method has the advantages that the consistency and the heat management efficiency of the battery pack are improved through the hybrid equalization strategy and the layered topology linkage control, the service life of the battery pack is prolonged, and the overall performance and the safety of the electric vehicle are improved.

The invention relates to a full-automatic injection molding optimization method, device and equipment based on digital twinning, and belongs to the technical field of intelligent manufacturing equipment. Inputting the sensor data into a digital twin model to construct equipment dynamic response simulation, and synchronously comparing the actual mode locking force with the offset of a preset pressure threshold; generating compensation data of mold locking pressure according to the offset, and dynamically correcting an acceleration curve of a servo motor in a glue injection stage on the basis of the displacement of a screw rod; in hot runner control, a thermal interference compensation coefficient is calculated according to a temperature difference value of adjacent temperature zones, and an output power gradient signal of each heating ring is adjusted; the corrected parameter information is transmitted to an equipment PLC through an industrial bus to execute control, and a compensation coefficient threshold value is iteratively updated according to a product weight fluctuation value in the next forming period; closed-loop data interaction of an equipment control system is achieved, and the injection molding process is optimized.

The invention relates to the technical field of task scheduling, and discloses a distributed task scheduling method, device and equipment for OpenHarmony Internet of Things equipment, and the method comprises the steps: carrying out the hardware parameter collection and equipment classification of the Internet of Things equipment in an OpenHarmony distributed network, and obtaining an equipment capability data set; performing task analysis and dependency analysis on the application program to obtain a task directed acyclic graph; carrying out calculation and resource allocation prediction on the equipment load to obtain an equipment resource reservation table; constructing a nonlinear optimization model, and solving to obtain an initial task allocation scheme; performing two-stage distributed reinforcement learning optimization to obtain a target task scheduling scheme; the target task scheduling scheme is deployed to the Internet of Things equipment, data collection and performance evaluation are carried out, and a performance evaluation data set is obtained.The efficient communication and cooperative computing between the equipment are achieved based on the distributed soft bus, the overhead of task migration and data transmission is reduced, and the overall performance of the system is improved.

The invention provides an intelligent network connection automobile abnormity detection system and method based on big data analysis, and the method comprises the steps: obtaining metadata in the communication between a vehicle CAN bus and a cloud, the metadata comprising a protocol type and a load feature, carrying out the analysis of the load feature according to the protocol type, and extracting a key field of a data package; constructing a load feature matrix according to the key field, and normalizing the heterogeneous data to obtain a feature data set in a uniform format; a mahalanobis distance algorithm is adopted to calculate the distance between each data point in the feature data set and a preset base line, and if the distance exceeds a preset threshold value, abnormal traffic is judged, and an abnormal traffic mark list is generated; fingerprint features of a transmission link are obtained from the 5G network slices, the fingerprint features of different slices are subjected to standardization processing, and a cross-slice consistent fingerprint feature data set is generated; therefore, security threats in a complex Internet of Vehicles environment can be effectively handled, and the accuracy and reliability of abnormal traffic detection are improved.

Power flow in a power distribution system is controlled using control commands generated based on values of system parameters. In this regard, generation prediction data, load prediction data, and real-time device status of equipment are utilized to generate scheduling data for power generation and power consumption and a network topology of the system is also obtained. The values of the system parameters are generated as an outcome of an unbalanced load flow analysis of the power distribution system using the scheduling data and the network topology. The unbalanced load flow analysis utilizes a compact multi-bus based nodal admittance model to represent relationships between nodal injected currents and nodal voltages at a plurality of non-overlapped phases of buses for a section formed by zero impedance branch connected with impedance branches in the power distribution system.

The present invention discloses a bus route optimization design method and system based on resident travel big data, the method comprising the steps of: obtaining mobile phone signaling data of residents in a target area; obtaining the stop points of residents' travel trajectories; dividing the target area into a number of traffic areas; obtaining an OD matrix based on the stop points of residents' travel trajectories and traffic areas; constructing a bus route planning model; generating a number of bus alternative routes based on a shortest path algorithm; obtaining a target bus route from the alternative routes based on a genetic algorithm and in combination with an objective function and an OD matrix. Compared with the prior art, the present invention not only innovatively combines spatiotemporal big data and genetic algorithms in technical means, improving the accuracy and efficiency of bus route planning, but also demonstrates strong advantages in system architecture and data processing capabilities, and can provide a more scientific, dynamic and sophisticated optimization solution for the urban public transportation system, contributing to the efficient operation of urban transportation and the construction of smart cities.

The invention provides a big-data-combined bus system full-data comprehensive management analysis method and system, and the method comprises the steps: collecting a real-time operation data set uploaded by a plurality of bus terminals in a target region, carrying out the multi-dimensional feature extraction, generating a bus operation feature set, carrying out the abnormality recognition based on a preset abnormality detection model, and obtaining a bus operation feature set; determining an abnormal operation event set; performing time-space association mapping on the bus operation feature set and the historical operation data set, constructing a bus operation knowledge graph, performing dynamic path planning and resource allocation analysis on the graph, generating a target scheduling strategy set, and performing priority adjustment on the abnormal operation event set based on the target scheduling strategy set. Generating a bus scheduling optimization instruction set and issuing the bus scheduling optimization instruction set to a corresponding bus terminal; and updating a weight parameter and a historical operation data set of the multi-task optimization model based on the execution feedback data. According to the method, multi-source real-time data can be integrated, and a scheduling strategy is dynamically optimized, so that the problems of data islands and strategy stiffness are solved.

The invention discloses a photovoltaic module and a photovoltaic module preparation method, the photovoltaic module comprises a battery piece, a welding strip, a bus bar and an insulating block, and the back surface of the battery piece is provided with a fine gate electrode and a first insulating layer; the first welding strip is electrically connected with the fine gate electrode with the first polarity, and the second welding strip is electrically connected with the fine gate electrode with the second polarity; the insulating blocks are located on the back face of the battery piece, the insulating blocks and the first insulating layers are alternately arranged in the extending direction of the fine gate electrodes, and the insulating blocks cover part of the fine gate electrodes of the second polarity and part of the second welding strip; the first insulating layer covers part of the fine gate electrode with the second polarity; the bus bar is located in the area, corresponding to the first insulating layer and the insulating block, of the back face of the battery piece, the bus bar extends in the length direction of the fine grid electrode, the bus bar is electrically connected with the first welding strip, and the bus bar is electrically isolated from the second welding strip through the insulating block; and the bus bar is electrically isolated from the fine gate electrode with the second polarity through the insulating blocks and the first insulating layers which are alternately arranged.

The invention discloses a tough city resource allocation method and system based on a block chain and edge computing, and relates to the technical field of city resource allocation, a federal protocol is utilized to exchange and shear a gradient abstract synchronization model version, then a prediction abstract containing fingerprints is written into a permission chain, and a time sequence is solidified through Byzantine consensus; an on-chain smart contract executes adaptive threshold evaluation based on sliding window prediction to generate a deployment intention with a verifiable path, the intention is sent to an execution subsystem through a side chain message bus in a low-delay mode, and cross-department resource rearrangement is completed through rolling optimization of an adaptive decision driver; an execution receipt is mapped into an incremental patch and written back to a local state tensor, a node trust weight is dynamically adjusted, and when the coverage degree and the weight rising range meet a triggering strategy, differential shearing training is started, and a new structure fingerprint and a model signature are generated; and efficient, credible and dynamic allocation and sustainable learning synchronous evolution of urban public resources in an emergency scene can be ensured.

The invention discloses an operation collaborative optimization method for an optical storage direct current flexible interaction system. Comprising the steps of collecting operation data such as photovoltaic output, an energy storage state, household load power and direct current bus transmission power, fusing power market price information, and constructing a multi-dimensional time series data set; then, predicting an adjustable load capacity interval of the system based on a coupled physical constraint neural network model embedded with DC bus power balance, voltage constraint and equipment operation limitation; further constructing a state-action space, solving a Pareto frontier by adopting a multi-objective optimization algorithm, and generating a light storage and home load collaborative scheduling strategy set; then combining the real-time operation state and the prediction deviation information, applying a voltage-power droop control mechanism to carry out strategy decoupling, and generating an energy storage power correction amount and a flexible load priority control instruction; and finally, a control instruction is issued to the optical storage direct flexible system, so that collaborative optimization operation with consideration of economical efficiency, safety and comfort of the system is realized.