79 results about "Group scheduling" patented technology

The invention provides a foaming machine group production scheduling method under multi-target constraint. The method comprises the following steps: S1, initializing resource and task data; s2, generating an initial production scheduling scheme; s3, carrying out feasibility check and conflict repair; s4, multi-algorithm fusion optimization is carried out; s5, making a decision and outputting a production scheduling scheme; s6, online rearrangement and exception handling are carried out; and S7, monitoring and data feedback are executed. Through the full-process design of data-initial scheme-feasible scheme-optimization scheme-execution-feedback, the problems of many resource conflicts, difficult target balance, poor dynamic adaptation and the like in traditional production scheduling are solved, and efficient and intelligent production scheduling of the foaming machine group is realized.

The invention relates to the technical field of water resource scheduling, in particular to a refined multi-dimensional collaborative scheduling optimization method and system for a cascade reservoir group. According to the method and the system, macroscopic prediction and real-time dynamic correction are combined, an intelligent gate actuator with local autonomous adjustment and fault processing capabilities is introduced, sensing, decision making, execution and feedback capabilities are dispersed to each gate unit, and a distributed intelligent scheduling architecture combining global collaborative optimization and local intelligent strain is formed. The invention provides a refined multi-dimensional collaborative scheduling optimization method and system for a cascade reservoir group, so as to solve or at least alleviate the problems of signal transmission lag, execution blind areas, insufficient system toughness and the like caused by centralized control in the existing cascade reservoir group scheduling method. Finer water volume scheduling, quicker emergency management and higher system operation reliability are realized, and the scheduling efficiency and the disaster prevention capability are improved.

The invention discloses a thread group scheduling method and device for a GPU (Graphics Processing Unit), the GPU and equipment. The method comprises the following steps of: 1) receiving a scheduling request of a thread group; 2) task type priority scheduling; according to a thread group weight value set by a user, obtaining execution priorities of the vertex thread group and the fragment thread group in the current scheduling period; 3) instruction type priority scheduling; pre-analyzing to-be-executed instructions of the thread group, and determining a priority sequence of schedulable instruction types; and 4) priority scheduling of the thread groups: selecting the thread group with the highest priority for scheduling according to the specified task type priority and instruction type priority in combination with the thread group generation time. The invention provides a thread group three-level scheduling strategy so as to improve the instruction throughput rate and the key task response speed of the GPU under the complex load.

The invention discloses a micro-grid group scheduling method and system based on hierarchical regulation and elastic load response, and belongs to the technical field of power system collaborative optimization and energy transaction, and the method comprises the steps: obtaining the power generation potential of a power generation side and the power utilization regulation potential of a demand side based on the operation constraint of the power generation side and the response constraint of the demand side; constructing a micro-grid group layered interactive coupling model based on the execution rule and the information interaction constraint; constructing a marketization transaction strategy model based on the transaction mode, the bidding mechanism and the income distribution mechanism; improving the particle swarm algorithm through model prediction control to obtain an optimized particle swarm algorithm; and based on the power generation of the power generation side, the power utilization regulation potential of the demand side, the micro-grid group interactive coupling model and the marketization transaction strategy model, obtaining an optimal scheduling scheme by using an optimized particle swarm algorithm. The technical problem that the feasibility of a scheduling scheme is difficult to improve in the prior art is solved.

The invention discloses a QMIX framework-based sluice group scheduling method. The method comprises the following steps of: constructing a simulation basin environment by utilizing a historical environment data set; constructing a multi-agent reinforcement learning method for cooperative sluices in the watershed based on a QMIX framework to realize dynamic cooperation and global optimization of the sluices in the watershed; designing a reinforcement learning single-agent DQN model of a single sluice, and supporting autonomous perception and decision of the single sluice; designing a multi-agent global reward function and a single-agent independent reward function, and balancing a group collaboration target and individual local requirements through a layered reward mechanism; a mixed experience playback mechanism based on high-priority experience similarity matching is introduced, and the problems that a traditional experience playback method is low in sample utilization efficiency and weak in key event generalization ability in a complex dynamic environment are solved. According to the method, the water gate intelligent agent can fully explore the scheduling action space in the compliance framework, and the robustness and the control accuracy of the water gate scheduling strategy under the QMIX framework are improved.

The invention discloses a group scheduling control method and system for a PCS energy storage system, relates to the technical field of group scheduling of energy storage systems, and solves the technical problems of insufficient SOC balance regulation and control accuracy and weak capacity proportion distribution fault-tolerant capability. The SOH correction coefficient is accurately calculated through the linear relation, it is ensured that the PCS with the high health degree and the large capacity preferentially undertakes the balancing task, the weak health battery is effectively protected, the cycle life of the battery is prolonged, multiple screening constraints of the available PCS are defined, and according to the size relation between the exceeding power and the total redundant power, a capacity proportion or redundant power proportion distribution strategy is adopted, so that the capacity of the PCS is effectively protected. Reasonable power distribution and no equipment overload risk are ensured, the power distribution deviation after the fault of a single PCS can be reduced, and the fault-tolerant response speed of the system is improved.

The embodiment of the invention provides a reservoir group multi-target scheduling method and system fusing an SHAP interpretability analysis mechanism. The method comprises the following steps: carrying out training data integration based on obtained historical operation data of a target basin reservoir group, carrying out reservoir group scheduling model training based on a DNN network structure, and carrying out multi-target iterative optimization on model structure parameters to obtain an optimal parameter set meeting multi-decision preference; based on the optimal parameter set, through an SHAP interpretability analysis mechanism, calculating to obtain a factor contribution matrix of each model input factor vector relative to model prediction output; performing statistical feature extraction based on the factor contribution matrix of each model input factor vector to obtain a corresponding factor feature vector; and performing rule mining based on the factor feature vector, and performing rule optimization based on weight and explanatory evaluation to obtain a structured scheduling rule set for real-time scheduling aided decision making. The implementation of the method can provide more explanatory decision support for multi-target scheduling of the reservoir group.

The invention discloses a distributed energy consumption optimization scheduling method and system for a heat pump group, and relates to the technical field of heat pump energy consumption optimization scheduling, and the method comprises the steps: dividing the heat pump group into a plurality of sub-regions, determining the optimal combination of heat pumps in each sub-region, and forming local optimization units of the sub-regions; collecting state data of each heat pump in each local optimization unit in real time, and generating a scheduling strategy of the heat pumps in the sub-regions by using a multi-target local optimization algorithm; establishing a cross-subarea information exchange and coordination mechanism, carrying out global optimization and dynamic correction on a scheduling strategy, and generating a final heat pump group scheduling scheme; and issuing the final heat pump group scheduling scheme to each local optimization unit, and adjusting the local optimization units based on real-time feedback to form a closed-loop iterative optimization mechanism. According to the method, distributed partition optimization is combined with cross-regional coordination and global dynamic correction, so that the problems of high calculation complexity, poor real-time performance and insufficient inter-regional energy utilization of centralized scheduling are solved.

The application provides a kind of multi-microgrid collaborative economic dispatching method based on blockchain, comprising: based on microgrid group multi-group architecture model, construct microgrid group dispatching architecture model based on blockchain;Based on objective function submodel, constraint condition submodel and incremental cost submodel, an economic dispatching model is constructed;Wherein, economic dispatching model includes: microgrid layer economic dispatching model and microgrid group layer economic dispatching model;Based on microgrid group dispatching architecture model, intra-group scheduling is carried out on microgrid layer economic dispatching model, and inter-group scheduling is carried out on microgrid group layer economic dispatching model, to obtain multi-microgrid collaborative economic dispatching result.The application constructs microgrid group system distributed dispatching architecture, designs system economic dispatching model with comprehensive economic and environmental protection targets, and proposes a kind of intra-group optimization and inter-group optimization economic dispatching method based on blockchain.In the case of ensuring good expansibility, the economic efficiency and fault tolerance of microgrid group are improved.

The application discloses a multi-service traffic grouping scheduling method for a P4 switch processor core, mainly comprising a feature extraction method based on a statistical interval and a Sketch, comprehensive data packet time correlation and traffic dynamic change, an optimized Bloom filter conflict detection mechanism, improved adaptability and accuracy of the algorithm in a limited resource environment; a decision tree model is combined with scheduling, a decision tree is reconstructed to adapt to a P4 switch operation mode and data processing demand, high-precision service flow classification under line-speed operation is ensured; a grouping scheduling method AD-PIFO is designed based on variable priority, data packet forwarding priority is dynamically adjusted, different service QoS demand is met, and the overall performance and efficiency of the switch are improved. The method is outstanding in high-priority traffic throughput and low-latency performance, and the medium-low-priority traffic throughput is better than that of similar algorithms, is stable and effective under different load conditions, has reasonable additional time overhead of data packet transmission, and is widely used in SDN network optimization data packet scheduling scenes.

The application discloses a kind of cascade reservoir group scheduling method and system for clean energy consumption, first, obtain the long sequence of the relative error of clean energy each period output and its mean, variance, according to which the output scene set is generated by using clean energy prediction output;Second, a large-scale scene set is reduced to several typical output scenes using clustering algorithm, and then the photovoltaic output process and its occurrence probability of different scenes are obtained;Finally, construct the applicable cascade reservoir group joint scheduling model, and then solve to obtain reasonable and feasible scheduling scheme using efficient optimization algorithm.The method disclosed by the application can quickly respond to the randomness and uncertainty characteristics of the clean energy output process, effectively handle the coupling operation constraints of cascade power stations, significantly improve the model calculation efficiency and scheduling scheme quality, and is suitable for the cascade reservoir group joint scheduling problem for clean energy consumption.

The embodiment of the invention provides a scheduling method of a working group, a graphics processor and electronic equipment, the scheduling method of the working group is applied to an arbitration module of the graphics processor, the graphics processor further comprises at least two execution modules, and the scheduling method comprises the following steps: aiming at each execution module, executing the execution modules; determining a first score of the execution module based on the resource request of the working group and the residual resource information of the execution module; under the condition that the first score of each execution module is smaller than a first score threshold value, a target execution module is determined from the at least two execution modules based on the first waiting duration of each execution module, and the first waiting duration of the execution module is the duration needed by the prediction execution module to release the target resource information; the target resource information is determined based on the resource request of the working group and the residual resource information of the execution module; and scheduling the working group to the target execution module.

The application provides a pump station group scheduling system and method based on digital twinning, and relates to the technical field of pump station scheduling.The pump station group digital twinning model is constructed according to the bearing temperature curve, the flow curve and the pump cabin pressure curve when the rated power works in history, the solving condition I, the solving condition II and the solving condition III are set according to the task quantity and the task time, the scheduling quantity that each pump station should obtain is solved in MATLAB, the scheduling quantity is simulated in the pump station group digital twinning model, the simulated running state is obtained, the running state score is constructed, the health state score is constructed according to the data of the pump station, the ability of each pump station to complete the task is judged by analyzing the order of the running state score and the health state score, if there is a situation that cannot be completed, the scheduling quantity is redistributed, the failure caused by the overload operation of the pump station is avoided, and the smooth progress of the scheduling task is ensured.

Embodiments of the present disclosure disclose a virtual cluster-based crowd scheduling system and device. A specific implementation of the system includes: a trace synchronization module that automatically identifies a load object created by a user in a virtual cluster, synchronizes task annotation metadata corresponding to the load object to a corresponding execution unit in a host cluster, and writes address annotation metadata corresponding to the load object in the execution unit; a scheduling module that reads task annotation metadata of each execution unit, generates a scheduling score value corresponding to each execution unit in each execution unit according to the read task annotation metadata set, and batches each execution unit to a corresponding resource adaptation node, the scheduling module being deployed in the host cluster; and a billing module configured to generate a task billing sheet. The implementation improves the versatility and resource utilization efficiency of the system.

The embodiment of the invention provides a causal relationship-based reservoir group multi-objective optimization scheduling method and system. The method comprises the steps of determining a multi-source decision factor stationary time sequence involved in reservoir group scheduling; scheduling-driven causal correlation analysis is carried out based on the multi-source decision factor stationary time sequence, and a scheduling causal network atlas is constructed based on an analysis result; based on the scheduling causal network map, through quantitative analysis of the hysteresis effect and causal intensity of each potential path, after path logic rationality verification, an effective driving path set is obtained; based on the effective driving path set, constructing a reservoir group scheduling mapping model; a multi-objective optimization algorithm is adopted to collaboratively optimize structural parameters of the model and input causal driving factors, so that good scheduling benefits and causal consistency can be generated during subsequent reservoir group scheduling planning based on the model. The implementation of the scheme can improve the scientificity and interpretability of scheduling.

The invention discloses a scheduling method and system for a micro-grid group, and the method is applied to a target micro-grid group at least comprising a plurality of sub-micro-grids, and the method comprises the steps: obtaining a day-ahead global scheduling scheme of the target micro-grid group; in the process of executing the day-ahead global scheduling scheme, analyzing the operation fluctuation signal to determine the scheduling demand of the first sub-microgrid; determining the operation tension degree of the second sub-micro-grid in a non-fluctuation state; based on the network topology of the target micro-grid group, analyzing the electrical coupling relationship between the first sub-micro-grid and the second sub-micro-grid, and screening according to an analysis result to obtain an effective second sub-micro-grid; preferentially scheduling the effective second sub-micro-grid based on the scheduling demand and the operation tension degree, and determining a scheduling scheme; and adjusting the power output of each second sub-microgrid in the target microgrid group at least according to the scheduling scheme. According to the micro-grid group scheduling method and system provided by the invention, the operation efficiency of the micro-grid group is effectively improved.

The invention relates to the technical field of water conservancy projects. By providing the digital twinborn basin reservoir group scheduling method and system, the method comprises the following steps: constructing a real-time mirror image digital twinborn platform of a physical basin by fusing an Internet of Things sensing network, a hydrological and hydrodynamic model and a historical operation database; establishing a multi-dimensional value evaluation index system including flood control benefit, power generation benefit, water supply guarantee and ecological maintenance; according to the multi-dimensional value evaluation index system, collecting cost input and benefit output data of each scheduling subject through a preset digital platform to obtain a multi-subject value data set; calculating the benefit distribution proportion of each main body under different scheduling schemes through a value distribution algorithm; generating a candidate scheduling scheme set through a benefit distribution proportion, flood control safety constraints and ecological flow constraints; and performing simulation evaluation on the candidate scheduling scheme set, and outputting a final scheduling scheme so as to improve the execution fluency of the multi-agent cooperative scheduling scheme.

The present application relates to the technical field of emergency management. Specifically relates to a kind of wisdom emergency management method, device and medium, its method includes: obtaining emergency alarm information, monitoring center is based on emergency dispatch time datum synchronous acquisition monitoring information and on-site audio and video information corresponding to emergency alarm information, and monitoring information and audio and video information are fused and calculated, generate event credibility weight, when event credibility weight exceeds preset credibility weight threshold, group scheduling instruction is issued to emergency communication terminal and emergency monitoring terminal, in the process of group scheduling instruction issuing, when detecting that communication network delay exceeds preset network delay threshold, edge computing node is directly executed local broadcast and early warning instruction based on emergency dispatch time datum and synchronization deviation information, and the execution state of local broadcast and early warning instruction is fed back to cloud management platform.The present application has the effect of improving the timeliness of emergency management.

The present application relates to reservoir scheduling technical field, disclose a kind of cascade reservoir group scheduling trajectory dynamic optimization method, comprising the following steps: collecting scheduling basic data;Optimization function and constraint condition of cascade reservoir group scheduling are constructed and calculation parameter is set;Using artificial experience decision or conventional method, obtain the initial trajectory of each reservoir each stage;Start iteration, execute several times dynamic programming method and establish historical trajectory library;Continue iteration, execute multi-type flight mode dynamic optimization, randomly select lev flight, spiral flight or navigation flight mode combination historical trajectory optimization current trajectory, iteration until meeting termination condition output optimal scheduling trajectory.The present application also discloses a kind of cascade reservoir group scheduling trajectory dynamic optimization.The present application cascade reservoir group scheduling trajectory dynamic optimization method and system, break through the dimension disaster defect that dynamic programming exists in solving complex reservoir group scheduling trajectory optimization problem, present significant convergence ability and calculation precision.

The invention belongs to the technical field of industrial automation control, and particularly provides an energy-saving pump dynamic energy consumption intelligent scheduling management method based on big data, and the method mainly comprises the steps: obtaining pump set operation data and pipe network pressure data, carrying out the preprocessing of the pump set operation data and the pipe network pressure data, and obtaining standardized pipe network data; pipe network pressure difference and real-time hydraulic impedance are calculated according to the standardized pipe network data, and a hydraulic impedance model is established after verification and smoothing; and impedance parameters are extracted from the hydraulic impedance model, and the total required lift is calculated in combination with the real-time total flow. The method effectively solves the problems of overload or low-efficiency operation of a pump set, low system fluid conveying energy efficiency and high energy consumption caused by focusing a single parameter and not giving full consideration to the dynamic hydraulic coupling effect and topological change of a pipe network in traditional scheduling, can improve the overall fluid conveying energy efficiency of the pipe network system, reduces unnecessary energy consumption, and improves the system performance. And a more accurate decision support is provided for pump group scheduling.

The invention discloses a reservoir group long series scheduling process multi-objective optimization method based on space-time similarity dimensionality reduction, and belongs to the technical field of reservoir scheduling of hydraulic engineering. Performing space-time multi-scale dimension reduction on the scheduling process to obtain a dimension-reduced scheduling process; according to the scheduling process after dimension reduction, based on a multi-objective optimization scheduling algorithm, similarity judgment is carried out on the offspring individuals; directly reusing the parent scheduling process for the individuals which are determined to be similar to obtain corresponding objective function values, and scheduling the reservoir group scheduling model for the individuals which are determined to be dissimilar to obtain corresponding objective function values; and updating the non-dominated solution set according to the obtained objective function value, and generating an optimized reservoir group length series scheduling process. According to the method, the optimized reservoir group length series scheduling process can be quickly generated on the premise of ensuring the quality of the solution set.

The invention provides a distributed photovoltaic group control and group scheduling strategy test method and device, and the method comprises the steps: obtaining nameplate parameters and historical data of distributed photovoltaic inverters in a target region, carrying out the clustering analysis through the electrical distance and dynamic characteristic similarity, and generating sub-clusters and equivalent model parameters; deploying to an RTDS platform to construct a digital twinborn model; receiving a power regulation instruction, distributing a regulation quantity, simulating power climbing, and calculating grid-connected point voltage fluctuation; injecting irradiance and temperature disturbance, and monitoring power tracking precision and response delay; and finally, a steady-state precision and dynamic response performance report of the adjustment strategy is generated. According to the invention, the digital twin model is constructed to simulate power regulation, strategy verification and optimization are realized, and the stability and response efficiency of the distributed photovoltaic system are improved.

The invention discloses a hardware event group scheduling method for a computer processor performance monitoring unit. The method comprises the following steps: S1, acquiring an event group set and the number of counters; s2, performing descending sorting on the event groups according to the number of events by using a non-incremental sorting strategy; s3, initializing an empty round; s4, iteratively distributing the event group to an existing round or creating a new round; and S5, outputting the round set of the existing round or the new round obtained in the step S4 as a scheduling scheme of the event group on a performance monitoring counter, and the method has the advantages that a hardware event group scheduling problem is converted into a one-dimensional boxing problem, and a non-incremental sorting strategy and an iterative greedy distribution strategy are utilized, so that the time complexity of a hardware event scheduling process is remarkably reduced, and the scheduling efficiency is improved. A low-overhead and high-precision performance data observation scheme is constructed, on the premise that accuracy is guaranteed, efficient execution of large-scale performance analysis tasks is achieved, and performance monitoring efficiency and system performance observation precision are improved.

A gNodeB apparatus, a system, a method, and a machine-readable medium are provided. The apparatus includes one or more processors to encode a message for a single-cell multicast, broadcast, or groupcast transmission to a group of user equipment (UEs), the message to configure the UEs for at least one of channel quality indicator (CQI) feedback or hybrid automatic repeat request acknowledgement (HARQ / ACK) feedback such that at least one of CQI feedback or HARQ / ACK feedback can be turned off or such that both CQI feedback and HARQ / ACK feedback can be used, and to transmit the message to a communication resource of the gNB for transmission to the UEs. The one or more processors can further encode a multicast, broadcast, or groupcast physical layer transmission mapped by a higher layer to a common service for transmission to the UEs.

The invention relates to a power distribution-micro-user real-time power interaction method considering user response uncertainty. The method comprises the following steps: step 1, describing a power distribution network dispatching dynamic state through a Markov decision process; based on an Actor-Critic framework, constructing a micro-configuration interaction model; training an intelligent agent by using historical experience data, and generating a scheduling instruction issued to the micro-grid group in combination with a day-ahead scheduling result and a real-time power state; step 2, based on the micro-grid group scheduling instruction issued by the power distribution network in the step 1, performing parallel execution by each micro-grid, constructing a micro-grid user interaction model according to a multi-arm long machine theory, and solving the model by adopting an online learning algorithm fused with a confidence interval strategy, dynamically selecting a user combination execution instruction capable of responding to the micro-grid group scheduling instruction issued by the power distribution network in the step 1, so as to minimize the response deviation of the micro-grid; and sending a response instruction to the user, collecting actual response data of the user to continuously update the online learning algorithm parameters, summarizing the actual response data, and uploading the summarized actual response data to the power distribution network, thereby completing power distribution-micro-user real-time power interaction. According to the method, the problem that the response of the micro-grid is uncertain during micro-distribution optimization operation can be solved.

This invention discloses a parallel pump group scheduling method and system based on dynamic programming, belonging to the technical field of intelligent pump group scheduling. The method involves data acquisition and preprocessing, discretizing and equivalently treating the variable frequency pumps as n equivalent fixed frequency pumps. Then, single-pump performance curves and pipeline network performance curves are fitted. Based on the single-pump performance curves, the high-efficiency operating range of each pump is determined. Then, using water supply flow demand, water supply head demand, and the high-efficiency operating range of each pump as hard constraints for pump group operation, candidate pump group combinations are selected. The start-up and shutdown costs and usage time of each pump are incorporated as soft constraints into the total cost, constructing a minimum objective function for the total cost. Finally, a dynamic programming algorithm is used to obtain the global optimal solution, generating the optimal pump group scheduling sequence within the scheduling cycle. This invention balances low energy consumption and equipment health, and is applicable to mixed pump group scenarios including fixed-frequency and variable frequency pumps, significantly reducing energy consumption in traditional scheduling and mitigating equipment wear.

The embodiment of the invention discloses a group scheduling system and device based on a virtual cluster. A specific embodiment of the system comprises a traceability synchronization module which automatically identifies a load object created by a user in a virtual cluster, synchronizes task annotation metadata corresponding to the load object to a corresponding execution unit in a host cluster, and writes address annotation metadata corresponding to the load object in the execution unit; the scheduling module is used for reading the task annotation metadata of each execution unit, generating a scheduling score value corresponding to each execution unit in each execution unit according to the read task annotation metadata set, scheduling each execution unit to the corresponding resource adaptation node in batches, and deploying the scheduling module in a host cluster; the charging module is configured to generate a task charging list. According to the embodiment, the universality and the resource utilization efficiency of the system are improved.

The invention discloses a computing cluster resource scheduling method and device, a server and a computer readable storage medium. According to the method, the expected resource utilization rate is calculated based on the resource request and the total amount of occupied resources, the strong reserved water level is taken as the boundary to screen and preselect the passing nodes, the strong reserved water level ensures that the cluster always keeps the resource capacity capable of accepting the large-specification container group, the problem of large-specification container group scheduling failure caused by resource fragmentation in the prior art is solved, and the resource utilization rate is improved. The response capability of the cluster to future resource demands is ensured; then, further combining the relative relationship between the expected resource utilization rate and the weak reserved water level, selecting a node with low expected resource utilization rate and high occupied resource total amount from the pre-selected passing nodes as a target node, so that the resource utilization concentration ratio is improved by utilizing the characteristic of high occupied resource total amount to reduce fragments; and excessive concentration of the resources is avoided under the condition that the expected resource utilization rate is low, and dynamic balance of the resources in container group deployment is guaranteed.

The invention relates to the technical field of power systems, and discloses a forward and reverse heavy overload photovoltaic AGC group scheduling method, system, device, medium and product. According to the topological connection relation between feeder switches and photovoltaic electrical devices in a power distribution network, all the photovoltaic electrical devices correspondingly connected with the feeder switches are determined; a photovoltaic scheduling cluster corresponding to each feeder switch is formed, and a forward heavy overload feeder and a reverse heavy overload feeder are determined according to the real-time current of the feeder switches; and under the condition that the photovoltaic electrical equipment participating in adjustment in the target area has a power adjustment demand, adjusting a photovoltaic scheduling cluster corresponding to a feeder switch to which a forward heavy overload feeder or a reverse heavy overload feeder belongs, so that the adjusted power adjustment demand reaches a preset target power. Therefore, the heavy overload condition can be accurately adjusted.

The invention discloses a small hydropower station group scheduling method and system considering power station characteristics and power grid constraints. The method comprises the following steps: constructing a fixed constraint condition according to static information of each stage of small hydropower station group; according to runoff and wind and light energy output prediction, dynamic constraint conditions are established in combination with power grid load requirements; based on an NSGA-III model, determining a cascade small hydropower station group optimization scheduling scheme; and completing small hydropower station group scheduling according to the obtained scheduling scheme. According to the method, multiple groups of Pareto optimal scheduling schemes can be generated by taking the maximum total output and the minimum abandoned water as targets on the premise of meeting ecological flow, power grid load balance and unit operation constraints. The method can effectively improve the water energy resource utilization efficiency of small and medium-sized watersheds, enhances the regional new energy consumption capability, and adapts to the operation characteristics of small hydropower station intra-day peak scheduling and limited management personnel.