7 results about "Capacity sharing" patented technology

The invention relates to an intelligent scheduling decision support method and system for a community bus special line, and solves the problems of unreasonable transport capacity distribution and insufficient key travel demand guarantee caused by incapability of distinguishing travel purposes in an existing scheduling method, and the method comprises the steps: firstly, integrating card swiping, reservation and static data to construct a travel demand data set; secondly, through a clustering algorithm, identifying travel destination modes and extracting multi-modal features, generating a prediction report containing a passenger flow thermodynamic diagram and a space-time probability matrix through prediction of an adaptive multi-head attention model, and further calculating service priorities of the modes; then, a decision framework coordinated by route planning and station jump decision intelligent agents is constructed, a global reward function is endowed with differentiated weights according to priorities, and a dynamic scheduling scheme is jointly generated; the method has the following effects: community bus accurate scheduling based on travel purpose identification and priority guarantee is realized, and transport capacity sharing is upgraded to on-demand intelligent distribution.

The present application relates to a kind of active and reactive power collaborative layered dynamic voltage support and optimization control method for load center power grid of receiving end, belong to power system and its automation technical field.The method is aimed at artificial intelligence data center internal AI workload second-level fluctuation and grid-connected converter apparent capacity constraint characteristics, constructs active and reactive power coupling dynamic support model including delay-tolerant type load response delay.By time-varying voltage sensitivity linearization, establish collaborative time-varying model predictive control (TV-MPC) model, and adopt AIDC dynamic aggregation and device layer capacity sharing distribution mechanism, reduce online optimization dimension.Control architecture is divided into coordination layer, aggregation layer and device layer: coordination layer generates active reduction and reactive reference instruction of AIDC layer;Aggregation layer is according to real-time capacity dynamic decomposition instruction;Device layer executes control and feedback state.The present application method can effectively improve the minimum value and recovery speed of key node voltage after fault, meet the real-time requirement of hundred-millisecond-level online control.

The invention relates to the technical field of traffic and logistics, in particular to an equilibrium solution solving method and system for a subway passenger and freight transport capacity sharing system, and the method comprises the steps: reading a database, obtaining the transport capacity data of each time period, and enabling the transport capacity data to at least comprise subway operation data and passenger flow data; obtaining redundant transport capacity data according to the subway operation data and the passenger flow data; according to the equilibrium solution solving method and system of the subway passenger and freight capacity sharing system, through an optimization model based on the benefit and cost structure of different participants, the conditions and constraints for realizing the capacity sharing under various market conditions are clarified, and the balance solution solving method and system of the subway passenger and freight capacity sharing system can be used for solving the balance solution of the subway passenger and freight capacity sharing system. The invention further discloses an optimal cooperation strategy between the logistics companies and the metro operators under different transport capacity distribution mechanisms by analyzing the respective dominant situations of a single logistics company and two logistics companies.

The present application relates to power system power source planning method technical field, especially a kind of multi-region power system power source planning method considering capacity sharing, including the construction load growth driven time sequence uncertainty probability model;Establish the effective capacity refined evaluation model under the random failure of multi-source unit;System capacity distribution analytical transformation based on semi-invariant and series expansion.The present application breaks the limitation of traditional single region independent planning by establishing the capacity sharing mechanism between receiving end and sending end regional power grid.Can dynamically adjust inter-regional power resource allocation according to the degree of capacity scarcity, significantly reduce cost under the premise of guaranteeing reliability.

The invention discloses a dynamic computing power resource fragment integration system, which relates to the technical field of data resource management and comprises a mode selection module, a dual-mode implementation module, an anti-fragment punishment module and a rollback mechanism module. The mode selection module is used for dynamically switching a residual capacity sharing mode or a filling priority mode based on the global utilization rate and the large loadable ratio; the dual-mode implementation module respectively executes resource allocation and task placement of two modes; the anti-fragment punishment module calculates the number of tailings and large damage through simulation placement, eliminates candidate nodes generating the tailings, and protects continuous resources; the rollback mechanism module is used for processing the special situation that all candidates generate tailings, and infinite queuing of tasks is prevented through hole filling tasks, minimum damage drop point selection and mode switching. The problem of fragmentation of distributed computing power resources is effectively solved, and the resource utilization rate and the throughput capacity are improved.

The invention discloses a manufacturing service exception handling method, device and equipment for a numerical control machine tool, and a medium, relates to the technical field of manufacturing service scheduling, is applied to a capacity sharing platform, and comprises the steps: monitoring the exception state information of the manufacturing service of a target numerical control machine tool when the manufacturing service runs according to an initial capacity supply and demand scheme; in response to the capacity supply and demand scheme adjustment instruction, adjusting the initial capacity supply and demand scheme by using a preset supply and demand adjustment model based on the abnormal state information; the preset supply and demand adjustment model is a model constructed based on a principle of maximizing adjustment satisfaction and minimizing adjustment amplitude; the adjustment satisfaction comprises satisfaction values of the demand side and the supplier; and manufacturing service operation of the target numerical control machine tool is controlled according to the adjusted target capacity supply and demand scheme, so that manufacturing service abnormity processing is completed. Therefore, the influence of service abnormity on the demand side and the supply side can be fully considered, the response capability and robustness of the capacity sharing platform are improved, and the acceptance of a user to a scheme adjustment result is enhanced.

A method, computer program product, and computer system are provided for container cross-cluster capacity scaling. The method includes broadcasting local capacity information of capacity availability or capacity requirement for the local cluster and receiving broadcasts from each of one or more other clusters providing capacity information including capacity availability or capacity requirements. The method may map the received capacity information with the local capacity information and may determine a suitable cross-cluster capacity sharing when a capacity requirement of the local cluster maps to a capacity availability of another cluster or when a capacity availability of the local cluster maps to a capacity requirement of another cluster. The method may coordinate the deallocation of a node from the cluster having the capacity availability and reallocation of the node to the cluster having the capacity requirement.