Multi-mode dispatcher training simulation system in cloud environment

Abstract

The invention discloses a multi-mode dispatcher training simulation system in a cloud environment, which is built on a cloud platform and comprises a user layer, an access layer, a simulation micro-application layer, a simulation public service layer, a simulation public resource layer and a simulation resource exchange layer. The user layer can perform mode selection and scene selection, and the simulation micro-application layer creates a simulation instance for training according to the selected mode and scene. Through autonomous model selection and scene selection, training in modes of autonomous practice, exercise, examination and the like can be realized, and simulation instance construction of multiple scenes such as a city dispatching scene, a local dispatching scene, a city-local joint scene and the like can be realized. According to the invention, the requirements of multi-scene and multi-mode multi-stage regulation and control combined training are met, participants in various regions can carry out simulation training anytime and anywhere without being limited by time and space, and the professional skill training efficiency of regulation and control integrated operators is effectively improved.

Description

technical field [0001] The invention relates to a multi-mode dispatcher training simulation system in a cloud environment, and belongs to the technical field of smart grid dispatching. Background technique [0002] The D5000 simulation training system is based on the service provided by the intelligent dispatching technical support system. Using digital simulation technology, it can simulate the behavior of the power system under various working conditions, so that the control personnel can carry out the normal operation of the system in exactly the same environment as the actual control center. Accident handling and system recovery training, familiar with various operations, familiar with the analysis and processing of secondary signals and messages of the power system, while observing the system status and implementing control measures, experience the changes of the system in a highly realistic manner, which can support It provides training for operation monitoring, equipm...

AI Technical Summary

Problems solved by technology

[0003] At present, the traditional D5000-based training simulation system has the following deficiencies: In terms of system deployment, each region needs to be deployed independently, the demand for hardware resources is large, and the utilization rate is low; In terms of training scope, simultaneous training of multiple users and multiple scenarios is not possible, and the drill form is single; in terms of application environment creation, it takes a long time to create a new application

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