Regulation and control cloud-based intelligent evaluation method for regulation and control simulation training system

Abstract

The invention discloses a regulation and control cloud-based intelligent evaluation method for a regulation and control simulation training system, wherein the method comprises the following steps: giving standard operation steps according to teaching plans of different types of training, and setting the logic relation among all standard operation steps; setting a score deduction basis according to requirements of regulators on operation regulations, power grid safety, power supply reliability and power supply economy, and setting score deduction values and weights of various score deduction items; after student operation is finished, automatic scoring is carried out, and handling manually operation which cannot be recognized by a teacher; and integrating automatic scoring and manual scoring, generating and issuing an evaluation report, and achieving authority distribution and checking through a regulation and control cloud platform. According to the method, the workload of teachers and the feedback obtaining time of students can be reduced, the training effect can be improved, the actual combat ability of regulation personnel is rapidly improved, and safe operation of a power gridis guaranteed.

Description

technical field [0001] The invention relates to the field of electric power system and automation thereof, in particular to a training evaluation method of a controller simulation simulator, in particular to an intelligent evaluation method of a control simulation training system based on a control cloud. Background technique [0002] As the integration and coordination of regulation and control services become higher and higher, the requirements for the accident handling capabilities of regulation and control personnel also increase. Strengthen business process training for normal and abnormal state dispatching and monitoring, early warning training for power grids and weak links of equipment before accidents, rapid fault location, fault analysis and accident plan drill training during accidents, reliable and efficient operation of recovery plans after accidents, etc. The training is of great significance to the improvement of the professional ability of the control personn...

AI Technical Summary

Problems solved by technology

[0003] The existing control training simulation system (DTS) must be based on the D5000 system technically, and cannot comprehensively evaluate the training process evaluation and the overall evaluation of the training steps. It can only set basic and simple rules, and it is difficult to match and judge the complex operation process of the trainees.

The existing system cannot integrate system evaluation and manual evaluation. The evaluation process mainly relies on experienced instructors to evaluate the overall operation of students by reviewing snapshot sections and a large amount of unprocessed information, which is time-consuming and laborious; in addition, due to the uncertainty of manual scoring Due to the diversity of students' operations, the existing scoring mechanism is difficult to give accurate, objective and reasonable evaluation results

Moreover, the training results are not stored in the cloud, and a large number of personnel participating in the training evaluation cannot view the evaluation results in a timely and effective manner to obtain feedback, and the training effect is poor

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