Modularized risk prediction method and device for power distribution terminal and storable medium
A technology for power distribution terminals and risk prediction, which is applied in instruments, complex mathematical operations, data processing applications, etc., and can solve the problems of large errors in risk prediction methods.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2019-03-19
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Abstract
Description
technical field
[0001] The present application relates to the field of operation, maintenance and management of power distribution terminals, in particular to a modularized risk prediction method, device and storage medium for power distribution terminals. Background technique
[0002] With the continuous advancement of the power marketization process and the continuous improvement of users' requirements for power reliability and quality, the future power grid must be able to provide safer, more reliable, clean and high-quality power supply, and provide better services. Therefore, the construction of smart grid has become the main development direction of the transformation and progress of the power industry.
[0003] The power distribution terminal is the on-site monitoring and control equipment of power distribution automation, and its reliability is very important to power distribution automation. During the actual operation of the power distribution terminal, there are ...
Examples
Embodiment Construction
[0049] Embodiments of the present application provide a modularized risk prediction method, device and storage medium for power distribution terminals, which are used to solve the technical problem of large errors in existing risk prediction methods based on the entire power distribution terminal.
[0050] Information entropy was first introduced by Shannon into information theory, and it has been widely used in engineering technology, social economy and other fields. The entropy weight method determines the objective weight according to the variability of the index. Generally speaking, if the information entropy of an index is smaller, it indicates that the value of the index varies more, the more information it provides, the greater the role it can play in the comprehensive evaluation, and the greater its weight. On the contrary, the greater the information entropy of an indicator, the smaller the variation of the indicator value, the less information it provides, the smaller...