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Method for improving fire detection effect based on federated learning in intelligent power plant

A technology of federation and power plants, applied in the field of industrial Internet of Things to improve federated learning and training, to achieve dynamic trade-offs, satisfy privacy and security, and improve learning efficiency

Pending Publication Date: 2021-04-02
西安君能清洁能源有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the synchronization architecture is not suitable for heterogeneous node resources

Method used

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  • Method for improving fire detection effect based on federated learning in intelligent power plant
  • Method for improving fire detection effect based on federated learning in intelligent power plant
  • Method for improving fire detection effect based on federated learning in intelligent power plant

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Embodiment Construction

[0059] The present invention is further described below in conjunction with accompanying drawing:

[0060] A method for improving fire detection performance based on federated learning in smart power plants, DTs in smart power plants, including,

[0061] The DT of an industrial device is established by its own server, collects and processes the current physical state of the device, and dynamically presents the history and current behavior of the device in digital form.

[0062] In time t, the DT of training node i after calibrating the deviation between the mapped value and the actual value i (t) can be expressed as:

[0063]

[0064] in is the training parameter of node i, is the training state of node i, f i (t) is the computing power of node i, Indicates the frequency deviation of the CPU, E i (t) represents energy loss.

[0065] Federated learning in smart power plants, including,

[0066] In federated learning, the initialization task must first be broadcast...

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Abstract

The invention discloses a method for improving a fire detection effect based on federated learning in an intelligent power plant, which adaptively reduces energy consumption by combining DTs and a deep Q network (DQN), and designs an asynchronous federated learning framework to eliminate a streamer effect at the same time. The DT can realize accurate modeling and synchronous updating, so that theintelligence of the intelligent power plant is enhanced. Meanwhile, the DT can also create a virtual object in a digital space through software definition, and accurately map an entity in a physical space according to the state and the function of the virtual object, so that decision making and execution are facilitated. finally, the DT maps the running state and behavior of the equipment to the digital world in real time, so that the reliability and accuracy of the learning model are improved.

Description

technical field [0001] The invention belongs to the technical field of improving federated learning training in the industrial Internet of Things, and in particular relates to a method for improving fire detection effects based on federated learning in a smart power plant. Background technique [0002] As society's demand for clean energy continues to increase, the industry of clean energy continues to expand, and the scale of clean energy, especially the photovoltaic industry, has grown rapidly in recent years. Some companies responsible for the investment, construction and operation of distributed new energy projects manage multiple distributed photovoltaic power plants, which are distributed in every corner of the country. The company has built a production and operation center for centralized operation and management of all distributed power stations. [0003] At the same time, the photovoltaic power generation system is mainly composed of photovoltaic modules, controll...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06K9/62G06N3/04G06N3/08
CPCG06Q10/04G06Q50/06G06N3/08G06N3/045G06F18/23213
Inventor 杨端许晓伟韩志英孙曼雷施雨张翰轩
Owner 西安君能清洁能源有限公司