Power plant boiler combustion state prediction device and method
The combustion state prediction device uses a machine learning-based physical model to enable real-time monitoring and optimization of boiler combustion, addressing computational challenges and improving operational efficiency and pollutant reduction in coal-fired power plants.
JP2026506931APending Publication Date: 2026-02-27KOREA ELECTRIC POWER CORP +5
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Patent Information
- Application Number
- JP2025546719
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-02-16
- Filing Date
- 2023-07-14
- Publication Date
- 2026-02-27
AI Technical Summary
Technical Problem
Existing methods for monitoring and predicting combustion states in large-scale facilities like coal-fired power plants are computationally intensive, resource-heavy, and primarily used in the design stage, making real-time monitoring during operation difficult.
Method used
A combustion state prediction device and method using a prediction model based on a physical model, incorporating machine learning, to receive and analyze operation data for real-time monitoring and optimization of boiler combustion.
Benefits of technology
Enables real-time prediction and monitoring of combustion states, stabilizing boiler operation, optimizing efficiency, and minimizing pollutants by tracking incomplete combustion and adjusting operating conditions.
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Smart Images
Figure 2026506931000001_ABST
Abstract
The present invention discloses a device and method for predicting the combustion state of a power plant boiler. The device for predicting the combustion state of a power plant boiler of the present invention includes an operating variable input module that receives input of operating variables for boiler operation, an operating information database that stores boiler operating information, an output module that displays predicted data, and a processor operatively coupled to the operating variable input module, the operating information database, and the output module, wherein the processor runs an execution program to predict the boiler combustion state based on a prediction model based on the operating variables input from the operating variable input module and the boiler operating information stored in the operating information database, and output the predicted data via the output module.
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