Intelligent gasification feedstock blending system and method

Through the intelligent gasification raw material mixing system, the coal mixing ratio is optimized by using the rapid analysis and attribute prediction module, the problems of low and inaccurate coal mixing efficiency in the existing technology are solved, and the intelligent control and operational stability of gasification raw materials are achieved.

JP7668270B2Active Publication Date: 2025-04-24CHINA PETROLEUM & CHEMICAL CORP +1
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Patent Information

Application Number
JP2022518779
Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
Priority Date
2019-09-24
Filing Date
2020-09-24
Publication Date
2025-04-24
Estimated Expiration
2040-09-24

AI Technical Summary

Technical Problem

The existing coal mixing technology in the coal chemical industry is inefficient and inaccurate, making it difficult to build a coal mixing solution for the entire life cycle process, resulting in unstable gasifier operation.

Method used

Develop an intelligent gasification raw material mixing system, including a rapid analysis module, an attribute prediction module, an optimization module and an economic evaluation module, and build a raw material mixing plan for the whole life cycle through the analysis of the characteristic spectrum of raw materials, attribute prediction, optimization of the mixing ratio and economic evaluation of raw materials.

Benefits of technology

It improves the efficiency and accuracy of coal mixing, realizes intelligent and precise control of gasified raw materials, and reduces the adverse impact of raw material attribute problems on gasification furnace operation.

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Abstract

[0013] An embodiment of the present invention provides an intelligent gasification feedstock blending system and method, belonging to the coal chemical industry. The gasification feedstock blending subsystem includes a feedstock property rapid analysis module for obtaining feedstock property parameters based on the characteristic spectral line intensity of the feedstock fed to the furnace; a feedstock property prediction module for forming a prediction model and predicting the property parameters of the feedstock blend using the prediction model based on the feedstock property parameters and blending ratios; a feedstock blending plan optimization module for forming an optimization model and obtaining an optimized feedstock blending plan using the optimization model based on the property parameters of the feedstock blend; and a feedstock blending plan economic evaluation module for outputting a feedstock blending plan with the best technical and economical efficiency. The present invention establishes an intelligent gasification feedstock blending system that can be used throughout the entire lifecycle process, achieving intelligent and accurate control of gasification feedstock blending.
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