Recently, the boiler combustion optimization project of Zhongkong Technology and Zhejiang Xinan Chemical Group Co., LTD. Jiande Thermal Power Plant (hereinafter referred to as “Jiande Thermal Power Plant”) based on industrial AI has successfully completed acceptance and won high praise from users. In the process of project implementation, Zhongcontrol Technology team has combined Transformer architecture and other industrial AI technologies to create combustion optimization control solutions, which has realized the successful application of industrial AI technology in this field, guaranteed the safe and intelligent operation of the three circulating fluidized bed boilers in Jiande Thermal Power Plant, and improved the comprehensive benefits of the enterprise. It has set a benchmark for the digitalization and intelligent upgrading of the thermoelectric industry.

Jiande thermal power Plant

01

PXIE-8822  Cogeneration industry boiler operation core pain points

Circulating fluidized bed boiler combustion in the traditional cogeneration industry generally has the following pain points:
1. The traditional control based on conventional algorithms has limitations when facing the scenarios of boiler combustion with strong coupling, large inertia, large lag and multi-variable control, and the load demand response is not timely.
2. The combustion situation is complex and changeable, and the traditional control mode is easy to lead to insufficient combustion or large exhaust smoke loss, resulting in low thermal efficiency.
3. In the traditional mother-control operation mode, the boiler load is manually distributed, and multi-mode distribution cannot be carried out according to the boiler energy efficiency, load conditions and combustion conditions, thus affecting the overall boiler combustion efficiency.
4. Conventional boiler NOx adjustment has a large inertia lag, in order to avoid NOx exceeding the standard, usually increase the amount of ammonia injection, resulting in a higher ammonia escape problem.

These factors directly or indirectly cause the boiler low automatic control rate, large fluctuation of operating parameters, adjustment lag, insufficient combustion, large exhaust smoke loss, low thermal efficiency problems.

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Built on Transformer architecture

AI combustion optimization control system

Boiler combustion optimization control solution based on industrial AI realizes big data optimization control, and constructs intelligent optimization control system through Transformer architecture, integrates time series prediction model, cascade recommendation algorithm, and feedforward + feedback control mode to optimize and control key parameters, making boiler combustion more stable. By adopting multi-objective cooperative optimization, the stable combustion state and the optimal bed temperature of the boiler are maintained without overtemperature and coking during the combustion optimization process, which makes the operation more efficient and improves the combustion efficiency of the boiler.

PXIE-8822  AI boiler combustion optimization control architecture

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Help Jiande Thermal Power Plant “improve human efficiency, stable operation and increase income”

The boiler combustion intelligent optimization control system based on industrial AI has undergone multiple rounds and long cycle alternating verification tests with remarkable results. In the boiler combustion optimization project of Jiande Thermal Power Plant, the automatic control rate of the system reached more than 95%, the average fluctuation range of key operating parameters was reduced by more than 30%, and the index of coal consumption per ton of steam was reduced by more than 1% compared with manual operation. The key parameters of boiler combustion were used as characteristic feedforward, and ammonia escape was reduced by more than 20% compared with manual control when nitrogen oxides were not exceeded. Effectively reduce the work intensity of the operator, improve the boiler combustion efficiency, and effectively help Jiande thermal power plant “improve human efficiency, stable operation and increase income”.

Above: Comparison between the predicted value and the actual value of pipe pressure predicted by TFT model

The following figure: AI smoke oxygen content optimization and control diagram

Industrial intelligence is an important force to promote future industrial development, central control technology will continue to provide customers with “AI+ safety”, “AI+ quality”, “AI+ low-carbon”, “AI+ efficiency” intelligent solutions, promote the industry to intelligent, efficient, sustainable direction, leading the revolutionary change of industrial production.