Intelligent full-process balancing regulation model and system application for Linz-Donawitz gas

Linz-Donawitz Gas (LDG) is a vital secondary energy generated during the converter blowing process. In balancing its recovery into gas holders and distribution to end-users, traditional scheduling mainly relies on manual expertise, long plagued by bottlenecks such as uncoordinated operational interfaces and high full gas-holder venting rates. To enhance LDG utilization efficiency, this study proposes a methodology for constructing production-consumption prediction models and a coordinated optimization strategy targeting gas-holder level stabilization, through systematic analysis of LDG pipeline network dynamics and recovery-distribution processes. A full-process balancing and scheduling model is established, encompassing gas recovery prediction, multi-constraint adjustment for compressors, and optimized allocation for end-users. Furthermore, a closed-loop execution mechanism is designed to send model-generated commands to the industrial control system. Deployed under actual operating conditions at a steel plant, the developed intelligent regulation system automatically adjusts compressor delivery volumes and modulates gas consumption at adjustable users, significantly improving pipeline network stability and balancing capacity. Operational results demonstrate that post-implementation, the frequency of full gas-holder venting events decreased from an average of 4.39 times per day to 0.37 times under same operating conditions, with significant effects. This provides an implementable solution for intelligent dispatching of secondary energy in steel enterprises, actively responding to low-carbon and energy-efficient development requirements.