Air separation equipment can achieve precise energy saving through four core paths.
1、 Deploy intelligent monitoring system: Real time monitoring of all parameters, installing high-precision sensors on key equipment and pipelines such as air compressors, expanders, and heat exchangers to collect real-time parameters such as temperature, pressure, flow rate, liquid level, and vibration. Integrate monitoring data into cloud platforms to generate visualization tools such as energy consumption trend charts and unit consumption comparison reports.
2、 Application of intelligent control algorithm: adaptive expansion machine control, based on AI algorithm to dynamically adjust parameters such as inlet temperature and speed of the expansion machine, so that it always operates at the optimal efficiency point. Intelligent molecular sieve switching, by monitoring parameters such as pressure difference and temperature of the molecular sieve adsorber, combined with an adsorption cycle model, dynamically optimizes the switching time. Intelligent scheduling of peak and valley electricity prices, combined with the peak and valley electricity price policies of the power grid, increases equipment load during low electricity price periods, and uses backup liquefaction devices to store liquids; Reduce load during peak electricity price periods by injecting reserve liquids to maintain product output and reduce compressor energy consumption.
3、 Building an intelligent operation and maintenance platform: fault warning and health management. By analyzing historical data such as equipment vibration and temperature, a fault prediction model is established to identify potential problems such as bearing wear and seal leakage in advance. Intelligent optimization of spare parts inventory, predicting spare parts life based on equipment operation data, and dynamically adjusting inventory strategies.
4、 Optimize intelligent scheduling strategy: Multi unit collaborative operation, dynamically allocate production tasks through intelligent scheduling algorithms in multiple sets of air separation equipment scenarios. Intelligent linkage with the user side, connecting the operating data of the air separation equipment with the gas demand on the user side to achieve on-demand production.
