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Real Time Optimisation of Industrial Gas Supply Networks

机译:工业气体供应网络的实时优化

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A supply network consisting of multiple air separation units and compressors supplies oxygen gas at two pressures to a major steelmaker in South Wales. Each machine has a different efficiency curve, power requirement, and capacity. The aim was to minimise the cost of power and liquid usage of the supply network whilst meeting customer gas flow demands and preventing product spill.Mass balances of the site were produced and integrated into a Microsoft Excel spreadsheet representation of the supply network. A mixed integer nonlinear programming approach was adopted to allow machines to operate within flow limits and turn on or off based on demand. The GRG nonlinear solver method was used to minimise the cost of running the network arrangement, determined by the sum of all estimated machine powers and the cost of liquid back up usage. Constraints were programmed to maintain steady state, meet demand, and keep machine flows within bounds.This work demonstrates that extra power requirement, liquid vapourisation and product spill caused by inefficient compression arrangements result in annual site losses of £0.6M. It is shown that through real time optimisation of the gas network a significant reduction in these financial losses can be achieved.
机译:由多个空气分离装置和压缩机组成的供应网络以两种压力向南部威尔士的一家大型钢铁生产商供应氧气。每台机器都有不同的效率曲线,功率要求和容量。目的是在满足客户燃气流量需求和防止产品泄漏的同时,最大程度地减少供应网络的电力和液体使用成本。生产站点的大量平衡并将其集成到供应网络的Microsoft Excel电子表格中。采用了混合整数非线性编程方法,以允许机器在流量限制内运行并根据需要打开或关闭。 GRG非线性求解器方法用于最小化运行网络设备的成本,该成本由所有估计的机器功率之和和备用液体的成本决定。对约束进行了编程以保持稳态,满足需求并使机器流量保持在范围之内。这项工作表明,由于压缩效率低下而导致的额外动力需求,液体汽化和产品溢出导致每年现场损失£ 0.6M。结果表明,通过天然气网络的实时优化,可以大大减少这些财务损失。

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