화학공학소재연구정보센터
Applied Energy, Vol.218, 232-245, 2018
Control data, Sankey diagrams, and exergy: Assessing the resource efficiency of industrial plants
Studies analysing the resource use of industrial production are often performed at highly aggregated levels, e.g. yearly across industry sectors. Conversely, the remit of work performed at the operational level is limited to the management of energy or concerned with aspects such as safety or reliability, both of which fail to consider material efficiency options at that scale. This gap is filled by applying the concept of exergy to the disaggregated time-scales and scopes typical of real-time operations. Our tool measures the resource efficiency of processes and visually traces the use of both energy and materials from available control data. This is exemplified through the case study of a Tata Steel basic oxygen steelmaking plant, where resource flows are visualised using Sankey diagrams. An analysis of the resource efficiency variations across batches and days for a period of 29 days - over 900 batches - show the plant's inefficiencies primarily arise from the converter process, the resource efficiency of which varies from 87.4% to 93.7%. By recovering material and energy by-products, and reducing fuel inputs we estimate that 7% of the total exergy input can be saved or further utilised. About 60% of these improvements arise from energy-related measures. The remaining 40% emanates from reductions in material use, a contribution which would be missed if using conventional energy metrics. This approach makes three contributions. First, it gives industry a single metric of resource efficiency that can jointly measure the system-level performance of material and energy transformations. Second, it provides a new picture of the plant's operational resource use. Third, it allows managers to have more detailed information on resource flows and thus helps place material-efficiency improvements on an equal footing to energy efficiency. This, therefore, provides a clearer picture of where interventions can deliver the greatest efficiency gains.