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Integrated Material Flow Analysis and Process Modeling to Increase Energy and Water Efficiency of Industrial Cooling Water Systems
Author(s) -
SchleiPeters Ina,
Wichmann Matthias Gerhard,
Matthes IngoGeorg,
Gundlach FriedrichWilhelm,
Spengler Thomas Stefan
Publication year - 2018
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/jiec.12540
Subject(s) - process engineering , process (computing) , industrial ecology , heat exchanger , identification (biology) , water cooling , efficient energy use , material flow , computer science , material flow analysis , industrial engineering , energy (signal processing) , scale (ratio) , water flow , control (management) , flow (mathematics) , environmental science , environmental economics , engineering , mechanical engineering , sustainability , environmental engineering , mathematics , artificial intelligence , waste management , ecology , biology , operating system , quantum mechanics , statistics , botany , physics , electrical engineering , economics , geometry
Summary Cooling water systems (CWS) are one of the main energy and water using operations in industry. Existing CWS in operation provide high improvement potentials in environmental and economic performance through optimized operation and system control. Industry often fails to realize these potentials, given that the efficiency measures as well as their technical, economic, and ecological impact are mostly unknown because of the lack of appropriate approaches. This article presents a holistic approach to the systematic identification and assessment of efficiency measures that support industry in improving the operation and system control of large‐scale CWS consisting of one or multiple cooling towers, heat exchangers, and pumps. Based on material flow analysis coupled with process modeling, a material and energy flow model of CWS is developed. The model enables the investigation of different adjustments in operation of CWS in order to identify and assess specific efficiency measures. The approach is applied to a CWS of a real manufacturing facility. The results show, first, high validity of the approach as compared to a real system. Second, the effectiveness of the approach, given that the model allows fast and simple identification and assessment of efficiency measures that save up to 16% energy and 24% water in the presented case study.