Abstract
Optimal steam process drive sizing is crucial for efficient and sustainable operation of energy-intense industries. Recent years have brought several methods assessing this problem, which differ in complexity and user-friendliness. In this paper, a novel complex method was developed and presented and its superiority over other approaches was documented on an industrial case study. Both the process-side and steam-side characteristics were analyzed to obtain correct model input data: Driven equipment performance and efficiency maps were considered, off-design and seasonal operation was studied, and steam network topology was included. Operational data processing and sizing calculations were performed in a linked MATLAB®–Aspen Plus® environment, exploiting the strong sides of both software tools. The case study aimed to replace a condensing steam turbine by a backpressure one, revealing that: 1. Simpler methods neglecting frictional pressure losses and off-design turbine operation efficiency loss undersized the drive and led to unacceptable loss of deliverable power to the process; 2. the associated process production loss amounted up to 20%; 3. existing bottlenecks in refinery steam pipelines operation were removed; however, new ones were created; and 4. the effect on the marginal steam source operation may vary seasonally. These findings accentuate the value and viability of the presented method.
Highlights
Cogeneration and polygeneration systems are an essential part of industrial production of materials and energies, consuming or generating heat, electricity, mechanical, and chemical energy [1,2]
Starting with techno-economic studies optimizing the efficiency of a single equipment unit [24,27,30,34,35], through steam consumption optimization in a single production unit [25,32,38,39], and cogeneration potential exploitation [19,33,36,40,41] to total site heat and power integration [20,21,22,23,28,33,37,42], Processes 2020, 8, 1495; doi:10.3390/pr8111495
Steam system topology and the impact of pressure and heat losses from steam pipelines on optimal cogeneration system sizing and operation has been addressed in several papers [22,37,43,44,45], but most studies consider neither off-design operation of steam turbines nor variable steam pressure levels as important aspects in the optimization procedure
Summary
Cogeneration and polygeneration systems are an essential part of industrial production of materials and energies, consuming or generating heat, electricity, mechanical, and chemical energy [1,2].Ambitious efforts of national and European institutions to reduce greenhouse gases emissions and to ensure sustainable industrial production [3,4,5,6,7,8,9] at the same time cannot be successfully met without increasing material and energy efficiency of the industry [10,11,12,13] by simultaneous energy, economic, environmental, and risk and safety optimization [14,15,16] of existing industrial cogeneration and polygeneration systems [17,18].Efficient steam production, and its transport and use for both process heating and polygeneration purposes, has been targeted on various complexity levels in numerous recent studies [19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38]. Cogeneration and polygeneration systems are an essential part of industrial production of materials and energies, consuming or generating heat, electricity, mechanical, and chemical energy [1,2]. Ambitious efforts of national and European institutions to reduce greenhouse gases emissions and to ensure sustainable industrial production [3,4,5,6,7,8,9] at the same time cannot be successfully met without increasing material and energy efficiency of the industry [10,11,12,13] by simultaneous energy, economic, environmental, and risk and safety optimization [14,15,16] of existing industrial cogeneration and polygeneration systems [17,18]. A systematic method comprising characteristics of a real steam system operation [35,46] (variable pipeline loads, steam pressures, and temperatures) as well as real process steam/work demands has the potential to fill the knowledge and experience the gap between the modeling approach in utility systems’ optimization and real steam system operation
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