Summary Key performance indicators (KPIs) are powerful tools that industries can use not only to monitor their activities but also to highlight their unexploited potential. Energy‐based KPIs are nowadays mostly used to evaluate industrial process performances. However, these indicators might present some limitations and might give misleading results in some circumstances. An example is represented by industrial processes that make use of different energy forms (eg, electricity and heat) and of different material inputs, and that are therefore difficult to compare in terms of energy. A further example can be found in the Carnot engine that, despite being ideal, can have quite low energy efficiency (eg, the energy efficiency of a Carnot engine working between 700 and 300 K is 57%), suggesting that its performance can be improved. The use of exergy‐based KPIs allows us to overcome many of the limitations of energy‐based indicators. The exergy efficiency of Carnot engines is 100%, clearly indicating that the system cannot be further improved. Moreover, the use of specific exergy consumption instead of specific energy consumption to monitor the performance of a process allows one to take into account possible differences in quality of material and energy streams. In the present work, exergy‐based KPIs for industrial use are reviewed. The paper outlines advantages and limitations of the reviewed indicators, with the scope of promoting their use in industry. A systematic use of exergy‐based KPIs not only gives a meaningful representation of process performances in terms of resource use but it can also direct efforts to improve the processes. To better understand their meaning under different circumstances, the revised indicators are applied to 3 industrial processes.

The Octavius FP7 project focuses on demonstration of CO 2 capture for zero emission power generation. As part of this work many partners are involved using different rate based simulation tools to develop tomorrow's new power plants. A benchmarking is performed, in order to synchronize accuracy and quality control the used modeling tools.The aim is to have 6 independent partners produce results on simulation tasks which are well defined in this work. The results show the performance of a typical simulation tool ranging from in-house process simulator to Aspen Plus® and combination of the two, using CAPE-Open. Definitions of the models are outlined describing the used assumptions on mass transfer correlations, hydraulics, thermodynamic models, kinetics, and property packages. A sensitivity study is carried out for absorption and desorption which shows the performance of capture percentage, specific reboiler duties, loading of rich and lean solutions, pressure drop, flooding, concentration and temperature profiles, product purity, and condenser performance. The overall conclusion is that most predicted properties vary in the order of 5-10% percent, often more than accuracy in experimental pilot plant measurements. There is a general good resemblance between modeling results. A few important properties like specific reboiler duty and reboiler temperature plus concentration and temperature profiles vary more than expected. Also high flooding scenarios in the stripper are difficult cases. Efficiencies are discussed as part of the summary. Recommendations for modeling principles and best practice are given.

The potential for increased energy utilisation and reduced carbon footprint has been investigated for the industrial park Mo Industri Park (MIP), located at Mo i Rana, Norway. Process data has been gathered to quantify the energy flows between industrial clients. The energy flows have been visualised quantitatively in Sankey diagrams, while the quality of the available energy is presented in the form of a grand composite curve. High temperature flue gas from ferrosilicon (FeSi) production at Elkem Rana represent the largest heat source available for utilisation. A theoretical assessment of potential applications for this energy is presented and includes: (1) electricity production; (2) local biocarbon production, where surplus heat is utilised for drying of wood chips; (3) post combustion carbon capture, where surplus heat is utilised for solvent regeneration. The results indicate that increasing the current energy recovery from 400 GWh to >640 GWh is realistic. The increase in energy recovery can be used for reducing the carbon footprint of the industrial park. Investment in a common utility network for surplus heat may lower the threshold for establishing other energy clients at MIP. These are possibilities which may be investigated in more detail in future work.

This study proposes a dynamic model that describes key characteristics of fermentative butanol production from glucose and xylose mixtures. The model has 12 parameters and incorporates noncompetitive inhibitory interaction between sugars as well as inhibitions due to high substrate and butanol concentrations. Different pre-growth strategies to achieve co-utilization of sugars were explored together with their effects on fermentation kinetics. Mixed sugar fermentation by the cultures pre-grown on a mixture of glucose and xylose showed a higher endurance to inhibition, a 2-fold increase in butanol production and a 1.5-fold increase in total sugar consumption compared to cultures pre-grown on xylose only. The average squared correlation coefficients (r 2 ) between experimental observations and model predictions were 0.917 and 0.926 for fermentations done by the cultures pre-grown on xylose only, and pregrown on a mixture of glucose and xylose, respectively. Sensitivity analysis on the model parameters revealed that the growth parameters were the most critical. The proposed model can serve as a basis for modeling of microbial butanol production from lignocellulosic biomass and be applied to other substrates and microorganisms.

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