System-level energy consumption modeling and optimization for cellulosic biofuel production

2018 ◽  
Vol 226 ◽  
pp. 935-946 ◽  
Author(s):  
Yuntian Ge ◽  
Lin Li
Keyword(s):  
Energy Consumption ◽  
Biofuel Production ◽  
System Level ◽  
Level Energy ◽  
Modeling And Optimization ◽  
Cellulosic Biofuel ◽  
Energy Consumption Modeling

scholarly journals Model-Based Design of Energy-Efficient Human Activity Recognition Systems with Wearable Sensors

Technologies ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 89
Author(s):  
Florian Grützmacher ◽  
Albert Hein ◽  
Thomas Kirste ◽  
Christian Haubelt
Keyword(s):  
Energy Consumption ◽  
Activity Recognition ◽  
Human Activity ◽  
Energy Efficient ◽  
Human Activity Recognition ◽  
Sensor Data ◽  
System Level ◽  
Estimation Methods ◽  
Level Energy ◽  
Wearable Sensor

The advances in MEMS technology development allow for small and thus unobtrusive designs of wearable sensor platforms for human activity recognition. Multiple such sensors attached to the human body for gathering, processing, and transmitting sensor data connected to platforms for classification form a heterogeneous distributed cyber-physical system (CPS). Several processing steps are necessary to perform human activity recognition, which have to be mapped to the distributed computing platform. However, the software mapping is decisive for the CPS’s processing load and communication effort. Thus, the mapping influences the energy consumption of the CPS, and its energy-efficient design is crucial to prolong battery lifetimes and allow long-term usage of the system. As a consequence, there is a demand for system-level energy estimation methods in order to substantiate design decisions even in early design stages. In this article, we propose to combine well-known dataflow-based modeling and analysis techniques with energy models of wearable sensor devices, in order to estimate energy consumption of wireless sensor nodes for online activity recognition at design time. Our experiments show that a reasonable system-level average accuracy above 97% can be achieved by our proposed approach.

scholarly journals “Demand Control” an Innovative Way of Reducing the HVAC System’s Energy Consumption

Buildings ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 488
Author(s):  
Rand Talib ◽  
Nabil Nassif
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Optimization Technique ◽  
Comfort Level ◽  
Optimization Process ◽  
System Level ◽  
Time Zone ◽  
Modeling And Optimization ◽  
Automation Systems ◽  
Demand Control

According to EIA, the Heating Ventilation and Air Conditioning (HAVC) systems account for about 25% of the U.S.’s total commercial building’s energy use. Therefore, advanced modeling and optimization methods of the system components and operation offer great ways to reduce energy consumption in all types of buildings and mainly commercial buildings. This research introduced an innovative integrated two-level optimization technique for the HVAC system to reduce the total energy consumption while improving the indoor thermal comfort level. The process uses actual system performance data collected for the building automation systems (BAS) to create accurate component modeling and optimization process as the first level of optimization (MLO). Artificial neural networks were chosen to be the tool used to serve the process of modeling. The second optimization level utilizes the whole system-level optimization technique (SLO) using a genetic algorithm (G.A.). The proposed two-levels optimization technique will optimize the system setpoints, the supply air temperature, duct static pressure, minimum zone air flowrates, and minimum outdoor air ventilation rate. The proposed technique has contributed to the field of modeling and optimization of HVAC systems through several new contributions. (1) Implementing the demand control methodology with the optimization process to modify the electricity consumption power profile when the demand signal is received. (2) Implement the occupancy schedule inputs into the optimization process to adjust the ventilation airflow rates accordingly. (3) Implement the real-time zone occupancy sensor readings and adjust the zone’s ventilation flowrates and minimum flowrates. (4) Lastly, implementing the method of zone minimum air flowrates setpoint rests to reduce reheat requirements. The proposed optimization process was tested and validated, resulting in savings in the total energy consumed by the chilled water VAV system by 13.4%, 22.4 %, followed by 31% for July, February, and October, respectively.

scholarly journals Cellulosic biofuel production using emulsified simultaneous saccharification and fermentation (eSSF) with conventional and thermotolerant yeasts

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Shannon M. Hoffman ◽  
Maria Alvarez ◽  
Gilad Alfassi ◽  
Dmitry M. Rein ◽  
Sergio Garcia-Echauri ◽  
...  
Keyword(s):  
Simultaneous Saccharification And Fermentation ◽  
Agricultural Waste ◽  
Biofuel Production ◽  
Cellulosic Biofuels ◽  
Processing Times ◽  
Cellulosic Biofuel ◽  
Thermotolerant Yeasts ◽  
Rapid Hydrolysis ◽  
Dedicated Energy Crops ◽  
Simultaneous Saccharification

Abstract Background Future expansion of corn-derived ethanol raises concerns of sustainability and competition with the food industry. Therefore, cellulosic biofuels derived from agricultural waste and dedicated energy crops are necessary. To date, slow and incomplete saccharification as well as high enzyme costs have hindered the economic viability of cellulosic biofuels, and while approaches like simultaneous saccharification and fermentation (SSF) and the use of thermotolerant microorganisms can enhance production, further improvements are needed. Cellulosic emulsions have been shown to enhance saccharification by increasing enzyme contact with cellulose fibers. In this study, we use these emulsions to develop an emulsified SSF (eSSF) process for rapid and efficient cellulosic biofuel production and make a direct three-way comparison of ethanol production between S. cerevisiae, O. polymorpha, and K. marxianus in glucose and cellulosic media at different temperatures. Results In this work, we show that cellulosic emulsions hydrolyze rapidly at temperatures tolerable to yeast, reaching up to 40-fold higher conversion in the first hour compared to microcrystalline cellulose (MCC). To evaluate suitable conditions for the eSSF process, we explored the upper temperature limits for the thermotolerant yeasts Kluyveromyces marxianus and Ogataea polymorpha, as well as Saccharomyces cerevisiae, and observed robust fermentation at up to 46, 50, and 42 °C for each yeast, respectively. We show that the eSSF process reaches high ethanol titers in short processing times, and produces close to theoretical yields at temperatures as low as 30 °C. Finally, we demonstrate the transferability of the eSSF technology to other products by producing the advanced biofuel isobutanol in a light-controlled eSSF using optogenetic regulators, resulting in up to fourfold higher titers relative to MCC SSF. Conclusions The eSSF process addresses the main challenges of cellulosic biofuel production by increasing saccharification rate at temperatures tolerable to yeast. The rapid hydrolysis of these emulsions at low temperatures permits fermentation using non-thermotolerant yeasts, short processing times, low enzyme loads, and makes it possible to extend the process to chemicals other than ethanol, such as isobutanol. This transferability establishes the eSSF process as a platform for the sustainable production of biofuels and chemicals as a whole.

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