scholarly journals Multi-Objective Sustainability Optimization of Biomass Residues to Ethanol via Gasification and Syngas Fermentation: Trade-Offs between Profitability, Energy Efficiency, and Carbon Emissions

Fermentation ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. 201
Author(s):  
Elisa M. de Medeiros ◽  
Henk Noorman ◽  
Rubens Maciel Filho ◽  
John A. Posada
Keyword(s):  
Energy Efficiency ◽  
Sugarcane Bagasse ◽  
Carbon Footprint ◽  
Water Footprint ◽  
Ethanol Yield ◽  
Selling Price ◽  
Syngas Fermentation ◽  
Multi Objective ◽  
Trade Offs ◽  
Input Variables

This work presents a strategy for optimizing the production process of ethanol via integrated gasification and syngas fermentation, a conversion platform of growing interest for its contribution to carbon recycling. The objective functions (minimum ethanol selling price (MESP), energy efficiency, and carbon footprint) were evaluated for the combinations of different input variables in models of biomass gasification, energy production from syngas, fermentation, and ethanol distillation, and a multi-objective genetic algorithm was employed for the optimization of the integrated process. Two types of waste feedstocks were considered, wood residues and sugarcane bagasse, with the former leading to lower MESP and a carbon footprint of 0.93 USD/L and 3 g CO2eq/MJ compared to 1.00 USD/L and 10 g CO2eq/MJ for sugarcane bagasse. The energy efficiency was found to be 32% in both cases. An uncertainty analysis was conducted to determine critical decision variables, which were found to be the gasification zone temperature, the split fraction of the unreformed syngas sent to the combustion chamber, the dilution rate, and the gas residence time in the bioreactor. Apart from the abovementioned objectives, other aspects such as water footprint, ethanol yield, and energy self-sufficiency were also discussed.

Green Communications

2013 ◽  
pp. 134-155
Author(s):  
Haris I. Volos ◽  
Dinesh Datla ◽  
Xuetao Chen ◽  
An He ◽  
Ashwin Amanna ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Carbon Footprint ◽  
Low Carbon ◽  
Wireless Devices ◽  
Green Communications ◽  
Trade Offs ◽  
Common Goals ◽  
Definition Of ◽  
Key Techniques ◽  
Wireless Infrastructure

The exponential growth of wireless systems makes their carbon footprint hard to ignore. This chapter presents statistics related to the energy consumption of cellular networks’ infrastructure in order to motivate the need for more efficient and environmentally friendly communications. A definition of the term “Green Communications” is provided along with different metrics that can be used to quantify energy efficiency for the various aspects of wireless infrastructure. In addition to topics related to cellular infrastructure, the chapter presents a brief review of key techniques that can be potentially used for improving energy efficiency. Furthermore, since improving energy efficiency is not by itself sufficient for low-carbon systems, possible ways of using and managing energy harvested from renewable sources such as solar and ambient RF signals are discussed. Moreover, the concept of Wireless Distributed Computing is introduced to illustrate how a group of wireless devices can share their resources for achieving a set of common goals. Finally, resource allocation is examined for managing the trade-offs involved when simultaneously minimizing the carbon footprint and performing the necessary communication and computation tasks in mobile devices.

Multi-Objective Optimization in Industrial Robotic Cell Design

2010 ◽  
Author(s):  
Xiaolong Feng ◽  
Daniel Wa¨ppling ◽  
Hans Andersson ◽  
Johan O¨lvander ◽  
Mehdi Tarkian
Keyword(s):  
Energy Efficiency ◽  
Optimal Design ◽  
Cycle Time ◽  
Industrial Robot ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Trade Offs ◽  
Robotic Cells ◽  
Time And Energy ◽  
Robot Cell

It has become a common practice to conduct simulation-based design of industrial robotic cells, where Mechatronic system model of an industrial robot is used to accurately predict robot performance characteristics like cycle time, critical component lifetime, and energy efficiency. However, current robot programming systems do not usually provide functionality for finding the optimal design of robotic cells. Robot cell designers therefore still face significant challenge to manually search in design space for achieving optimal robot cell design in consideration of productivity measured by the cycle time, lifetime, and energy efficiency. In addition, robot cell designers experience even more challenge to consider the trade-offs between cycle time and lifetime as well as cycle time and energy efficiency. In this work, utilization of multi-objective optimization to optimal design of the work cell of an industrial robot is investigated. Solution space and Pareto front are obtained and used to demonstrate the trade-offs between cycle-time and critical component lifetime as well as cycle-time and energy efficiency of an industrial robot. Two types of multi-objective optimization have been investigated and benchmarked using optimal design problem of robotic work cells: 1) single-objective optimization constructed using Weighted Compromise Programming (WCP) of multiple objectives and 2) Pareto front optimization using multi-objective generic algorithm (MOGA-II). Of the industrial robotics significance, a combined design optimization problem is investigated, where design space consisting of design variables defining robot task placement and robot drive-train are simultaneously searched. Optimization efficiency and interesting trade-offs have been explored and successful results demonstrated.

Green Communications

2013 ◽  
pp. 495-516
Author(s):  
Haris I. Volos ◽  
Dinesh Datla ◽  
Xuetao Chen ◽  
An He ◽  
Ashwin Amanna ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Carbon Footprint ◽  
Low Carbon ◽  
Wireless Devices ◽  
Green Communications ◽  
Trade Offs ◽  
Common Goals ◽  
Definition Of ◽  
Key Techniques ◽  
Wireless Infrastructure

The exponential growth of wireless systems makes their carbon footprint hard to ignore. This chapter presents statistics related to the energy consumption of cellular networks' infrastructure in order to motivate the need for more efficient and environmentally friendly communications. A definition of the term “Green Communications” is provided along with different metrics that can be used to quantify energy efficiency for the various aspects of wireless infrastructure. In addition to topics related to cellular infrastructure, the chapter presents a brief review of key techniques that can be potentially used for improving energy efficiency. Furthermore, since improving energy efficiency is not by itself sufficient for low-carbon systems, possible ways of using and managing energy harvested from renewable sources such as solar and ambient RF signals are discussed. Moreover, the concept of Wireless Distributed Computing is introduced to illustrate how a group of wireless devices can share their resources for achieving a set of common goals. Finally, resource allocation is examined for managing the trade-offs involved when simultaneously minimizing the carbon footprint and performing the necessary communication and computation tasks in mobile devices.

Carbon footprint and water footprint assessment of virgin and recycled polyester textiles

2021 ◽  
pp. 004051752110062
Author(s):  
Weiran Qian ◽  
Xiang Ji ◽  
Pinghua Xu ◽  
Laili Wang
Keyword(s):  
Production Process ◽  
Environmental Impacts ◽  
Carbon Footprint ◽  
Water Scarcity ◽  
Water Footprint ◽  
Oxygen Demand ◽  
Polyester Fabric ◽  
Total Carbon ◽  
Fabric Production ◽  
Water Eutrophication

Recycled polyester textile fibers stemming from waste polyester material have been applied in the textile industry in recent years. However, there are few studies focusing on the evaluation and comparison of the environmental impacts caused by the production of virgin polyester textiles and recycled polyester textiles. In this study, the carbon footprint and water footprint of virgin polyester textiles and recycled polyester textiles were calculated and compared. The results showed that the carbon footprint of the virgin polyester textiles production was 119.59 kgCO2/100 kg. Terephthalic acid production process occupied the largest proportion, accounting for 45.83%, followed by polyester fabric production process, ethylene production process, paraxylene production process, ethylene glycol production process and polyester fiber production process. The total carbon footprint of waste polyester recycling was 1154.15 kgCO2/100 kg, approximately ten times that of virgin polyester textiles production. As for the water footprint, it showed that virgin polyester fabric production and recycled polyester fabric production both had great impact on water eutrophication and water scarcity. Chemical oxygen demand caused the largest water eutrophication footprint, followed by ammonia-nitrogen and five-day biochemical oxygen demand. The water scarcity footprint of virgin polyester fabric production and recycled polyester fabric production was 5.98 m3 H2Oeq/100 kg and 1.90 m3 H2Oeq/100 kg, respectively. The comprehensive evaluation of carbon footprint and water footprint with the life cycle assessment polygon method indicated that the polyester fabric production process exhibited greater environmental impacts both for virgin polyester and recycled polyester.

scholarly journals Characterizing Color Quality, Damage to Artwork, and Light Intensity of Multi-Primary LEDs for Museums

Heritage ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 188-197
Author(s):  
Dorukalp Durmus
Keyword(s):  
Energy Efficiency ◽  
Appearance Model ◽  
Light Sources ◽  
Great Flexibility ◽  
Oil Paintings ◽  
Damage Reduction ◽  
Output Variability ◽  
Color Quality ◽  
Trade Offs

Light causes damage when it is absorbed by sensitive artwork, such as oil paintings. However, light is needed to initiate vision and display artwork. The dilemma between visibility and damage, coupled with the inverse relationship between color quality and energy efficiency, poses a challenge for curators, conservators, and lighting designers in identifying optimal light sources. Multi-primary LEDs can provide great flexibility in terms of color quality, damage reduction, and energy efficiency for artwork illumination. However, there are no established metrics that quantify the output variability or highlight the trade-offs between different metrics. Here, various metrics related to museum lighting (damage, the color quality of paintings, illuminance, luminous efficacy of radiation) are analyzed using a voxelated 3-D volume. The continuous data in each dimension of the 3-D volume are converted to discrete data by identifying a significant minimum value (unit voxel). Resulting discretized 3-D volumes display the trade-offs between selected measures. It is possible to quantify the volume of the graph by summing unique voxels, which enables comparison of the performance of different light sources. The proposed representation model can be used for individual pigments or paintings with numerous pigments. The proposed method can be the foundation of a damage appearance model (DAM).

scholarly journals An integrated life cycle and water footprint assessment of nonfood crops based bioenergy production

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jun Li ◽  
Fengyin Xiong ◽  
Zhuo Chen
Keyword(s):  
Life Cycle ◽  
Environmental Sustainability ◽  
Large Scale ◽  
Water Footprint ◽  
Arable Land ◽  
Integrated Analysis ◽  
Actual Performance ◽  
Bioenergy Production ◽  
Trade Offs ◽  
Hybrid Pennisetum

AbstractBiomass gasification, especially distribution to power generation, is considered as a promising way to tackle global energy and environmental challenges. However, previous researches on integrated analysis of the greenhouse gases (GHG) abatement potentials associated with biomass electrification are sparse and few have taken the freshwater utilization into account within a coherent framework, though both energy and water scarcity are lying in the central concerns in China’s environmental policy. This study employs a Life cycle assessment (LCA) model to analyse the actual performance combined with water footprint (WF) assessment methods. The inextricable trade-offs between three representative energy-producing technologies are explored based on three categories of non-food crops (maize, sorghum and hybrid pennisetum) cultivated in marginal arable land. WF results demonstrate that the Hybrid pennisetum system has the largest impact on the water resources whereas the other two technology options exhibit the characteristics of environmental sustainability. The large variances in contribution ratio between the four sub-processes in terms of total impacts are reflected by the LCA results. The Anaerobic Digestion process is found to be the main contributor whereas the Digestate management process is shown to be able to effectively mitigate the negative environmental impacts with an absolute share. Sensitivity analysis is implemented to detect the impacts of loss ratios variation, as silage mass and methane, on final results. The methane loss has the largest influence on the Hybrid pennisetum system, followed by the Maize system. Above all, the Sorghum system demonstrates the best performance amongst the considered assessment categories. Our study builds a pilot reference for further driving large-scale project of bioenergy production and conversion. The synergy of combined WF-LCA method allows us to conduct a comprehensive assessment and to provide insights into environmental and resource management.

scholarly journals A Comparison of Genetic Representations and Initialisation Methods for the Multi-objective Shortest Path Problem on Multigraphs

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Lilla Beke ◽  
Michal Weiszer ◽  
Jun Chen
Keyword(s):  
Shortest Path ◽  
Time Budget ◽  
Exact Algorithm ◽  
Simple Graph ◽  
Shortest Path Problem ◽  
Future Application ◽  
Multi Objective ◽  
Trade Offs ◽  
Conflicting Objectives ◽  
Problem Instances

AbstractThis paper compares different solution approaches for the multi-objective shortest path problem (MSPP) on multigraphs. Multigraphs as a modelling tool are able to capture different available trade-offs between objectives for a given section of a route. For this reason, they are increasingly popular in modelling transportation problems with multiple conflicting objectives (e.g., travel time and fuel consumption), such as time-dependent vehicle routing, multi-modal transportation planning, energy-efficient driving, and airport operations. The multigraph MSPP is more complex than the NP-hard simple graph MSPP. Therefore, approximate solution methods are often needed to find a good approximation of the true Pareto front in a given time budget. Evolutionary algorithms have been successfully applied for the simple graph MSPP. However, there has been limited investigation of their applications to the multigraph MSPP. Here, we extend the most popular genetic representations to the multigraph case and compare the achieved solution qualities. Two heuristic initialisation methods are also considered to improve the convergence properties of the algorithms. The comparison is based on a diverse set of problem instances, including both bi-objective and triple objective problems. We found that the metaheuristic approach with heuristic initialisation provides good solutions in shorter running times compared to an exact algorithm. The representations were all found to be competitive. The results are encouraging for future application to the time-constrained multigraph MSPP.

scholarly journals Multi-Objective Optimization of Autonomous Microgrids with Reliability Consideration

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4466
Author(s):  
Maël Riou ◽  
Florian Dupriez-Robin ◽  
Dominique Grondin ◽  
Christophe Le Loup ◽  
Michel Benne ◽  
...  
Keyword(s):  
Power Systems ◽  
Rural Areas ◽  
Energy System ◽  
Design Stage ◽  
Multi Objective Optimization ◽  
Renewable Energy Resources ◽  
Nsga Ii ◽  
Renewable Integration ◽  
Multi Objective ◽  
Trade Offs

Microgrids operating on renewable energy resources have potential for powering rural areas located far from existing grid infrastructures. These small power systems typically host a hybrid energy system of diverse architecture and size. An effective integration of renewable energies resources requires careful design. Sizing methodologies often lack the consideration for reliability and this aspect is limited to power adequacy. There exists an inherent trade-off between renewable integration, cost, and reliability. To bridge this gap, a sizing methodology has been developed to perform multi-objective optimization, considering the three design objectives mentioned above. This method is based on the non-dominated sorting genetic algorithm (NSGA-II) that returns the set of optimal solutions under all objectives. This method aims to identify the trade-offs between renewable integration, reliability, and cost allowing to choose the adequate architecture and sizing accordingly. As a case study, we consider an autonomous microgrid, currently being installed in a rural area in Mali. The results show that increasing system reliability can be done at the least cost if carried out in the initial design stage.

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