Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies

Hybrid Renewable Power Systems for the Mining Industry: System Costs, Reliability Costs, and Portfolio Cost Risks

The mineral sector is responsible for more than 38% of total industrial energy use and 11% of total final energy consumption. A rising trend in the industry is the search for cleaner, less carbon-intensive and more efficient energy technologies that can also bring new business opportunities to the industry. Evidence suggests that the inclusion of energy storage and renewables alongside traditional fuel-based power alternatives can both reduce generation costs and carbon emissions in off-grid and distributed power systems. Previous research has quantified this outcome for other industrial and domestic sectors but little investigation has taken place to characterise the potential of hybrid systems in mining settings. The interest of this research is to assess the economic potential of hybrid renewable systems and evaluate the trade-offs associated with the context-dependent factors of the mining industry. An energy optimisation model, named HELiOS-Mining, was developed in order to account for these factors, and search for the least-cost generation alternatives in relation to technical characteristics (i.e. storage strategies, dispatch, demand-shifting, reliability requirements, fuel-mix), economic specificities (i.e. value of lost load, portfolio cost risk, financing), and spatial factors (i.e. access to resources, climate). Three major mining regions are investigated, including: grid-connected and off-grid mining in Northern Chile as well as off-grid mining in North-Western Australia and Yukon, Canada. The results of this research allow important insights to be made into the economics of hybridised power systems in mining settings. Research findings have identified that hybrid renewable power systems can generate life-cycle cost savings of up to 57% and carbon savings of up to 82% (against diesel or grid power baselines). Power systems that feature a renewable penetration of 60 to 85% of total capacity have the lowest costs in three out of four selected mines. Furthermore, portfolio analysis has demonstrated that such power systems can help reducing the cost risk of the industry associated with fuel price variations and carbon policies. Results also illustrate how assumptions about risk factors can drive large shifts in optima, and that concentrated solar power could be a key enabling technology for reducing the emissions of the mining industry

Early growth technology analysis : case studies in solar energy and geothermal energy

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 85-87).Public and private organizations try to forecast the future of technological developments and allocate funds accordingly. Based on our interviews with experts from MIT's Entrepreneurship Center, Sloan School of Management, and IBM, and review of literature, we found out that this important fund allocation process is dominated by reliance on expert opinions, which has important drawbacks alongside its advantages. In this Thesis, we introduce a data-driven approach, called early growth technology analysis, to technology forecasting that utilizes diverse information sources to analyze the evolution of promising new technologies. Our approach is based on bibliometric analysis, consisting of three key steps: extraction of related keywords from online publication databases, determining the occurrence frequencies of these keywords, and identifying those exhibiting rapid growth. Our proposal goes beyond the theoretical level, and is embodied in software that collects the required inputs from the user through a visual interface, extracts data from web sites on the fly, performs an analysis on the collected data, and displays the results. Compared to earlier software within our group, the new interface offers a much improved user experience in performing the analysis. Although these methods are applicable to any domain of study, this Thesis presents results from case studies on the fields of solar and geothermal energy. We identified emerging technologies in these specific fields to test the viability of our results. We believe that data-driven approaches, such as the one proposed in this Thesis, will increasingly be used by policy makers to complement, verify, and validate expert opinions in mapping practical goals into basic/applied research areas and coming up with technology investment decisions.by Ayse Kaya Firat.S.M.in Technology and Polic

Multifurnace optimization in electric smelting plants via load scheduling and control

For large electricity users, such as smelting plants, their electric loads cannot exceed a concerted limit in production. Traditional single-furnace optimization methods aim to satisfy the electric demand of a furnace to improve its production, and hence cannot consider the maximum demand constraint in a smelting plant. Maximum demand (MD) control is often utilized to keep the total electric demand within the limit via shedding the electric loads of some furnaces once the demand approaches the limit. However, the control method will enlarge the fluctuation of electric loads, which does harm to the production and causes a decline in energy-efficiency. In this paper, we propose a multifurnace optimization strategy to improve the production targets of a whole plant instead of a single furnace. In the strategy, an offline multiobjective load scheduling is first performed to assign electric loads for furnaces in each sampling period, taking into account of the MD constraint and production constraints. A multiobjective particle swarm optimization algorithm, combined with population initialization and constraint-handing strategies, is proposed to search for the Pareto optimal set of the scheduling problem, from which decision-makers can select one solution as the load scheduling program. A double closed-loop control mechanism is used to change the scheduled load into detailed load setpoints of furnaces and keep the actual loads up with the load setpoints. In the outer loop, the detailed load setpoints of furnaces are dynamically adjusted based on the deviation of actual loads from the scheduled loads. Thereafter, the desired setpoints are sent to the automatic control mechanism of each furnace, which is in the inner loop and responsible to keep the actual load up with the setpoint via a proportional-integral-derivative (PID) controller. The case study on a typical magnesia-smelting plant shows that the proposed multifurnace optimization strategy can achieve an increase of- about 12.29% in the production output, an improvement of about 0.46% of the magnesia in the product, and a slight reduction of 2.35% in electricity cost over the results of MD control

Proceedings of the 10th International Chemical and Biological Engineering Conference - CHEMPOR 2008

This volume contains full papers presented at the 10th International Chemical and Biological Engineering Conference - CHEMPOR 2008, held in Braga, Portugal, between September 4th and 6th, 2008.FC

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року

Second International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2021). Kryvyi Rih, Ukraine, May 19-21, 2021.Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року