Highlights We develop a research framework for energy-efficient scheduling (EES) Energetic coverage, energy-supply and energy-demand are main EES categories We categorize the current state of literature into the developed framework Numerical benefits of EES approaches with real-world case studies are presented ABSTRACT Because sustainable scheduling is attracting increasing amounts of attention from many manufacturing companies and energy is a central concern regarding sustainability, the purpose of this paper is to develop a research framework for "energy-efficient scheduling" (EES). EES approaches are scheduling approaches that have the objective of improving energy efficiency.Based on an iterative methodology, we review, analyze, and synthesize the current state of the literature and propose a completely new research framework to structure the research field. In doing so, the three dimensions "energetic coverage", "energy supply", and "energy demand" are introduced and used to classify the literature. Each of these dimensions contains categories and attributes to specify energy-related characteristics that are relevant for EES. We further provide an empirical analysis of the reviewed literature and emphasize the benefits that can be achieved by EES in practice.
One possibility for electrification of road transport consists of battery electric vehicles in combination with carbon-free sources of electricity. It is highly likely that lithium-ion batteries will provide the basis for this development. In the present paper, we use a recently developed, semi-quantitative assessment scheme to evaluate the relative supply risks associated with the elements used in the functional materials of six different lithium-ion battery types. Eleven different indicators in four supply risk categories are applied to each element; the weighting of the indicators is determined by external experts within the framework of an Analytic Hierarchy Process. The range of supply risk values on the elemental level is distinctly narrower than in our previous work on photovoltaic materials. The highest values are obtained for lithium and cobalt; the lowest for aluminium and titanium. Copper, iron, nickel, carbon (graphite), manganese and phosphorous form the middle group. We then carry out the assessment of the six battery types, to give comparative supply risks at the technology level. For this purpose the elemental supply risk values are aggregated using four different methods. Due to the small spread at the elemental level the supply risk values in all four aggregation methods also lie in a narrow range. Removing lithium, aluminium and phosphorous from the analysis, which are present in all types of battery, improves the situation. For aggregation with the simple arithmetic mean, an uncertainty analysis shows that only lithium-iron phosphate has a measurably lower supply risk compared to the other battery types. For the “cost-share” aggregation using seven elements, lithium cobalt oxide has a substantially higher supply risk than most other types
There is a growing concern over the security and sustainable supply of raw material among businesses and governments of developed, material-intensive countries. This has led to the development of a systematic analysis of risk incorporated with raw materials usage, often referred as criticality assessment. In principle, this concept is based on the material flow approach. The potential role of life cycle assessment (LCA) to integrate resource criticality through broadening its scope into the life cycle sustainability assessment (LCSA) framework has been discussed within the LCA communities for some time. In this article, we aim at answering the question of how to proceed toward integration of the geopolitical aspect of resource criticality into the LCSA framework. The article focuses on the assessment of the geopolitical supply risk of 14 resources imported to the seven major advanced economies and the five most relevant emerging countries. Unlike a few previous studies, we propose a new method of calculation for the geopolitical supply risk, which is differentiated by countries based on the import patterns instead of a global production distribution. Our results suggest that rare earth elements, tungsten, antimony, and beryllium generally pose high geopolitical supply risk. Results from the Monte Carlo simulation allow consideration of data uncertainties for result interpretation. Issues concerning the consideration of the full supply chain are exemplarily discussed for cobalt. Our research broadens the scope of LCA from only environmental performance to a resource supply-risk assessment tool that includes accessibility owing to political instability and market concentration under the LCSA framework.
Keywords:criticality assessment geopolitical supply risk industrial ecology life cycle assessment life cycle sustainability assessment resources
As a result of the global warming potential of fossil fuels there has been a rapid growth in the installation of photovoltaic generating capacity in the last decade. While this market is dominated by crystalline silicon, thin-film photovoltaics are still expected to make a substantial contribution to global electricity supply in future, due both to lower production costs and to recent increases in conversion efficiency. At present, cadmium telluride (CdTe) and copper-indium-gallium diselenide (CuInxGa1−xSe2) seem to be the most promising materials and currently have a share of ≈9% of the photovoltaic market. An expected stronger market penetration by these thin-film technologies raises the question as to the supply risks associated with the constituent elements. Against this background, we report here a semi-quantitative, relative assessment of mid- to long-term supply risk associated with the elements Cd, Te, Cu, In, Ga, Se and Mo. In this approach, the supply risk is measured using 11 indicators in the four categories “Risk of Supply Reduction”, “Risk of Demand Increase”, “Concentration Risk” and “Political Risk”. In a second step, the single indicator values, which are derived from publicly accessible databases, are weighted relative to each other specifically for the case of thin film photovoltaics. For this purpose, a survey among colleagues and an Analytic Hierarchy Process (AHP) approach are used, in order to obtain a relative, element-specific value for the supply risk. The aggregation of these elemental values (based on mass share, cost share, etc.) gives an overall value for each material. Both elemental and “technology material” supply risk scores are subject to an uncertainty analysis using Monte Carlo simulation. CdTe shows slightly lower supply risk values for all aggregation options
Highlights • This article proposes a characterization model for Geopolitical Supply Risk. • The characterization model is based on a socioeconomic cause-effect mechanism. • Supply risk is the multiple of probability and vulnerability. • Two embodiments of the characterization model are presented. • The methods are applied to conventional and electric vehicles.
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