Abstract: Chile has become one of the first few countries where renewable sources compete directly with conventional generation in price-based auctions. Moreover, the results of energy auctions during the last few years show a remarkable transition from conventional fossil fuels to renewable energies. In fact, the energy auction in 2017, to provide energy to customers from distribution companies, achieved a massive expansion in renewable technology at one of the lowest prices in the world. These positive results prompted the question if such results were permanent or temporal due to factors with limited effects. In this regard, this paper studies the key factors that drove the significant rise of renewable technologies in Chilean energy auctions, obtaining valuable lessons for regulators, not only in Chile, but also in the region and the world. For this purpose, we considered a well-proven method based on a hybrid multicriteria decision-making model to examine and prioritize the main drivers of the expansion of renewables in auctions. The results showed that some specific characteristics of the auction design, particularly the hourly supply blocks, the lead time for project construction, and contract duration, were the most significant drivers for the expansion of renewables in energy auctions. Moreover, the results showed that, provided that the auction design accommodates for such drivers, solar energy ends up as the most attractive technology in the Chilean auctions. The research also shows the main findings are robust by the application of a probabilistic sensitivity analysis.

Abstract: In this paper, initial steps are presented toward characterizing, quantifying, incorporating and communicating uncertainty applying a probabilistic analysis to countrywide emission baseline forecasts, using Chile as a case study. Most GHG emission forecasts used by regulators are based on bottom-up deterministic approaches. Uncertainty is usually incorporated through sensitivity analysis and/or use of different scenarios. However, much of the available information on uncertainty is not systematically included. The deterministic approach also gives a wide range of variation in values without a clear sense of probability of the expected emissions, making it difficult to establish both the mitigation contributions and the subsequent policy prescriptions for the future. To improve on this practice, we have systematically included uncertainty into a bottom-up approach, incorporating it in key variables that affect expected GHG emissions, using readily available information, and establishing expected baseline emissions trajectories rather than scenarios. The resulting emission trajectories make explicit the probability percentiles, reflecting uncertainties as well as possible using readily available information in a manner that is relevant to the decision making process. Additionally, for the case of Chile, contradictory deterministic results are eliminated, and it is shown that, whereas under a deterministic approach Chile's mitigation ambition does not seem high, the probabilistic approach suggests this is not necessarily the case. It is concluded that using a probabilistic approach allows a better characterization of uncertainty using existing data and modelling capacities that are usually weak in developing country contexts. Key policy insights Probabilistic analysis allows incorporating uncertainty systematically into key variables for baseline greenhouse gas emission scenario projections. By using probabilistic analysis, the policymaker can be better informed as to future emission trajectories. Probabilistic analysis can be done with readily available data and expertise, using the usual models preferred by policymakers, even in developing country contexts.

Abstract: In this paper, we consider a parallel machine scheduling problem in which machines have a limited workload capacity and jobs have deadlines and release dates. The problem is motivated by the operation of energy storage management systems for microgrids under emergency conditions and generalizes some problems that have already been studied in the literature for their theoretical value. In this work, we propose heuristic and exact algorithms to solve the problem. The heuristics are adaptations of classical bin packing heuristics in which additional conditions on the feasibility of a solution are imposed, whereas the exact method is a branch-and-price approach. The results show that the branch-andprice approach is able to optimally solve random instances with up to 250 jobs within a time limit of one hour, while the heuristic procedures provide near optimal solution within reduced running times. Finally, we also provide additional complexity results for a special case of the problem. (C) 2019 Elsevier Inc. All rights reserved.

Abstract: This paper shows how system design determines sustainability outcomes of cassava bioethanol production in Colombia. The recovery of the energy contained in by-products is recommended as compared to single product production. In particular, this study assesses the energy, greenhouse gases, water, and land use performance of alternative cassava cascades working at different scales, highlighting the implications of including anaerobic digestion technology in the chain. The centralized systems showed a poorer energy and greenhouse gases performance as compared to decentralized ones in part due to the artificial drying of cassava chips in the centralized facility. Under solar drying of cassava chips, systems with anaerobic digestion produced three to five times more energy than demanded and produced greenhouse gas savings of 0.3 kgCO(2eq) L EtOH-1. The water balance output depends upon the water reuse within the ethanol industry, which demands 21-23 L EtOH-1. In the anaerobic digestion scenarios, assuming liquid flows are treated separately, complete water recovery is feasible. Land use for cassava cultivation was calculated to be 0.27-0.35 ha tEtOH(-1). The energy and water content of the material to digest, the options for digestate reuse, and the recovery of the methane produced are major considerations substantially influencing the role of anaerobic digestion within cassava cascade configurations.

Abstract: The purpose of seismic provisions included in modern building codes is to obtain a satisfactory structural performance of buildings during earthquakes. However, in the United States and elsewhere, there are large inventories of buildings designed and constructed several decades ago, under outdated building codes. Some of these buildings are classified as non-ductile buildings. Currently, under the ATC-78 project, a methodology is being developed to identify seismically hazardous frame-wall buildings through a simple procedure that does not require full nonlinear analyses by the responsible engineer. This methodology requires the determination of the controlling plastic collapse mechanism, the base shear strength, and the ratio between the story drift ratio and the roof drift ratio, called parameter alpha, at collapse level. The procedure is calibrated with fully inelastic nonlinear analyses of archetype buildings. In this paper we first introduce an efficient scheme for modeling frame-wall buildings using the software OpenSees. Later, the plastic collapse mechanism, the base shear strength, and values of alpha are estimated from nonlinear static and dynamic analyses considering a large suite of ground-motion records that represent increasing hazard levels. The analytical experiment included several frame-wall combinations in 4 and 8-story buildings, intended to represent a broad range of conditions that can be found in actual buildings, where the simplified methodology to evaluate the risk of collapse can be applicable. Analysis results indicate that even walls of modest length may positively modify the collapse mechanism of nonductile bare frames preventing soft story failures.

Abstract: Doping twisted bilayer graphene away from charge neutrality leads to an enormous buildup of charge inhomogeneities within each moire unit cell. Here, we show, using unbiased real-space self-consistent Hartree calculations on a relaxed lattice, that Coulomb interactions smoothen this charge imbalance by changing the occupation of earlier identified “ring” orbitals in the AB/BA region and “center” orbitals at the AA region. For hole doping, this implies an increase of the energy of the states at the Gamma point, leading to a further flattening of the flat bands and a pinning of the Van Hove singularity at the Fermi level. The charge smoothening will affect the subtle competition between different possible correlated phases.

Abstract: The structure of biological communities is conventionally described as profiles of taxonomic units, whose ecological functions are assumed to be known or, at least, predictable. In environmental microbiology, however, the functions of a majority of microorganisms are unknown and expected to be highly dynamic and collectively redundant, obscuring the link between taxonomic structure and ecosystem functioning. Although genetic trait-based approaches at the community level might overcome this problem, no obvious choice of gene categories can be identified as appropriate descriptive units in a general ecological context. We used 247 microbial metagenomes from 18 biomes to determine which set of genes better characterizes the differences among biomes on the global scale. We show that profiles of oxidoreductase genes support the highest biome differentiation compared with profiles of other categories of enzymes, general protein-coding genes, transporter genes, and taxonomic gene markers. Based on oxidoreductases' description of microbial communities, the role of energetics in differentiation and particular ecosystem function of different biomes become readily apparent. We also show that taxonomic diversity is decoupled from functional diversity, e. g., grasslands and rhizospheres were the most diverse biomes in oxidoreductases but not in taxonomy. Considering that microbes underpin biogeochemical processes and nutrient recycling through oxidoreductases, this functional diversity should be relevant for a better understanding of the stability and conservation of biomes. Consequently, this approach might help to quantify the impact of environmental stressors on microbial ecosystems in the context of the global-scale biome crisis that our planet currently faces.

Abstract: Planning for new generation infrastructure in hydrothermal power systems requires consideration of a series of nonlinearities that are often ignored in planning models for policy analysis. In this article, three different capacity- planning models are used, one nonlinear and two linear ones, with different degrees of complexity, to quantify the impact of simplifying the head dependency of hydropower generation on investments in both conventional and renewable generators and system operations. It was found that simplified investment models can bias the optimal generation portfolios by, for example, understating the need for coal and combined-cycle gas units and overstating investments in wind capacity with respect to a more accurate nonlinear formulation, which could affect policy recommendations. It was also found that the economic cost of employing a simplified model can be below 10% of total system cost for most of the scenarios and system configurations analyzed, but as high as nearly 70% of total system cost for specific applications. Although these results are not general, they suggest that for certain system configurations both linear models can provide reasonable approximations to more complex nonlinear formulations. Uncertain water inflows were also considered using stochastic variants of all three planning models. Interestingly, if due to time or computational limitations only one of these two features could be accounted for, these results indicate that explicit modeling of the nonlinear-head effect in a deterministic model could yield better results (up to 0.6% of economic regret) than a stochastic linear model (up to 9.6% of economic regret) that considers the uncertainty of water inflows.