Modeling and Optimization of Quality Variability for Decision Support Systems in Biofuel Production

Biofuels are a promising alternative to fossil fuel depletion, due to their sustainable production from living or recently living organic matter (i.e., biomass). Biofuel production offers benefits that are not present in non-sustainable resources, like the reduction of air pollution. According to government agencies, biofuel production is expected to increase in the U.S. within the next few years because of government initiatives. In order to become a feasible alternative to satisfy market demand, biofuels require strategic improvements in areas such as supply chain management to deal with the variability within the biomass. Advanced analysis tools might be utilized to integrate biomass physical and chemical properties into the decision processes. This chapter introduces a principal component analysis (PCA) to determine significant factors that affect the operations within the supply chain and, later on, incorporates those factors in an optimization model for the decision analysis. The results show that incorporating quality-related properties has a significant impact in the solution of the optimization program

Algoritmo de búsqueda tabú para una variante del problema de coloración

El problema de coloración robusta generalizado (PCRG) resuelve problemas de horarios que consideran restricciones especiales. Al ser una generalización del problema de coloración robusta, que es a su vez una generalización del problema de coloración, el PCRG es entonces un problema NP-Completo, por lo que es necesario utilizar métodos aproximados para encontrar buenas soluciones en un tiempo de cómputo razonable. En este trabajo se presenta un algoritmo de búsqueda tabú para programar casos de 30 a 180 horas por semana, para algunos de ellos encuentra la solución óptima, en otros casos, la solución obtenida supera a la mejor solución conocida. También se presentan ejemplos de mayor tamaño a los conocidos, obteniendo resultados muy competitivos, lo que se puede verificar por la ausencia de conflicto entre clases

Algoritmo de búsqueda tabú para una variante del problema de coloración

El problema de coloración robusta generalizado (PCRG) resuelve problemas de horarios que consideran restricciones especiales. Al ser una generalización del problema de coloración robusta, que es a su vez una generalización del problema de coloración, el PCRG es entonces un problema NP-Completo, por lo que es necesario utilizar métodos aproximados para encontrar buenas soluciones en un tiempo de cómputo razonable. En este trabajo se presenta un algoritmo de búsqueda tabú para programar casos de 30 a 180 horas por semana, para algunos de ellos encuentra la solución óptima, en otros casos, la solución obtenida supera a la mejor solución conocida. También se presentan ejemplos de mayor tamaño a los conocidos, obteniendo resultados muy competitivos, lo que se puede verificar por la ausencia de conflicto entre clases

Simulation-Optimization Approach for the Logistics Network Design of Biomass Co-Firing with Coal at Power Plants

This work proposes a hybrid scheme that combines a simulation model and a mathematical programming model for designing logistic networks for co-firing biomass, specifically switchgrass, in conventional coal-fired power plants. The advantages of co-firing biomass include: (1) the creation of green jobs; (2) the efficient use of current power plant infrastructure; (3) fostering the penetration of renewable energy into power networks; and, (4) the reduction of greenhouse gas (GHG) emissions. The novelty of this work lies in the inclusion of (1) the inherent variability of biomass supply at the parcel level, and (2) the effects of climate change on future biomass supply when designing a feedstock logistic network. The design optimization is conducted at the farm/parcel level (most, if not all, previous works have used county level average data) and integrates the crop growth predictions employing United States Department of Agriculture’s (USDA’s) Agricultural Land Management with Numerical Assessment Criteria (ALMANAC) simulation model; the output of the simulations is input into the mixed integer linear programming (MILP) hub-and-spoke model to minimize the overall cost of the logistic network. Specifically, the MILP-based model selects the parcels and depot locations as well as biomass transportation flows by taking into consideration different types of soil, land cover characteristics, and predicted yields, which account for both historical and forecasted weather data. The hybrid methodology was tested by solving realistic situations, which considered varying weather conditions. The gross results indicate that the optimized logistic network enabled meeting a 20% biomass co-firing rate demand, which reduced 1,158,867 Mg per year in GHG emissions by co-firing with biomass

A Principal Component Analysis in Switchgrass Chemical Composition

In recent years, bioenergy has become a promising renewable energy source that can potentially reduce the greenhouse emissions and generate economic growth in rural areas. Gaining understanding and controlling biomass chemical composition contributes to an efficient biofuel generation. This paper presents a principal component analysis (PCA) that shows the influence and relevance of selected controllable factors over the chemical composition of switchgrass and, therefore, in the generation of biofuels. The study introduces the following factors: (1) storage days; (2) particle size; (3) wrap type; and (4) weight of the bale. Results show that all the aforementioned factors have an influence in the chemical composition. The number of days that bales have been stored was the most significant factor regarding changes in chemical components due to its effect over principal components 1 and 2 (PC1 and PC2, approximately 80% of the total variance). The storage days are followed by the particle size, the weight of the bale and the type of wrap utilized to enclose the bale. An increment in the number of days (from 75–150 days to 225 days) in storage decreases the percentage of carbohydrates by −1.03% while content of ash increases by 6.56%