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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A stochastic biomass blending problem in decentralized supply chains

Blending biomass materials of different physical or chemical properties provides an opportunity to adjust the quality of the feedstock to meet the specifications of the conversion platform. We propose a model which identifies the right mix of biomass to optimize the performance of the thermochemical conversion process at the mini-mum cost. This is a chance-constraint programming (CCP) model which takes into account the stochastic nature of biomass quality. The proposed CCP model ensures that process requirements, which are impacted by physical and chemical properties of biomass, are met most of the time. We consider two problem settings, a centralized and a decentralized supply chain. We propose a mixed-integer linear program to model the blending problem in the centralized setting and a bilevel program to model the blending problem in the decentralized setting. We use the sample average approximation method to approximate the chance constraints, and propose solution algorithms to solve this approximation. We develop a case study for South Carolina using data provided by the Billion Ton Study. Based on our results, the blends identified consist mainly of pine and softwood residues. The blends identified and the suppliers selected by both models are different. The cost of the centralized supply chain is 2%–6% lower. The implications of these results are twofold. First, these results could lead to improved collaborations in the supply chain. Second, these results provide an estimate of the approximation error from assuming centralized decision making in the supply chain.

09 BIOMASS FUELS↗
DOE OSTI2018

Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective

Feedstock price and availability are key challenges for biorefinery development and biomass blending has been suggested as a route to overcome these limitations. However, the impacts of feedstock blending on the variability of yields of hydrolyzed sugar remained unclear. This study quantifies the uncertainties in the sugar yields from the blends of corn stover, switchgrass, and grass clippings by considering both variable and model uncertainties. The results indicate that feedstock blending reduces the uncertainties in sugar yields and delivers feedstock of more uniform quality. A further investigation on xxx demonstrates that the reduction in overall uncertainty is achieved by reduced compositional uncertainties of blended feedstock. Based on these results, the optimization of blending ratios was performed with respect to three objectives: (1) probability of meeting the sugar yield target; (2) expected sugar yields; and (3) sugar yield per unit feedstock expense, while satisfying constraints of feedstock availability and cost. In conclusion, the optimization method developed in this study, is readily applied to other combinations of feedstocks, biofuels production processes, and constraints.

09 BIOMASS FUELS↗
DOE OSTI2020

Briquetting characteristics of woody and herbaceous biomass blends: Impact on physical properties, chemical composition, and calorific value

Abstract Intercropping (or polyculture) is gaining a lot of interest as it increases yields, allows better utilization of resources (water and nutrients), and provides better land management. The objective of this study is to understand the briquetting characteristics of woody and herbaceous biomass blends, which might result from intercropping. Tests were conducted on blends of lodgepole pine, switchgrass, and corn stover biomass using three hammer mill screen sizes (i.e., 4.8, 12.7, and 19.05 mm), three blend moistures (12%, 15%, and 18%, w.b.), and two‐ and three‐blend ratios (i.e., 1:1 and 1:1:1) using a pilot‐scale hydraulic briquette press. The briquette properties, such as unit and bulk density, durability rating after 5 days of storage (as they tend to attain stable density), and the energy consumption of the process were measured. The results indicate that moisture content of 12% and 15% (w.b.) and smaller hammer mill screen size of 4.8 mm increased the unit and bulk densities to >750 and >430 kg/m 3 and moisture content (15% and 18% (w.b.)) and hammer mill screen size of 12.7 and 19.05 mm produced briquettes with durability rating values of >95%. The higher moisture content of 18% (w.b.) and the hammer mill screen size of 12.7 and 19.05 mm had the highest energy consumption. The proximate and ultimate analysis showed that energy content improved by blending lodgepole pine with both corn stover and switchgrass and also showed increased calorific value and reduced ash content. Scanning electron microscopy micrographs showed interlocking of particles and cracks in the briquettes. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

Tumuluru, Jaya Shankar↗
DOE OSTI2020

Preservation of Microalgae, Lignocellulosic Biomass Blends by Ensiling to Enable Consistent Year-Round Feedstock Supply for Thermochemical Conversion to Biofuels

Seasonal variation in microalgae productivity is a significant barrier to economical production of algae biofuels and chemicals. Summer production can be 3–5 times higher than in the winter resulting in uneven feedstock supplies at algae biorefineries. A portion of the summer production must be preserved for conversion in the winter in order to maintain a biorefinery running at capacity. Ensiling, a preservation process that utilizes lactic acid fermentation to limit microbial degradation, has been demonstrated to successfully stabilize algae biomass (20% solids) and algae-lignocellulosic blends (40% algae-60% lignocellulosic biomass, dry basis) for over 6 months, resulting in fuel production cost savings with fewer emissions. Preservation of algae as blends could be beneficial to biorefineries that utilize thermochemical approaches to fuel production as co-processing of algae and lignocellulosic biomass has been observed to enhance biocrude yield and improve oil quality. This study conducts a resource assessment of biomass residues in the southern United States to identify materials available during peak algae productivity and in sufficient quantity to meet the algae storage needs of an algae biofuel industry. Eight feedstocks met the quantity threshold but only three, distillers grains, haylage, and yard waste, were also available in season. Storage experiments utilizing both freshwater and marine strains of microalgae – Scenedesmus acutus, Chlorella vulgaris, Chlorella zofingiensis, Nannochloropsis gaditana, and Porphyridium purpureum – and yard waste were conducted for 30 days. Storage losses were less than 10% in all but one case, and the pH of all but one blend was reduced to less than 4.7, indicating that yard waste is a suitable feedstock for blending with algae prior to storage. To better understand whether the benefits to conversion realized by processing blends might be affected by storage, elemental analysis and bomb calorimetry of pre- and post-storage algae-yard waste blends were conducted to characterize changes occurring during storage. Storing algae biomass as blends with lignocellulosic biomass could be an effective method of mitigating seasonal variability in algae biomass production while retaining the synergistic effect of co-processing algae blends in thermochemical conversion.

09 BIOMASS FUELS↗
DOE OSTI2015

Supply Chain Sustainability Analysis of Indirect Liquefaction of Blended Biomass to Produce High Octane Gasoline

The Department of Energy’s (DOE) Bioenergy Technologies Office (BETO) aims at developing and deploying technologies to transform renewable biomass resources into commercially viable, high-performance biofuels, bioproducts and biopower through public and private partnerships (DOE, 2015). BETO also performs a supply chain sustainability analysis (SCSA). This report describes the SCSA of the production of renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of lignocellulosic biomass. This SCSA was developed for the 2017 design case for feedstock logistics (INL, 2014) and for the 2022 target case for HOG production via IDL (Tan et al., 2015). The design includes advancements that are likely and targeted to be achieved by 2017 for the feedstock logistics and 2022 for the IDL conversion process. The 2017 design case for feedstock logistics demonstrated a delivered feedstock cost of $80 per dry U.S. short ton by the year 2017 (INL, 2014). The 2022 design case for the conversion process, as modeled in Tan et al. (2015), uses the feedstock 2017 design case blend of biomass feedstocks consisting of pulpwood, wood residue, switchgrass, and construction and demolition waste (C&D) with performance properties consistent with a sole woody feedstock type (e.g., pine or poplar). The HOG SCSA case considers the 2017 feedstock design case (the blend) as well as individual feedstock cases separately as alternative scenarios when the feedstock blend ratio varies as a result of a change in feedstock availability. These scenarios could be viewed as bounding SCSA results because of distinctive requirements for energy and chemical inputs for the production and logistics of different components of the blend feedstocks.

Cai, Hao↗
DOE OSTI2017

Biomass Blending and Densification: Impacts on Feedstock Supply and Biochemical Conversion Performance

The success of lignocellulosic biofuels and biochemical industries depends on an economic and reliable supply of high-quality biomass. Many research and development efforts, however, have been historically focused on the utilization of agriculturally derived cellulosic feedstocks, without considerations of their low energy density, high variations in compositions and potential supply risks in terms of availability and affordability. This book chapter demonstrated a strategy of feedstock blending and densification to address the supply chain challenges. Blending takes advantage of low cost feedstock to avoid the prohibitive costs incurred through reliance on a single feedstock resource while densification produces feedstocks with increased bulk density and desirable feed handling properties as well as reduced transportation cost. We also review recent research on the blending and densification dealing with various types of feedstocks with a focus on the impacts of these preprocessing steps on biochemical conversion, i.e., various thermochemical pretreatment chemistries and enzymatic hydrolysis, into fermentable sugars for biofuel production.

09 BIOMASS FUELS↗
DOE OSTI2016

Supply Chain Sustainability Analysis of Indirect Liquefaction of Blended Biomass to Produce High Octane Gasoline

This report describes the SCSA of the production of renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of lignocellulosic biomass. This SCSA was developed for both the 2015 SOT (Hartley et al., 2015; ANL, 2016; DOE, 2016) and the 2017 design case for feedstock logistics (INL, 2014) and for both the 2015 SOT (Tan et al., 2015a) and the 2022 target case for HOG production via IDL (Tan et al., 2015b). The design includes advancements that are likely and targeted to be achieved by 2017 for the feedstock logistics and 2022 for the IDL conversion process. In the SCSA, the 2015 SOT case for the conversion process, as modeled in Tan et al. (2015b), uses the 2015 SOT feedstock blend of pulpwood, wood residue, and construction and demolition waste (C&D). Moreover, the 2022 design case for the conversion process, as described in Tan et al. (2015a), uses the 2017 design case blend of pulpwood, wood residue, switchgrass, and C&D. The performance characteristics of this blend are consistent with those of a single woody feedstock (e.g., pine or poplar). We also examined the influence of using a single feedstock type on SCSA results for the design case. These single feedstock scenarios could be viewed as bounding SCSA results given that the different components of the feedstock blend have varying energy and material demands for production and logistics.

09 BIOMASS FUELS↗
DOE OSTI2021

Techno-Economic Analysis of decentralized preprocessing systems for fast pyrolysis biorefineries with blended feedstocks in the southeastern United States

This study evaluated the economic feasibility of fast pyrolysis biorefineries fed with blended pine residues and switchgrass in the Southeastern U.S. with different supply chain design. Previous techno-economic analyses (TEA) have focused on either blended biomass or decentralized preprocessing without investigating the impacts of varied process parameters, technology options, and real-world biomass distribution. This study fills the literature gap by modeling scenarios for different biomass blending ratios, biorefinery and preprocessing site (so-called depot) capacities, and alternative preprocessing technologies. High-resolution, real-world geospatial data were analyzed using Geographic Information Systems to facilitate supply chain design and TEA. For a decentralized system, the minimum fuel selling price (MFSP) of biofuel was 3.92–4.33 per gallon gasoline equivalent (GGE), while the MFSP for the centralized biorefinery at the same capacities ranged between 3.75–4.02/GGE. Implementing a high moisture pelleting process depot rather than a conventional pelleting process lowered the MFSP by 0.03–0.17/GGE. Scenario analysis indicated decreased MFSP with increasing biorefinery capacities but not necessarily with increasing depot size. Medium-size depots (500 OMDT/day) achieved the lowest MFSP. Here, this analysis identified the optimal blending ratios for two preprocessing technologies at varied depot sizes. Counterintuitively, increasing the proportion of higher cost switchgrass reduced the MFSP for large biorefineries (>5000 ODMT/day), but increased the MFSP for small biorefineries (1000–2500 ODMT/day). Although the decentralized systems have a higher MFSP based on current analysis, it has other potential benefits such as mitigated supply chain risks and improved feedstock quality that are difficult to be quantified in this TEA.

09 BIOMASS FUELS↗
DOE OSTI2017

Bio Blend Remix

Biomass blending is a method of mixing several types of biomass to reduce variability in cost and to improve the sustainability of biofuel productions. Idaho National Laboratory researchers have discovered ways to produce quality, low cost feedstocks year round under a wide variety of environmental conditions.

09 BIOMASS FUELS↗
DOE OSTI2017

Stochastic Models for an Optimal Blending of Biomass under Cost, Quality and Uncertainty Considerations

Blending biomass materials of different physical or chemical properties provides an opportunity to passively adjust the quality of the feedstock to meet the specifications of the conversion platform. We propose a model which identifies the right mix of biomass to optimize the performance of the Thermochemical conversion process at the minimum cost. This is a chance-constraint programming (CCP) model which takes into account the stochastic nature of biomass availability and quality. The proposed CCP model takes as inputs the physical and chemical properties, and biomass availability. We use the sample average approximation (SAA) method to solve the problem. We develop a case study for South Carolina by using data provided by the Billion Ton Study. We conduct extensive numerical analysis to evaluate the quality of the solutions obtained.

09 BIOMASS FUELS↗
DOE OSTI2017

Optimizing biomass feedstock blends with respect to cost, supply, and quality for catalyzed and uncatalyzed fast pyrolysis applications

Here, biomass cost, quality and quantity are important parameters to consider when choosing feedstocks and locations for biorefineries. Biomass cost is dependent upon type, location, quantities available in a given area and logistics costs as well the quality needed for the biorefinery. Biomass quality depends upon type, growth conditions, weather, harvesting methods, storage conditions as well as any preprocessing methods used to improve quality. Biomass quantity depends heavily on location as well as growth conditions, weather, harvesting methods and storage conditions. This study examines how all three of these parameters affect the biomass mixture that is needed in a biomass depot or biorefinery to achieve the lowest cost with the highest quality and at the quantities needed for biorefinery operation. Four biomass depots were proposed in South Carolina that would each process the predominant type of biomass available in that area and each produce 200,000 tons of feedstock per year. These depots would then feed a centrally located 800,000 ton biorefinery that would convert the feedstocks to pyrolysis oil using either catalyzed or uncatalyzed fast pyrolysis. The four depots each needed to produce different blends of biomass based upon the quantities available to them but still meet the minimum quality requirements for the biorefinery. Costs were minimized by using waste biomass resources such as construction and demolition waste, logging residues and forest residuals. Depending upon the quality specification required by the biorefinery, it was necessary to utilize preprocessing methods such as air classification and acid leaching to upgrade biomass quality. In the case of uncatalyzed fast pyrolysis, all four depots could produce biomass blends that were lower cost than the the preferred pyrolysis feedstock, clean pine, and meet quality and quantity specifications. For catalyzed fast pyrolysis, three of the four depots were able to produce blends that met both quality and quantity specifications at minimum cost. The fourth depot would not be able to produce a blend meeting specifications without increasing the supply radius for the depot.

09 BIOMASS FUELS↗
DOE OSTI2019

Methyl Ketones from Municipal Solid Waste Blends by One‐Pot Ionic‐Liquid Pretreatment, Saccharification, and Fermentation

Abstract The conversion of municipal solid waste (MSW) and lignocellulosic biomass blends to methyl ketones (MKs) was investigated by using bioderived ionic liquid (bionic liquid)‐based hydrolysates followed by fermentation with an engineered Escherichia coli strain. The hydrolysates were produced by a one‐pot process using six types of MSW–biomass blends, choline‐based bionic liquids, and commercial enzymes. Based on the sugar yields, one blend (corn stover/MSW=95:5, w / w ) and two bionic liquids {cholinium lysinate ([Ch][Lys]) and cholinium aspartate ([Ch] 2 [Asp])} were selected for scale‐up studies. Maximum yields of 82.3 % glucose and 54.4 % xylose were obtained from the selected blend in the scale‐up studies (6 L), which was comparable with 83.6 % glucose and 52.8 % xylose obtained at a smaller scale (0.2 L). Comparable or higher yields of medium‐chain (C 11 –C 17 ) MKs were achieved by using the MSW–biomass blend‐derived hydrolysates, relative to the sugar controls (glucose and xylose) with similar sugar feeding concentrations. Up to 1145 mg L −1 of MKs was produced by using MSW–biomass‐derived hydrolysates, and the MK titer decreased to 300 mg L −1 when the bionic‐liquid concentration in the hydrolysate increased from 1 to 2 %, indicative of bionic‐liquid inhibition. Technoeconomic analysis was conducted to investigate the economic potential of using the selected MSW–biomass blend as a feedstock to produce MKs.

Yan, Jipeng↗
DOE OSTI2019

Mitigation of variable seasonal productivity in algae biomass through blending and ensiling: An assessment of compositional changes in storage

Microalgae biomass has gained considerable attention in recent years as an attractive feedstock for biofuel production. However, seasonal variability in algae growth presents a challenge to delivering a consistent feedstock supply to a conversion facility. Drying is one approach to preserving algae produced in productive summer months for conversion in winter, but is energy intensive and costly. Ensiling is an alternative to drying that preserves algae in wet anaerobic conditions in the presence of organic acids. We have previously demonstrated that dry matter loss of algae:corn stover blends can be limited to 8% over 35 days using this approach. However, longer storage durations will be required to maintain a consistent feedstock supply to a biorefinery. Furthermore, the impacts to biomass quality that occur during storage are unknown. A Box-Behnken design of experiment was conducted to determine the influence of moisture, soluble sugar, and algae content on dry matter loss of algae:corn stover blends in wet anaerobic storage over a 30-day period. Using one-way analysis of variance (ANOVA) moisture and soluble sugar content were found to significantly affect dry matter loss in storage. The results of experimental design were then used to inform the initiation of a 180 day storage study that evaluated the storage performance and biomass composition of algae:corn stover blends containing 5, 20 or 40% algae. After 180 days of storage dry matter loss ranged from 6 – 17%. A relative increase in nitrogen content of stored blends indicates that protein content was unaffected by storage, while the carbohydrate fraction was most impacted, decreasing by 5 – 15%. For each stored blend the oxygen content decreased in storage resulting increased higher heating values (HHV). As a result, the impact that changes to biochemical and elemental composition of algae:corn stover blends has on biomass conversion to fuels and chemicals is discussed.

09 BIOMASS FUELS↗