Design of biomass value chains that are synergistic with the food-energy-water nexus: strategies and opportunities

Humanity’s future sustainable supply of energy, fuels and materials is aiming towards renewable sources such as biomass. Several studies on biomass value chains (BVCs) have demonstrated the feasibility of biomass in replacing fossil fuels. However, many of the activities along the chain can disrupt the food–energy–water (FEW) nexus given that these resource systems have been ever more interlinked due to increased global population and urbanisation. Essentially, the design of BVCs has to integrate the systems-thinking approach of the FEW nexus; such that, existing concerns on food, water and energy security, as well as the interactions of the BVCs with the nexus, can be incorporated in future policies. To date, there has been little to no literature that captures the synergistic opportunities between BVCs and the FEW nexus. This paper presents the first survey of process systems engineering approaches for the design of BVCs, focusing on whether and how these approaches considered synergies with the FEW nexus. Among the surveyed mathematical models, the approaches include multi-stage supply chain, temporal and spatial integration, multi-objective optimisation and uncertainty-based risk management. Although the majority of current studies are more focused on the economic impacts of BVCs, the mathematical tools can be remarkably useful in addressing critical sustainability issues in BVCs. Thus, future research directions must capture the details of food–energy–water interactions with the BVCs, together with the development of more insightful multi-scale, multi-stage, multi-objective and uncertainty-based approaches

Perspectives for Greening European Fossil-Fuel Infrastructures Through Use of Biomass: The Case of Liquid Biofuels Based on Lignocellulosic Resources

Given the importance of climate change it is vital to find a transition away from fossil fuels. The transition will include electrification of several sectors, for example road transport, but considering the strong dependency on carbon-based fuels and associated infrastructures, it is reasonable to assume that biomass-based hydrocarbon will play a key role to smoothen the transition away from fossil fuels. This study provides an analysis of direct and indirect technological options for liquid biofuels based on lignocellulosic resources in the context of greening European fossil-fuel infrastructures. Direct options are those which result in integration of biogenic feedstock in a fossil-based process and then co-processing in a downstream conventional unit or substituting a conventional part of the production chain of a liquid fuel by a bio-based one. Indirect options are those which pave the way for ramping-up biomass supply chain in the form of infrastructure and market. Examples of direct options in the focus of this study are biomass gasification for production of intermediates and biomass pyrolysis substituting fossil feedstock. Examples of indirect options are co-firing biomass in coal-fired power plants and integrating biomass gasification plants with district heating (DH) networks. Such options are important for establishing biomass supply chains and markets. This study also assesses the potential of biomass use in other industrial sectors not directly related with fossil-based fuel or energy production, such as the pulp and paper industry and the iron and steel industry. In this context, opportunities and barriers for both direct and indirect greening options are discussed, focusing mainly on technological and logistic aspects. It is highlighted that fossil-fuel infrastructures can act as drivers for the development of advanced biofuels production as they can reduce the initial risks, in terms of cost and technological maturity, offering the opportunity to increase gradually the demand for biomass, and develop the logistic infrastructure. It is, however, important to make sure that such biofuel production processes are part of a long-term strategy, which needs incentives to overcome current barriers and eventually phase out fossil infrastructures

A Systems Framework for Shale Gas Monetization

The aim of this study is to provide a systems perspective on shale gas monetization to fuels and chemicals. The properties of shale reservoirs and shale gas production processes will be discussed briefly before focusing on four main building blocks of the chemicals industry: methanol, ethylene, propylene, and butadiene. For each of these building blocks, the main derivatives and their chemical processes are discussed as well as the changes incurred on their markets because of the shale gas boom. In addition, the chemistry of gas-to-liquids (GTL) technology and existing commercial applications of it are detailed. Also, an overview of existing and proposed plants for each of the five monetization pathways will be given. Based on this survey, an optimization formulation is developed and solved to determine the optimal pathways of a given shale gas resource. The objective of the optimization formulation is to maximize profit based on capital and operating costs of the given processes, feedstock prices, the sales prices of the produced chemicals while accounting for supply, demand, technical, and environmental factors (e.g., CO2). A case study is solved for the Barnett and Eagle Ford shale formations

A GIS-based Multi-objective Optimization of a Lignocellulosic Biomass Supply Chain: A Case Study in Tennessee

To achieve an economically and environmentally sustainable lignocellulosic biomass (LCB)-based biofuel industry sector, the design and location of a sustainable LCB supply chain is important. In this study, a multi-objective optimization model integrated with high-resolution geographical data was developed to examine the optimal switchgrass supply chain for a potential biorefinery in Tennessee, specifically evaluating the potential tradeoffs between the objectives of minimizing plant-gate cost and GHG emissions from the switchgrass supply chain. The key findings of this study are as follows: both plant-gate feedstock cost and GHG emissions were sensitive to the type of land converted into switchgrass production, the type of land use change also affected the density of the feedstock supply region due to the spatial heterogeneity in the availability of different types of land, hence affecting transportation-related cost and GHG emissions, and a tradeoff relationship was discovered between cost and GHG emissions for the switchgrass supply chain, primarily driven by the type of land converted. As a result of land use changes and transportation distances, the imputed cost to reduce one unit of GHG emissions was initially modest; however, the imputed cost increased considerably when the supply chain GHG emissions were further mitigated. This implied that the location of switchgrass production and the resulting changes in crop production should be considered in targeting government incentives to encourage switchgrass-based biofuel production in the state and the southeastern region. Sensitivity analyses indicated that the dry matter loss (DML) decomposition, if considered as a source of GHG emissions, would considerably increase the supply chain GHG emissions. Different harvest and storage technology used in the feedstock supply chain altered the DML rate and corresponding GHG emissions however did not change the tradeoffs between the two objectives significantly. The consideration of GHG emissions from cattle relocation, on the other hand, appears to reduce the GHG emission level of the supply chain to a great extent and change the tradeoff relation between the two objectives

Optimal energy supply network determination and life cycle analysis for hybrid coal, biomass, and natural gas to liquid (CBGTL) plants using carbon-based hydrogen production

A mixed-integer linear optimization formulation is developed to analyze the United States energy supply chain network for the hybrid coal, biomass, and natural gas to liquids (CBGTL) facilities. Each state is discretized into octants and each octant centroid serves as a potential location of one facility. The model selects the optimal locations of CBGTL facilities, the feedstock combination, and size of each facility that gives the minimum overall production cost. Two case studies are presented to investigate the effects of various technologies and hydrogen prices. The CBGTL network is capable to supply transportation fuel demands for the country at a cost between $15.68 and$22.06/GJ LHV ($76.55-$112.91/bbl crude oil) of produced liquid fuels for both case studies. Life cycle analysis on each facility in the supply chain network shows that the United States fuel demands can be fulfilled with an excess of 50% emissions reduction compared to petroleum based processes. (C) 2011 Elsevier Ltd. All rights reserved

ECONOMIC MODELING & OPTIMIZATION OF A REGION SPECIFIC MULTI-FEEDSTOCK BIOREFINERY SUPPLY CHAIN

The objective of this thesis is to include strategic and tactical level decisions into the biorefinery supply chain design for a specific region while comparing multiple conversion technologies and biomass feedstocks. The allocation of biomass feedstocks, products, and the respective supply chain configuration locations are determined while ensuring the regions monthly biomass availability and product market demand constraints are met. This research considers all actions required to bring the bio-based products to market from harvesting, storing, and processing the biomass to market distribution. Two different conversion technologies are chosen for comparison: one advanced conversion technology and one conventional technology. Potential investors and policy makers will be able to use this region specific tool by maximizing annual profitability to evaluate potential lignocellulosic biomass feedstocks and conversion technologies for the production of energy, fuels, and chemicals. The tool utilizes ILOG OPL software for optimization while interfacing with Microsoft Excel for parameter inputs and results output. From the sensitivity analysis, further insight is gained to what key drivers greatly influence the performance of each supply chain. The results demonstrate the practicality of this tool, which then can be further analyzed through other models such as discrete event simulation

Modeling of Biorefinery Supply Chain Economic Performance with Discrete Event Simulation

As competition for fossil fuels accelerates, alternative sources of chemicals, fuels, and energy production become more appealing to researchers and the layman. Among the candidates to fill this growing niche is lignocellulosic biomass. Many researchers have examined supply chain design and optimization for biofuel and bioenergy production throughout the years. However, these models often fail to capture the variability and uncertainty inherent to the biomass supply chain. Multiple factors with high degrees of stochasticity can have major impacts on the performance of a biorefinery: weather, biomass quality, feedstock availability, and market demand for products are just a few. To begin to address this issue, a discrete event simulation model has been developed to examine the economic performance of a region specific, multifeedstock biorefinery supply chain. Probability distributions developed for product demand and feedstock supply begin to address the random nature of the supply chain. Model development is discussed in the context of a multidisciplinary framework for biorefinery supply chain design. A case study, sensitivity analysis, and scenario analysis, are utilized to examine the capabilities of the model

Integrated Techno-Economic and Life Cycle Analyses of Biomass Utilization for Value-Added Bioproducts in the Northeastern United States

A multi-stage spatial analysis was first conducted to select locations for lignocellulosic biomass-based bioproduct facility, using Geographical Information System (GIS) spatial analysis, multi-criteria analysis ranking algorithm, and social-economic assessment. A case study was developed to determine locations for lignocellulosic biorefineries using feedstocks including forest residue biomass and three energy crops for 13 states in the northeastern United States. In the entire study area, 11.1% of the counties are high-suitable, 48.8% are medium-suitable for biorefinery siting locations. A non-parametric analysis of cross-group surveys showed that preferences on biorefinery siting are homogeneous for experts in academia and industry groups, but people in government agencies presented different opinions. With the Maximum Likelihood test, parameters of distributions and mean values were estimated for nine weighted criteria. Social asset evaluation focusing on degree of rurality and social capital index further sorted counties with higher community acceptance and economic viability. A total of 15 counties were selected with the highest potential for biorefinery sites in the region. A mixed-integer linear programming model was then developed to optimize the multiple biomass feedstock supply chains, including feedstock establishment, harvest, storage, transportation, and preprocessing. The model was applied for analyses of multiple biomass feedstocks at county level for 13 states in the northeastern United States. In the base case with a demand of 180,000 dry Mg/year of biomass, the delivered costs ranged from $67.90 to$86.97 per dry Mg with an average of $79.58 /dry Mg. The biomass delivered costs by county were from$67.90 to 150.81 per dry Mg across the northeastern U.S. Considered the entire study area, the delivered cost averaged $85.30 /dry Mg for forest residues,$84.47 /dry Mg for hybrid willow, $99.68 for switchgrass and$97.87 per dry Mg for Miscanthus. Seventy seven out of 387 counties could be able to deliver biomass at $84 per dry Mg or less a target set by US DOE by 2022. A sensitivity analysis was also conducted to evaluate the effects of feedstock availability, feedstock price, moisture content, procurement radius, and facility demand on the delivered cost. Our results showed that procurement radius, facility capacity, and forest residue availability are the most sensitive factors affecting the biomass delivered costs. An integrated life cycle and techno-economic assessment was carried out for three bioenergy products derived from multiple lignocellulosic biomass. Three cases were studied for production of pellets, biomass-based electricity, and pyrolysis bio-oil. The LCA was conducted for estimating environmental impacts on cradle-to-gate basis with functional unit of 1000 MJ for bioenergy production. Pellet production had the lowest GHG emissions, water and fossil fuels consumption, for 8.29 kg CO2 eq, 0.46 kg, and 105.42 MJ, respectively. Conversion process presented a greater environmental impact for all three bioenergy products. With producing 46,926 tons of pellets, 260,000 MWh of electricity, and 78,000 barrels of pyrolysis oil, the net present values (NPV) for all three cases indicated only pellet and biopower production cases were profitable with NPVs$1.20 million for pellet, and $81.60 million for biopower. The pellet plant and biopower plant were profitable only when discount rates are less than or equal to 10A study evaluated the environmental and economic impacts of activated carbon (AC) produced from lignocellulosic biomass was evaluated for energy storage purpose. Results indicate that overall “in-plant production” process presented the highest environmental impacts. Normalized results of life cycle impact assessment showed that the AC production had environmental impacts mainly on carcinogenics, ecotoxicity, and non-carcinogenics categories. We then further focused on life cycle analysis from raw biomass delivery to plant gate, the results showed “feedstock establishment” has the most significant environmental impact, ranging from 50.3$6.66 million, and annual operation cost was $15.46 million. The AC required selling price (RSP) was$16.79 per kg, with the discounted payback period (DPB) of 9.98 years. Alternative cases of KOH-reuse and steam processes had GHG emission of 15.4 kg CO2 eq, and 10.2 kg CO2 eq for every 1 kg activated carbon, respectively. Monte Carlo simulation showed 49.96% of the probability for an investment to be profitable in activated carbon production for supercapacitor electrodes

A Comprehensive Optimization Framework for Designing Sustainable Renewable Energy Production Systems

As the world has recognized the importance of diversifying its energy resource portfolio away from fossil resources and more towards renewable resources such as biomass, there arises a need for developing strategies which can design renewable sustainable value chains that can be scaled up efficiently and provide tangible net environmental benefits from energy utilization. The objective of this research is to develop and implement a novel decision-making framework for the optimal design of renewable energy systems. The proposed optimization framework is based on a distributed, systematic approach which is composed of different layers including systems-based strategic optimization, detailed mechanistic modeling and operational level optimization. In the strategic optimization the model is represented by equations which describe physical flows of materials across the system nodes and financial flows that result from the system design and material movements. Market uncertainty is also incorporated into the model through stochastic programming. The output of the model includes optimal design of production capacity of the plant for the planning horizon by maximizing the net present value (NPV). The second stage consists of three main steps including simulation of the process in the simulation software, identification of critical sources of uncertainties through global sensitivity analysis, and employing stochastic optimization methodologies to optimize the operating condition of the plant under uncertainty. To exemplify the efficacy of the proposed framework a hypothetical lignocellulosic biorefinery based on sugar conversion platform that converts biomass to value-added biofuels and biobased chemicals is utilized as a case study. Furthermore, alternative technology options and possible process integrations in each section of the plant are analysed by exploiting the advantages of process simulation and the novel hybrid optimization framework. In conjunction with the simulation and optimization studies, the proposed framework develops quantitative metrics to associate economic values with technical barriers. The outcome of this work is a new distributed decision support framework which is intended to help economic development agencies, as well as policy makers in the renewable energy enterprises

STRATEGIC DECISION MAKING IN SUPPLY CHAINS UNDER RISK OF DISRUPTIONS

Ph.DDOCTOR OF PHILOSOPH