Insight into the Sustainable Integration of Bio- and Petroleum Refineries for the Production of Fuels and Chemicals.

A petroleum refinery heavily depends on crude oil as its main feedstock to produce liquid fuels and chemicals. In the long term, this unyielding dependency is threatened by the depletion of the crude oil reserve. However, in the short term, its price highly fluctuates due to various factors, such as regional and global security instability causing additional complexity on refinery production planning. The petroleum refining industries are also drawing criticism and pressure due to their direct and indirect impacts on the environment. The exhaust gas emission of automobiles apart from the industrial and power plant emission has been viewed as the cause of global warming. In this sense, there is a need for a feasible, sustainable, and environmentally friendly generation process of fuels and chemicals. The attention turns to the utilization of biomass as a potential feedstock to produce substitutes for petroleum-derived fuels and building blocks for biochemicals. Biomass is abundant and currently is still low in utilization. The biorefinery, a facility to convert biomass into biofuels and biochemicals, is still lacking in competitiveness to a petroleum refinery. An attractive solution that addresses both is by the integration of bio- and petroleum refineries. In this context, the right decision making in the process selection and technologies can lower the investment and operational costs and assure optimum yield. Process optimization based on mathematical programming has been extensively used to conduct techno-economic and sustainability analysis for bio-, petroleum, and the integration of both refineries. This paper provides insights into the context of crude oil and biomass as potential refinery feedstocks. The current optimization status of either bio- or petroleum refineries and their integration is reviewed with the focus on the methods to solve the multi-objective optimization problems. Internal and external uncertain parameters are important aspects in process optimization. The nature of these uncertain parameters and their representation methods in process optimization are also discussed

Modeling Bioenergy Supply Chains: Feedstocks Pretreatment, Integrated System Design Under Uncertainty

Biofuels have been promoted by governmental policies for reducing fossil fuel dependency and greenhouse gas emissions, as well as facilitating regional economic growth. Comprehensive model analysis is needed to assess the economic and environmental impacts of developing bioenergy production systems. For cellulosic biofuel production and supply in particular, existing studies have not accounted for the inter-dependencies between multiple participating decision makers and simultaneously incorporated uncertainties and risks associated with the linked production systems.This dissertation presents a methodology that incorporates uncertainty element to the existing integrated modeling framework specifically designed for advanced biofuel production systems using dedicated energy crops as feedstock resources. The goal of the framework is to support the bioenergy industry for infrastructure and supply chain development. The framework is flexible to adapt to different topological network structures and decision scopes based on the modeling requirements, such as on capturing the interactions between the agricultural production system and the multi-refinery bioenergy supply chain system with regards to land allocation and crop adoption patterns, which is critical for estimating feedstock supply potentials for the bioenergy industry. The methodology is also particularly designed to incorporate system uncertainties by using stochastic programming models to improve the resilience of the optimized system design.The framework is used to construct model analyses in two case studies. The results of the California biomass supply model estimate that feedstock pretreatment via combined torrefaction and pelletization reduces delivered and transportation cost for long-distance biomass shipment by 5% and 15% respectively. The Pacific Northwest hardwood biofuels application integrates full-scaled supply chain infrastructure optimization with agricultural economic modeling and estimates that bio-jet fuels can be produced at costs between 4 to 5 dollars per gallon, and identifies areas suitable for simultaneously deploying a set of biorefineries using adopted poplar as the dedicated energy crop to produce biomass feedstocks. This application specifically incorporates system uncertainties in the crop market and provides an optimal system design solution with over 17% improvement in expected total profit compared to its corresponding deterministic model

Novel approach for integrated biomass supply chain synthesis and optimisation

Despite looming energy crises, fossil resources are still widely used for energy and chemical production. Growing awareness of the environmental impact from fossil fuels has made sustainability one of the main focuses in research and development. Towards that end, biomass is identified as a promising renewable source of carbon that can potentially replace fossil resources in energy and chemical productions. Although many researches on converting biomass to value-added product have been done, biomass is still considered underutilised in the industry. This is mainly due to challenges in the logistic and processing network of biomass. An integrated biomass supply chain synthesis and optimisation are therefore important. Thus, the ultimate goal of this thesis is to develop a novel approach for an integrated biomass supply chain. Firstly, a multiple biomass corridor (MBC) concept is presented to integrate various biomass and processing technologies into existing biomass supply chain system in urban and developed regions. Based on this approach, a framework is developed for the synthesis of a more diversified and economical biomass supply chain system. The work is then extended to consider the centralisation and decentralisation of supply chain structure. In this manner, P-graph-aided decomposition approach (PADA) is proposed, whereby it divides the complex supply chain problem into two smaller sub-problems – the processing network is solved via mixed-integer linear programming (MILP) model, whereas the binaries-intensive logistic network configuration is determined through P-graph framework. As existing works often focus on supply chain synthesis in urban regions with well-developed infrastructure, resources integrated network (RIN) – a novel approach for the synthesis of integrated biomass supply chain in rural and remote regions is introduced to enhance rural economies. This approach incorporates multiple resources (i.e. bioresources, food commodities, rural communities’ daily needs) into the value chain and utilises inland water system as the mode of transport, making the system more economically feasible. It extends the MBC approach for technology selection and adopts vehicle routing problem (VRP) for inland water supply and delivery network. To evaluate the performance of the proposed integrated biomass supply chain system, a FANP-based (fuzzy analytical network process) sustainability assessment tool is established. A framework is proposed to derive sustainability index (SI) from pairwise comparison done by supply chain stakeholders to assess the sustainability of a system. Fuzzy limits are introduced to reduce uncertainties in human judgment while conducting the pairwise comparison. To design a sustainable integrated biomass supply chain, a FANP-aided, a novel multiple objectives optimisation framework is proposed. This approach transforms multiple objective functions into single objective function by prioritising each of the objective through the FANP framework. The multiple objectives are then normalised via max-min aggregation to ensure the trade-off between objectives is performed on the same scale. At the end of this thesis, viable future works of the whole programme is presented for consideration

Biofuel supply chain, market, and policy analysis

Renewable fuel is receiving an increasing attention as a substitute for fossil based energy. The US Department of Energy (DOE) has employed increasing effort on promoting the advanced biofuel productions. Although the advanced biofuel remains at its early stage, it is expected to play an important role in climate policy in the future in the transportation sector. This dissertation studies the emerging biofuel supply chain and markets by analyzing the production cost, and the outcomes of the biofuel market, including blended fuel market price and quantity, biofuel contract price and quantity, profitability of each stakeholder (farmers, biofuel producers, biofuel blenders) in the market. I also address government policy impacts on the emerging biofuel market. The dissertation is composed with three parts, each in a paper format. The first part studies the supply chain of emerging biofuel industry. Two optimization-based models are built to determine the number of facilities to deploy, facility locations, facility capacities, and operational planning within facilities. Cost analyses have been conducted under a variety of biofuel demand scenarios. It is my intention that this model will shed light on biofuel supply chain design considering operational planning under uncertain demand situations. The second part of the dissertation work focuses on analyzing the interaction between the key stakeholders along the supply chain. A bottom-up equilibrium model is built for the emerging biofuel market to study the competition in the advanced biofuel market, explicitly formulating the interactions between farmers, biofuel producers, blenders, and consumers. The model simulates the profit maximization of multiple market entities by incorporating their competitive decisions in farmers’ land allocation, biomass transportation, biofuel production, and biofuel blending. As such, the equilibrium model is capable of and appropriate for policy analysis, especially for those policies that have complex ramifications and result in sophisticate interactions among multiple stakeholders. The third part of the dissertation investigates the impacts of flexible fuel vehicles (FFVs) market penetration levels on the market outcomes, including cellulosic biofuel production and price, blended fuel market price, and profitability of each stakeholder in the biofuel supply chain for imperfectly competitive biofuel markets. In this paper, I investigate the penetration levels of FFVs by incorporating the substitution among different fuels in blended fuel demand functions through “cross price elasticity” in a bottom-up equilibrium model framework. The complementarity based problem is solved by a Taylor expansion-based iterative procedure. At each step of the iteration, the highly nonlinear complementarity problems with constant elasticity of demand functions are linearized into linear complimentarity problems and solved until it converges. This model can be applied to investigate the interaction between the stakeholders in the biofuel market, and to assist decision making for both cellulosic biofuel investors and government

Bioprospecting: Forest bioeconomy and bioproducts

Extraction of the valuable bioproducts from forest resources is crucial inorder to reduce carbon emission, creating sustainable environment and contributions in national economy. Norway consists of a large area of boreal forest resources and biomass which has a very potential sources for providing bio based products. This approachs for searching, identifying of commercially valuable products from natural resources is termed as bioprospecting. Biorefineries are the platforms that manufacture bioproducts involving different stage/ process such as raw materials processing, technical process or methods for production of chemicals, and extraction/ recovery process for desired products. Apart from using biorefineries as the platform for value creation, appropriate strategies, plans and policies are also required to achieve the goal. The study has reviewed the possibilities of valuable products from Norwegian tree species eg. Scots pine, Norway spruce and Birch with the inclusion of case studies in Norway, Finland and Sweden. Furthermore, this study discuss and suggest the strategies to create the value from forest resources, figured out challenges related to Norwegian forest industry, and some recommendations to increase the value from Norwegian forest. While concluding this paper, the study was concluded with the focus on approaches like collaboration across related sectors, sustainable utilization of renewable forest resources along with its productions and extractions

Modeling, Optimization and Economic Evaluation of Residual Biomass Gasification

Gasification is a thermo-chemical process which transforms biomass into valuable synthesis gas. Integrated with a biorefinery it can address the facility’s residue handling challenges and input demands. A number of feedstock, technology, oxidizer and product options are available for gasification along with combinations thereof. The objective of this work is to create a systematic method for optimizing the design of a residual biomass gasification unit. In detail, this work involves development of an optimization superstructure, creation of a biorefining scenario, process simulation, equipment sizing & costing, economic evaluation and optimization. The superstructure accommodates different feedstocks, reactor technologies, syngas cleaning options and final processing options. The criterion for optimization is annual worth. A biorefining scenario for the production of renewable diesel fuel from seed oil is developed; gasification receives the residues from this biorefinery. Availability of Soybeans, Jatropha, Chinese Tallow and woody biomass material is set by land use within a 50-mile radius. Four reactor technologies are considered, based on oxidizer type and operating pressure, along with three syngas cleaning methods and five processing options. Results show that residual gasification is profitable for large-scale biorefineries with the proper configuration. Low-pressure air gasification with filters, water-gas shift and hydrogen separation is the most advantageous combination of technology and product with an annual worth of $9.1 MM and a return on investment of 10.7 percent. Low-pressure air gasification with filters and methanol synthesis is the second most advantageous combination with an annual worth of$9.0 MM. Gasification is more economic for residue processing than combustion or disposal, and it competes well with natural gas-based methanol synthesis. However, it is less economic than steam-methane reforming of natural gas to hydrogen. Carbon dioxide credits contribute to profitability, affecting some configurations more than others. A carbon dioxide credit of $33/t makes the process competitive with conventional oil and gas development. Sensitivity analysis demonstrates a 10 percent change in hydrogen or electricity price results in a change to the optimal configuration of the unit. Accurate assessment of future commodity prices is critical to maximizing profitability

Integrating bio-hubs in biomass supply chains: Insights from a systematic literature review

Biomass sources are geographically scattered, and seasonal changes influence their availability. Variations in location, type, and feedstock quality impose logistical and storage challenges. Such a dispersion and variety of biomass sources, as well as the dispersion of demand points, may undermine the economies of scale and increase the risk of supply shortage. By consolidating biomass preprocessing and distribution activities in bio-hub facilities, they can contribute to the overall resilience of biomass supply chains (BSCs) and ensure a more sustainable and cost-efficient approach to bioenergy production. As such, investigating the advantages and challenges associated with bio-hub implementation can offer invaluable insights on the efficiency and sustainability of BSCs. Despite its critical role, a major part of the literature on BSCs is confined to the decision-making processes related to biomass suppliers and bioconversion facilities. To bridge this research gap, the current study conducts a systematic literature review on bio-hub implementation within BSCs in the period of the last ten years. Shortlisted papers are classified and analyzed meticulously to extract possible improvements from BSC and modeling perspectives. From the BSC viewpoint, one notable gap is the little attention to mid-term and short-term decisions of bio-hub operations such as inventory control, resource management and production planning. Furthermore, the results revealed that environmental and social aspects of bio-hub implementation require considerable attention. From the modeling perspective, findings illustrate the underutilization of integrated approaches to incorporate micro-level and macro-level information in decision-making. In this regard, a number of areas are suggested for further exploration

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