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

A MULTIDISCIPLINARY TECHNO-ECONOMIC DECISION SUPPORT TOOL FOR VALIDATING LONG-TERM ECONOMIC VIABILITY OF BIOREFINING PROCESSES

Increasing demand for energy and transportation fuel has motivated researchers all around the world to explore alternatives for a long-term sustainable source of energy. Biomass is one such renewable resource that can be converted into various marketable products by the process of biorefining. Currently, research is taking strides in developing conversion techniques for producing biofuels from multiple bio-based feedstocks. However, the greatest concern with emerging processes is the long-term viability as a sustainable source of energy. Hence, a framework is required that can incorporate novel and existing processes to validate their economic, environmental and social potential in satisfying present energy demands, without compromising the ability of future generations to meet their own energy needs. This research focuses on developing a framework that can incorporate fundamental research to determine its long-term viability, simultaneously providing critical techno-economic and decision support information to various stakeholders. This contribution links various simulation and optimization models to create a decision support tool, to estimate the viability of biorefining options in any given region. Multiple disciplines from the Process Systems Engineering and Supply Chain Management are integrated to develop the comprehensive framework. Process simulation models for thermochemical and biochemical processes are developed and optimized using Aspen Engineering Suite. Finally, for validation, the framework is analyzed by combining the outcomes of the process simulation with the supply chain models. The developed techno-economic model takes into account detailed variable costs and capital investments for various conversion processes. Subsequently, case studies are performed to demonstrate the applicability of the decision support tool for the Jackson Purchase region of Western Kentucky. The multidisciplinary framework is a unique contribution in the field of Process Systems Engineering as it demonstrates simulation of process optimization models and illustrates its iterative linking with the supply chain optimization models to estimate the economics of biorefinery from multi-stakeholder perspective. This informative tool not only assists in comparing modes of operation but also forecasts the effect of future scenarios, such as, utilization of marginal land for planting dedicated energy crops and incorporation of emerging enzymatic processes. The resulting framework is novel and informative in assisting investors, policy makers and other stakeholders for evaluating the impacts of biorefining. The results obtained supports the generalizability of this tool to be applied in any given region and guide stakeholders in making financial and strategic decisions

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

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

Pathways to a forest-based bioeconomy in 2060 within policy targets on climate change mitigation and biodiversity protection

While climate change and biodiversity loss have exposed humanity to major systemic risks, policymakers in more than 40 countries have proposed the transition from a fossil-based to a bio-based economy as a solution to curb the risks. In the boreal region, forests have a prominent role in contributing to bioeconomy development; however, forest-based bioeconomy transition pathways towards sustainability and the required actions have not yet been identified. Participatory backcasting was employed in this study to 'negotiate' such pathways among Finnish stakeholders by 2060 in three forest-based value networks: forest biorefineries, fibre-based packaging and wooden multistorey construction. There are many alternative pathways, ranging from incremental to more radical, to a forest-based bioeconomy within a framework of ambitious climate and biodiversity targets. Path dependence can support incremental development on bioeconomy transition pathways, and this should be considered when planning transition towards sustainability. Orchestration of the more radical changes requires actions from legislators, raw material producers, consumers and researchers, because the possibilities for business development vary between different companies and value networks. The envisioned actions between the pathways in and across the networks, such as forest diversification and diverse wood utilisation, can offer cobenefits in climate change mitigation and biodiversity protection.Peer reviewe

On the design of a European bioeconomy that optimally contributes to sustainable development

The inevitability for a change in humankind's resource and fossil energy consumption is demonstrated by global crises such as the climate change, disturbances of natural cycles, and the loss of biodiversity. The sun provides sufficient energy to generate electricity and by photosynthesis, solar radiation is converted into energy chemically bound in biomolecules, which provide building blocks for the production of various materials, chemicals, or fuels. The bioeconomy puts biomass at the center of an economy that attempts to cover resource and energy demand by renewable materials to address the global challenges. However, the finiteness of the terrestrial surface limits renewables, requiring a prioritization of use. The Sustainable Development Goals (SDGs) provide a common ground for global peace, prosperity, improved health and education, reduced inequality, and spur economic growth while tackling climate change and biodiversity loss, making it the most comprehensive framework for defining objectives in the design of the bioeconomy. Against this background, this dissertation is particularly dedicated to the design of bioeconomic value chains based on agroforestry residues in the European Union, considering economic, environmental, and social objectives to optimally exploit the potential to contribute to a sustainable development. All objectives are matched to SDGs to unveil congruencies, conflicts and trade-offs between different goals, and to provide aggregated insights and courses of action in the agroforestry residue-based bioeconomy to politics, the scientific community, and corporate decision-makers. The availability of agroforestry residue volumes and their current uses is the first major concern of a bioeconomy aligned with the SDGs to be assessed in this work. Key findings are that the most promising agricultural residue in the EU is wheat straw, followed by maize stover, barley straw, and rapeseed straw, which together account for about 80% of EU’s cereals and oil crops residues. In forestry, waste bark from the two coniferous species, spruce and pine, are most promising with the highest supplies in Scandinavia and central EU. The time-series-based forecast model predicts a total increase of the bioeconomic potential of the prioritized agricultural feedstocks from 113 Mt in 2017 to 127 Mt in 2030. The forecast indicates the largest increase of all investigated crops for corn stover at up to 20% until 2030, while rapeseed straw production is forecasted to decrease in many regions. To take environmental and social aspects into account on a regional level, along with international competitiveness, this dissertation develops a multi-criteria strategic network design model for the planning of bioeconomic value chains. The environmental and social objectives are derived by means of Life Cycle Assessment and Social Life Cycle Assessment, respectively. The developed set of 35 economic, environmental, and social objective functions allows for the consideration of 16 of the 17 SDGs. The model is applied for the planning of a second-generation bioethanol production network based on agricultural residues in the EU. Single-criteria optimization shows that sustainably available agroforestry residues could substitute up to 22% of the petrol demand in the EU in 2018 under optimal production networks for certain objectives (i.a., global warming). For environmental objectives, the decision to substitute petrol or edible crops-based ethanol has the highest impact. The greenhouse gas benefits could amount to up to 59 Mt CO2 eq., conforming to about 1.35% of the EU’s 2018 total emissions. However, global warming optimization leads to opportunity costs for other objectives. While for ecosystem quality, for example, the achieved value reaches 50% of its optimum, other categories like land use and water consumption could even be net deteriorated by optimizing global warming. For objectives such as land use, only 19% of the total agroforestry residues is used to substitute 100% of the edible crops-based ethanol, which would free up 11.7 billion m2 crop land. Social objectives lead to large and labor-intensive production networks distributed all over the EU. Depending on the social objective, the value creation slightly shifts regionally. To optimize local employment, the network relocates to regions with high unemployment rates, such as Spain, Italy, and parts of France. Economically strong metropolitan regions are at a disadvantage in favor of weaker regions of Central and Eastern EU when optimizing economic development. At best, up to 140,000 new jobs could be created in the EU while 12,000 jobs could be lost due to substitution of reference products. In terms of network extend, most socially and environmentally optimal production networks are similar, although the substitution decision has little impact for social objectives. This means that interesting trade-offs between social and environmental objectives can be found with only minor sacrifices. Economically optimal networks are much smaller and more centralized than environmental ones, and lead to costs of about 0.75 €/l second-generation ethanol. Environmental optimization results in cost between 0.88 €/l to 2.00 €/l, which implies that large-scale bioethanol production is not economically feasible with today’s oil prices and taxes. While the single-criteria optimization reveals conflicts within and between the environment, social, and economic dimensions, Pareto optimization is conducted to unveil trade-offs between conflicting goals. Significant environmental and social benefits can often be realized with only small economic detriments, and vice versa, economic profitability can substantially be improved at low environmental opportunity cost. Furthermore, the applied Pareto optimization shows that the endpoints human health and ecosystem quality are suitable aggregators of environmental impact categories, wherefore they could serve as representative of the environmental dimension in decision-making. Nonetheless, a transparent consideration of a broad range of impacts and knowledge about the categories’ contributions remains indispensable to reveal possible negative consequences of a decision. In a final step, the objective functions are matched to SDGs, and opportunity cost between the objective functions are calculated to unveil congruencies and conflicts between different goals. The assessment of relationships between the different SDGs supports the perception that different aspects of sustainability are not equally directed. Sustainability, expressed by the SDGs, is rather case-specific and varies between a multitude of interdependent social, environmental, and economic criteria. Decision-makers, whether at the corporate level pursuing one or more business objectives or at the policy level, using the SDGs as a framework, should be aware of the reciprocities between the different criteria. The dissertation shows that the European bioeconomy has a great potential to contribute to sustainable development. Multi-criteria optimization models enable sound trade-off decisions that are aligned to the SDGs

Integrated network design for forest bioenergy value chain - decisions support system for the transformation of the Canadian forest industry

Les usines de bioénergie devraient jouer un rôle important dans la production d'énergie verte à partir de la biomasse forestière. Pour intégrer l'usine de bioénergie dans la chaîne d'approvisionnement forestière, l'industrie a besoin de nouveaux investissements ainsi que de la conception et de la gestion de la chaîne de valeur. D'un autre côté, les incertitudes associées aux nouveaux produits sur le marché peuvent ajouter des risques supplémentaires à un investissement aussi important dans la chaîne d'approvisionnement forestière instable. Par conséquent, l'objectif principal de cette thèse est d'étudier la conception du réseau de bioénergie forestière dans un contexte déterministe et stochastique. La première partie de la thèse propose une plate-forme expérimentale pour intégrer la conception et le pilotage de la chaîne de valeur puisque le nouveau design ne sera réalisable que s'il considère au préalable la planification. La plateforme a inclus plusieurs actions collaboratives entre tous les partenaires impliqués dans la chaîne d'approvisionnement. Cette plateforme est la base d’un nouvel outil éducatif appelé jeu de transport. Ensuite, la plate-forme a été utilisée pour concevoir un réseau optimisé de bioénergie forestière. La chaîne d'approvisionnement forestière de Terre-Neuve, composée de quatre acteurs majeurs de l’industrie forestière, a été considérée comme notre étude de cas. La rentabilité de l'ajout de nouvelles installations de bioénergie ainsi que de nouveaux terminaux dans plusieurs emplacements potentiels ont été évalués. Enfin, à la troisième partie de la thèse, nous repensons le réseau bioénergétique en tenant compte de l'incertitude de la demande et des prix de tous les produits finaux de la nouvelle chaîne de valeur. Plusieurs bioprocédés potentiels avec différentes technologies ont été évalués dans notre étude de cas. Pour fournir une solution tenant compte du risque, nous avons développé deux nouveaux modèles de gestion des risques. Les résultats dans les trois parties ont clairement démontré l'impact de la planification intégrée, des usines de bioénergie et de la collaboration sur l'amélioration de la performance de la chaîne d'approvisionnement forestière. En général, le travail accompli dans ce projet permettra une transformation en douceur de la chaîne d'approvisionnement forestière en tenant compte des risques d'investissement. En ce qui concerne les résultats obtenus grâce aux études de cas, nous croyons que la plateforme et les approches proposées dans cette thèse peuvent être considérées comme des outils novateurs et pratiques pour le problème de la conception des réseaux de bioénergie forestière.Bioenergy plants are expected to play an important role in green energy production from forestry biomass. To incorporate bioenergy plant in the forest supply chain, the industry requires new investments as well as new value chain design and management. On the other side, the uncertainties associated with demand and price of new products in the market may add risks to such large investment in current forest supply chain. Hence, the main objective of this thesis is to analyze and to propose new design of the forest bioenergy network in both a deterministic and a stochastic context. The first part of the thesis has proposed four optimization models for strategic, tactical and operational planning levels of the supply chain. The models have included several collaborative actions between all involved stakeholders of the supply chain. They have been integrated in a new educational tool called hierarchical transportation game. In the second part of the thesis, we have integrated the developed optimization models to propose an integrated value chain design and value chain management optimization model. This model has been used to analyze a forest bioenergy network in Newfoundland. Newfoundland forest supply chain comprising four major stakeholders was considered as our case study. The profitability of adding a new bioenergy plant as well as new terminals in several potential locations have been evaluated. Finally, in a third part of the thesis we have proposed the bioenergy network taking into account uncertainty on demand and price of all final products of a new value chain. Several potential bioprocesses with different technologies have been evaluated for our case study. To provide a risk-averse solution, we have proposed two risk management models. The results from the three parts of the thesis have demonstrated the impact of integrated planning, bioenergy plants and collaboration on improvement of forest value chain. In general, the work in this thesis can support an efficient transformation of the forest supply chain considering investment risks. The optimization models and approaches proposed in this thesis are novel and practical for the forest bioenergy network design problem