Irreversible investment, uncertainty, and ambiguity: The case of bioenergy sector

Jouvet, Pierre‐André; Cadre, Elodie Le; Orset, Caroline

doi:10.1016/j.eneco.2011.08.018

Cited by 8 publications

(3 citation statements)

References 28 publications

(30 reference statements)

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“…(footnote continued) For example, Keppo and Lu[77] show that, in absence of competition, a large producer whose decisions affect the electricity price might decide to postpone further the investment as compared as to a small one facing the same uncertainties. Moreover, Jouvet et al[78] find that uncertainty over the degree of future competition might hamper investments 6. Other influencing factors are introduction and level of the CO 2 price, as well as emissions allowance prices for other pollutants.…”

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confidence: 99%

Greening the power generation sector: Understanding the role of uncertainty

Romano

Fumagalli

2018

Renewable and Sustainable Energy Reviews

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confidence: 99%

Greening the power generation sector: Understanding the role of uncertainty

Romano

Fumagalli

2018

Renewable and Sustainable Energy Reviews

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“…Thus, it has a direct impact on potential sales revenue and raw material/required energy supply. Here several issues Market volatility (Markandya & Pemberton, 2010), market size (Jouvet, Le Cadre, & Orset, 2012), market conditions (Dal Mas, Giarola, Zamboni, & Bezzo, 2010;Zheng et al, 2018), uncertain demand quantity (Guillen et al, 2005) (You & Grossmann, 2008) (You et al, 2009) (Kostin, Guillén-Gosálbez, Mele, Bagajewicz, & Jiménez, 2012) (Hahn & Kuhn, 2012) (Ruiz-Femenia et al, 2013) (Govindan & Fattahi, 2017).…”

Section: IVmentioning

confidence: 99%

A contribution to sustainable management of integrated material/energy networks in process industries

Morakabatchiankar

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Towards sustainability forces process industries to change their traditional patterns. Therefore, efficient retrofitting has been a significant challenge and raised several issues, motivating the process system engineering (PSE) to develop models. These models mainly aim to optimize profitability, cost reduction, energy consumption, demand satisfaction, the environmental impact associated with the production process, and social acceptance. Nevertheless, such optimization is significantly complicated if considering the presence of uncertainty and seeking compromised outcomes. This thesis aims to extend a general model to facilitate retrofitting in industrial processes and expedite optimization of the issues. Such a contribution based on developing efficient mathematical models allows coordinating many decision variables synchronizing the production and distribution tasks in terms of economic and environmental criteria. This thesis presents an overview of the retrofitting requirement towards sustainable material/energy networks, describing and analyzing the current methods, tools, and models used and identifying the most relevant open issues. The second part focused on developing current models stressing energy integration in the processing system. This part first explores how the economic performance of the network can be enhanced and environmental impacts improved simultaneously by integrating an energy generation unit into the production system. Furthermore, the network sustainability performance was explored under demand uncertainties. Additional risk indicators (including financial and environmental risk metrics) have been included to add risk management capability to the model. This part also explores the strategies that efficiently select the number of scenarios. Consequently, a novel generalized mathematical formulation that integrates equations regarding energy generation and material production decision variables is efficiently solved. The effect of uncertainty on the economic and environmental performance is analyzed by using risk analysis. Finally, the model was extended to solve multi-renewable energy generation integrated into the multi-product production process under demand uncertainty. The importance and effect of the energy/material integration over the network configuration are analyzed through sensitivity analysis. The third part of this thesis provides the conclusions and further work to be developed. El camino hacia la sostenibilidad obliga a las industrias de procesos a cambiar los patrones de trabajo tradicionales. La modernización eficiente es un importante desafío que plantea múltiples problemas, lo que ha llevado a la ingeniería de sistemas de procesos (PSE) a desarrollar modelos que intentan no solo optimizar la rentabilidad, reducir de costes o satisfacer demanda de productos y servicios, sino también afrontar el impacto ambiental asociado al proceso productivo y la aceptación social de dicho proceso, en entornos volátiles, en los que la consideración de la incertidumbre asociada al escenario de trabajo es esencial. Esta tesis tiene como objetivo ampliar y flexibilizar los modelos de gestión de cadena de suministro existentes para facilitar la retroadaptación de los procesos industriales y agilizar la optimización de los problemas de toma de decisiones en este entorno. Tal aporte está basado en el desarrollo de modelos matemáticos eficientes que permite coordinar diferentes variables de decisión, sincronizando las tareas de producción y distribución en términos de criterios económicos y ambientales. Para ello, en primer lugar se presenta una visión general del requisito de adaptación hacia redes de materiales / energía sostenibles, describiendo y analizando los métodos, herramientas y modelos actuales utilizados e identificando los problemas abiertos más relevantes. La segunda parte de esta Tesis se centra en el desarrollo de modelos que enfatizan la integración energética en el sistema de proceso. Esta parte explora primero cómo se pueden mejorar simultáneamente el desempeño económico de la red y los impactos ambientales mediante la integración de unidades de generación de energía en el sistema de producción. Además, se ha explorado el rendimiento de la sostenibilidad de la red bajo incertidumbre en la demanda. Se han incluido indicadores de riesgo adicionales (incluidas métricas de riesgo financiero y ambiental) para incorporar en el modelo la capacidad de gestión de riesgos. Esta parte también explora las estrategias que seleccionan de manera eficiente el número de escenarios a considerar. En consecuencia, se resuelve de forma eficiente una formulación matemática novedosa que generaliza e integra ecuaciones relativas a decisiones de producción energética y de materiales. El efecto de la incertidumbre sobre el desempeño económico y ambiental se analiza mediante análisis de riesgo. Finalmente, el modelo se amplía para abordar la utilización coordinada de diferentes formas de energía renovable, y su integración en el proceso de producción multi-producto bajo incertidumbre en la demanda. La importancia y el efecto de la integración de la toma de decisiones sobre la configuración de la red se discuten a través de diferentes análisis de sensibilidad. La tercera parte de esta tesis resume las conclusiones de todos estos trabajos y plantea ampliaciones y nuevas líneas de mejora que surgen a partir de los modelos y procedimientos desarrollados en esta tesis.

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“…The most common way to support bioenergy and other renewable solutions is capital investment subsidies (IRENA, 2022). Along with the novelty of renewable technologies, bio-based production requires an intensive initial capital investment due to the low (energy) density and heterogeneity of biomass, which requires expensive pre-treatment and processing facilities (Jouvet et al, 2012). Fixed investment subsidies are, therefore, implemented for faster industry growth (Newes et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Assessment of alternative sustainability aspects of bioeconomy innovations : A case study approach

Tassinari

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The Earth's climate system continues to change at an unprecedented rate and ongoing research underscores the urgent need for rapid progress in global and national adaptation and mitigation efforts. The European Union (EU) aims to become the first climate-neutral bloc of countries by 2050 and aspires to achieve a modern and resource-efficient economy. With that goal, on 11 December 2019, the European Commission (EC) launched the ambitious "European Green Deal". To implement it, on 22 June 2020, the EC established the EU Taxonomy Regulation to ensure the efficient movement of capital toward truly green investments (based on the degree of sustainability of an activity). However, there is currently no consensus on what should be assessed and how, which lead to different interpretations and meanings of sustainability performance as well as information inefficiencies that complicate and impair investment into facilitating green transactions. This thesis aims to contribute, through innovative approaches and methods, to a more detailed and careful evaluation of alternative paths to sustainable innovation that apply technologies and social practices based on bio-based materials to transform or re-design conventional production systems (namely, circular bioeconomy systems).Given the complexity and heterogeneity of bio-based systems, the literature contains several coexisting narratives on bioeconomy. After the introduction, the thesis begins by systematically reviewing the versatility of empirical studies-notably, case studies-along with the narratives surrounding the bioeconomy concept (i.e., an ecological economy, a science-based economy, and a biomass-based economy). The results of Chapter 1 provide an overview of how the narratives of the concept of bioeconomy affect the versatility of the case study research. Based on the low density of the illustrated semantic networks, we conclude that future empirical research on bio-based phenomena should be more transdisciplinary and rely more on cross-sectoral approaches. Further work is also required in developing common research protocols that support transparency and replicability of case studies in the bioeconomy.Building on the knowledge gained from this literature review, the thesis discusses three concrete cases, with both scientific and practical implications, of sustainability performance assessments. These studies capture the heterogeneity and complexity of bio-based systems, which differ in terms of feedstock, level of technological maturity,

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Irreversible investment, uncertainty, and ambiguity: The case of bioenergy sector

Cited by 8 publications

References 28 publications

Greening the power generation sector: Understanding the role of uncertainty

Greening the power generation sector: Understanding the role of uncertainty

A contribution to sustainable management of integrated material/energy networks in process industries

Assessment of alternative sustainability aspects of bioeconomy innovations : A case study approach

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