The value of switching inputs in a biodiesel production plant

Brandão, Luiz Eduardo Teixeira; Penedo, Gilberto Master; Bastian-Pinto, Carlos de Lamare

doi:10.1080/1351847x.2011.607005

Cited by 10 publications

(4 citation statements)

References 6 publications

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“…Methods in this group solve versions of the Bellman Equations ( 26) expressed for finite subsets of states and actions and accordingly specified dynamics for the market state component. In particular, trees or grids with associated transition probabilities represent the evolution of this component (see, e.g., Brandão et al 2013, Devalkar et al 2011, 2018, Felix and Weber 2012, Geman and Kourouvakalis 2008, Goel and Gutierrez 2011, Hahn and Dyer 2008, Jaillet et al 2004, Kamrad and Ernst 2001, Lai et al 2011, Manoliu 2004, Parsons 2013, Secomandi 2010b, Tseng and Lin 2007, Zhou et al 2016, and Wu et al 2012. This approach is limited to applications with low-dimensional state and action spaces, unless other approximations are made (Devalkar et al 2011, Lai et al 2010, and Nadarajah et al 2015.…”

Section: Approximations and Boundsmentioning

confidence: 99%

“…In particular, trees or grids with associated transition probabilities represent the evolution of this component (see, e.g., Brandão et al. 2013, Devalkar et al. 2011,2018, Felix and Weber 2012, Geman and Kourouvakalis 2008, Goel and Gutierrez 2011, Hahn and Dyer 2008, Jaillet et al.…”

Section: Solution Approaches and Implications Of Price Model Choicementioning

confidence: 99%

“…The extant literature on energy and commodity operations includes two main types of models: (i) Ones that optimize operating policies taking capacity levels or production technologies as given and (ii) ones that optimize investment policies that choose these levels or technologies, possibly along with the optimization of operating policies. Research that illustrates the former strand includes Smith and McCardle (1998), Deng et al (2001), Kamrad and Ernst (2001), Tseng and Barz (2002), Jaillet et al (2004), Manoliu (2004), Smith (2005), Tseng and Lin (2007), Cortazar et al (2008), Boogert and de Jong (2008), Geman and Kourouvakalis (2008), Hahn and Dyer (2008), Kjaer (2008), N€ as€ akk€ al€ a and Keppo (2008), Carmona and Ludkovski (2010), Lai et al (2010), Secomandi (2010aSecomandi ( ,b, 2015Secomandi ( , 2018, Brandão et al (2013), Denault et al (2013), Lai et al (2011), Devalkar et al (2011Devalkar et al ( , 2018, Goel and Gutierrez (2011), Goel and Tanrisever (2017), Kim and Powell (2011), Felix and Weber (2012), Secomandi and Wang (2012), Wu et al (2012), Arvesen et al (2013), Kouvelis et al (2013Kouvelis et al ( , 2018, Mazi eres and Boogert (2013), Parsons (2013), …”

Section: Introductionmentioning

confidence: 99%

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A Discussion of Non‐Gaussian Price Processes for Energy and Commodity Operations

Gambaro

Secomandi

2021

Production and Operations Management

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Energy sources and commodities exhibit high price risk. This risk is thus an important feature of operational models of the value chains for these goods. These models typically employ Gaussian‐based representations of the evolution of this uncertainty. This approach facilitates the optimization of operational policies but is at odds with empirical facts about energy and commodity prices, which are better captured by non‐Gaussian processes. We discuss this alternative modeling strategy, focusing on Lévy processes. As an illustration, we show that it substantially increases the optimal policy value in a simplified merchant natural gas storage setting. Further, we highlight potential implications of using this approach to formulate realistic energy and commodity operations models. Our work has broader relevance for modeling the dynamics of both other market variables and operational quantities, such as exchange rates and demand forecasts. The study of how the adoption of non‐Gaussian processes may impact energy and commodity operations is an appealing area for future research.

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Section: Approximations and Boundsmentioning

confidence: 99%

Section: Solution Approaches and Implications Of Price Model Choicementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Discussion of Non‐Gaussian Price Processes for Energy and Commodity Operations

Gambaro

Secomandi

2021

Production and Operations Management

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“…Factoring uncertainty into the cost/benefit analysis for entry into the biofuel supply chain has recently gained popularity (Brandão, et al, 2009, Burke, 2012, Pederson and Zou, 2009, Schmit, et al, 2009 but this approach has not been applied to the analysis of investment in a second generation drop-in biofuel plants. This paper fills this gap by developing a real options model of a plant's decision making for optimal entry, exit, mothball, and reactivation trigger prices for a second-generation corn stover fed biofuel plant.…”

mentioning

confidence: 99%