Implications of integrating electricity supply dynamics into life cycle assessment: A case study of renewable distributed generation

Amor, Ben; Gaudreault, Caroline; Pineau, Pierre‐Olivier; Samson, Réjean

doi:10.1016/j.renene.2014.03.063

Cited by 38 publications

(29 citation statements)

References 27 publications

(49 reference statements)

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“…Policy studies often use more complex methods to estimate emissions resulting from electricity generation, but expecting an analyst assessing a product's life cycle emissions to model the electricity system in great detail could be unrealistic (Amor et al. ). Factors that make an analyst's task more challenging include temporal variation, electricity trading, and marginal emissions, which are all particularly difficult and data intensive to model.…”

Section: Discussionmentioning

confidence: 99%

“…Ignoring temporal variation can reduce the relevance of a study if a load varies substantially with time (Amor et al. ). It can make a significant difference in emissions if a load occurs during on‐peak or off‐peak hours (Mathiesen et al.…”

Section: Methodsmentioning

confidence: 99%

“…Information required to estimate which specific generators are marginal, such as price bids, are typically not publicly available (Amor et al. ). Even when necessary data are available (possibly from regional transmission organizations or independent system operators [ISOs]), identifying the marginal generators is difficult and greatly increases analysis time (Mathiesen et al.…”

Section: Methodsmentioning

confidence: 99%

“…), making it extremely important for practitioners to “exercise caution and sensitivity” when modeling electricity supply scenarios (Amor et al. ). This article describes the algorithm's logic and structure, and presents the algorithm's recommended method types for particular loads alongside those used in previous literature.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Decision Support Algorithm for Evaluating Carbon Dioxide Emissions from Electricity Generation in the United States

Ryan

Johnson

Keoleian

et al. 2017

J of Industrial Ecology

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This article presents an algorithm to aid practitioners in determining the most appropriate method to estimate carbon dioxide emissions from an electricity load. Applications include sustainability assessments of products, processes, energy efficiency improvements, changes in generation infrastructure, and changes in electricity demand. Currently, there is no consensus on appropriate methods for calculating greenhouse gas emissions resulting from specific electricity loads. Previous research revealed significant differences in emissions when different methods were used, a situation that could result in divergent sustainability or policy recommendations. In this article, we illustrate the distribution of emissions estimates based on method characteristics such as region size, temporal resolution, average or marginal approaches, and time scales. Informed by these findings, a decision support algorithm is presented that uses a load's key features and an analyst's research question to provide recommendations on appropriate method types. We defined four different cases to demonstrate the utility of the algorithm and to illustrate the variability of methods used in previous studies. Prior research often employed simplifying assumptions, which, in some cases, can result in electricity being allocated to the incorrect generating resources and improper calculation of emissions. This algorithm could reduce inappropriate allocation, variability in assumptions, and increase appropriateness of electricity emissions estimates. Keywords:electricity generation electric utility emissions factor greenhouse gas (GHG) emissions industrial ecology marginal emissions Supporting information is linked to this article on the JIE website Conflict of interest statement: The authors have no conflict to declare.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Decision Support Algorithm for Evaluating Carbon Dioxide Emissions from Electricity Generation in the United States

Ryan

Johnson

Keoleian

et al. 2017

J of Industrial Ecology

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“…It is well known that PV represents a sustainable energy solution (Pearce, 2002) to the world's energy challenges as it has significant environmental benefits as shown by numerous life cycle analysis (LCA) studies (Fthenakis et al, 2008;Fthenakis andKim, 2009, 2011;Cucchiella and D'adamo, 2013;Peng et al, 2013;Amor et al, 2014;Lamnatou et al, 2015). The reduced materials needed for the X-wire racking would indicate a further improved environmental impact to transition away from fossil fuels to PV.…”

Section: Discussionmentioning

confidence: 99%

Total U.S. cost evaluation of low-weight tension-based photovoltaic flat-roof mounted racking

Wittbrodt

Pearce

2015

Solar Energy

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The economics in the U.S. of solar photovoltaic (PV) systems is changing rapidly as the cost per unit power of PV modules has dropped quickly. These costs reductions have two important results: marked decrease in levelized cost of electricity (LCOE) into ranges competitive or better than traditional electricity-generation technologies and the economic role of racking has been gaining prominence relative to that of modules. As the relative importance of costs of PV racking has been marginal historically, there has been relatively little progress on reducing the materials and costs associated with it, which has caused racking to contribute to a significant portion of costs of entire PV systems. In order to overcome this challenge this study investigates a novel low-weight PV racking system for commercial rooftops based on crossed cables (X-wires) and compares it to racking systems already available on the market on capital costs, labor costs for installation, and technical specifications such as adaptability and power packing factor. The results of over 80% cost reduction and 33% increase in power density are presented and conclusions are drawn about the potential for tension-based racking systems to further reduce total PV systems costs on commercial flat roof tops resulting in LCOE savings of $0.01-$0.02/kW h.

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Defining Temporally Dynamic Life Cycle Assessment: A Review

Sohn

Kalbar

Goldstein

et al. 2020

Integr Envir Assess & Manag

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Durable goods last for years, decades, or even centuries. The environmental implications of the changing social, economic, and material conditions in which these goods are embedded can be overlooked by conventional life cycle assessment (LCA) that assumes a static world. To avoid this oversight, methods such as dynamic LCA (DLCA) are increasingly being used. Despite the growing use of DLCA, numerous questions remain, including how this dynamism is incorporated and what aspects of any given DLCA are dynamic. To answer these questions, we performed a review of 56 DLCAs, of which 44 propose a framework for DLCA covering all International Organization for Standardization phases of an LCA or that carry out a DLCA. Three types of LCA dynamism are identified and assessed for the reviewed literature: dynamic process inventory, dynamic systems, and dynamic characterization, while a further 2 types of LCA dynamism, dynamic scope and dynamic weighting, are proposed but not applied in the assessed literature. We found that the implementation of DLCA varies widely, and inventories accounting for dynamic characteristics are by far the most prevalent expression of DLCA. To reduce confusion surrounding the discussion of DLCA, we propose a definition of DLCA and its subtypes: full DLCA, partial DLCA, and prospective LCA. It is concluded that, among the current array of DLCA definitions, the implementation of partially dynamic LCA (PDLCA), which applies dynamism in only some parts of the LCA, is common and likely to continue. This is because PDLCA offers quantifiable marginal utility in terms of increased validity of the assessment, in relation to conventional LCA methods, but caution is needed in applying PDLCA because of potential for introducing bias into the LCA. To avoid this problem, we propose incorporating system dynamism as part of a sensitivity analysis, particularly in PDLCA that are limited by missing data. Integr Environ Assess Manag 2020;16:314-323. © 2019 SETAC

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Implications of integrating electricity supply dynamics into life cycle assessment: A case study of renewable distributed generation

Cited by 38 publications

References 27 publications

Decision Support Algorithm for Evaluating Carbon Dioxide Emissions from Electricity Generation in the United States

Decision Support Algorithm for Evaluating Carbon Dioxide Emissions from Electricity Generation in the United States

Total U.S. cost evaluation of low-weight tension-based photovoltaic flat-roof mounted racking

Defining Temporally Dynamic Life Cycle Assessment: A Review

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