Birth to death analysis of the energy payback ratio and CO2 gas emission rates from coal, fission, wind, and DT-fusion electrical power plants

White, S.; Kulcinski, G.L.

doi:10.1016/s0920-3796(00)00158-7

Cited by 96 publications

(64 citation statements)

References 3 publications

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“…The two net-energy metrics commonly applied to electricity generation technologies are the energy return on investment (EROI) and energy payback time (EPBT). EROI for electricity generation has been widely studied, especially coal-fired electricity, including carbon capture (Wu et al 2016;White and Kulcinski 2000), wind power (Kubiszewski et al 2010), solar photovoltaics (Bhandari et al 2015;Koppelaar 2016;Louwen et al 2016) and gas-fired generation (Moeller and Murphy 2016). The boundaries and types of analysis vary between studies, but all those just cited adopt the electricity busbar or inverter output as the EROI numerator-electricity distribution and management of the grid system as a whole is typically excluded from the analysis boundary.…”

Section: Discussionmentioning

confidence: 99%

An Exploration of Divergence in EPBT and EROI for Solar Photovoltaics

Palmer

Floyd²

2017

Biophys Econ Resour Qual

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Solar photovoltaics (PV) is widely regarded as one of the most promising renewable energy technologies. Net energy analysis (NEA) is a tool to evaluate the energetic performance of all energy supply technologies, including solar PV. Results across studies can appear to diverge sharply, which leads to contestation of NEA's relevance to energy transition feasibility assessment and contributes to ongoing uncertainty in relation to the critical issue of the sustainability of PV. This study explores how PV NEA approaches differ, including in relation to goal definitions, methodologies and boundaries of analysis. It focuses on two principal NEA metrics, energy return on investment (EROI) and energy payback time (EPBT). Here we show that most of the apparent divergence between studies is accounted for by six factors-life-cycle assessment methodology, age of the primary data, PV cell technology, the treatment of intermittency, equivalence of investment and output energy forms, and assumptions about real-world performance. The apparent divergence in findings between studies can often be traced back to different goal definitions. This study reviews the differing approaches and makes the case that NEA is important for assessing the role of PV in future energy systems, but that findings in the form of EROI or EPBT must be considered with specific reference to the details of the particular study context, and the research questions that it seeks to address. NEA findings in a particular context cannot definitively support general statements about EROI or EPBT of PV electricity in all contexts.

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Section: Discussionmentioning

confidence: 99%

An Exploration of Divergence in EPBT and EROI for Solar Photovoltaics

Palmer

Floyd²

2017

Biophys Econ Resour Qual

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“…The majority of the aforementioned studies [4][5][6][7][8][9][10][11][12][14][15][16][17][18][19][20][21][22][23][24][25][26][27]29] that performed the LCA of nuclear power generation systems defined the system boundary conditions to include front-end activities (mining, milling, refinery, conversion, enrichment, fuel fabrication), operation of power plants to generate electricity, back-end activities (interim storage, waste conditioning, waste disposal), transportation, construction of the nuclear power plant, and decommissioning of the nuclear power plant. One study [13] defined their boundary conditions to include all the activities associated with the majority of the studies that are listed above and the only exception being that the fuel cycle results were borrowed from the then existing literature.…”

Section: Review Of Nuclear Lca Studiesmentioning

confidence: 99%

Quantification of the Lifecycle Greenhouse Gas Emissions from Nuclear Power Generation Systems

2016

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This paper statistically quantifies the lifecycle greenhouse gas (GHG) emissions from six distinct reactor-based (boiling water reactor (BWR), pressurized water reactor (PWR), light water reactor (LWR), heavy-water-moderated reactor (HWR), gas-cooled reactor (GCR), fast breeder reactor (FBR)) nuclear power generation systems by following a two-step approach that included (a) performing a review of the lifecycle assessment (LCA) studies on the reactor-based nuclear power generation systems; and (b) statistically evaluating the lifecycle GHG emissions (expressed in grams of carbon dioxide equivalent per kilowatt hour, gCO 2 e/kWh) for each of the reactor-based nuclear power generation systems to assess the role of different types of nuclear reactors in the reduction of the lifecycle GHG emissions. Additionally, this study quantified the impacts of fuel enrichment methods (centrifuge, gaseous diffusion) on GHG emissions. The mean lifecycle GHG emissions resulting from the use of BWR (sample size, N = 15), PWR (N = 21), LWR (N = 7), HWR (N = 3), GCR (N = 1), and FBR (N = 2) in nuclear power generation systems are 14.52 gCO 2 e/kWh, 11.87 gCO 2 e/kWh, 20.5 gCO 2 e/kWh, 28.2 gCO 2 e/kWh, 8.35 gCO 2 e/kWh, and 6.26 gCO 2 e/kWh, respectively. The FBR nuclear power generation systems produced the minimum lifecycle GHGs. The centrifuge enrichment method produced lower GHG emissions than the gaseous diffusion enrichment method.

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“…For coal we harmonized to a 40 year lifetime and 0.55 capacity factor [4] and then averaged the input energy data from Weisbach et al [3] for hard coal and brown coal with the results from White and Kulchinski [5]. After harmonization, the data from these sources was in relatively close agreement.…”

Section: Simulation Input Datamentioning

confidence: 99%

Dynamic EROI Assessment of the IPCC 21st Century Electricity Production Scenario

Neumeyer

Goldston

2016

Sustainability

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Abstract:The Energy Return on Investment (EROI) is an important measure of the energy gain of an electrical power generating facility that is typically evaluated based on the life cycle energy balance of a single facility. The EROI concept can be extended to cover a collection of facilities that comprise a complete power system and used to assess the expansion and evolution of a power system as it transitions from one portfolio mix of technologies to another over time. In this study we develop a dynamic EROI model that simulates the evolution of a power system and we perform an EROI simulation of one of the electricity production scenarios developed under the auspices of the Intergovernmental Panel on Climate Change (IPCC) covering the global supply of electricity in the 21st century. Our analytic tool provides the means for evaluation of dynamic EROI based on arbitrary time-dependent demand scenarios by modeling the required expansion of power generation, including the plowback needed for new construction and to replace facilities as they are retired. The results provide insight into the level of installed and delivered power, above and beyond basic consumer demand, that is required to support construction during expansion, as well as the supplementary power that may be required if plowback constraints are imposed. In addition, sensitivity to EROI parameters, and the impact of energy storage efficiency are addressed.

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Birth to death analysis of the energy payback ratio and CO2 gas emission rates from coal, fission, wind, and DT-fusion electrical power plants

Cited by 96 publications

References 3 publications

An Exploration of Divergence in EPBT and EROI for Solar Photovoltaics

An Exploration of Divergence in EPBT and EROI for Solar Photovoltaics

Quantification of the Lifecycle Greenhouse Gas Emissions from Nuclear Power Generation Systems

Dynamic EROI Assessment of the IPCC 21st Century Electricity Production Scenario

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