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Investigation of possible approaches for consequential electricity markets in ecoinvent

Pettersson, Malin (2015) FMI820 20151
Environmental and Energy Systems Studies
Abstract (Swedish)
Version 3 av ecoinvent är den första databasen att erbjuda möjligheten att koppla samman livscykelinventeringar (LCI) utefter olika länkningsalgoritmer. Genom dessa länkningsalgoritmer tar ecoinvent nu fram bakgrundslivscykelinventeringar med både medeldata och långsiktig marginaldata (t.ex. över elmarknader i olika länder). Idealt sett representerar långsiktig marginaldata över elmarknader den ytterligare kraftverkskapaciteten som behöver installeras (installationsmarginal) för att täcka en förändrad efterfrågan av elektricitet inom en specifik marknad. Sådana LCI-data används inom konsekvensLCA (cLCA) och behövs för att korrekt bedöma miljöpåverkan av att ändra ursprung eller produktionssätt i ett produktsystem som använder elektricitet.... (More)
Version 3 av ecoinvent är den första databasen att erbjuda möjligheten att koppla samman livscykelinventeringar (LCI) utefter olika länkningsalgoritmer. Genom dessa länkningsalgoritmer tar ecoinvent nu fram bakgrundslivscykelinventeringar med både medeldata och långsiktig marginaldata (t.ex. över elmarknader i olika länder). Idealt sett representerar långsiktig marginaldata över elmarknader den ytterligare kraftverkskapaciteten som behöver installeras (installationsmarginal) för att täcka en förändrad efterfrågan av elektricitet inom en specifik marknad. Sådana LCI-data används inom konsekvensLCA (cLCA) och behövs för att korrekt bedöma miljöpåverkan av att ändra ursprung eller produktionssätt i ett produktsystem som använder elektricitet. Den nuvarande sammankopplingen av inventeringar till ’konsekvensbaserade elmarknader’ är behäftad med tillkortakommanden genom att exempelvis marknadsspecifika förhållanden inte modelleras, att endast redan producerande tekniker inkluderas, och att el från kraftvärmeverk inte anses vara en del av framtida installationer, vilket resulterar i orealistisk output från framtida installationsmarginaler. Eftersom majoriteten av producerade varor och tjänster i varje sektor av ekonomin till stor del är beroende av elektricitet, behöver angreppsättet för hur konsekvensbaserade elmarknader modelleras förbättras för att stödja relevanta konsekvensLCA-resultat.

I denna uppsats gjordes en litteraturstudie över vilka aktuella angreppsätt som rekommenderas för modellering av eltillförsel i konsekvensLCA. För närvarande är konsekvensversionen av ecoinvent definierad utifrån småskaliga, långsiktiga beslut. Baserat på litteraturstudien ansågs det bästa angreppssättet vara att använda nationella officiella prognoser för elsektorn över perioden 2008-2035. För att bedöma angreppssättets tillförlitlighet tillämpades det på ecoinvents elmarknader för Brasilien, Kina, Indien, Japan, Ryssland och Schweiz. Tillämpningen gav mer diversifierade elmarknadsmixer jämfört med status quo, och kom runt de nuvarande tillkortakommandena. En fortsatt bedömning av angreppssättet gjordes genom att beräkna miljöpåverkan med IPCC 2007 GWP, 100a och ReCiPe 2008 livscykelspåverkananalys (LCIA). Förändringar observerades i alla midpoint-indikatorer, t.ex. en tydlig minskning av global uppvärmningspotential (GWP), partiklarbildning, och försurning, för de studerade marknaderna vars nuvarande konsekvenselmarknad innehåller stor andel fossil tillförsel. Sammanfattningsvis rekommenderas användande av prognoser från datakällor med samstämda bakgrundsantaganden för att förbättra de kvarvarande konsekvenselmarknaderna i ecoinvent. För att möjliggöra modellering av storskaliga beslut kan framtida studier inkludera dataset över fler scenarier och tidsramar för användaren av ecoinvent att välja emellan, såväl som implementering av en dynamisk optimeringsmodell. (Less)
Abstract
Version 3 of the ecoinvent database is the first background database to offer the possibility to link life cycle inventories (LCI) according to different linking algorithms. Using those algorithms, ecoinvent now provides both average and long-term, marginal background LCI data, (e.g. for electricity markets for different countries). Long-term, marginal data for electricity markets ideally represents the additional power plant capacity that needs to be installed to cover a change in demand for electricity in that market. Such LCI data is used in consequential LCA (cLCA) and is needed for an accurate assessment of the environmental impacts of a decision to alter the source or production method of a product system using electricity. The... (More)
Version 3 of the ecoinvent database is the first background database to offer the possibility to link life cycle inventories (LCI) according to different linking algorithms. Using those algorithms, ecoinvent now provides both average and long-term, marginal background LCI data, (e.g. for electricity markets for different countries). Long-term, marginal data for electricity markets ideally represents the additional power plant capacity that needs to be installed to cover a change in demand for electricity in that market. Such LCI data is used in consequential LCA (cLCA) and is needed for an accurate assessment of the environmental impacts of a decision to alter the source or production method of a product system using electricity. The current linking of inventories into ‘consequential’ electricity markets is associated with shortcomings, e.g. due to the fact that market-specific conditions are not modelled, only already producing technologies are included, and electricity produced in combined heat-and power-plants is considered not taking part in future installations and results in unrealistic output of future build-margins. Because the majority of goods and services produced in every sector of the economy rely heavily on electricity, the modelling approach for the consequential electricity markets must be improved to allow the ecoinvent database to provide relevant results for cLCAs.

In this thesis, a literature study was performed to investigate which approaches are currently being recommended for modelling electricity supply in cLCA.
Currently, the consequential version of ecoinvent is defined for small-scale, long-term decisions. From the literature study, the best approach was determined to be the use of nation-wide official forecasts of the power sector covering the time horizon 2008-2035. To determine the reliability of that approach, it was applied to Brazil, China, India, Japan, Russia and Switzerland. The results of these applications demonstrate more diversified mixes for all markets compared to status quo, overcoming the current shortcomings. A continued evaluation of the approach using the IPCC 2007 GWP, 100a and the ReCiPe 2008 life cycle impact assessment (LCIA) methods shows changes in all midpoint indicators, e.g. a clear reduction in Global Warming Potential (GWP), particulate matter formation and acidification for the studied markets with large shares of fossil supply in the current consequential markets. In summation, it is recommended to continue using the forecasts from consistent data sources to improve the remaining consequential electricity markets in ecoinvent. Future work may include using several scenario and time-frame datasets for the ecoinvent user to choose between, as well as implementation of a dynamic optimization model to allow for large-scale decision modelling. (Less)
Please use this url to cite or link to this publication:
author
Pettersson, Malin
supervisor
organization
course
FMI820 20151
year
type
H3 - Professional qualifications (4 Years - )
subject
keywords
KonsekvensLCA, ecoinvent, elmarknader, långsiktig marginaldata, LCI-modellering, prognoser, Consequential LCA, electricity markets, long-term marginal data, LCI modelling, forecasts
report number
ISRN LUTFD2/TFEM--15/5136--SE + (1-105)
ISSN
1102-3651
language
English
id
9004355
date added to LUP
2020-02-06 10:10:13
date last changed
2020-02-06 10:10:13
@misc{9004355,
  abstract     = {{Version 3 of the ecoinvent database is the first background database to offer the possibility to link life cycle inventories (LCI) according to different linking algorithms. Using those algorithms, ecoinvent now provides both average and long-term, marginal background LCI data, (e.g. for electricity markets for different countries). Long-term, marginal data for electricity markets ideally represents the additional power plant capacity that needs to be installed to cover a change in demand for electricity in that market. Such LCI data is used in consequential LCA (cLCA) and is needed for an accurate assessment of the environmental impacts of a decision to alter the source or production method of a product system using electricity. The current linking of inventories into ‘consequential’ electricity markets is associated with shortcomings, e.g. due to the fact that market-specific conditions are not modelled, only already producing technologies are included, and electricity produced in combined heat-and power-plants is considered not taking part in future installations and results in unrealistic output of future build-margins. Because the majority of goods and services produced in every sector of the economy rely heavily on electricity, the modelling approach for the consequential electricity markets must be improved to allow the ecoinvent database to provide relevant results for cLCAs. 

In this thesis, a literature study was performed to investigate which approaches are currently being recommended for modelling electricity supply in cLCA. 
Currently, the consequential version of ecoinvent is defined for small-scale, long-term decisions. From the literature study, the best approach was determined to be the use of nation-wide official forecasts of the power sector covering the time horizon 2008-2035. To determine the reliability of that approach, it was applied to Brazil, China, India, Japan, Russia and Switzerland. The results of these applications demonstrate more diversified mixes for all markets compared to status quo, overcoming the current shortcomings. A continued evaluation of the approach using the IPCC 2007 GWP, 100a and the ReCiPe 2008 life cycle impact assessment (LCIA) methods shows changes in all midpoint indicators, e.g. a clear reduction in Global Warming Potential (GWP), particulate matter formation and acidification for the studied markets with large shares of fossil supply in the current consequential markets. In summation, it is recommended to continue using the forecasts from consistent data sources to improve the remaining consequential electricity markets in ecoinvent. Future work may include using several scenario and time-frame datasets for the ecoinvent user to choose between, as well as implementation of a dynamic optimization model to allow for large-scale decision modelling.}},
  author       = {{Pettersson, Malin}},
  issn         = {{1102-3651}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Investigation of possible approaches for consequential electricity markets in ecoinvent}},
  year         = {{2015}},
}