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GenX

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Project GenX
Host MIT and Princeton University
Status active
Scope/type power sector investment planning
Code license GPLv2
Website genx.mit.edu
Repository github.com/GenXProject/GenX
Documentation genxproject.github.io/GenX/dev/

GenX is power sector capacity expansion model originally developed by researchers in the United States.[1][2] The framework is written in Julia (the only such project listed here as of 2021) and uses the JuMP library for building the underlying optimization problem.[3][4] GenX through JuMP can utilize various open source optimization solvers (including CBC/CLP) and commercial solvers (including CPLEX and Gurobi). In June 2021, the project launched as an active open source project and test suites are provided to assist onboarding.[5]

In parallel, the PowerGenome project is designed to provide GenX with a comprehensive current state dataset of the United States electricity system.[6] That dataset can then be used as a springboard for the development of future scenarios.

GenX has been used to explore long-term storage options in systems with high renewables shares.[7][8] While North America remains a key focus, the software has been applied to problems in India,[9] Italy,[10] and Spain.[11]

WCF trials

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  • stub

References

  1. ^ Jenkins, Jesse D; Sepulveda, Nestor A (27 November 2017). Enhanced decision support for a changing electricity landscape: the GenX configurable electricity resource capacity expansion model — An MIT Energy Initiative Working Paper — Revision 1.0 (PDF). Cambridge, Massachusetts, USA: Massachusetts Institute of Technology. Retrieved 2021-04-06. MITEI-WP-2017-10.
  2. ^ "GenX documentation". GenX project. Retrieved 2021-06-09.
  3. ^ Dunning, Iain; Huchette, Joey; Lubin, Miles (2017). "JuMP: a modeling language for mathematical optimization" (PDF). SIAM Review. 59 (2): 295–320. doi:10.1137/15M1020575. ISSN 0036-1445. Retrieved 2018-05-21.
  4. ^ "JuMP". JuMP. Retrieved 2021-06-09.
  5. ^ Jenkins, Jesse (9 June 2021). "GenX open source release". Open Energy Modelling Initiative. Retrieved 2021-06-09. Public mailing list posting.
  6. ^ Schivley, Greg (26 March 2020). Create capacity expansion model inputs with PowerGenome (MP4) (webcast). Open Energy Modelling Initiative (openmod). Retrieved 2020-09-16. MP4 webcast 00:10:55.
  7. ^ Sepulveda, Nestor A; Jenkins, Jesse D; Edington, Aurora; Mallapragada, Dharik S; Lester, Richard K (May 2021). "The design space for long-duration energy storage in decarbonized power systems". Nature Energy. 6 (5): 506–516. doi:10.1038/s41560-021-00796-8. ISSN 2058-7546. Closed access icon
  8. ^ Mallapragada, Dharik S; Sepulveda, Nestor A; Jenkins, Jesse D (1 October 2020). "Long-run system value of battery energy storage in future grids with increasing wind and solar generation". Applied Energy. 275: 115390. doi:10.1016/j.apenergy.2020.115390. ISSN 0306-2619. Closed access icon
  9. ^ Rudnick García, Iván (September 2019). Decarbonizing the Indian power sector by 2037: evaluating different pathways that meet long-term emissions targets (PDF). Cambridge, Massachusetts, USA: Massachusetts institute Of Technology (MIT). Retrieved 2021-06-09.
  10. ^ Bompard, E; Botterud, A; Corgnati, S; Huang, T; Jafari, M; Leone, P; Mauro, S; Montesano, G; Papa, C; Profumo, F (1 November 2020). "An electricity triangle for energy transition: application to Italy". Applied Energy. 277: 115525. doi:10.1016/j.apenergy.2020.115525. ISSN 0306-2619. Closed access icon
  11. ^ Oyler, Anthony Fratto; Parsons, John E (May 2020). The value of pumped hydro storage for deep decarbonization of the Spanish grid — Working paper CEEPR WP 2020-007 (PDF). Cambridge, Massachusetts, USA: MIT Center for Energy and Environmental Policy Research (CEEPR). Retrieved 2021-06-09.

Miscellaneous

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REMIND-D

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REMIND-D
  • documentation[1]
    • evince ~/synk/pdfs/2012-schmid-etal-remind-d-hybrid-energy-economy-model-of-germany-pik.pdf &
  • documentation (identical to above)[2]
    • evince ~/synk/pdfs/2012-schmid-etal-remind-d-hybrid-energy-economy-model-of-germany-ceem.pdf &
  • recommended paper: Schmid and Knopf (2012)[3]
    • evince ~/synk/pdfs/2012-schmid-and-knopf-ambitious-mitigation-scenarios-for-germany-participatory-approach.pdf &
  • report version (of above?)[4]
    • evince ~/synk/pdfs/2012-schmid-and-knopf-ambitious-mitigation-scenarios-for-germany-participatory-approach-report.pdf &
  • the project it was embedded in[5]
  • see email traffic from Eva Schmidt (24-Nov-2016)
    • Actually it was more about a pilot project to involve stakeholders in scenario development. The paper attached presents the process and resulting scenarios.
REMIND
  • REMIND documentation[6]
    • evince ~/synk/pdfs/2015-luderer-etal-description-remind-model-version-1-6.pdf &

References

  1. ^ Schmid, Eva; Knopf, Brigitte; Bauer, Nico (February 2012). REMIND–D: a hybrid energy–economy model of Germany (PDF). Potsdam, Germany: Potsdam Institute for Climate Impact Research (PIK). Retrieved 2016-11-24. Dated January 2012 inside.
  2. ^ Schmid, Eva; Knopf, Brigitte; Bauer, Nico (September 2012). REMIND-D: a hybrid energy-economy model of Germany (PDF). Milan, Germany: Fondazione Eni Enrico Mattei (FEEM). Retrieved 2016-12-14. Dated January 2012 inside.
  3. ^ Schmid, Eva; Knopf, Brigitte (December 2012). "Ambitious mitigation scenarios for Germany: a participatory approach". Energy Policy. 51: 662–672. doi:10.1016/j.enpol.2012.09.007. ISSN 0301-4215.
  4. ^ Schmid, Eva; Knopf, Brigitte (December 2012). Ambitious mitigation scenarios for Germany: a participatory approach (PDF). Potsdam, Germany: Potsdam Institute for Climate Impact Research (PIK). Retrieved 2016-11-24.
  5. ^ "ENCI-LowCarb: Engaging civil society in low carbon scenarios". Retrieved 2016-11-24.
  6. ^ Luderer, Gunnar; Leimbach, Marian; Bauer, Nico; Kriegler, Elmar; Baumstark, Lavinia; Bertram, Christoph; Giannousakis, Anastasis; Hilaire, Jérôme; Klein, David; Levesque, Antoine; Mouratiadou, Ioanna; Pehl, Michaja; Pietzcker, Robert; Piontek, Franziska; Roming, Niklas; Schultes, Anselm; Schwanitz, Valeria Jana; Strefler, Jessica (November 2015). Description of the REMIND model (version 1.6). Potsdam, Germany: Potsdam Institute of Climate Impact Research. Retrieved 2016-12-15.

Germanwatch

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  • Climate Change Performance Index 2017[1]
    • press release and report are available

References

  1. ^ "Climate Change Performance Index 2017: global energy transition has started". Clean Energy Wire (CLEW). Berlin, Germany. 17 November 2016. Retrieved 2016-11-17.

Climate Action Plan 2050

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EU legislation

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Climate study

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Natural gas campaign

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  • natural gas campaign in Germany in late-2016[1]

References

  1. ^ ""German gas sector declares energy war on coal industry"". Clean Energy Wire (CLEW). Berlin, Germany. 28 October 2016. Retrieved 2016-10-31.

EU Energy Union

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  • EU Energy Union document, 2015[1]

References

  1. ^ Energy Union package — A framework strategy for a resilient Energy Union with a forward-looking climate change policy — COM(2015) 80 final. Brussels, Belgium: European Commission. 25 February 2015. Retrieved 2016-10-27.

Priority dispatch

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Documents leaked in late-2016 reveal that a confidential European Union impact assessment analyzes four scenarios for paring back the 'priority dispatch' system afforded to renewable generation in many countries. The assessment concludes that removing priority dispatch could increase carbon emissions by 45 million to 60 million tonnes per annum or up to 10%, with the aim of making European energy generators more flexible and cost-competitive. Priority dispatch is mandated under the current EU renewable energy directive, although the United Kingdom, the Netherlands, and Sweden do not comply. Industry sources told The Guardian that it is "highly likely" that priority dispatch will be removed from the next EU directive, which takes effect from 2020. Sources also said that renewable generators would seek financial compensation if priority dispatch is eliminated. The WindEurope trade association reacted strongly to the news.[1]

References

  1. ^ Neslen, Arthur (1 November 2016). "Renewables could lose European power grid priority, documents reveal". The Guardian. London, United Kingdom. ISSN 0261-3077. Retrieved 2016-11-01.

IPCC integrated modeling

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  • Bruckner (2016) essay on IPCC update[1]
    • evince ~/synk/pdfs/2016-bruckner-decarbonizing-global-energy-system.pdf &
  • Waldman (2015) on IPCC's shifting position on nuclear power[2]

References

  1. ^ Bruckner, Thomas (January 2016). "Decarbonizing the global energy system: An updated summary of the IPCC report on mitigating climate change". Energy Technology. 4 (1): 19–30. doi:10.1002/ente.201500387. ISSN 2194-4296. Retrieved 2016-10-26.
  2. ^ Waldman, Suzanne (8 February 2015). "Timeline: The IPCC's shifting position on nuclear energy". Bulletin of the Atomic Scientists. Retrieved 2016-10-26.

EMF

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  • Sweeney (1983)[1]
    • evince ~/synk/pdfs/1983-sweeney-energy-model-comparison-overview.pdf &




References

  1. ^ Sweeney, James L (1983). "Chapter 12: Energy model comparison: an overview" (PDF). In Thrall, Robert M; Thompson, Russell G; Holloway, Milton L (eds.). Large-scale energy models: prospects and potentials. Boulder, CO, USA: Westview Press. pp. 191–217. Retrieved 2016-10-22. Copyright held by American Association for the Advancement of Science (AAAS).

CCL-D

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EMF 32

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US GHG and revenue recycling scenarios

The Energy Modeling Forum (EMF), coordinated by Stanford University, is due to release its EMF 32 report in late-2016.[1] The study is titled "US GHG and revenue recycling scenarios" and will, among other things, look at the redistribution of revenue from selected climate policies. I image a carbon tax or fee is one of those policies. Quoting from the EMF website:

The purpose of this modeling exercise is to use energy-economic models to assess emissions, energy and economic outcomes from a plausible range of US policies to reduce greenhouse gases (GHGs). In addition to standard emphasis on the effects of such policies on emissions, energy prices and macroeconomic performance, an economic issue of particular interest will be how fiscal decisions on revenue distribution might also affect these outcomes.[1]

The study appears appropriate for this article and should probably be added when released. Best wishes. RobbieIanMorrison (talk) 19:17, 24 October 2016 (UTC)

References

  1. ^ a b "EMF 32: US GHG and revenue recycling scenarios". Energy Modeling Forum (EMF). Standford, CA, USA. Retrieved 2016-10-22.

IIASA study

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  • Ummel (2016) IIASA working paper[1]
    • evince ~/synk/pdfs/2016-ummel-impact-ccl-proposed-carbon-fee-and-dividend-policy.pdf &

References

  1. ^ Ummel, Kevin (April 2016). Impact of CCL's proposed carbon fee and dividend policy: A high-resolution analysis of the financial effect on US households — Working Paper v1.4 (PDF). Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA). Retrieved 2016-07-08.

Environmental taxation study

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  • status: read
  • Klenert et al (2016)[1]
    • circulated by CCL-D
    • evince ~/synk/pdfs/2016-klenert-etal-environmental-taxation-inequality-engels-law.pdf &

References

  1. ^ Klenert, David; Schwerhoff, Gregor; Edenhofer, Ottmar; Mattauch, Linus (2016). "Environmental taxation, inequality and Engel's law: the double dividend of redistribution". Environmental and Resource Economics: 1–20. doi:10.1007/s10640-016-0070-y. ISSN 1573-1502.

Kirstins material

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  • Rausch et al (2010)[1]
    • evince ~/synk/pdfs/2010-rausch-etal-distributional-implications-alternative-us-greenhouse-gas-control-measures.pdf &
  • Hinkle and Richter (2016)[2]
    • evince ~/synk/pdfs/2016-hinkle-and-richter-financial-impact-households-carbon-fee-and-dividend.pdf &
  • Ummel (2016)
    • evince ~/synk/pdfs/2016-ummel-impact-ccl-proposed-carbon-fee-and-dividend-policy.pdf &

References

  1. ^ Rausch, Sebastian; Metcalf, Gilbert E; Reilly, John M; Paltsev, Sergey (July 2010). "Distributional implications of alternative US greenhouse gas control measures". The BE Journal of Economic Analysis and Policy. 10 (2). doi:10.2202/1935-1682.2537. ISSN 1935-1682. Retrieved 2016-12-02. Open access icon
  2. ^ Hinkle, Jerry; Richter, Daniel (5 May 2016). Financial Impact on Households of Carbon Fee and Dividend — Summary — Version 2 (PDF). Coronado, CA, USA: Citizens' Climate Lobby. Retrieved 2016-12-02.

Energy modeling

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  • Huntington et al (1982) on modeling for insight[1]
  • Strachan and Kannan (2008) on hybrid modeling for the UK[2]
  • Pfenninger et al (2014)[3]
    • to add: energy modeling
    • evince ~/synk/pdfs/2014-pfenninger-etal-energy-systems-modeling-for-twenty-first-century-energy-challenges.pdf &
  • Herbst et al (2012) on an introduction to energy system modeling[4]
    • to add: energy modeling
    • evince ~/synk/pdfs/2012-herbst-etal-intro-to-energy-system-modelling.pdf &
  • Strachan et al (2016) on reinventing the energy modelling–policy interface[5]
    • to add: energy modeling? Open Energy Modelling Initiative?
    • evince ~/synk/pdfs/2016-strachan-etal-reinventing-the-energy-modelling-policy-interface.pdf &
    • "Third, silos are built-up around different modelling approaches. These silos of modellers — for example, IAMs, energy system optimization models (ESOMs), agent-based models, and systems dynamics, computable general equilibrium (CGE), electricity dispatch, transport discrete choice and building stock models — form their own professional networks, attend specific conferences, publish in a core set of journals and utilize different data banks (for example, CGE modellers and the Global Trade Analysis Project initiative)." (p1)

References

  1. ^ Huntington, Hillard G; Weyant, John P; Sweeney, James L (1 January 1982). "Modeling for insights, not numbers: the experiences of the energy modeling forum". Omega: The International Journal of Management Science. 10 (5): 449–462. doi:10.1016/0305-0483(82)90002-0. ISSN 0305-0483.
  2. ^ Strachan, Neil; Kannan, Ramachandran (November 2008). "Hybrid modelling of long-term carbon reduction scenarios for the UK". Technological Change and the Environment. 30 (6): 2947–2963. doi:10.1016/j.eneco.2008.04.009. ISSN 0140-9883.
  3. ^ Pfenninger, Stefan; Hawkes, Adam; Keirstead, James (May 2014). "Energy systems modeling for twenty-first century energy challenges". Renewable and Sustainable Energy Reviews. 33: 74–86. doi:10.1016/j.rser.2014.02.003. ISSN 1364-0321.
  4. ^ Herbst, Andrea; Toro, Felipe; Reitze, Felix; Jochem, Eberhard (2012). "Introduction to energy systems modelling" (PDF). Swiss Journal of Economics and Statistics. 148 (2): 111–135. Retrieved 2016-11-04.
  5. ^ Strachan, Neil; Fais, Birgit; Daly, Hannah (29 February 2016). "Reinventing the energy modelling–policy interface". Nature Energy. 1: 16012. doi:10.1038/nenergy.2016.12. ISSN 2058-7546.
  6. ^ Gargiulo, Maurizio; Gallachóir, Brian Ó (1 March 2013). "Long-term energy models: principles, characteristics, focus, and limitations". Wiley Interdisciplinary Reviews: Energy and Environment (WENE). 2 (2): 158–177. doi:10.1002/wene.62. ISSN 2041-840X.

WEM

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References

  1. ^ World Energy Model documentation — 2016 version (PDF). Paris, France: OECD/IEA. 2016. Retrieved 2016-11-30.

Energy systems

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Ongoing

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 Done

  • evince ~/synk/pdfs/2007-quelhas-etal-multiperiod-network-flow-model-us-model-description.pdf &
  • systems versus sectors[1]
  • energy modeling using MARKAL for low carbon pathways for the United Kingdom[2]
    • evince ~/synk/pdfs/2009-anandarajah-etal-energy-systems-modelling-ukerc.pdf &

References

  1. ^ Kannan, Ramachandran; Strachan, Neil (April 2009). "Modelling the UK residential energy sector under long-term decarbonisation scenarios: Comparison between energy systems and sectoral modelling approaches". Applied Energy. 86 (4): 416–428. doi:10.1016/j.apenergy.2008.08.005. ISSN 0306-2619.
  2. ^ Anandarajah, Gabrial; Strachan, Neil; Ekins, Paul; Kannan, Ramachandran; Hughes, Nick (March 2009). Pathways to a low carbon economy: Energy systems modelling — UKERC Energy 2050 Research Report 1 — UKERC/RR/ESM/2009/001. United Kingdom: UK Energy Research Centre (UKERC). Retrieved 2016-10-22.

Modeling

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  • Van Beeck (1999) on classifying energy models[1]
    • evince ~/synk/pdfs/1999-van-beeck-classification-of-energy-models.pdf &
  • Bahn et al (2005) in the EOLSS encyclopedia[2]
    • evince ~/synk/pdfs/2005-bahn-etal-mathematical-modeling-and-simulation-methods-in-energy-systems.pdf &
  • Van Ruijven et al (2008) on energy models and concepts[3]
    • evince ~/synk/pdfs/2008-van-ruijven-etal-modeling-energy-and-development.pdf &
  • Wei et al (2006)[4]

References

  1. ^ Van Beeck, Nicole MJP (August 1999). Classification of energy models — FEW Research Memorandum — Vol 777 (PDF). Tilburg, Netherlands: Tilburg University, Faculty of Economics and Business Administration. Retrieved 2016-10-25.
  2. ^ Bahn, O; Haurie, A; Zachary, DS (May 2005). "Mathematical modeling and simulation methods in energy systems". Encyclopedia of Life Support Systems (EOLSS) (PDF). Oxford, UK: EOLSS Publishers. ISSN 0711-2440. Retrieved 2016-10-25.
  3. ^ van Ruijven, Bas; Urban, Frauke; Benders, René MJ; Moll, Henri C; van der Sluijs, Jeroen P; de Vries, Bert; van Vuuren, Detlef P (December 2008). "Modeling energy and development: an evaluation of models and concepts" (PDF). World Development. 36 (12): 2801–2821. doi:10.1016/j.worlddev.2008.01.011. ISSN 0305-750X. Retrieved 2016-10-25.
  4. ^ Wei, Yi-Ming; Wu, Gang; Fan, Ying; Liu, Lan-Cui (2006). "Progress in energy complex system modelling and analysis". International Journal of Global Energy Issues. 25 (1–2): 109–128. doi:10.1504/IJGEI.2006.008387.

Modeling and developing countries

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  • Urban et al (2007) on modeling energy systems for developing countries[1]

References

  1. ^ Urban, Frauke; Benders, René MJ; Moll, Henri C (June 2007). "Modelling energy systems for developing countries". Energy Policy. 35 (6): 3473–3482. doi:10.1016/j.enpol.2006.12.025. ISSN 0301-4215. Slightly adapted version

PRIMES

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References

PRIMES

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PRIMES is an energy model developed at the E3MLab, Institute of Communication and Computer Systems, National Technical University of Athens (ICCS/NTUA), Athens, Greece.

References

[edit]
  • evince ~/synk/pdfs/2010-connolly-etal-r-e-model-survey.pdf &
  • PRIMES and RAINS (air pollution model)[1]
  • Capros and Manzos (2000)[2]
    • Abstract: In preparation of the Green Paper on greenhouse gas emissions trading within the European Union, the cost implications of EU-wide emissions trading carbon dioxide were estimated by E3-Lab with their PRIMES energy systems model. According to the report, if each EU member States implemented its target under the Burden sharing agreement individually, the total annual cost for the EU to reach the Kyoto target would be £9.0 billion.
    • evince ~/synk/pdfs/2000-capros-and-manzos-economic-effects-eu-emission-trading-primes.pdf &
  • Capros et al (2012)[3]
    • Abstract: This paper presents the main energy-related projections for various scenarios quantified with the PRIMES energy system model, used for the impact assessment study accompanying "Roadmap for moving to a competitive low-carbon economy in 2050" published in March 2011 by the European Commission. / The analysis shows that decarbonising the EU economy in the time horizon to 2050 is feasible with currently known technologies provided that considerable restructuring in energy demand and supply sectors goes together with technology improvement. Energy system costs will have to increase, with capital costs increasing significantly. The results confirm that strategies combining all decarbonisation options are more cost-efficient than strategies excluding some options.
    • evince ~/synk/pdfs/2012-capros-etal-transformations-energy-system-decarbonization-eu-to-2050.pdf &
    • also a special issue on European Energy System Models
  • Capros etal (2011) on EU climate package[4]
    • Abstract: In 2009 the EU decided to reduce greenhouse gas emissions at least by 20% in 2020 compared to 1990 and to supply 20% of energy needs by 2020 from renewable energy sources. This paper uses an energy model coupled with a non-CO2 greenhouse gas model to assess the range of policy options that were debated to meet both targets. Policy options include trading of renewable targets, carbon trading in power plants and industry and the use of the Clean Development Mechanism to improve cost-efficiency. The models also examined fairness by analysing the distribution of emission reduction in the non-emission trading sector, the distribution of CO2 allowances in the emission trading sector and the reallocation of renewable targets across Member States. The overall costs of meeting both targets range from 0.4% to 0.6% of GDP in 2020 for the EU as a whole. The redistribution mechanisms employed significantly improve fairness compared to a cost-effective solution.
    • evince ~/synk/pdfs/2011-capros-etal-analysis-eu-climate package.pdf &
  • Capros (2013) on EU emissions trends to 2020[5]
    • Blurb: This report is an update and extension of the previous trend scenarios for development of energy systems taking account of transport and GHG emissions developments. The publication presents the new 'EU reference scenario 2013', finalised in July 2013. It focuses even more than previous ones on the energy, transport and climate dimensions of EU developments and the various interactions among policies, including now also specific sections on emission trends not related to energy. Its time horizon has been extended up to 2050. It reports for the first time on EU28 including Croatia.
    • evince ~/synk/pdfs/2013-capros-etal-eu-energy-transport-ghg-emissions-trends-to-2020.pdf &
  • PRIMES model description (2015)[6]
    • evince ~/synk/pdfs/2015-e3mlab-primes-model-detailed-description.pdf &
  • PRIMES summary manual (2000)[7]
    • evince ~/synk/pdfs/2000-capros-primes-energy-system-model-summary-description.pdf &
    • contains history of PRIMES
  • PRIMES webpage[8]
  • EnergyPLAN website[9]
    • gives a summary of PRIMES

References

  1. ^ Syri, Sanna; Amann, Markus; Capros, Pantelis; Mantzos, Leonidas; Cofala, Janusz; Klimont, Zbigniew (September 2001). "Low-CO2 energy pathways and regional air pollution in Europe". Energy Policy. 29 (11): 871–884. doi:10.1016/S0301-4215(01)00022-2. ISSN 0301-4215.
  2. ^ Capros, P; Manzos, L (1 May 2000). The economic effects of EU-wide industry-level emission trading to reduce greenhouse gases: results from PRIMES energy systems model. European Commission. Environment Directorate-General. Retrieved 2016-11-04.
  3. ^ Capros, Pantelis; Tasios, Nikolaos; De Vita, Alessia; Mantzos, Leonidas; Paroussos, Leonidas (September 2012). "Transformations of the energy system in the context of the decarbonisation of the EU economy in the time horizon to 2050" (PDF). Energy Strategy Reviews. 1 (2): 85–96. doi:10.1016/j.esr.2012.06.001. ISSN 2211-467X. Retrieved 2016-11-03.
  4. ^ Capros, Pantelis; Mantzos, Leonidas; Parousos, Leonidas; Tasios, Nikolaos; Klaassen, Ger; Van Ierland, Tom (March 2011). "Analysis of the EU policy package on climate change and renewables" (PDF). Energy Policy. 39 (3): 1476–1485. doi:10.1016/j.enpol.2010.12.020. ISSN 0301-4215. Retrieved 2016-11-04.
  5. ^ Capros, P; De Vita, A; Tasios, N; Papadopoulos, D; Siskos, P; Apostolaki, E; Zampara, M; Paroussos, L; Fragiadakis, K; Kouvaritakis, N; Höglund-Isaksson, L; Winiwarter, W; Purohit, P; Böttcher, H; Frank, S; Havlík, P; Gusti, M; Witzke, HP (2013). EU energy, transport, and GHG emissions trends to 2020 — Reference scenario 2013 (PDF). Luxembourg: Publications Office of the European Union. doi:10.2833/17897. ISBN 978-92-79-33728-4. Retrieved 2016-11-04. Report prepared by E3M-Lab, Institute of Communication and Computer Systems, National Technical University of Athens (ICCS-NTUA), Athens, Greece for the Directorate-General for Energy, Directorate-General for Climate Action, and Directorate-General for Mobility and Transport, European Commission, Brussels, Belgium.
  6. ^ PRIMES model 2013–2014 — Detailed model description (PDF). Athens, Greece: E3MLab/ICCS, National Technical University of Athens. 2015. Retrieved 2016-11-04.
  7. ^ Capros, Pantelis (2000). The PRIMES energy system model — Summary description (PDF). Athens, Greece: National Technical University of Athens. Retrieved 2016-11-04.
  8. ^ "The PRIMES Model". E3MLab, Institute of Communication and Computer Systems, National Technical University of Athens (ICCS/NTUA). Athens, Greece. Retrieved 2016-11-04.
  9. ^ "PRIMES — EnergyPLAN". EnergyPLAN. Aalborg University, Denmark. Retrieved 2016-11-04.
  • evince ~/synk/pdfs/2010-connolly-etal-r-e-model-survey.pdf &
  • evince ~/synk/pdfs/2010-ecf-energy-saving.pdf &
  • evince ~/synk/pdfs/2012-schroeder-etal-emf-28-12-06-2012.pdf &
  • evince ~/synk/pdfs/2012-weijermars-etal-models-and-actors-in-energy-mix-optimization.pdf &
  • evince ~/synk/pdfs/2013-knopf-etal-tranforming-the-energy-system-in-europe.pdf &
  • evince ~/synk/pdfs/2015-despres-etal-variable-renewable-sources-models.pdf &
2007-martinot-etal-renewable-energy-futures.pdf:    Green-X, PRIMES, and POLES,
2009-ccc-meeting-carbon-budgets-progress-report.pdf:based on PRIMES modelling
2009-recipe-wp-sectors.pdf:in this paper are: the PRIMES model (EU Commission,
2010-connolly-etal-r-e-model-survey.pdf:4.27.     PRIMES                             <<
2010-ecf-energy-saving.pdf:energy outlook for the EU with the PRIMES model.          <<
2010-ecf-vol-1-technical-and-economic-diagrams.pdf:split by PRIMES, forecast
2010-edwards-etal-indirect-land-use-change-models-and-results.pdf:by the PRIMES
2010-hirschhausen-etal-dena-network-study-ii-for-wwf-de.pdf:Szenarien (PRIMES-
2010-unger-etal-coordinated-use-of-energy-system-models.pdf:et al 1981), PRIMES
2011-european-commission-energy-roadmap-2050.pdf:is the PRIMES energy system
2011-heaps-etal-making-energy-system-optimization-methodologies-accessible-and-affordable.pdf:PRIMES
2011-howells-etal-osemosys-open-source-energy-modeling-system.pdf:2010), PRIMES
2012-brand-etal-uk-transport-carbon-model.pdf:as PRIMES (Syri et al., 2001) and
2012-eu-energy-markets-in-the-european-union-in-2011.pdf:to the PRIMES baseline
2012-gerbaulet-etal-abnehmende-bedeutung-der-braunkohleverstromung.pdf:PRIMES
2012-haller-CO2-power-system-integration-fluctuating-res-phd.pdf:and PRIMES
2012-pahle-etal-kosten-des-ausbaus-erneuerbarer-energien.pdf:PRIMES an das
2012-schroeder-etal-current-and-prospective-costs-generation.pdf:in the PRIMES
2012-schroeder-etal-emf-28-12-06-2012.pdf:cost evolution in the PRIMES model.         <<
2012-weijermars-etal-models-and-actors-in-energy-mix-optimization.pdf:the PRIMES      <<
2013-capros-power-choices-reloaded-summary-presentation.pdf:PRIMES model
2013-eurelectric-power-choices-reloaded-key-messages.pdf:     the PRIMES energy
2013-knopf-etal-beyond-2020-strategies-and-costs-transforming-european-energy-system.pdf:PRIMES
2013-knopf-etal-tranforming-the-energy-system-in-europe.pdf:PRIMES                    <<
2014-pfenninger-etal-energy-systems-modeling-for-twenty-first-century-energy-challenges.pdf:PRIMES
2015-despres-etal-variable-renewable-sources-models.pdf:PRIMES and WEM (World         <<

WikiWoods

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Images

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SRU

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 Done: 100% renewable energy


  • "Ambitious climate protection and industrial competitiveness"
  • "Shaping the Electricity Market of the Future"
  • "Environment and Free Trade: Environmentally sound design of TTIP"
  • "Climate-friendly, reliable, affordable: 100% renewable electricity supply by 2050"

Checklist paper

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  • Cao et al (2016)[1]

References

  1. ^ Cao, Karl-Kiên; Cebulla, Felix; Gómez Vilchez, Jonatan J; Mousavi, Babak; Prehofer, Sigrid (28 September 2016). "Raising awareness in model-based energy scenario studies — a transparency checklist". Energy, Sustainability and Society. 6 (1): 28–47. doi:10.1186/s13705-016-0090-z. ISSN 2192-0567. Retrieved 2016-10-04.{{cite journal}}: CS1 maint: unflagged free DOI (link) Open access icon

General

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Scenario method[1]

Scenarios[2]

Good definition of system, earlier review pre-OOD[3]

IRGC study on future energy demand[4]

Model archaeology[5]

    • evince ~/synk/pdfs/2015-dodds-etal-model-archeaology.pdf &

References

  1. ^ Wright, George; Goodwin, Paul (October 2009). "Decision making and planning under low levels of predictability: enhancing the scenario method" (PDF). International Journal of Forecasting. 25 (4): 813–825. doi:10.1016/j.ijforecast.2009.05.019. ISSN 0169-2070. Retrieved 2016-10-05.
  2. ^ Börjeson, Lena; Höjer, Mattias; Dreborg, Karl-Henrik; Ekvall, Tomas; Finnveden, Göran (September 2006). "Scenario types and techniques: towards a user's guide". Futures. 38 (7): 723–739. doi:10.1016/j.futures.2005.12.002. ISSN 0016-3287. The energy system consists of an integrated set of technical and economic activities operating within a complex societal framework.
  3. ^ Hoffman, Kenneth C; Wood, David O (1 November 1976). "Energy system modeling and forecasting". Annual Review of Energy. 1 (1): 423–453. doi:10.1146/annurev.eg.01.110176.002231. ISSN 0362-1626.
  4. ^ IRGC (2015). Assessment of future energy demand: a methodological review providing guidance to developers and users of energy models and scenarios (PDF). Lausanne, Switzerland: International Risk Governance Council (IRGC). Retrieved 2016-10-05. (registration required)
  5. ^ Dodds, Paul E; Keppo, Ilkka; Strachan, Neil (2015). "Characterising the evolution of energy system models using model archaeology". Environmental Modeling and Assessment. 20 (2): 83–102. doi:10.1007/s10666-014-9417-3. ISSN 1573-2967. Open access icon

Model types

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2010 review[1]

Variable renewables typology[2]

Twenty-first century[3]

Urban systems[4]

Improving energy decisions[5]

Scenarios in the EU Energy Roadmap 2050[6]

    • evince ~/synk/pdfs/2010-bhattacharyya-review-energy-system-models.pdf &
    • evince ~/synk/pdfs/2016-droste-franke-etal-improving-energy-decisions-summary.pdf &

References

  1. ^ Bhattacharyya, Subhes C; Timilsina, Govinda R (23 November 2010). "A review of energy system models" (PDF). International Journal of Energy Sector Management. 4 (4): 494–518. doi:10.1108/17506221011092742. ISSN 1750-6220. Retrieved 2016-10-05.
  2. ^ Després, Jacques; Hadjsaid, Nouredine; Criqui, Patrick; Noirot, Isabelle (1 February 2015). "Modelling the impacts of variable renewable sources on the power sector: reconsidering the typology of energy modelling tools". Energy. 80: 486–495. doi:10.1016/j.energy.2014.12.005. ISSN 0360-5442.
  3. ^ Pfenninger, Stefan; Hawkes, Adam; Keirstead, James (May 2014). "Energy systems modeling for twenty-first century energy challenges". Renewable and Sustainable Energy Reviews. 33: 74–86. doi:10.1016/j.rser.2014.02.003. ISSN 1364-0321.
  4. ^ Keirstead, James; Jennings, Mark; Sivakumar, Aruna (August 2012). "A review of urban energy system models: approaches, challenges and opportunities". Renewable and Sustainable Energy Reviews. 16 (6): 3847–3866. doi:10.1016/j.rser.2012.02.047. ISSN 1364-0321.
  5. ^ Droste-Franke, Bert; Carrier, Martin; Kaiser, Matthias; Schreurs, Miranda; Weber, Christoph; Ziesemer, Thomas (2015). Improving energy decisions: towards better scientific policy advice for a safe and secure future energy system. Switzerland: Springer International Publishing. doi:10.1007/978-3-319-11346-3. ISBN 978-3-319-11345-6. The summary is downloadable.
  6. ^ Description of scenarios in the Energy Roadmap 2050 — SEC(2011) 1565 Part 2/2 (PDF). Brussels, Belgium: European Commission. 2011. Retrieved 2016-10-06. The six models used are listed in table 6, p 111.

Other

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US DOE Public Access Plan[1]

Storylines[2]

Bayesian Model Averaging[3]

Guidelines on electricity data transparency[4]

References

  1. ^ Public Access Plan (PDF). US Department of Energy. 24 July 2014. Retrieved 2016-10-05.
  2. ^ Trutnevyte, Evelina; Barton, John; O'Grady, Áine; Ogunkunle, Damiete; Pudjianto, Danny; Robertson, Elizabeth (November 2014). "Linking a storyline with multiple models: a cross-scale study of the UK power system transition". Technological Forecasting and Social Change. 89: 26–42. doi:10.1016/j.techfore.2014.08.018. ISSN 0040-1625. Retrieved 2016-10-06.
  3. ^ Culka, Monika (2016). "Uncertainty analysis using Bayesian Model Averaging: a case study of input variables to energy models and inference to associated uncertainties of energy scenarios". Energy, Sustainability and Society. 6 (1): 1–24. doi:10.1186/s13705-016-0073-0. ISSN 2192-0567.{{cite journal}}: CS1 maint: unflagged free DOI (link) Open access icon
  4. ^ ERGEG Advice on Comitology Guidelines for Fundamental Electricity Data Transparency — Initial Impact Assessment — E10-ENM-05-01 (PDF). Brussels, Belgium: European Regulators' Group for Electricity and Gas (ERGEG). 7 December 2010. Retrieved 2016-10-06.

Energy scenarios

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  • Volkery and Ribeiro (2009) on scenario planning in public policy[1]
  • Varum and Melo (2010) on scenario planning[2]
  • Blomgren et al (2011) on scenario planning in the energy sector in Europe[3]
    • evince ~/synk/pdfs/2011-blomgren-etal-scenario-planning-strategic-action-energy-europe.pdf &
  • Börjeson et al (2006) on a user's guide to scenario types and techniquies[4]

References

  1. ^ Volkery, Axel; Ribeiro, Teresa (November 2009). "Scenario planning in public policy: understanding use, impacts and the role of institutional context factors". Technological Forecasting and Social Change. 76 (9): 1198–1207. doi:10.1016/j.techfore.2009.07.009. ISSN 0040-1625.
  2. ^ Varum, Celeste Amorim; Melo, Carla (2010). "Directions in scenario planning literature – a review of the past decades". Futures. 42 (4): 355–369. doi:10.1016/j.futures.2009.11.021.
  3. ^ Blomgren, Henrik; Jonsson, Peder; Lagergren, Fredrik (25 May 2011). "Getting back to scenario planning: strategic action in the future of energy Europe" (PDF). 2011 8th International Conference on the European Energy Market (EEM): 792–801. doi:10.1109/EEM.2011.5953118. ISSN 2165-4077. Retrieved 2016-12-13.
  4. ^ Börjeson, Lena; Höjer, Mattias; Dreborg, Karl-Henrik; Ekvall, Tomas; Finnveden, Göran (September 2006). "Scenario types and techniques: towards a user's guide". Futures. 38 (7): 723–739. doi:10.1016/j.futures.2005.12.002. ISSN 0016-3287.
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