Abstract
Purpose
Demand-side management is a promising way to increase the integration of renewable energy sources by adapting part of the demand to balance power systems. However, the main challenges of evaluating the environmental performances of such programs are the temporal variation of electricity generation and the distinction between generation and electricity use by including imports and exports in real-time.
Methods
In this paper, we assessed the environmental impacts of electricity use in France by developing consumption factors based on historical hourly data of imports, exports, and electricity generation of France, Germany, Great Britain, Italy, Belgium, and Spain. We applied a life cycle approach with four environmental indicators: climate change, human health, ecosystem quality, and resources. The developed dynamic consumption factors were used to assess the environmental performances of demand-side management programs through optimized changes in consumption patterns defined by the flexibility of 1 kWh every day in 2012–2014.
Results and discussion
Between 2012 and 2014, dynamic consumption factors in France were higher on average than generation factors by 21.8% for the climate change indicator. Moreover, the dynamic consideration of electricity generation of exporting countries is essential to avoid underestimating the impacts of electricity imports and therefore electricity use. The demand response programs showed a range of mitigation up to 38.5% for the climate change indicator. In addition, an environmental optimization cost 1.4 € per kg CO2 eq. for 12% mitigation of emissions as compared to an economic optimization. Finally, embedding the costs of some environmental impacts in the electricity price with a carbon price enhanced the efficiency of economic demand response strategies on the GHG emissions mitigation.
Conclusions
The main scientific contribution of this paper is the development of more accurate dynamic electricity consumption factors. The dynamic consumption factors are relevant in LCAs of industrial processes or operational building phases, especially when consumption varies over time and when the power system participates in a wide market with exports and imports such as in France. In the case of demand-side management programs, dynamic consumption factors could prevent an environmentally damaging energy from being imported, despite the economic interest of system operators. However, the approach used in this study was attributional and did not assess the local grid responses of load shifting programs. Therefore, a more comprehensive model could be created to assess the local short-term dynamic consequences of located prospective consumptions and the global long-term consequences of demand-side management programs.
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References
50 Hertz (2016) Grid data. http://www.50hertz.com/en/Grid-Data. Accessed 21 March 2016 2016
Amin SM, Wollenberg BF (2005) Toward a smart grid: power delivery for the 21st century. IEEE Power Energy Mag 3(5):34–41. https://doi.org/10.1109/MPAE.2005.1507024
Amprion (2016) Grid data. http://www.amprion.net/en/grid-data. Accessed 21 March 2016
BM Reports (2016) Data download. https://www.bmreports.com/bmrs/?q=eds/main. Accessed 21 March 2016
Bristow D, Richman R, Kirsh A, Kennedy CA, Pressnail KD (2011) Hour-by-hour analysis for increased accuracy of greenhouse gas emissions for a low-energy condominium design. J Ind Ecol 15(3):381–393. https://doi.org/10.1111/j.1530-9290.2011.00335.x
Chamorro HR, Ghandhari M, Eriksson R (2013) Wind power impact on power system frequency response. Paper presented at the North American Power Symposium (NAPS), 22-24 Sept 2013
Ciroth A (2007) ICT for environment in life cycle applications openLCA—a new open source software for life cycle assessment. Int J Life Cycle Assess 12(4):209–210. https://doi.org/10.1065/lca2007.06.337
Dandres T, Vandromme N, Obrekht G, Wong A, Nguyen KK, Lemieux Y, Cheriet M, Samson R (2016) Consequences of future data center deployment in Canada on electricity generation and environmental impacts: a 2015–2030 prospective study. J Ind Ecol 21(5):1312–1322. https://doi.org/10.1111/jiec.12515
Dandres T, Farrahi Moghaddam R, Nguyen KK, Lemieux Y, Samson R, Cheriet M (2017) Consideration of marginal electricity in real-time minimization of distributed data centre emissions. J Clean Prod 143:116–124. https://doi.org/10.1016/j.jclepro.2016.12.143
EEX (2016) Power - Germany. https://www.eex-transparency.com/homepage/power/germany. Accessed 21 March 2016
ELIA (2016) Grid data - data download page. http://www.elia.be/en/grid-data/data-download. Accessed 21 March 2016
ENTSOE (2016a) Day-ahead prices. https://transparency.entsoe.eu/transmission-domain/r2/dayAheadPrices/show. Accessed 21 March 2016
ENTSOE (2016b) Total load - day ahead/actual. https://transparency.entsoe.eu/load-domain/r2/totalLoadR2/show. Accessed 21 March 2016
European Commission (2011) ILCD handbook—recommendations for life cycle impact assessment in the European context. European Commission, Joint Research Centre. Institute for Environment and Sustainability
European Commission (2013) The EU Emissions Trading System (EU ETS). European Commission
Finn P, O’Connell M, Fitzpatrick C (2011) Reduced usage phase impact using demand side management. Paper presented at the 2011 I.E. International Symposium on Sustainable Systems and Technology (ISSST)
Gan D, Feng D, Xie J (2013) Electricity markets and power system economics. CRC Press, Boca Raton. https://doi.org/10.1201/b15550
Goedkoop M, Heijungs R, Huijbregts M, De Schryver A, Struijs J, Van Zelm R (2009) ReCiPe 2008: a life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level
Gordon C, Fung A (2009) Hourly emission factors from the electricity generation sector: a tool for analyzing the impact of renewable technologies in Ontario. Trans Can Soc Mech Eng 33:105–118
Hirth L (2013) The market value of variable renewables: the effect of solar wind power variability on their relative price. Energy Econ 38:218–236. https://doi.org/10.1016/j.eneco.2013.02.004
Intergovernmental Panel on Climate Change (IPCC) (2014) Summary for Policymakers. In: Field CB et al (eds) Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 1–32
International Energy Agency (IEA) (2015) CO2 emissions from fuel combustion—highlights. IEA
International Organization for Standardization (ISO) (2006) ISO 14044: environmental management—life cycle assessment—requirements and guidelines. ISO
Itten R, Frischknecht R, Stucki M, Scherrer P, Psi I (2012) Life cycle inventories of electricity mixes and grid. treeze Ltd., fair life cycle thinking
Jolliet O, Margni M, Charles R, Humbert S, Payet J, Rebitzer G, Rosenbaum R (2003) IMPACT 2002+: a new life cycle impact assessment methodology. Int J Life Cycle Assess 8:324
Jolliet O, Saadé M, Crettaz P (2010) Analyse du cycle de vie: comprendre et réaliser un écobilan vol 23. PPUR presses polytechniques
Kopsakangas-Savolainen M, Mattinen MK, Manninen K, Nissinen A (2017) Hourly-based greenhouse gas emissions of electricity—cases demonstrating possibilities for households and companies to decrease their emissions. J Clean Prod 153:384–396. https://doi.org/10.1016/j.jclepro.2015.11.027
Litterman B (2013) What is the right price for carbon emissions regulation 36:38
Marriott J, Matthews HS (2005) Environmental effects of interstate power trading on electricity consumption mixes. Environ Sci Technol 39(22):8584–8590. https://doi.org/10.1021/es0506859
Marriott J, Matthews HS, Hendrickson CT (2010) Impact of power generation mix on life cycle assessment and carbon footprint greenhouse gas results. J Ind Ecol 14(6):919–928. https://doi.org/10.1111/j.1530-9290.2010.00290.x
Mathiesen BV, Münster M, Fruergaard T (2009) Uncertainties related to the identification of the marginal energy technology in consequential life cycle assessments. J Clean Prod 17(15):1331–1338. https://doi.org/10.1016/j.jclepro.2009.04.009
Maurice E, Dandres T, Farrahi Moghaddam R, Nguyen K, Lemieux Y, Cherriet M, Samson R (2014) Modelling of electricity mix in temporal differentiated life-cycle-assessment to minimize carbon footprint of a cloud computing service. Paper presented at the ICT for Sustainability (ICT4S-14)
Messagie M, Mertens J, Oliveira L, Rangaraju S, Sanfelix J, Coosemans T, van Mierlo J, Macharis C (2014) The hourly life cycle carbon footprint of electricity generation in Belgium, bringing a temporal resolution in life cycle assessment. Appl Energ 134:469–476. https://doi.org/10.1016/j.apenergy.2014.08.071
Miara A, Tarr C, Spellman R, Vörösmarty CJ, Macknick JE (2014) The power of efficiency: optimizing environmental and social benefits through demand-side-management. Energy 76:502–512. https://doi.org/10.1016/j.energy.2014.08.047
Office fédéral de l'énergie (OFEN) (2014) Statistique suisse de l’électricité 2014. Conféderation Suisse, Bern
Palensky P, Dietrich D (2011) Demand side management: demand response, intelligent energy systems, and smart loads. IEEE Trans Ind Inf 7(3):381–388. https://doi.org/10.1109/TII.2011.2158841
Pearce D (2003) The social cost of carbon and its policy implications. Oxf Rev Econ Pol 19(3):362–384. https://doi.org/10.1093/oxrep/19.3.362
Red Electrica De Espana (2016) Spanish Peninsula—electricity demand tracking in real time. https://demanda.ree.es/movil/peninsula/demanda/total. Accessed 21 March 2016
Rehl T, Lansche J, Müller J (2012) Life cycle assessment of energy generation from biogas—attributional vs. consequential approach. Renew Sust Energ Rev 16(6):3766–3775. https://doi.org/10.1016/j.rser.2012.02.072
Roux C, Schalbart P, Peuportier B (2016) Accounting for temporal variation of electricity production and consumption in the LCA of an energy-efficient house. J Clean Prod 113:532–540. https://doi.org/10.1016/j.jclepro.2015.11.052
RTE (2016) éco2mix. http://www.rte-france.com/en/eco2mix/eco2mix. Accessed 21 March 2016
Saini S (2004) Conservation v. generation: the significance of demand-side management (DSM), its tools and techniques. Refocus 5(3):52–54. https://doi.org/10.1016/S1471-0846(04)00146-5
Spork CC, Chavez A, Gabarrell Durany X, Patel MK, Villalba Méndez G (2015) Increasing precision in greenhouse gas accounting using real-time emission factors. J Ind Ecol 19(3):380–390. https://doi.org/10.1111/jiec.12193
Stoll P, Bag G, Rossebo JEY, Rizvanovic L, Akerholm M (2011) Scheduling residential electric loads for green house gas reductions. Paper presented at the 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe), 5-7 Dec. 2011
Strbac G (2008) Demand side management: benefits and challenges. Energy Pol 36(12):4419–4426. https://doi.org/10.1016/j.enpol.2008.09.030
TENNET (2016) Network figures - overview. https://www.tennettso.de/site/en/Transparency/publications/network-figures/overview. Accessed 21 March 2016
TERNA (2016) Transparency report. http://www.terna.it/en-gb/sistemaelettrico/transparencyreport.aspx. Accessed 21 March 2016
The Climate Group (2008) Smart 2020: enabling the low carbon economy in the information age vol 1. Global eSustainability Initiative (GeSI), London
Transnet BW (2016) Key figures. https://www.transnetbw.com/en/key-figures. Accessed 21 March 2016
Turconi R, Boldrin A, Astrup T (2013) Life cycle assessment (LCA) of electricity generation technologies: overview, comparability and limitations. Renew Sust Energ Rev 28:555–565. https://doi.org/10.1016/j.rser.2013.08.013
Vogtländer JG, Brezet H, Hendriks CF (2001) The virtual eco-costs ‘99 A single LCA-based indicator for sustainability and the eco-costs-value ratio (EVR) model for economic allocation. Int J Life Cycle Assess 6(3):157–166. https://doi.org/10.1007/BF02978734
Weisser D (2007) A guide to life-cycle greenhouse gas (GHG) emissions from electric supply technologies. Energy 32(9):1543–1559. https://doi.org/10.1016/j.energy.2007.01.008
Wernet G, Bauer C, Steubing B, Reinhard J, Moreno-Ruiz E, Weidema B (2016) The ecoinvent database version 3 (part I): overview and methodology. Int J Life Cycle Assess 21(9):1218–1230. https://doi.org/10.1007/s11367-016-1087-8
Yamin HY (2004) Review on methods of generation scheduling in electric power systems. Electr Power Syst Res 69(2-3):227–248. https://doi.org/10.1016/j.epsr.2003.10.002
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The authors thank NSERC, Ericsson, and Varitron Technologies for funding the project CRDPJ 46997
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Milovanoff, A., Dandres, T., Gaudreault, C. et al. Real-time environmental assessment of electricity use: a tool for sustainable demand-side management programs. Int J Life Cycle Assess 23, 1981–1994 (2018). https://doi.org/10.1007/s11367-017-1428-2
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DOI: https://doi.org/10.1007/s11367-017-1428-2