Skip to main content

Real-time environmental assessment of electricity use: a tool for sustainable demand-side management programs



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.


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.


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.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7


  1. 50 Hertz (2016) Grid data. Accessed 21 March 2016 2016

  2. Amin SM, Wollenberg BF (2005) Toward a smart grid: power delivery for the 21st century. IEEE Power Energy Mag 3(5):34–41.

    Article  Google Scholar 

  3. Amprion (2016) Grid data. Accessed 21 March 2016

  4. BM Reports (2016) Data download. Accessed 21 March 2016

  5. 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.

    Article  CAS  Google Scholar 

  6. 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

  7. 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.

    Article  Google Scholar 

  8. 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.

    Article  Google Scholar 

  9. 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.

    Article  Google Scholar 

  10. EEX (2016) Power - Germany. Accessed 21 March 2016

  11. ELIA (2016) Grid data - data download page. Accessed 21 March 2016

  12. ENTSOE (2016a) Day-ahead prices. Accessed 21 March 2016

  13. ENTSOE (2016b) Total load - day ahead/actual. Accessed 21 March 2016

  14. 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

  15. European Commission (2013) The EU Emissions Trading System (EU ETS). European Commission

  16. 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)

  17. Gan D, Feng D, Xie J (2013) Electricity markets and power system economics. CRC Press, Boca Raton.

    Book  Google Scholar 

  18. 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

  19. 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

    Article  Google Scholar 

  20. 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.

    Article  Google Scholar 

  21. 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

    Google Scholar 

  22. International Energy Agency (IEA) (2015) CO2 emissions from fuel combustion—highlights. IEA

  23. International Organization for Standardization (ISO) (2006) ISO 14044: environmental management—life cycle assessment—requirements and guidelines. ISO

  24. 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

  25. 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

    Article  Google Scholar 

  26. Jolliet O, Saadé M, Crettaz P (2010) Analyse du cycle de vie: comprendre et réaliser un écobilan vol 23. PPUR presses polytechniques

  27. 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.

    Article  Google Scholar 

  28. Litterman B (2013) What is the right price for carbon emissions regulation 36:38

  29. Marriott J, Matthews HS (2005) Environmental effects of interstate power trading on electricity consumption mixes. Environ Sci Technol 39(22):8584–8590.

    Article  CAS  Google Scholar 

  30. 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.

    Article  Google Scholar 

  31. 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.

    Article  Google Scholar 

  32. 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)

  33. 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.

    Article  CAS  Google Scholar 

  34. 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.

    Article  Google Scholar 

  35. Office fédéral de l'énergie (OFEN) (2014) Statistique suisse de l’électricité 2014. Conféderation Suisse, Bern

    Google Scholar 

  36. Palensky P, Dietrich D (2011) Demand side management: demand response, intelligent energy systems, and smart loads. IEEE Trans Ind Inf 7(3):381–388.

    Article  Google Scholar 

  37. Pearce D (2003) The social cost of carbon and its policy implications. Oxf Rev Econ Pol 19(3):362–384.

    Article  Google Scholar 

  38. Red Electrica De Espana (2016) Spanish Peninsula—electricity demand tracking in real time. Accessed 21 March 2016

  39. 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.

    Article  Google Scholar 

  40. 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.

    Article  Google Scholar 

  41. RTE (2016) éco2mix. Accessed 21 March 2016

  42. Saini S (2004) Conservation v. generation: the significance of demand-side management (DSM), its tools and techniques. Refocus 5(3):52–54.

    Article  Google Scholar 

  43. 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.

    Article  CAS  Google Scholar 

  44. 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

  45. Strbac G (2008) Demand side management: benefits and challenges. Energy Pol 36(12):4419–4426.

    Article  Google Scholar 

  46. TENNET (2016) Network figures - overview. Accessed 21 March 2016

  47. TERNA (2016) Transparency report. Accessed 21 March 2016

  48. The Climate Group (2008) Smart 2020: enabling the low carbon economy in the information age vol 1. Global eSustainability Initiative (GeSI), London

  49. Transnet BW (2016) Key figures. Accessed 21 March 2016

  50. 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.

    Article  CAS  Google Scholar 

  51. 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.

    Article  Google Scholar 

  52. Weisser D (2007) A guide to life-cycle greenhouse gas (GHG) emissions from electric supply technologies. Energy 32(9):1543–1559.

    Article  CAS  Google Scholar 

  53. 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.

    Article  Google Scholar 

  54. Yamin HY (2004) Review on methods of generation scheduling in electric power systems. Electr Power Syst Res 69(2-3):227–248.

    Article  Google Scholar 

Download references


The authors thank NSERC, Ericsson, and Varitron Technologies for funding the project CRDPJ 46997

Author information



Corresponding author

Correspondence to Alexandre Milovanoff.

Additional information

Responsible editor: Alexander Passer

Electronic supplementary material


(DOCX 212 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

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).

Download citation


  • Demand-side management
  • Dynamic inventory
  • Electricity generation
  • Emission factors
  • Greenhouse gas emissions
  • Life cycle assessment (LCA)