Skip to main content

Advertisement

SpringerLink
Log in

Interactive energetic, environmental and economic analysis of renewable hybrid energy system

  • Original Paper
  • Published:
International Journal on Interactive Design and Manufacturing (IJIDeM) Aims and scope Submit manuscript

Abstract

One of the commitments of the European community is to increase the share of energy produced from renewable sources in order to minimize costs and risks, or that the society has to bear to produce electricity, in addition to compliance with European pollutant gas (CO2, SO2, NOx and PM) objectives. An ever-increasing body of research aims to study the actual energy savings of buildings with systems of renewable energy production implemented with storage systems, evaluating the potential energy savings. To date, however, the analysis of the environmental impacts of the total life cycle was not taken into account. Thus, no assessment has been made whether the amount of energy saved (esaved) outweighs the energy needed for production, use and disposal (einvested). This study presents an approach for the analysis and evaluation of the energy flows, environmental impacts and cost of a new modular and integrated system of renewable electricity generation and intelligent electrochemical storage systems, that allows auto-production and self-consumption of electricity in residential buildings (smart grid). The results show that the total impact depends on the configuration chosen, from the consumption profile and the types of users. If the duration of use is short and the savings achieved are small, the expected benefits will not always be achieved, in terms of costs for the user and the environmental impact.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. U.S. Department of Energy: The smart grid: an introduction, p. 575. http://www.oe.energy.gov/SmartGridIntroduction.htm (2008). Accessed 11 June 2018

  2. Ipakchi, A., Albuyeh, F.: Grid of the future. IEEE Power Energ Mag 2, 52–62 (2009). https://doi.org/10.1109/mpe.2008.931384

    Article  Google Scholar 

  3. Milan, C., Bojesen, C., Nielsen, M.P.: A cost optimization model for 100% renewable residential energy supply systems. Energy 48(1), 118–127 (2012)

    Article  Google Scholar 

  4. Marszal, A.J., Heiselberg, P., Bourrelle, J.S., Musall, E., Voss, K., Sartori, I., et al.: Zero energy building—a review of definitions and calculation methodologies. Energy Build 43(4), 971–979 (2011)

    Article  Google Scholar 

  5. Johansson, B.: Security aspects of future renewable energy systems: a short overview. Energy 61, 598–605 (2013)

    Article  Google Scholar 

  6. Dincer, I.: Renewable energy and sustainable development: a crucial review. Renew Sustain Energy Rev 4(2), 157–175 (2000)

    Article  Google Scholar 

  7. Salvadora, M., Grieua, S.: Methodology for the design of energy production and storage systems in buildings: minimization of the energy impact on the electricity grid. Energy Build 47, 659–673 (2012)

    Article  Google Scholar 

  8. Escribano, G., Marín-Quemada, J.M., San Martín, E.: RES and risk: renewable energy׳s contribution to energy security. A portfolio-based approach. Renew Sustain Energy Rev 26, 549–559 (2013)

    Article  Google Scholar 

  9. Chalvatzis, K.J., Hooper, E.: Energy security vs climate change: theoretical framework development and experience in selected EU electricity markets. Renew Sustain Energy Rev 13(9), 2703–2709 (2009). https://doi.org/10.1016/j.rser.2009.07.013

    Article  Google Scholar 

  10. Colmenar-Santos, A., Campiñez-Romero, S., Pérez-Molina, C., Castro-Gil, M.: Profitability analysis of grid-connected photovoltaic facilities for household electricity self-sufficiency. Energy Policy 51, 749–764 (2012)

    Article  Google Scholar 

  11. Mulder, G., Ridder, F., Six, D.: Electricity storage for grid connected household dwellings with PV panel. Sol Energy 84, 1284–1293 (2010)

    Article  Google Scholar 

  12. Beaudin, M., Zareipour, H., Schellenberglabe, A., Rosehart, W.: Energy storage for mitigating the variability of renewable electricity sources: an updated review. Energy Sustain Dev 14, 302–314 (2010)

    Article  Google Scholar 

  13. Hemdan, N.G.A., Kurrat, M.: Interconnection of decentralized renewable resources into distribution grids: implications and planning aspects. Electr Power Syst Res 81, 1410–1423 (2011)

    Article  Google Scholar 

  14. Nykamp, S., Molderink, A., Hurink, J.L., Smit, G.J.M.: Statistics for PV, wind and biomass generators and their impact on distribution grid planning. Energy 45, 924–932 (2012)

    Article  Google Scholar 

  15. Borowy, B.S., Salameh, Z.M.: Optimum photovoltaic array size for a hybrid wind–PV system. IEEE Trans Energy Convers 9(3), 482–488 (1994)

    Article  Google Scholar 

  16. Diaf, S., Diaf, D., Belhamel, M., Haddadi, M., Louche, A.: A methodology for optimal sizing of autonomous hybrid PV/wind system. Energy Policy 35(11), 5708–5718 (2007)

    Article  Google Scholar 

  17. Liciotti, D., Paolanti, M., Pietrini, R., Frontoni, E., Zingaretti, P.: Convolutional networks for semantic heads segmentation using top-view depth data in crowded environment. In: Proceedings-International Conference on Pattern Recognition 2018, pp. 1384–1389.

  18. Kim, S.K., Jeon, J.H., Cho, C.H., Ahn, J.B., Bodgan, S.H.: Dynamic modeling and control of a grid-connected hybrid generation system with versatile power transfer. IEEE Trans Industr Electron 55(4), 1677–1688 (2008)

    Article  Google Scholar 

  19. Schaefer, H., Hagedorn, G.: Hidden energy and correlated environmental characteristics of P.V. power generation. Renewable Energy 2(2), 159–166 (1992)

    Article  Google Scholar 

  20. Bastos-Filho, C.J.A., Miranda, P.: Multi-objective particle swarm optimization using speciation. In: IEEE Symposium on Swarm Intelligence (SIS), 2011, pp. 1–6

  21. Dagdougui, H., Minciardi, R., Ouammi, A., Robba, M., Sacile, R.: Modeling and optimization of a hybrid system for the energy supply of a “green” building. Energy Convers Manag 64, 351–363 (2012)

    Article  Google Scholar 

  22. Lee, K.H., Lee, D.W., Baek, N.C., Kwon, H.M., Lee, C.J.: Preliminary determination of optimal size for renewable energy resources in buildings using RETScreen. Energy 47(1), 83–96 (2012)

    Article  Google Scholar 

  23. Ioannou, A.K., Stefanakis, N.E., Boudouvis, A.G.: Design optimization of residential grid-connected photovoltaics on rooftops. Energy Build 76, 588–596 (2014)

    Article  Google Scholar 

  24. Rezaie, B., Esmailzadeh, E., Dincer, I.: Renewable energy options for buildings: case studies. Energy Build 43(1), 56–65 (2011)

    Article  Google Scholar 

  25. Fabrizio, E., Corrado, V., Filippi, M.: A model to design and optimize multienergy systems in buildings at the design concept stage. Renew. Energy 35(3), 644–655 (2010)

    Article  Google Scholar 

  26. Germani, M., Landi, D., Rossi, M.: Efficiency and Environmental analysis of a systems for renewable electricity generation and electrochemical storage of residential buildings. In: The 22nd CIRP Conference on Life Cycle Engineering, vol. 29, pp. 839–844 (2015)

  27. Yau, N., Yang, J.: Case-based reasoning in construction management. Comput. Aided Civ. Infrastruct Eng 13(2), 143–150 (1998)

    Article  Google Scholar 

  28. Ng, S.: EQUAL: a case-based contractor prequalifier. Autom. Constr. 19(2), 443–457 (2001)

    Article  Google Scholar 

  29. Chua, D., Li, D., Chan, W.: Case-based reasoning approach in bid decision making. J. Constr. Eng. Manag. ASCE 127(1), 35–45 (2001)

    Article  Google Scholar 

  30. Luu, D., Ng, S., Chen, S.: A case-based procurement advisory system for construction. Adv Eng Softw 34(7), 429–438 (2003)

    Article  Google Scholar 

  31. Dogan, S., Arditi, D., Günaydin, H.: Using decision trees for determining attribute weights in a case-based model of early cost prediction. J. Constr. Eng. Manag. ASCE 134(2), 146–152 (2008)

    Article  Google Scholar 

  32. Typology Approach for Building Stock Energy Assessment (TABULA): Intelligent Energy Europe Programme (IEE) (2012). http://episcope.eu/building-typology/. Accessed 11 June 2018

  33. Smart Domestic Appliances in Sustainable Energy Systems (Smart-A): Intelligent Energy Europe Programme (IEE) (2008). http://www.smart-a.org/WP2_D_2_3_Synergy_Potential_of_Smart_Appliances.pdf. Accessed 11 June 2018

  34. Zimmermann, J.P.: End-use metering campaign in 400 households in Sweden. Assessment of the Potential Electricity Savings, Swedish Energy Agency 2009. http://www.enertech.fr/pdf/54/consommations%20usages%20electrodomestiques%20en%20Suede_2009.pdf. Accessed 11 June 2018

  35. Residential Monitoring to Decrease Energy Use and Carbon Emissions in Europe (REMODECE): Intelligent Energy Europe Programme (IEE) (2008). http://remodece.isr.uc.pt/. Accessed 11 July 2018

  36. Landi, D., Capitanelli, A., Germani, M.: Ecodesign and energy labelling: the role of virtual prototyping. Proc. CIRP 61, 87–92 (2017)

    Article  Google Scholar 

  37. ISO: 14040:2006—Environmental management—LCA—principles and framework (2006a)

  38. ISO: 14044:2006—Environmental management—LCA—requirements and guidelines (2006b)

  39. Basher, S.A., Raboy, D.G.: The misuse of net present value in energy efficiency standards. Renew Sustain Energy Rev 96, 218–225 (2018)

    Article  Google Scholar 

  40. Mohseni-Bonab, S.M., Rabiee, A., Jalilzadeh, S., Mohammadi-Ivatloo, B., Nojavan, S.: Probabilistic multi objective optimal reactive power dispatch considering load uncertainties using Monte Carlo simulations. Oper. Autom. Power Eng. 3(1), 83–93 (2015)

    Google Scholar 

  41. Deb, K.: Multi-objective optimization using evolutionary algorithms, vol. 16. Wiley, New York (2001)

    MATH  Google Scholar 

  42. Mohseni-Bonab, S.M., Rabiee, A., Mohammadi-Ivatloo, B.: Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: a stochastic approach. Renew. Energy 85, 598–609 (2016)

    Article  Google Scholar 

  43. Castorani, V., Landi, D., Germani, M.: Determination of the optimal configuration of energy recovery ventilator through virtual prototyping and DoE techniques. Proc. CIRP 50, 52–57 (2016)

    Article  Google Scholar 

  44. Capitanelli, A., Landi, D., Germani, M., Papetti, A.: A methodology to design a knowledge-based tool for residential buildings simulation. In: International Mechanical Engineering Congress and Exposition, ASME IMECE 2015, November 13–19, Houston, TX

  45. http://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=ten00117&plugin=1. Accessed 06 June 2018

  46. http://www.energymarketprice.com/. Accessed 06 June 2018

  47. GSE: Rapporto statistico solare fotovoltaico, 2016. https://www.gse.it/documenti_site/Documenti%20GSE/Rapporti%20statistici/Solare%20Fotovoltaico%20-%20Rapporto%20Statistico%202016.pdf. Accessed 06 June 2018

Download references

Author information

Authors and Affiliations

  1. Università Politecnica delle Marche, Via Brecce Bianche, 60131, Ancona, Italy

    Daniele Landi, Vincenzo Castorani & Michele Germani

Authors
  1. Daniele Landi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vincenzo Castorani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michele Germani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daniele Landi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Landi, D., Castorani, V. & Germani, M. Interactive energetic, environmental and economic analysis of renewable hybrid energy system. Int J Interact Des Manuf 13, 885–899 (2019). https://doi.org/10.1007/s12008-019-00554-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12008-019-00554-x

Keywords

Search

Navigation