Open Access
Renew. Energy Environ. Sustain.
Volume 9, 2024
Article Number 3
Number of page(s) 11
Published online 01 March 2024
  1. Worldometer, World population. Available: [Google Scholar]
  2. Our World in Data, Per capita electricity use (2022). Available: [Google Scholar]
  3. L. Proskuryakova, Updating energy security and environmental policy: energy security theories revisited, J. Environ. Manage. 223, 203–214 (2018) [CrossRef] [Google Scholar]
  4. California Independent Systems Operator, California Public Utilities Commission, & California Energy Commission, Root Cause Analysis: Mid-August 2020 Extreme Heat Wave, 2021 [Google Scholar]
  5. S.N. Malik, D.R. Baker, M. Chediak, Blackouts threaten entire U.S. west this summer as heat awaits (Bloomberg, 2021) [Google Scholar]
  6. Y. Tang, G. Bu, J. Yi, Analysis and lessons of the blackout in Indian power grid on July 30 and 31, 2012, in: Z. Dianji, G. Xuebao(Eds.), Proceedings of the Chinese Society of Electrical Engineering, 2012, Vol. 32, pp. 167–174 [Google Scholar]
  7. H.N. Amadi, E.N. Okafor, Analysis of methodologies for the evaluation of power outage costs, Int. J. Eng. Res. Technol. 4, 956 (2015) [Google Scholar]
  8. Red Eléctrica de España (REDE), REData Evaluation of renewable and non-renewable generation, electrical system: national, 2022. Available: [Google Scholar]
  9. Red Eléctrica de España (REDE), Renewable energy could account for 50% of Spain's electricity generation mix in 2023. Available: [Google Scholar]
  10. G. Notton, M.L. Nivet, C. Voyant, C. Paoli, C. Darras, F. Motte, A. Fouilloy, Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting, Renew. Sustain. Energy Rev. 87, 96–105 (2018) [CrossRef] [Google Scholar]
  11. T. Aziz, N. Ketjoy, PV penetration limits in low voltage networks and voltage variations, IEEE Access 5, 16784–16792 (2017) [CrossRef] [Google Scholar]
  12. Eurostat, Final energy consumption by sector. Available: [Google Scholar]
  13. Eurostat, Final energy consumption. Available: [Google Scholar]
  14. NIUS, España compra más gas ruso que nunca en 2022, en plena guerra de Ucrania. Available: [Google Scholar]
  15. Z. A. Al Muala, M. A. Bany Issa, D.S-R. Pascual, P. M. Bello Bugallo, Realistic home energy management system considering the life cycle of photovoltaic and energy storage systems, Sustainability 15, 11205 (2023) [CrossRef] [Google Scholar]
  16. S. Mitova, R. Kahsar, Urban energy system impact analysis: integration of household solar panels and electric vehicles into smart cities via storage and smart charging, Renew. Energy Environ. Sustain. 7, 25 (2022) [CrossRef] [EDP Sciences] [Google Scholar]
  17. International Energy Agency (IEA), Energy policy review Spain 2021 (OECD Publishing, Paris, 2021) [Google Scholar]
  18. International Renewable Energy Agency (IRENA), Innovation landscape brief: time-of-use tariffs (International Renewable Energy Agency, Abu Dhabi, 2019) [Google Scholar]
  19. Red Eléctrica de España (REDE). Active Energy Invoicing Price (2022). Available: [Google Scholar]
  20. L. Larrosa-Lopez, D. Pecondon-Tricas, D. Ribo-Perez, M. Alcazar-Ortega, Demand Response participation in Ancillary Services: a set of regulatory proposals for policymakers in Spain, in: the Proceedings of the 2020 Global Congress on Electrical Engineering (GC-ElecEng), Valencia, Spain, 4-6 September 2020 [Google Scholar]
  21. Agency for the Cooperation of Energy Regulators (ACER), Council of European Energy Regulators (CEER), Annual Report on the Results of Monitoring the Internal Electricity and Gas Markets in 2015, 2016 [Google Scholar]
  22. F.D. Davis, Perceived usefulness, perceived ease of use, and user acceptance of information technology (Management Information Systems Research Center, University of Minnesota, 1989), Vol. 13, pp. 319–340 [Google Scholar]
  23. B. Khalid, M. Urbański, M. Kowalska-Sudyka, E. Wysłocka, B. Piontek, Evaluating consumers' adoption of renewable energy, Energies 14, 7138 (2021) [CrossRef] [Google Scholar]
  24. C-f. Chen, X. Xu, L. Arpan, Between the technology acceptance model and sustainable energy technology acceptance model: Investigating smart meter acceptance in the United States, Energy Res. Soc. Sci. 25, 93–104 (2017) [CrossRef] [Google Scholar]
  25. J. Billanes, P. Enevoldsen, Influential factors to residential building Occupants' acceptance and adoption of smart energy technologies in Denmark, Energy Build. 276, 112524 (2022) [CrossRef] [Google Scholar]
  26. W.K.S. Karunarathna, W. Jayaratne, S. Dasanayaka, S. Ibrahim, F. Samara, Factors affecting household's use of energy-saving appliances in Sri Lanka: an empirical study using a conceptualized technology acceptance model, Energy Effic. 16, 15 (2023) [CrossRef] [Google Scholar]
  27. A. Shuhaiber, I. Mashal, Understanding users' acceptance of smart homes, Technol. Soc. 58, 101110 (2019) [CrossRef] [Google Scholar]
  28. E-S. Park, B.Y. Hwang, K. Ko, D. Kim, Consumer acceptance analysis of the home energy management system, Sustain. 9, 2351 (2017) [CrossRef] [Google Scholar]
  29. L. Yang, S. B. Danwana, I. F. Yassaanah, An empirical study of renewable energy technology acceptance in Ghana using an extended technology acceptance model, Sustainability 13, 10791 (2021) [CrossRef] [Google Scholar]
  30. A.M. Zeru, D.D. Guta, Factors influencing rural household attitude towards solar home system in Ethiopia, Renew. Energy Environ. Sustain. 6, 42 (2021) [CrossRef] [EDP Sciences] [Google Scholar]
  31. S. Im, J.P. Workman Jr., Market orientation, creativity, and new product performance in high-technology firms, J. Mark. 68, 114–132 (2004) [CrossRef] [Google Scholar]
  32. D.M. Szymanski, M.W. Kroff, L.C. Troy, Innovativeness and new product success: insights from the cumulative evidence, J. Acad. Mark. Sci. 35, 35–52 (2007) [CrossRef] [Google Scholar]
  33. R. Ianole-Călin, E. Druică, A risk integrated technology acceptance perspective on the intention to use smart grid technologies in residential electricity consumption, J. Clean. Prod. 370, 133436 (2022) [CrossRef] [Google Scholar]
  34. M.N. Akroush, M.I. Zuriekat, H.I. Al Jabali, N.A. Asfour, Determinants of purchasing intentions of energy-efficient products: the roles of energy awareness and perceived benefits, Int. J. Energy Sect. Manag. 13, 128–148 (2019) [CrossRef] [Google Scholar]
  35. J. Chou, C. Kim, T. Ung, I, G. Ayu, N. Yutami, G. Lin, H. Son, Cross-country review of smart grid adoption in residential buildings, Renew. Sustain. Energy Rev. 48, 192–213 (2015) [CrossRef] [Google Scholar]
  36. L. Hua, S. Wang, Antecedents of consumers' intention to purchase energy-efficient appliances: an empirical study based on the technology acceptance model and theory of planned behavior, Sustainability 11, 2994 (2019) [CrossRef] [Google Scholar]
  37. M. Tsuei, Y.Y. Hsu, Parents' acceptance of participation in the integration of technology into children's instruction, Asia-Pac. Educ. Res. 28, 457–467 (2019) [CrossRef] [Google Scholar]
  38. R.M. Baron, D.A. Kenny, The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations, J. Pers. Soc. Psychol. 51, 1173–1182 (1986) [CrossRef] [PubMed] [Google Scholar]
  39. B.M. Byrne, Structural equation modeling with AMOS: basic concepts, applications, and programming, 1st edn. (Lawrence Erlbaum Associates Publishers, Mahwah, NJ, 2001) [Google Scholar]
  40. G. Schuitema, J.S. Anable, Skippon, N. Kinnear, The role of instrumental, hedonic and symbolic attributes in the intention to adopt electric vehicles, Transp. Res. Part A: Policy Pract. 48, 39–49 (2013) [CrossRef] [Google Scholar]
  41. M. Partanen-Hertell, P. Harju-Autti, K. Kreft-Burman, D. Pemberton, Raising environmental awareness in the Baltic Sea Area (Finnish Environment Institute, Helsinki, 1999) [Google Scholar]
  42. A. Thornton, Public attitudes and behaviours towards the environment − tracker survey: a report to the department for environment, food and rural affairs (TNS. Defra, London, 2009) [Google Scholar]
  43. Y. Zhang, C. Xiao, G. Zhou, Willingness to pay a price premium for energy-saving appliances: role of perceived value and energy efficiency labeling, J. Clean. Prod. 242, 118555 (2020) [CrossRef] [Google Scholar]
  44. N. Iliopoulos, M. Onuki, M. Esteban, Shedding light on the factors that influence residential demand response in Japan, Energies 14, 2795 (2021) [CrossRef] [Google Scholar]
  45. G.A. Alkaws, N. Ali, Y. Baashar, An empirical study of the acceptance of IoT-based smart meter in malaysia: the effect of electricity-saving knowledge and environmental awareness, IEEE Access 8, 42794–42804 (2020) [CrossRef] [Google Scholar]
  46. M. Sobocińska, Processes of modernization of consumption in Poland in the context of the sustainable consumption and the functioning of the renewable energy market, Energies 15, 289 (2022) [CrossRef] [Google Scholar]
  47. H. Rustantono, B.E. Soetjipto, W. Wahjoedi, S. Sunaryanto, Socio-economic factors and rural competitive advantage: the moderating role of economic literacy, J. Asian Finance Econ. Bus. 7, 151–159 (2020) [CrossRef] [Google Scholar]
  48. Y. Pei, S. Wang, J. Fan, M. Zhang, An empirical study on the impact of perceived benefit, risk and trust on E-payment adoption: comparing quick pay and union pay in China, in: the Proceedings of the 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, Hangzhou, Zhejiang, China, 26–27 August 2015, pp. 198–202 [Google Scholar]
  49. S.C. Wang, E. Sy, K. Fang, The post-adoption behavior of online knowledge community: Decomposing customer value, J. Comput. Inform. Syst. 51, 60–70 (2010) [Google Scholar]
  50. M. Beaudin, H. Zareipour, Home energy management systems: a review of modelling and complexity, Renew. Sustain. Energy Rev. 45, 318–335 (2015) [Google Scholar]
  51. G. Rausser, W. Strielkowski, G. Mentel, Consumer attitudes toward energy reduction and changing energy consumption behaviors, Energies 16, 1478 (2023) [CrossRef] [Google Scholar]
  52. K. Hoffmann-Burdzińska, A. Stolecka-Makowska, O. Flak, M. Lipowski, M. Łapczyński, Consumers' social responsibility in the process of energy consumption—the case of Poland, Energies 15, 5127 (2022) [CrossRef] [Google Scholar]
  53. A. Immonen, M. Kopsakangas-Savolainen, Capturing consumers' awareness and the intention to support carbon neutrality through energy efficient consumption, Energies 15, 4022 (2022) [CrossRef] [Google Scholar]
  54. S.F. Abdolmaleki, P.M. Bello Bugallo, Evaluation of renewable energy system for sustainable development, Renew. Energy Environ. Sustain. 6, 44 (2021) [CrossRef] [EDP Sciences] [Google Scholar]
  55. C.E. Werts, R.L. Linn, K.G. Joreskog, Interclass reliability estimates: testing structural assumptions, Educ. Psychol. Meas. 33, 25–33 (1974) [CrossRef] [Google Scholar]
  56. J.F. Hair, W.C. Black, B.J. Babin, R.E. Anderson, Multivariate data analysis, Seventh edn. (Prentice Hall, Upper Saddle River, New Jersey, 2010) [Google Scholar]
  57. R.P. Bagozzi, Y. Yi, The degree of intention formation as a moderator of the attitude-behavior relationship, Soc. Psychol. Q. 52, 266–279 (1989) [CrossRef] [Google Scholar]
  58. P. Holmes-Smith, Introduction to structural equation modeling using LISREL (ACSPRI-Winter training program, Perth., Australia, 2001) [Google Scholar]
  59. J.F. Hair, R.E. Anderson, R.L. Tatham, W.C. Black, Multivariate data analysis, fifth edn. ( Prentice-Hall Inc., New Jersey, 1998) [Google Scholar]
  60. A.M. Al Muala, The impact of green marketing on purchasing decision of durable goods an empirical study on energy saving lamps consumers in Amman, Jordan, PalArch's J. Arch. Egypt/Egyptol. 17, 1810–1823 (2020) [Google Scholar]
  61. J.F. Hair, W.C. Black, B.J. Babin, R.E. Anderson, R. Tatham, Multivariate data analysis, Sixth edn. (Uppersaddle River, New Jersey, 2006) [Google Scholar]
  62. J.C. Anderson, D.W. Gerbing, Structural equation modeling in practice: a review and recommended two-step approach, Psychol. Bull. 103, 411–423 (1988) [CrossRef] [Google Scholar]
  63. J., y Chin, S-C. Lin, A behavioral model of managerial perspectives regarding technology acceptance in building energy management systems, Sustainability 8, 641 (2016) [CrossRef] [Google Scholar]
  64. A. Shanmugam, M. T. Savarimuthu, T.C. Wen, Factors affecting Malaysian behavioral intention to use mobile banking with mediating effects of attitude, Acad. Res. Int. 5, 236 (2014) [Google Scholar]
  65. G.H. Koksalmis, M. Pamuk, Promoting an energy saving technology in Turkey: the case of green roof systems, Environ. Eng. Manag. J. 20, 863–870 (2021) [CrossRef] [Google Scholar]
  66. S.K. Olson-Hazboun, R.S. Krannich, P.G. Robertson, Public views on renewable energy in the Rocky Mountain region of the United States: distinct attitudes, exposure, and other key predictors of wind energy, Energy Res. Soc. Sci. 21, 167–179 (2016) [CrossRef] [Google Scholar]
  67. J. Fergen, J.B. Jacquet, Beauty in motion: expectations, attitudes, and values of wind energy development in the rural US, Energy Res. Soc. Sci. 11, 133–141 (2016) [CrossRef] [Google Scholar]
  68. S. Oluoch, P. Lal, A. Susaeta, N. Vedwan, Assessment of public awareness, acceptance and attitudes towards renewable energy in Kenya, Sci. Afr. 9.e00512 (2020) [Google Scholar]
  69. H. Kim, E. Park, S.J. Kwon, J.Y. Ohm, H.J. Chang, An integrated adoption model of solar energy technologies in South Korea, Renew. Energy 66, 523–531 (2014) [CrossRef] [Google Scholar]
  70. J. Stragier, L. Hauttekeete, L.D. Marez, Introducing Smart grids in residential contexts: Consumers' perception of smart household appliances, in: 2010 IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply (Waltham, Massachusetts, USA, 27–29 September 2010), pp. 135–142 [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.