Demand Response Requirements from the Cultural, Social, and Behavioral Perspectives
Abstract
:1. Introduction
2. Methodologies, Concepts and Theoretical Framework
- A theoretical framework is presented by considering three important sociological factors: familiarizing customers with DSM programs, lifestyle theories, and the new environmental paradigm.
- Different customer’s reactions to DR programs with respect to the electricity prices are investigated. A desirability function and loss aversion concept are also introduced.
- The effects of response fatigue, gamification, and subsidies on increasing the DR participation rates are investigated. Finally, considering economic, cultural, and social capitals and their related components, an analytical model is presented.
- Introducing the DSM programs to customers and investors;
- Investigating consumption and lifestyle theories;
- Examining the new environmental paradigm, as well as value and knowledge.
2.1. Introducing the DSM Programs to Customers and Investors
2.2. Investigating Consumption and Lifestyle Theories
2.3. Examining the New Environmental Paradigm, as Well as Value and Knowledge
- Humans vary from other animal species due to cultural and genetic traits;
- Cultural and social elements, are essential determinants of human difference;
- Human cultural and social relations are complex, and the biophysical environment is vast and ambiguous;
- Culture is a cumulative notion, meaning technological and social progress may be limitless and cure all societal issues [79].
- Humans have unique traits. They are one of the species that are reliant on the global ecosystem for survival.
- Human life is not only influenced by cultural and social factors, but also by the complex loop of causes, effects, and feedback. As a result, even purposeful human actions may have unintended consequences.
- Humans are dependent on the biophysical environment, live in it, and are affected by this environment’s biological and physical limitations.
- Humans should never violate ecological laws, even if they are able to overcome limitations by relying on their initiatives.
- Environmental value
- Environmental knowledge
3. Customers’ Sensitivity to Electricity Price and Electricity Consumption
4. Enhancement of DR Programs’ Participation Rate
5. Capitals and Analytical Model
5.1. Economic Capital
5.2. Cultural Capital
5.2.1. Embodied Cultural Capital
5.2.2. Institutionalized Cultural Capital
5.3. Social Capital
5.3.1. Social Trust
- Trust does not directly enhance people’s access to information. However, trust in information sources (such as friends, news resources, and government agencies) increases the likelihood of influencing people’s behavior.
- People with higher levels of social trust are more motivated to save energy because they believe that others will also have responsible behaviors, and thus, this increases their behaviors’ effectiveness.
5.3.2. Social Participation
5.4. Analytical Model
- Study influences of cultural, economic, and social capitals—as concepts derived from Bourdieu’s theory (Bourdieu’s theory defines lifestyle as a set of systematic activities that arise from the stamina of each individual. According to Bourdieu’s theory, lifestyle identifies the individuals personalities and also distinguishes between different social classes [110]) of consumption and lifestyle—on the electricity consumption behavior;
- Find out how people’s knowledge of electricity affects electricity consumption behavior;
- Investigate the effects of environmental value on the electricity consumption behavior using the Kaiser value scale (Kaiser value scale: Kaiser et al. introduced environmental attitude as a powerful predictor of ecological behavior. They used a unified concept of attitude and a probabilistic measurement approach to overcome the lack of the consideration of behavior constraints beyond people’s control. They confirmed three essential variables for consumption behavior studies: (1) environmental knowledge, (2) environmental values, and (3) ecological behavior intention [83]);
- Evaluate how the environmental attitude derived from NEP influences electricity consumption behavior.
6. Discussion, Solutions, and Outlook
6.1. Discussion
6.2. Solutions
6.3. Outlook
7. Conclusions
- Cultural aspect: Culture is a determining factor to create long-term human behavior, including values, beliefs, customs, and traditions. Changing sustainable behaviors requires a culture shift. Therefore, from the cultural viewpoint, the most important features are stability and adhesion.
- Social aspect: One of the most significant factors for power system operators in persuading people to participate in DR programs is building trust in the source of information.
- Behavioral aspect: There are numerous barriers for the successful implementation of DR programs that target energy consumption behaviors. One of the most challenging problems is to remain in DR for a long term. Incentives and penalties may have different effects in short/long-term horizon times. However, implementing DR programs necessitates a detailed understanding of the effects of daily living routines and behavioral norms on energy consumption, as well as a complete understanding of the characteristics of the target groups.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Moshiri, S.; Shahmoradi, A. Estimation of Natural Gas and Electricity Demand of Households in the Country: A Micro-Study Based on Household Budget. J. Econ. Res. 2006, 41, 305–335. (In Persian) [Google Scholar]
- Hashemi Parinchi, Z.; Darvish Rouhani, B. Smart Energy Consumption in Smart Homes. In Proceedings of the 2nd National Conference on Modifying the Electricity Consumption Pattern, Ahwaz, Iran, 22–23 February 2010; p. 131. (In Persian). [Google Scholar]
- Enelx. What Is Demand Side Management? 2021. Available online: https://www.enelx.com/en/questions-and-answers/eindustry/what-is-demand-side-management (accessed on 9 August 2021).
- RESPOND Project 4 Differences between Demand Side Management & Demand Response. Available online: http://project-respond.eu/4-differences-between-demand-side-management-demand-response/ (accessed on 9 August 2021).
- Arasteh, H.; Vahidinasab, V.; Sepasian, M.S.; Aghaei, J. Stochastic System of Systems Architecture for Adaptive Expansion of Smart Distribution Grids. IEEE Trans. Ind. Inform. 2019, 15, 377–389. [Google Scholar] [CrossRef]
- Arasteh, H.; Sepasian, M.S.; Vahidinasab, V.; Siano, P. SoS-Based Multiobjective Distribution System Expansion Planning. Electr. Power Syst. Res. 2016, 141, 392–406. [Google Scholar] [CrossRef]
- Arasteh, H.R.; Parsa Moghaddam, M.; Sheikh-El-Eslami, M.K.; Abdollahi, A. Integrating Commercial Demand Response Resources with Unit Commitment. Int. J. Electr. Power Energy Syst. 2013, 51, 153–161. [Google Scholar] [CrossRef]
- Amini, M.H.; Talari, S.; Arasteh, H.; Mahmoudi, N.; Kazemi, M.; Abdollahi, A.; Bhattacharjee, V.; Shafie-Khah, M.; Siano, P.; Catalão, J.P.S. Demand response in future power networks: Panorama and state-of-the-art. In Sustainable Interdependent Networks II; Springer: Berlin/Heidelberg, Germany, 2019; Volume 186, pp. 167–191. [Google Scholar]
- Felts, A. Home Energy Conservation: Psychological and Environmental Worldviews; University of Missouri: Columbia, MO, USA, 2008. [Google Scholar]
- Kaheh, Z.; Arasteh, H.; Siano, P. Social and Economic Factors in Demand-Side Flexibility. In Flexibility in Electric Power Distribution Networks; CRC Press: Boca Raton, FL, USA, 2021; pp. 1–19. [Google Scholar] [CrossRef]
- Latiers, A. Demand Response Perspectives for Belgium. Reflets Perspect. La Vie Econ. 2015, 54, 185–203. [Google Scholar] [CrossRef]
- Steve Sorrell Reducing Energy Demand: A Review of Issues, Challenges and Approaches. Renew. Sustain. Energy Rev. 2015, 47, 74–82. [CrossRef] [Green Version]
- What Is Culture? Available online: https://sphweb.bumc.bu.edu/otlt/mph-modules/PH/CulturalAwareness/CulturalAwareness2.html (accessed on 15 April 2021).
- Akbari, N.; Talebi, H.; Jalaei, A. An Investigation of Socio-Cultural Factors Affecting the Household Energy Consumption after the Implementation of Targeted Subsidies Law. J. Appl. Sociol. 2017, 27, 1–26. [Google Scholar] [CrossRef]
- Dolwick, J.S. “The Social” and beyond: Introducing Actor-Network Theory. J. Marit. Archaeol. 2009, 4, 21–49. [Google Scholar] [CrossRef]
- Cardoso, C.A.; Torriti, J.; Lorincz, M. Making Demand Side Response Happen: A Review of Barriers in Commercial and Public Organisations. Energy Res. Soc. Sci. 2020, 64, 101443. [Google Scholar] [CrossRef]
- Good, N.; Ellis, K.A.; Mancarella, P. Review and Classification of Barriers and Enablers of Demand Response in the Smart Grid. Renew. Sustain. Energy Rev. 2017, 72, 57–72. [Google Scholar] [CrossRef] [Green Version]
- Breukers, S.; Mourik, R.; Heiskanen, E. Changing Energy Demand Behavior: Potential of Demand-Side Management. Handb. Sustain. Eng. 2013, 773–792. [Google Scholar] [CrossRef]
- Ruff, L.E. Economic Principles of Demand Response in Electricity. October 2002. Available online: https://hepg.hks.harvard.edu/files/hepg/files/ruff_economic_principles_demand_response_eei_10-02.pdf (accessed on 9 August 2021).
- Wang, B.; Cai, Q.; Sun, Z. Determinants of Willingness to Participate in Urban Incentive-Based Energy Demand-Side Response: An Empirical Micro-Data Analysis. Sustainability 2020, 12, 8052. [Google Scholar] [CrossRef]
- El Geneidy, R.; Howard, B. Contracted Energy Flexibility Characteristics of Communities: Analysis of a Control Strategy for Demand Response. Appl. Energy 2020, 263, 114600. [Google Scholar] [CrossRef]
- Gheuens, R. Barriers to Residential Demand Response in Belgium and the Netherlands. Master’s Thesis, Universitat Politècnica de Catalunya, Barcelona, Spain, 2020. [Google Scholar]
- Salehi, S. Investigating the Role of New Cultural Factors in Improving the Pattern of Electricity Consumption; Mazandaran Electricity Distribution: Sari, Iran, 2013. (In Persian) [Google Scholar]
- Hashemi Asl, D. Expansion of the Residential Customers’ Consumption Pattern and the Development of Improvement Strategies. Master’s Thesis, Iran University of Science and Technology, Tehran, Iran, 2002. (In Persian). [Google Scholar]
- Talebzadeh, M. Management of the Electricity Consumption of the Residential Customers. In Proceedings of the 9th National Conference on Power Distribution Networks, Zanjan, Iran, 28–29 April 2004. (In Persian). [Google Scholar]
- Lotfi Poor, M.; Lotfi, A. Investigating and Estimating the Parameters Affecting the Residential Demand in Khorasan Province. J. Knowl. Dev. 2005, 15, 67-47. [Google Scholar]
- Fazeli, M.; Kolahi, M.; Salehabadi, I.; Rahbari, Z. A Comparative Study to Evaluate the Effects of Various Methods of Informing Energy Consumption on Consumers’ Persuasion for Energy Saving, First Report: Theoretical and Methodological Foundations. In Proceedings of the Niroo Research Institute (NRI), Tehran, Iran, 11–13 April 2006. (In Persian). [Google Scholar]
- Safari Nia, M.; Ahadi, H.; Bakhshi, M. The Effect of Behavioral Methods, Cognitive Methods, and Behavioral-Cognitive (Combined) Methods on Changing Attitudes of Students’ Electricity Consumption and Family Electricity Consumption Pattern. In Proceedings of the 6th National Conference on Energy, Tehran, Iran, 12–13 June 2003. (In Persian). [Google Scholar]
- Taboli, H.; Khajavi, H. Relationship between Home Energy Consumption and Contextual Variables. Rahbord-e Yas 20, 9 February 2010. (In Persian) [Google Scholar]
- Moosayi, M. Culture, Consumption and Fundamental Principles. 23 July 2009. Available online: https://www.sid.ir/en/journal/ViewPaper.aspx?ID=178107 (accessed on 15 December 2020). (In Persian).
- Nahidi, M.; Kiavar, F. Investigation of Causative Relationship between Energy Price and Energy Consumption in Industry Sector in Iran Economic. In Proceedings of the Monthly Magezine Gas and Energy, Tehran, Iran, 24 July 2010; Volume 5. (In Persian). [Google Scholar]
- Veysi, R.; Nazoktabar, H. Factors Affecting the Culture of Electricity Consumption in Tehran, Iran. In Proceedings of the 2nd National Conference on Modifying the Electricity Consumption Pattern, Ahwaz, Iran, 22–23 February 2011. (In Persian). [Google Scholar]
- Sarmast, B.; Poorhassan, R. Factors Affecting the Change in Electricity Consumption Pattern: A Case Study of Tabriz, Iran. In Proceedings of the 2nd National Conference on Modifying the Electricity Consumption Pattern, Ahwaz, Iran, 22–23 February 2011. (In Persian). [Google Scholar]
- Yavari, K.; Ahmadzadeh, K. Investigating the Relationship between Energy Consumption and Population (Case Study: Southwest Asian Countries), July 2010. Available online: https://www.sid.ir/en/journal/ViewPaper.aspx?ID=211193 (accessed on 15 April 2021). (In Persian).
- Amini, M.; Toolayi, R.; Amini, A. Energy Saving in Iran, Non Price Based Solutions. Iran. J. Soc. Probl. 2010, 1, 139–153. [Google Scholar]
- Mohammadi, A. Survey of Household Electricity Consumption among Residents of Urban Areas (Case Study: Gorgan, Iran). Master’s Thesis, Faculty of Humanities and Social Sciences, Mazandran University, Babolsar, Iran, 2011. Available online: https://ganj.irandoc.ac.ir//#/articles/f5cea2250aae8a913e2e74c2d1707267 (accessed on 15 April 2021). (In Persian).
- Mohammadi, A.; Salehi, S.; Khoshfar, G. Lifestyle and Its Impact on Electricity Consumption. In Proceedings of the 1st International Conference on New Approaches to Energy Conservation; Niroo Research Institute (NRI), Tehran, Iran, 18–19 December 2011. (In Persian). [Google Scholar]
- Salehi, S.; Khoshfar, G.; Mehnatfar, Y.; Mohammadi, A. Investigating Social and Cultural Factors Affecting Targeted Energy Subsidies and Energy Consumption (Case Study: Gorgan Electricity Company, Iran). In Proceedings of the International Conference on Economic, Kerman, Iran, 7–8 March 2012. (In Persian). [Google Scholar]
- Gholizadeh, A.; Barati, J. Analysis of Factors Influencing Residential Energy and Electricity Consumption of Household in Iran: Focus on Energy Productivity. 2011. Available online: https://www.sid.ir/en/journal/ViewPaper.aspx?ID=325095 (accessed on 10 July 2021). (In Persian).
- Samsami, H.; Hassanzadeh, E. Measuring the Effect of Daylight Saving Time on Electricity Consumption in Tehran, Yazd, Esfahan and Fars Provinces. 2013. Available online: https://www.sid.ir/en/journal/ViewPaper.aspx?ID=278877 (accessed on 23 February 2021). (In Persian).
- Salehi, S.; Mahmoodi, H.; Dibayi, N.; Karimzadeh, S. An Analysis of the Relationship between the New Environmental Paradigm AndHousehold Energy Consumption. 2012. Available online: https://envs.sbu.ac.ir/article_96464.html (accessed on 23 February 2021). (In Persian).
- Rahmani, N. The Effectiveness of TV Commercials (Effects of Electricity Consumption Commercials on School Children’s Behavior and Effective Demographic Factors). Master’s Thesis, Faculty of Broadcasting, University of Kurdistan, Kurdistan, Iran, 2012. (In Persian). [Google Scholar]
- Isazadeh, S.; Mehranfar, J. Investigating the Relationship between Energy Consumption and Urbanization Level in Iran (Application of Vector Error Correction Model and Factor Analysis Method). 2012. Available online: https://www.sid.ir/en/journal/ViewPaper.aspx?ID=324640 (accessed on 2 January 2021). (In Persian).
- Mohammadi, N. The Effect of Subsidies on the Behavior of Household Electricity Subscribers (Case Study: Household Electricity Subscribers in District 3 of Shiraz, Iran). Master’s Thesis, Allameh Tabataba’i University, Tehran, Iran, 2012. (In Persian). [Google Scholar]
- Zare Shahabadi, A. Socio-Cultural Factors Affecting Energy Consumption Patterns of Households in Yazd. 2013. Available online: https://www.magiran.com/paper/1903456?lang=en (accessed on 23 November 2021). (In Persian).
- Beheshti, S.S. Sociological Explanation of Energy Carrier Consumption and Presentation of Optimal Consumption Pattern. Ph.D. Thesis, Isfahan University, Isfahan, Iran, 2013. Available online: https://lib.ui.ac.ir/dL/search/default.aspx?Term=11025&Field=0&DTC=3 (accessed on 23 November 2021). (In Persian).
- Salehi Sarook, F. Survey of Electricity Consumption Savings and Social Factors Affecting It among Married Women in Yasuj, Iran. Master’s Thesis, Yasuj University, Yasuj, Iran, 2013. (In Persian). [Google Scholar]
- Mahdian, A. An Investigation of (Socio-Economic & Cultural) Factors Underpinning Household Energy Consumption (Case Study: Malayer City). Master’s Thesis, Mazandaran University, Babolsar, Iran, 2013. (In Persian). [Google Scholar]
- Dzioubinski, O.; Dzioubinski, O.; Chipman, R.; Chipman, R.; Nations, U.; Nations, U. Trends in Consumption and Production: Household Energy Consumption. In Proceedings of the United Nations DESA Discussion Paper. 1999. p. 21. Available online: https://www.un.org/esa/sustdev/publications/esa99dp6.pdf (accessed on 23 November 2021).
- Brandon, G.; Lewis, A. Reducing Household Energy Consumption: A Qualitative and Quantitative Field Study. J. Environ. Psychol. 1999, 19, 75–85. [Google Scholar] [CrossRef]
- Yust, B.L.; Guerin, D.A.; Coopet, J.G. Residential Energy Consumption: 1987 to 1997. Fam. Consum. Sci. Res. J. 2002, 30, 323–349. [Google Scholar] [CrossRef]
- York, R. Demographic Trends and Energy Consumption in European Union Nations, 1960–2025. Soc. Sci. Res. 2007, 36, 855–872. [Google Scholar] [CrossRef]
- Aune, M. Energy Comes Home. Energy Policy 2007, 35, 5457–5465. [Google Scholar] [CrossRef] [Green Version]
- Reddy, B.S.; Srinivas, T. Energy Use in Indian Household Sector—An Actor-Oriented Approach. Energy 2009, 34, 992–1002. [Google Scholar] [CrossRef]
- Mustapha Harzallah, I. Application of Value Beliefs Norms Theory to the Energy Conservation Behaviour. J. Sustain. Dev. 2010, 3, 129–139. [Google Scholar]
- Moezzi, M.; Lutzenhiser, L. What’s Missing in Theories of the Residential Energy User. In Proceedings of the 2010 ACEEE Summer Study Energy Efficiency in Buildings, Pacific Grove, CA, USA, 15–20 August 2010; pp. 207–221. [Google Scholar]
- Chao, L.; Qing, S. An Empirical Analysis of the Influence of Urban Form on Household Travel and Energy Consumption. Comput. Environ. Urban Syst. 2011, 35, 347–357. [Google Scholar] [CrossRef]
- Government, U.K. Behaviour Change and Energy Use. Energy 2011, 1, 35. [Google Scholar]
- Pape, J.; Rau, H.; Fahy, F.; Davies, A. Developing Policies and Instruments for Sustainable Household Consumption: Irish Experiences and Futures. J. Consum. Policy 2011, 34, 25–42. [Google Scholar] [CrossRef]
- Hemmes, F. Waste Not, Want Not: How Utilities Can Help Consumers Save Energy. Energy 2012, 7, 1–16. [Google Scholar]
- Shuling Chen Lillemo Measuring the Effect of Procrastination and Environmental Awareness on Households’ Energy-Saving Behaviours: An Empirical Approach. Energy Policy 2014, 66, 249–256. [CrossRef]
- Yamaguchi, Y.; Chen, C.F.; Shimoda, Y.; Yagita, Y.; Iwafune, Y.; Ishii, H.; Hayashi, Y. An Integrated Approach of Estimating Demand Response Flexibility of Domestic Laundry Appliances Based on Household Heterogeneity and Activities. Energy Policy 2020, 142, 111467. [Google Scholar] [CrossRef]
- Alexander, D.; Leemon, A.; Petkovic, M.; Richards, C. Towards a Two-Sided Market … the Role for Demand Response in Tomorrow’s Grid: Expert Panel|EcoGeneration. Available online: https://www.ecogeneration.com.au/towards-a-two-sided-market-the-role-for-demand-response-in-tomorrows-grid-expert-panel/ (accessed on 15 April 2021).
- Nicolson, M.; Moon, B. Applying Behavioural Insights to Forward Looking Charging Reform Results from a Literature Review by Ofgem’s Behavioural Insights Unit. 2019. Available online: https://www.ofgem.gov.uk/publications/applying-behavioural-insights-forward-looking-charging-reform (accessed on 10 June 2021).
- Demand Response as a Powerful Flexibility Resource for Value Creation in Regulated Markets. Available online: https://www.energy-pool.eu/en/demand-response-powerful-flexibility-resource-value-creation-regulated-markets/ (accessed on 15 April 2021).
- IEA Behavioural Insights for Demand-Side Energy Policy and Programmes: An Environment Scan. Available online: https://userstcp.org/news/behavioural-insights-for-demand-side-energy-policy-and-programmes-report-published (accessed on 15 April 2021).
- European Smart Grids Task Force Expert Group 3 Demand Side Flexibility—Perceived Barriers and Proposed Recommendations. Available online: https://ec.europa.eu/energy/sites/ener/files/documents/eg3_final_report_demand_side_flexiblity_2019.04.15.pdf (accessed on 15 April 2021).
- Sharma, A.; Sharma, H. Demand Side Response: Drivers, Challenges, and Opportunities. In Proceedings of the International Conference on Advancements in Computing & Management (ICACM), Jaipur, India, 13–14 April 2019. [Google Scholar] [CrossRef]
- Nursimulu, A. Demand-Side Flexibility for Energy Transitions: Ensuring the Competitive Development of Demand Response Options; SSRN: Rochester, NY, USA, 2016. [Google Scholar] [CrossRef] [Green Version]
- Osunmuyiwa, O.O.; Peacock, A.D.; Payne, S.; Vigneswara Ilavarasan, P.; Jenkins, D.P. Divergent Imaginaries? Co-Producing Practitioner and Householder Perspective to Cooling Demand Response in India. Energy Policy 2021, 152, 112222. [Google Scholar] [CrossRef]
- Zhang, G.; Xue, S.; Zhang, X. Evaluation of Social and Economic Benefits of Demand Response. IOP Conf. Ser. Earth Environ. Sci. 2020, 571, 012098. [Google Scholar] [CrossRef]
- Valdes, J.; Poque González, A.B.; Ramirez Camargo, L.; Valin Fenández, M.; Masip Macia, Y.; Dorner, W. Industry, Flexibility, and Demand Response: Applying German Energy Transition Lessons in Chile. Energy Res. Soc. Sci. 2019, 54, 12–25. [Google Scholar] [CrossRef]
- Hashemi Majoumerd, S.M.; Zandieh, M.; Alem-Tabriz, A.; Rabieh, M. Key Success Factors for Demand Response Implementation: A Hybrid Multi-Criteria Decision Making Approach. J. Ind. Syst. Eng. 2020, 13, 240–261. [Google Scholar]
- Khalid, R.; Christensen, T.H.; Gram-Hanssen, K.; Friis, F. Time-Shifting Laundry Practices in a Smart Grid Perspective: A Cross-Cultural Analysis of Pakistani and Danish Middle-Class Households. Energy Effic. 2019, 12, 1691–1706. [Google Scholar] [CrossRef] [Green Version]
- Fröhlich, P.; Esterl, T.; Adams, S.; Kuch, D.; Yilmaz, S.; Katzeff, C.; Winzer, C.; Diamond, L.; Schrammel, J.; Lukszo, Z.; et al. Towards a Social License To Automate in Demand Side Management: Challenges, Perspectives and Regional Aspects. Geoforum 2020, 55, 43–52. [Google Scholar]
- Aalami, H.A.; Parsa Moghadam, M. How to Introduce Consumers to Consumption Management. In Proceedings of the 3rd National Conference on Power Distribution Networks, Shiraz, Iran, 11 May 1993; pp. 15–23. (In Persian). [Google Scholar]
- Hendry, J. Man and the Identity Crisis; Mohammadian, N., Ed.; Mohammadian, N., Translator; Chapakhsh: Tehran, Iran, 2002. [Google Scholar]
- Abazari, Y.; Chavoshian, H. From Social Class to Lifestyle; New Approaches in Sociological Analysis of Social Identity. 2002. Available online: https://www.sid.ir/en/journal/ViewPaper.aspx?ID=21159 (accessed on 15 April 2021). (In Persian).
- Khosh Kholgh, M. The Effects of Social, Economical and Cultural Factors on Energy Consumption Behavior (Case Study: Electrical Energy in Tehran); Tehran University: Tehran, Iran, 2015. [Google Scholar]
- Salehi, S. New Environmental Paradigm and Energy Consumption. 2010. Available online: https://www.sid.ir/en/journal/ViewPaper.aspx?ID=503639 (accessed on 15 April 2021). (In Persian).
- Karimzadeh, S. A Survey on Social Factors Underpinning Environmental Behaviours (Energy Consumption). Master’s Thesis, Iranian Research Institute for Information Science and Technology, Tehran, Iran, 2010. Available online: https://ganj.irandoc.ac.ir//#/articles/95dd632a12a59779e1a2906dfef0cd03 (accessed on 8 April 2021).
- Ferdousi, S.; Mortazavi, S.; Rezvani, N. The Relation between Bio-Environmental Knowledge and Pro-Environmental Behavior. 2007. Available online: https://www.sid.ir/en/journal/ViewPaper.aspx?ID=110956 (accessed on 10 April 2021). (In Persian).
- Kaiser, F.G.; Wölfing, S.; Fuhrer, U. Environmental Attitude and Ecological Behaviour. J. Environ. Psychol. 1999, 19, 1–19. [Google Scholar] [CrossRef] [Green Version]
- Aalami, H.A.; Moghaddam, M.P.; Yousefi, G.R. Demand Response Modeling Considering Interruptible/Curtailable Loads and Capacity Market Programs. Appl. Energy 2010, 87, 243–250. [Google Scholar] [CrossRef]
- Luft, J. Bonus and Penalty Incentives Contract Choice by Employees. J. Account. Econ. 1994, 18, 181–206. [Google Scholar] [CrossRef]
- Aghapour, R.; Sepasian, M.S.; Arasteh, H.; Vahidinasab, V.; Catalão, J.P.S. Probabilistic Planning of Electric Vehicles Charging Stations in an Integrated Electricity-Transport System. Electr. Power Syst. Res. 2020, 189, 106698. [Google Scholar] [CrossRef]
- Aalami, H.A.; Moghaddam, M.P.; Yousefi, G.R. Modeling and Prioritizing Demand Response Programs in Power Markets. Electr. Power Syst. Res. 2010, 80, 426–435. [Google Scholar] [CrossRef]
- Moghaddam, M.P.; Abdollahi, A.; Rashidinejad, M. Flexible Demand Response Programs Modeling in Competitive Electricity Markets. Appl. Energy 2011, 88, 3257–3269. [Google Scholar] [CrossRef]
- Conejo, A.J.; Morales, J.M.; Baringo, L. Real-Time Demand Response Model. IEEE Trans. Smart Grid 2010, 1, 236–242. [Google Scholar] [CrossRef]
- Allcott, H.; Mullainathan, S. Behavioral Science and Energy Policy. Science 2010, 327, 1204–1205. [Google Scholar] [CrossRef]
- Dodson, J.D. Relative Values of Reward and Punishment in Habit Formation. Psychobiology 1917, 1, 231–276. [Google Scholar] [CrossRef]
- Baboli, P.T.; Eghbal, M.; Moghaddam, M.P.; Aalami, H. Customer Behavior Based Demand Response Model. In Proceedings of the IEEE Power and Energy Society General Meeting, San Diego, CA, USA, 22–26 July 2012. [Google Scholar] [CrossRef]
- Ramos, A.; Gago, A.; Labandeira, X.; Linares, P. The Role of Information for Energy Efficiency in the Residential Sector. Energy Econ. 2015, 52, S17–S29. [Google Scholar] [CrossRef] [Green Version]
- Santarius, T. Energy Efficiency, Human Behavior, and Economic Growth: Challenges to Cutting Energy Demand to Sustainable Levels. AIP Conf. Proc. 2015, 1652, 70–81. [Google Scholar] [CrossRef]
- Carmon, Z.; Ariely, D. Focusing on the Forgone: How Value Can Appear So Different to Buyers and Sellers. J. Consum. Res. 2000, 27, 360–370. [Google Scholar] [CrossRef]
- Baboli, P.T. Demand Response Model Considering Loss Aversion Concept. 2017. Available online: https://www.magiran.com/paper/1661853?lang=en (accessed on 2 August 2021). (In Persian).
- Tversky, A.; Kahneman, D. Advances in Prospect Theory: Cumulative Representation of Uncertainty. J. Risk Uncertain. 1992, 5, 297–323. [Google Scholar] [CrossRef]
- Kahneman, D.; Tversky, A. Choices, Values, and Frames. Am. Psychol. 1984, 39, 341–350. [Google Scholar] [CrossRef]
- Tversky, A.; Kahneman, D. Loss Aversion in Riskless Choice: A Reference-Dependent Model. Choices Values Fram. 2019, 143–158. [Google Scholar] [CrossRef] [Green Version]
- Kim, J.H.; Shcherbakova, A. Common Failures of Demand Response. Energy 2011, 36, 873–880. [Google Scholar] [CrossRef]
- VaasaETT EMPOWER DEMAND 2—Energy Efficiency through Information and Communication Technology—Best Practice Examples and Guidance. 2013. Available online: https://www.esmig.eu/esmig-publications/empower-demand-report-phase-ii/ (accessed on 13 September 2021).
- Albertarelli, S.; Fraternali, P.; Herrera, S.; Melenhorst, M.; Novak, J.; Pasini, C.; Rizzoli, A.E.; Rottondi, C. A Survey on the Design of Gamified Systems for Energy and Water Sustainability. Games 2018, 9, 38. [Google Scholar] [CrossRef] [Green Version]
- Casals, M.; Gangolells, M.; Macarulla, M.; Forcada, N.; Fuertes, A.; Jones, R.V. Assessing the Effectiveness of Gamification in Reducing Domestic Energy Consumption: Lessons Learned from the EnerGAware Project. Energy Build. 2020, 210, 109753. [Google Scholar] [CrossRef]
- Largue, P. Game On: Gamification in the Energy Sector. 2020. Available online: https://www.smart-energy.com/industry-sectors/digitalisation/game-on-gamification-in-the-energy-sector/ (accessed on 16 September 2021).
- S3C Guideline: Gamification—Making Energy Fun. 2015. Available online: http://www.smartgrid-engagement-toolkit.eu/fileadmin/s3ctoolkit/user/guidelines/guideline_gamification_-_making_energy_fun.pdf%0Ahttp://www.smartgrid-engagement-toolkit.eu/fileadmin/s3ctoolkit/user/guidelines/GUIDELINE_GAMIFICATION_-_MAKING_ENERGY_FUN.pdf (accessed on 3 March 2021).
- Joskow, P.L.; Marron, D.B. What Does a Negawatt Really Cost? Energy J. 1992, 13, 41–74. [Google Scholar] [CrossRef]
- Fazeli, M. Consumption and Lifestyle; Sobh-e Sadeq Publication: Qom, Iran, 2003. (In Persian) [Google Scholar]
- Ghasemi, V.; Rabbani, R.; Rabbani Khorasgani, A.; Alizadeh Aqdam, M. Structural and Capital Determinants of A Health-Promoting Lifestyle. JSPI 2009, 1387, 181–213. [Google Scholar]
- Tajbakhsh, K.; Khakbaz, A.; Poyan, H. Social Capital: Trust, Democracy and Development; Shiraze Publication: Tehran, Iran, 2005; Volume 1. (In Persian) [Google Scholar]
- Mahdavi Kani, M.S. The Concept of Lifestyle and Its Scope in Social Sciences. Cult. Res. Q. 2007, 1, 199–230. (In Persian) [Google Scholar]
Ref. | Different Aspects | Type of Customers | ||||
---|---|---|---|---|---|---|
Cultural | Social | Behavioral | Economic | Environmental | ||
[23] | √ | √ | √ | Urban citizens | ||
[24] | √ | √ | Residential | |||
[25] | √ | √ | Residential | |||
[26] | √ | √ | √ | Residential | ||
[27] | √ | √ | Industrial | |||
[28] | √ | √ | Residential (Schools) | |||
[29] | √ | √ | Residential | |||
[30] | √ | √ | Rural citizens | |||
[31] | √ | √ | Industrial | |||
[32] | √ | √ | Industrial and Residential | |||
[33] | √ | √ | Urban citizens | |||
[34] | √ | √ | Urban citizens | |||
[35] | √ | √ | √ | Industrial | ||
[36] | √ | √ | √ | √ | Residential and Urban citizens | |
[37] | √ | √ | Residential | |||
[38] | √ | √ | √ | √ | Industrial | |
[39] | √ | Residential | ||||
[40] | √ | √ | √ | Urban citizens | ||
[41] | √ | √ | Residential | |||
[42] | √ | √ | √ | Residential (Schools) | ||
[43] | √ | √ | √ | Urban citizens | ||
[44] | √ | √ | Residential | |||
[45] | √ | √ | √ | Residential | ||
[46] | √ | √ | Industrial | |||
[47] | √ | √ | √ | Residential | ||
[48] | √ | √ | √ | √ | √ | Residential |
[49] | √ | √ | Residential | |||
[50] | √ | √ | Residential | |||
[51] | √ | √ | √ | Residential | ||
[52] | √ | √ | √ | Country citizens | ||
[53] | √ | √ | √ | Residential | ||
[54] | √ | √ | Residential | |||
[55] | √ | √ | Rural citizens | |||
[56] | √ | Residential | ||||
[57] | √ | √ | √ | Residential and Urban citizens | ||
[58] | √ | √ | Industrial and Residential | |||
[59] | √ | √ | √ | Residential | ||
[60] | √ | √ | Industrial and Residential | |||
[61] | √ | √ | Industrial | |||
[62] | √ | √ | √ | Residential | ||
[63] | √ | √ | √ | Industrial and Residential | ||
[64] | √ | √ | √ | Industrial and Residential | ||
[65] | √ | √ | √ | √ | Country citizens | |
[66] | √ | √ | √ | √ | √ | Industrial and Residential |
[67] | √ | √ | √ | Industrial and Country citizens | ||
[68] | √ | √ | Industrial and Residential | |||
[69] | √ | √ | √ | √ | Industrial | |
[70] | √ | √ | √ | √ | √ | Residential |
[71] | √ | √ | Industrial and Country citizens | |||
[72] | √ | √ | √ | Industrial | ||
[73] | √ | √ | √ | Residential | ||
[74] | √ | √ | Residential | |||
[75] | √ | √ | √ | √ | √ | Industrial and Residential |
Percentage | 41.50 | 66.03 | 64.15 | 58.49 | 39.62 | - |
Ref. | Main Results |
---|---|
[23] | There is a close relationship between electricity consumption and gender, environmental lifestyle variables, ecological awareness, and environmental value. |
[24] | Cultural attributes, residence, and income have significant effects on electricity consumption. |
[25] | Behavioral attributes of residential customers are highly dependent on the characteristics of households, types of residential houses, and the features of the electrical appliances. |
[26] | Electricity consumption management at a residential building is dependent on various social and economic factors, including household income, the number of family members, usage rates and prices of electrical appliances, building infrastructure, number of rooms, and education level. |
[27] | Customer awareness of energy is introduced as the most important variable in the social aspect of DR programs. Prosumer’s energy consumption behaviors are shaped depending on their understanding of the energy system’s infrastructure. |
[28] | Direct learning through brochures, books, and videos is presented as one of the most significant behavioral variables in enhancing individual engagement in energy management programs, based on the findings of an experiment. |
[29] | According to the findings of their experiment, the higher a household’s income, the more inefficient their energy usage is. Moreover, the higher the family members’ degrees of education and awareness, the more energy efficient their behaviors. |
[30] | Rural society’s consumption behavior is mainly affected by the ceremonial points of view, which mostly consist of cultural and behavioral issues. |
[31] | Energy carrier price increases have an inverse impact on energy consumption, meaning that as prices rise, the energy consumption is reduced. Moreover, the population of the society has a direct influence on energy consumption. However, the authors concluded that the relationship between economic growth and energy consumption is direct in the short term, while inverse in the long term. |
[32] | Transparency of information about the electricity supply process, comprehensive explanation of the remaining amount of fossil fuel, improving cultural components, providing effective advice on purchasing electrical appliances, and paving the way for sustainable electricity usage are all important factors for better implementation of DR programs. |
[33] | It is stated that cultural and economic capitals are the most critical factors influencing the electricity consumption patterns of urban citizens. |
[34] | Gross domestic product (GDP), population size, urban population rate, and age factors significantly affect DSM programs. |
[35] | It is essential to consider cultural, social, environmental, and technical factors for designing the DR road map. The authors stated that the most significant aspects in developing an efficient energy framework in various sectors, including industry, transportation, and agriculture, are regulation modification, public education, the reduction of transmission losses, and the enhancement of renewable energy sources (RES) integration. |
[36] | The effects of several non-technical factors on energy usage were studied. For example, cultural capital, economic capital, gender, age, education level, employment status, number of electrical appliances in the house, people’s views about subsidies, monthly income, and housing style (owned or rented) are among the aspects. |
[37] | Energy consumption management in the home is influenced by various social, behavioral, and structural factors, such as people’s age, architecture of the house, the building’s infrastructure, and people’s lifestyles. |
[38] | The more that companies value the environment and the more they know about it, the more willing they are to participate in energy management and DR programs. |
[39] | In this research, household income is introduced as the most important factor in the improper increase in electricity consumption. |
[40] | It is concluded that the “Daylight Saving Time” law has a well-positive impact on the energy consumption of households. |
[41] | The amount of energy consumption and the rate of participation in energy consumption management programs largely depends on the type of environmental attitude of individuals. Therefore, the more that people are concerned about the environment, the more willing they are to assist DSM operators by participating in DR programs. |
[42] | The effectiveness of TV commercials on modifying students’ energy consumption behavior is investigated. Educational advertisements and raising students’ awareness of DSM programs have a long-term impact on energy usage optimization. |
[43] | Technology adoption level, urbanization, and economic growth are introduced as the most significant factors in total energy consumption modification, respectively. |
[44] | The impact of subsidies on household electricity usage is investigated. |
[45] | Based on a study on the socio-cultural factors on the households’ energy consumption behaviors, it turns out that international media, high education, high wealth, marital status, and low normativeness affect the energy consumption behaviors. |
[46] | Lifestyle, environmental friendliness, and commitment to frugal activities are sociological characteristics that impact DR programs. |
[47] | There are direct links between energy conservation and understanding of saving measures, commitment, and awareness of the repercussions of excessive usages, meaning that as the rates of these factors increase, energy conservation behaviors improve. |
[48] | They performed an extensive study on the social, cultural, and economic factors that influence home energy usage. The findings reveal that people’s attention to the environment, their rate of access to facilities, their level of faith in energy system operators, and their chance to obtain trustworthy news sources for understanding energy management programs play an important role in their consumption patterns. |
[49] | People have often objected to the consumption management regulations imposed by power system operators, claiming that the regulations violate their privacy by directly affecting their energy consumption. Furthermore, policies such as influencing people’s energy usage to change living standards frequently conflict with social welfare objectives and often have negative repercussions. |
[50] | The authors conducted a qualitative and quantitative field study to identify the most important factors in reducing household energy consumption. They claimed that the financial status of the head of the household, the type of housing unit (e.g., apartment, house, or ranch house), and the characteristics of electrical appliances are the most critical factors. |
[51] | The size and age of the house, the number of home inhabitants, seasons of the year, and people’s age and income influence energy consumption behaviors. |
[52] | The more people that a country has, the more efficient its energy usage becomes. The same can be said about the age of people, meaning that the behavior of people consuming electricity becomes more efficient with age. Furthermore, the more economically developed a country is and/or the greater its urban population, the more energy it consumes. |
[53] | By studying the concept of domestication, the authors offered a novel strategy to reduce consumption in the private sector. However, they also concluded that energy consumption in the private sector is part of a complex network. As a result, it is important to comprehend this network in order to accomplish a more permanent energy reduction. |
[54] | They looked at the current energy consumption patterns in the residential sector and analyzed the reasons behind the usage patterns. This study shows that the role of homeowners in choosing a source of energy is very important and is influenced by the family’s income. |
[55] | They introduced the energy conservation behavior concept as one of the aspects of sustainable consumer behavior. They concluded that individuals’ values and beliefs activate personal norms, which leads to conservation behavior. |
[56] | They examined some of the most important assumptions and ideas about how people utilize energy in their homes. They investigated the influence of erroneous conclusions from simplified theories on energy efficiency. They also recommended a new method for reducing energy use. |
[57] | Residential energy consumption is influenced by the social and economic factors of the family members, such as gender and income, as well as their vehicles’ features and number. |
[58] | In collaboration with the private sector and local authorities, the government can encourage people (individuals or communities) to save energy and improve consumption patterns by using their own behavioral insights. |
[59] | The country’s specific political conditions and the policy framework determine the form of daily consumption of households. The effectiveness of three policy tools (legislative, economic, and communicative) on residential consumption is also investigated. |
[60] | Consumers become encouraged to use less energy and improve their consumption behaviors if they receive energy consumption feedback. Customers were asked to record and submit their electricity meter readings. The results showed that individuals who took part in the trial spent 6% to 7% less energy than those who did not. |
[61] | A survey is utilized to investigate how procrastination and environmental awareness impact people’s heating-energy-saving behaviors. According to the findings, people who have a propensity for procrastination are considerably less likely to engage in most heating energy-saving actions. It was also found that there is a positive relationship between environmental awareness and involvement in daily energy-saving activities, such as reducing the indoor temperature. |
[62] | This research developed a multidisciplinary framework by combining home data from a population census, activity-based energy demand modeling, and a survey on behavioral intentions to participate in DR and change energy consumption. The findings emphasize the significance of promoting DR to the majority of people, especially those who are underserved, as well as overcoming behavioral and cultural hurdles to DR promotion. |
[63] | Customers should adjust their demand to lower-cost times and avoid higher-cost periods. The cost reductions in network build-out, smoothing peak demand and reducing the pressure on production at peak periods, benefit all DR stakeholders. |
[64] | They performed a literature analysis to summarize what is known about how small energy users (e.g., households and small- and medium-sized enterprises) may react to time-of-use electricity tariffs and which tools may be available to assist them in doing so. To predict users’ behaviors, they used behavioral science theory. |
[65] | They investigated the challenges of the participation of demand-side resources in the regulated electricity market and provided solutions to overcome DR implementation barriers in this market. They also mentioned the advantages of DR for utilities, and how it may be used in regulated markets. |
[66] | They discussed behavioral factors acting as the barriers for energy-saving behaviors, the adoption of energy-efficient and clean technologies, and sustainable mobility options. Finally, they provided a snapshot of how energy ministries, regulatory agencies, and utilities may use behavioral insights to design and execute more successful energy policies and DR programs by analyzing some case studies. |
[67] | An analysis of the deployment of demand-side flexibility and DR implementation is provided in order to identify barriers for demand-side flexibility to access relevant markets and products through explicit mechanisms. It focused on explicit DR and addressed implicit DR in conjunction with the explicit one. |
[68] | DR concepts and drivers originating the requirement of demand flexibility are provided in this research. A detailed categorization of various DR programs is also provided based on economic, technical, and technological factors. They pointed out that various DR schemes could investigate grid behavior and thus, contribute significantly to grid stability and investment saving. |
[69] | This overview of DR implementation has highlighted and covered a number of gaps in knowledge about DR, including the risks of power system transformations, realizable potential, consumer engagement, business models, market design, and regulation. |
[70] | They investigated the effects of the householders’ and practitioners’ views of DR programs on the residential DR acceptance rate. Their findings showed that technical variables could improve practitioners’ comprehension of DR, as well as householder agency, which is critical for residential DR adoption. They also found that achieving a decarbonized future based on DR will be difficult without addressing the householders’ agencies, and consumers may stay tied to present socio-cultural actions that prevent DR adoption. |
[71] | They suggested a social and economic benefit evaluation model to encourage DR participation. In addition, the investment needs for promoting the usage of DR were examined, and practical DR application strategies were proposed. |
[72] | They analyzed medium and large industrial clients, based on the significance of the industry sector, the complexity of executing the regulatory framework, and the importance given to the industrial customers in the legislation and DR literature. Consequently, they highlighted the challenges in untying the full DR potential of the productive industries and provided recommendations for the promotion of DR. |
[73] | An analytical framework is offered to assist governments in achieving the best possible results from their activities. They developed an evaluation methodology for assessing the effects of different factors in DR implementation, using prior studies and experts’ comments. The suggested model considered the intricate interdependencies between variables and dimensions, resulting in a cause–effect diagram that could be used to compare alternative implementation approaches. |
[74] | The purpose of this study was to conduct a qualitative, interview-based, comparative assessment of how householders adjust their habits in response to changing power supply networks. In a cross-cultural examination, using theories on temporalities of practices emphasizes the importance of the local socio-material and cultural context. |
[75] | Individual, community, organizational, electricity system, and national levels should be considered for developing DSM programs. They suggested the concept of “social license” to propose prospective beneficiaries of future DSM programs. The idea of social license for DSM is presented to demonstrate how post-industrial societies can transit to a low-carbon future by enrolling citizens in the management of electricity systems. |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Shekari, M.; Arasteh, H.; Sheikhi Fini, A.; Vahidinasab, V. Demand Response Requirements from the Cultural, Social, and Behavioral Perspectives. Appl. Sci. 2021, 11, 11456. https://doi.org/10.3390/app112311456
Shekari M, Arasteh H, Sheikhi Fini A, Vahidinasab V. Demand Response Requirements from the Cultural, Social, and Behavioral Perspectives. Applied Sciences. 2021; 11(23):11456. https://doi.org/10.3390/app112311456
Chicago/Turabian StyleShekari, Mohammadreza, Hamidreza Arasteh, Alireza Sheikhi Fini, and Vahid Vahidinasab. 2021. "Demand Response Requirements from the Cultural, Social, and Behavioral Perspectives" Applied Sciences 11, no. 23: 11456. https://doi.org/10.3390/app112311456
APA StyleShekari, M., Arasteh, H., Sheikhi Fini, A., & Vahidinasab, V. (2021). Demand Response Requirements from the Cultural, Social, and Behavioral Perspectives. Applied Sciences, 11(23), 11456. https://doi.org/10.3390/app112311456