Published in Issue 2019-04-10
How to Cite
Khan, I. (2019). Energy-saving behaviour as a demand-side management strategy in the developing world: the case of Bangladesh. International Journal of Energy and Environmental Engineering, 10(4 (December 2019). https://doi.org/10.1007/s40095-019-0302-3
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Abstract
Abstract Although demand-side management (DSM) needs to be more customer centred, either with or without smart technologies (e.g. smart grid), less attention has been paid to the developing world in relation to DSM strategy development. The main reasons have been lack of appropriate technology and capital costs. Importantly, there are alternative DSM strategies that require minimum or no cost to implement and provide immediate results, of which energy-saving behaviour of the occupants at residences is one. This study explores the potentiality of this energy-saving behaviour as a DSM strategy for the least developed economies, focusing particularly on Bangladesh. The literature suggests that energy-saving behaviour could reduce energy demand by a maximum of 21.9%. However, this potential DSM scheme seems underestimated in the national DSM programme of Bangladesh. The Energy Efficiency and Conservation Master Plan (EECMP) of Bangladesh (a DSM program) shows that efficiency improvement in the use of home appliances could reduce electricity demand in the residential sector by about 28.8%, but this does require a long time to be implemented, whereas the inclusion of energy-saving behaviour as a demand response strategy in residences along with the EECMP might achieve demand reduction of up to 50.7%. Although the findings from this study are specific to Bangladesh, these could be useful guidelines for the policymakers of other developing nations where national DSM strategy development is underway.Keywords
- Energy-saving behaviour,
- Residential electricity consumption,
- Demand-side management,
- Demand response,
- Energy efficiency and conservation,
- Bangladesh
References
- IEA: Global Energy and CO2 Status Report 2017, 2018.
- https://www.iea.org/publications/freepublications/publication/GECO2017.pdf
- . Accessed 29 Sept 2018
- Khan (2018) Importance of GHG emissions assessment in the electricity grid expansion towards a low-carbon future: a time-varying carbon intensity approach (pp. 1587-1599) https://doi.org/10.1016/j.jclepro.2018.06.162
- Gustafsson et al. (2018) Potential for district heating to lower peak electricity demand in a medium-size municipality in Sweden https://doi.org/10.1016/j.jclepro.2018.03.038
- Saffari et al. (2018) Optimized demand side management (DSM) of peak electricity demand by coupling low temperature thermal energy storage (TES) and solar PV (pp. 604-616) https://doi.org/10.1016/j.apenergy.2017.11.063
- Khan et al. (2018) Analysis of greenhouse gas emissions in electricity systems using time-varying carbon intensity (pp. 1091-1101) https://doi.org/10.1016/j.jclepro.2018.02.309
- Khan (2019) Temporal carbon intensity analysis: renewable versus fossil fuel dominated electricity systems (pp. 309-323) https://doi.org/10.1080/15567036.2018.1516013
- Jiang et al. (2016) Analyzing the impact of the 5CP Ontario peak reduction program on large consumers (pp. 96-100) https://doi.org/10.1016/j.enpol.2016.02.052
- Turner et al. (2015) Peak load reductions: electric load shifting with mechanical pre-cooling of residential buildings with low thermal mass (pp. 1057-1067) https://doi.org/10.1016/j.energy.2015.02.011
- Gellings (1985) The concept of demand-side management for electric utilities (pp. 1468-1470) https://doi.org/10.1109/PROC.1985.13318
- Gellings et al. (1986) Integrating demand-side management into utility planning (pp. 81-87) https://doi.org/10.1109/TPWRS.1986.4334958
- Ford et al. (2017) Categories and functionality of smart home technology for energy management (pp. 543-554) https://doi.org/10.1016/j.buildenv.2017.07.020
- Lu et al. (2018) A dynamic pricing demand response algorithm for smart grid: reinforcement learning approach (pp. 220-230) https://doi.org/10.1016/j.apenergy.2018.03.072
- Bergaentzlé et al. (2014) Demand-side management and European environmental and energy goals: an optimal complementary approach (pp. 858-869) https://doi.org/10.1016/j.enpol.2013.12.008
- Faruqui et al. (2007) The power of 5 percent (pp. 68-77) https://doi.org/10.1016/j.tej.2007.08.003
- Khan, I., Halder, P.K: Electrical energy conservation through human behavior change: perspective in Bangladesh. Int. J. Renew. Energy Res.
- 6
- , 43–52 (2016).
- http://www.ijrer.com/index.php/ijrer/article/view/3030
- . Accessed 30 Sept 2018
- Strbac (2008) Demand side management: benefits and challenges (pp. 4419-4426) https://doi.org/10.1016/j.enpol.2008.09.030
- Nan et al. (2018) Optimal residential community demand response scheduling in smart grid (pp. 1280-1289) https://doi.org/10.1016/j.apenergy.2017.06.066
- Eissa (2018) First time real time incentive demand response program in smart grid with “i-Energy” management system with different resources (pp. 607-621) https://doi.org/10.1016/j.apenergy.2017.12.043
- Zafar et al. (2018) Prosumer based energy management and sharing in smart grid (pp. 1675-1684) https://doi.org/10.1016/j.rser.2017.07.018
- van Leeuwen et al. (2017) Review of urban energy transition in the Netherlands and the role of smart energy management (pp. 941-948) https://doi.org/10.1016/j.enconman.2017.05.081
- Romero Rodríguez et al. (2018) Contributions of heat pumps to demand response: a case study of a plus-energy dwelling (pp. 191-204) https://doi.org/10.1016/j.apenergy.2018.01.086
- Yin et al. (2017) Energy management of DC microgrid based on photovoltaic combined with diesel generator and supercapacitor (pp. 14-27) https://doi.org/10.1016/j.enconman.2016.11.018
- Bahl et al. (2017) Optimization-based identification and quantification of demand-side management potential for distributed energy supply systems (pp. 889-899) https://doi.org/10.1016/j.energy.2017.06.083
- Alasseri et al. (2017) A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs (pp. 617-635) https://doi.org/10.1016/j.rser.2017.04.023
- Celik et al. (2017) Electric energy management in residential areas through coordination of multiple smart homes (pp. 260-275) https://doi.org/10.1016/j.rser.2017.05.118
- Kakran and Chanana (2019) Operation management of a renewable microgrid supplying to a residential community under the effect of incentive-based demand response program (pp. 121-135) https://doi.org/10.1007/s40095-018-0286-4
- Gils (2016) Economic potential for future demand response in germany—modelling approach and case study (pp. 401-415) https://doi.org/10.1016/j.apenergy.2015.10.083
- Batić et al. (2016) Combined energy hub optimisation and demand side management for buildings (pp. 229-241) https://doi.org/10.1016/j.enbuild.2016.05.087
- Chou et al. (2017) Spatiotemporal analysis and visualization of power consumption data integrated with building information models for energy savings (pp. 219-229) https://doi.org/10.1016/j.resconrec.2016.03.008
- Kepplinger et al. (2016) Field testing of demand side management via autonomous optimal control of a domestic hot water heater (pp. 730-735) https://doi.org/10.1016/j.enbuild.2016.06.021
- Kepplinger et al. (2015) Autonomous optimal control for demand side management with resistive domestic hot water heaters using linear optimization (pp. 50-55) https://doi.org/10.1016/j.enbuild.2014.12.016
- Jack et al. (2018) A minimal simulation of the electric demand of a domestic hot water cylinder (pp. 104-112) https://doi.org/10.1016/j.apenergy.2017.11.044
- Yan et al. (2014) A novel air-conditioning system for proactive power demand response to smart grid (pp. 25-28) https://doi.org/10.1016/j.enconman.2014.09.072
- Elahee (2014) Energy management and air-conditioning in buildings in mauritius: towards achieving sustainability in a small-island developing economy vulnerable to climate change (pp. 629-638) https://doi.org/10.1016/j.egypro.2014.12.426
- Verrilli et al. (2016) Demand side management for heating controls in microgrids (pp. 611-616) https://doi.org/10.1016/j.ifacol.2016.03.123
- Vázquez-Canteli and Nagy (2019) Reinforcement learning for demand response: a review of algorithms and modeling techniques (pp. 1072-1089) https://doi.org/10.1016/j.apenergy.2018.11.002
- Darby and McKenna (2012) Social implications of residential demand response in cool temperate climates (pp. 759-769) https://doi.org/10.1016/j.enpol.2012.07.026
- PNNL, Pacific Northwest GridWise Testbed Demonstration Projects: Part I. Olympic Peninsula Project, Washington (2007).
- https://www.pnnl.gov/main/publications/external/technical_reports/PNNL-17167.pdf
- . Accessed 29 Sept 2018
- Ma et al. (2016) Residential power scheduling for demand response in smart grid (pp. 320-325) https://doi.org/10.1016/j.ijepes.2015.11.099
- Yoon et al. (2014) Demand response for residential buildings based on dynamic price of electricity (pp. 531-541) https://doi.org/10.1016/j.enbuild.2014.05.002
- Nyholm et al. (2016) Demand response potential of electrical space heating in Swedish single-family dwellings (pp. 270-282) https://doi.org/10.1016/j.buildenv.2015.11.019
- Zhang et al. (2016) Thermal comfort during temperature cycles induced by direct load control strategies of peak electricity demand management (pp. 9-20) https://doi.org/10.1016/j.buildenv.2016.03.020
- Keshtkar et al. (2016) Adaptive residential demand-side management using rule-based techniques in smart grid environments (pp. 281-294) https://doi.org/10.1016/j.enbuild.2016.09.070
- Mehta et al. (2014) Safe control of thermostatically controlled loads with installed timers for demand side management (pp. 784-791) https://doi.org/10.1016/j.enconman.2014.06.049
- Reynders et al. (2013) Potential of structural thermal mass for demand-side management in dwellings (pp. 187-199) https://doi.org/10.1016/j.buildenv.2013.03.010
- Kwok et al. (2017) Complying with voluntary energy conservation agreements (I): air conditioning in Hong Kong’s shopping malls (pp. 213-224) https://doi.org/10.1016/j.resconrec.2016.10.014
- Kwok et al. (2017) Complying with voluntary energy conservation agreements (II): lighting in Hong Kong’s shopping malls (pp. 225-234) https://doi.org/10.1016/j.resconrec.2016.10.013
- Zakeri et al. (2017) Economic potential of industrial demand side management in pulp and paper industry (pp. 1681-1694) https://doi.org/10.1016/j.energy.2017.11.075
- Paulus and Borggrefe (2011) The potential of demand-side management in energy-intensive industries for electricity markets in Germany (pp. 432-441) https://doi.org/10.1016/j.apenergy.2010.03.017
- Finn and Fitzpatrick (2014) Demand side management of industrial electricity consumption: promoting the use of renewable energy through real-time pricing (pp. 11-21) https://doi.org/10.1016/j.apenergy.2013.07.003
- Thakur and Chakraborty (2016) Demand side management in developing nations: a mitigating tool for energy imbalance and peak load management (pp. 895-912) https://doi.org/10.1016/j.energy.2016.08.030
- Harish and Kumar (2014) Demand side management in India: action plan, policies and regulations (pp. 613-624) https://doi.org/10.1016/j.rser.2014.02.021
- Akinbulire et al. (2014) Techno-economic and environmental evaluation of demand side management techniques for rural electrification in Ibadan, Nigeria (pp. 375-385) https://doi.org/10.1007/s40095-014-0132-2
- Siddiqui et al. (2012) Demand response in Indian electricity market (pp. 207-216) https://doi.org/10.1016/j.enpol.2012.06.030
- Ikpe and Torriti (2018) A means to an industrialisation end? Demand Side Management in Nigeria (pp. 207-215) https://doi.org/10.1016/j.enpol.2018.01.011
- Yang (2006) Demand side management in Nepal (pp. 2341-2362) https://doi.org/10.1016/j.energy.2005.12.008
- Yang (2017) Opportunities and barriers to demand response in China (pp. 51-55) https://doi.org/10.1016/j.resconrec.2015.11.015
- Proença et al. (2011) Potential for electricity savings by reducing potable water consumption in a city scale (pp. 960-965) https://doi.org/10.1016/j.resconrec.2011.05.003
- IEA: Electricity Information (2017).
- http://www.iea.org
- . Accessed 30 Sept 2018
- BPDB: Annual Report: 2016–2017, Dhaka (2017).
- http://www.bpdb.gov.bd/download/annual_report/AnnualReport2016-17(3).pdf
- . Accessed 29 Sept 2018
- Khan (2019) Power generation expansion plan and sustainability in a developing country: a multi-criteria decision analysis (pp. 707-720) https://doi.org/10.1016/J.JCLEPRO.2019.02.161
- EECMP: Energy Efficiency and Conservation Master Plan up to 2030, Dhaka (2015).
- http://sreda.gov.bd/files/EEC_Master_Plan_SREDA.pdf
- . Accessed 14 Sept 2018
- Sharifi et al. (2017) A review on Demand-side tools in electricity market (pp. 565-572) https://doi.org/10.1016/j.rser.2017.01.020
- Nolan and O’Malley (2015) Challenges and barriers to demand response deployment and evaluation (pp. 1-10) https://doi.org/10.1016/j.apenergy.2015.04.083
- Good et al. (2017) Review and classification of barriers and enablers of demand response in the smart grid (pp. 57-72) https://doi.org/10.1016/j.rser.2017.01.043
- Borg and Kelly (2011) The effect of appliance energy efficiency improvements on domestic electric loads in European households (pp. 2240-2250) https://doi.org/10.1016/j.enbuild.2011.05.001
- EPRI: Principles and practice of Demand Side Management, Palo Alto, California (1993).
- https://www.epri.com/
- . Accessed 6 Oct 2018
- Uddin et al. (2018) A review on peak load shaving strategies (pp. 3323-3332) https://doi.org/10.1016/j.rser.2017.10.056
- Torriti (2016) Routledge https://doi.org/10.4324/9781315781099
- Aalami, H., Yousefi, G.R., Parsa Moghadam, M.: Demand response model considering EDRP and TOU programs. In: 2008 IEEE/PES Transm. Distrib. Conf. Expo., IEEE, 2008: pp. 1–6. https://doi.org/10.1109/tdc.2008.4517059
- Newsham and Bowker (2010) The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: a review (pp. 3289-3296) https://doi.org/10.1016/j.enpol.2010.01.027
- Marwan and Kamel (2011) Demand side response to mitigate electrical peak demand in Eastern and Southern Australia (pp. 133-142) https://doi.org/10.1016/j.egypro.2011.10.019
- FERC: Assessment of demand response and advanced metering (2006)
- https://www.smartgrid.gov/files/Northwest_Open_Automated_Demand_Response_Technology_Demonstr_200612.pdf
- . Accessed 11 Nov 2018
- Taylor, B., Taylor, C.: Demand response: managing electric power peak load shortages with market mechanisms (2015).
- https://www.raponline.org/
- . Accessed 17 Nov 2018
- Bolívar Jaramillo and Weidlich (2016) Optimal microgrid scheduling with peak load reduction involving an electrolyzer and flexible loads (pp. 857-865) https://doi.org/10.1016/j.apenergy.2016.02.096
- Song, L., Xiao, Y., Van Der Schaar, M.: Non-stationary demand side management method for smart grids. In: IEEE Int. Conf. Acoust. Speech Signal Process., IEEE, Florence, Italy, 2014: pp. 7759–7763.
- https://doi.org/10.1109/icassp.2014.6855110
- Fernandes et al. (2014) Dynamic load management in a smart home to participate in demand response events (pp. 592-906) https://doi.org/10.1016/j.enbuild.2014.07.067
- Thein et al. (2018) Reinforcement learning based methodology for energy-efficient resource allocation in cloud data centers https://doi.org/10.1016/j.jksuci.2018.11.005
- Jiang and Fei (2011) Dynamic residential demand response and distributed generation management in smart microgrid with hierarchical agents (pp. 76-90) https://doi.org/10.1016/j.egypro.2011.10.012
- Marinescu et al. (2017) Prediction-based multi-agent reinforcement learning in inherently non-stationary environments (pp. 1-23) https://doi.org/10.1145/3070861
- Glavic et al. (2017) Reinforcement learning for electric power system decision and control: past considerations and perspectives (pp. 6918-6927) https://doi.org/10.1016/j.ifacol.2017.08.1217
- Dusparic, I., Taylor, A., Marinescu, A., Cahill, V., Clarke, S.: Maximizing renewable energy use with decentralized residential demand response. In: IEEE 1st Int. Smart Cities Conf., IEEE, Guadalajara, Mexico, 2015: pp. 1–6.
- https://doi.org/10.1109/isc2.2015.7366212
- Pina et al. (2012) The impact of demand side management strategies in the penetration of renewable electricity (pp. 128-137) https://doi.org/10.1016/j.energy.2011.06.013
- Tascikaraoglu et al. (2014) A demand side management strategy based on forecasting of residential renewable sources: a smart home system in Turkey (pp. 309-320) https://doi.org/10.1016/j.enbuild.2014.05.042
- Aghaei and Alizadeh (2013) Demand response in smart electricity grids equipped with renewable energy sources: a review (pp. 64-72) https://doi.org/10.1016/j.rser.2012.09.019
- Mesarić and Krajcar (2015) Home demand side management integrated with electric vehicles and renewable energy sources (pp. 1-9) https://doi.org/10.1016/j.enbuild.2015.09.001
- Nahiduzzaman et al. (2018) Households energy conservation in Saudi Arabia: lessons learnt from change-agents driven interventions program (pp. 998-1014) https://doi.org/10.1016/j.jclepro.2018.03.052
- Han et al. (2013) Intervention strategy to stimulate energy-saving behavior of local residents (pp. 706-715) https://doi.org/10.1016/j.enpol.2012.10.031
- Karlin et al. (2012) Dimensions of conservation: exploring differences among energy behaviors (pp. 423-452) https://doi.org/10.1177/0013916512467532
- Nicholls and Strengers (2015) Peak demand and the ‘family peak’ period in Australia: understanding practice (in)flexibility in households with children (pp. 116-124) https://doi.org/10.1016/j.erss.2015.08.018
- Laicane et al. (2015) Reducing household electricity consumption through demand side management : the role of home appliance scheduling and peak load reduction (pp. 222-229) https://doi.org/10.1016/j.egypro.2015.06.032
- Powells et al. (2014) Peak electricity demand and the flexibility of everyday life (pp. 43-52) https://doi.org/10.1016/j.geoforum.2014.04.014
- Spees, K., Lave, L.: Impacts of responsive load in PJM : load shifting and real time pricing. Energy J.
- 29
- , 101–121 (2008).
- https://www.jstor.org/stable/41323159
- . Accessed 17 Nov 2018
- Meyabadi and Deihimi (2017) A review of demand-side management: reconsidering theoretical framework (pp. 367-379) https://doi.org/10.1016/j.rser.2017.05.207
- Behrangrad (2015) A review of demand side management business models in the electricity market (pp. 270-283) https://doi.org/10.1016/j.rser.2015.03.033
- Darby, S.: The effectiveness of feedback on energy consumption (2006).
- http://www.eci.ox.ac.uk/research/energy/downloads/smart-metering-report.pdf
- . Accessed 29 Sept 2018
- Buchanan et al. (2014) Feeding back about eco-feedback: how do consumers use and respond to energy monitors? (pp. 138-146) https://doi.org/10.1016/j.enpol.2014.05.008
- Du et al. (2017) Impact of information feedback on residential electricity demand in China (pp. 324-334) https://doi.org/10.1016/j.resconrec.2017.07.004
- Karlin et al. (2015) The effects of feedback on energy conservation: a meta-analysis (pp. 1205-1227) https://doi.org/10.1037/a0039650
- Schultz et al. (2015) Using in-home displays to provide smart meter feedback about household electricity consumption: a randomized control trial comparing kilowatts, cost, and social norms (pp. 351-358) https://doi.org/10.1016/j.energy.2015.06.130
- Becker (1978) Joint effect of feedback and goal setting on performance: a field study of residential energy conservation (pp. 428-433) https://doi.org/10.1037/0021-9010.63.4.428
- McCalley and Midden (2002) Energy conservation through product-integrated feedback: the roles of goal-setting and social orientation (pp. 589-603) https://doi.org/10.1016/S0167-4870(02)00119-8
- Martiskainen, M.: Affecting consumer behaviour on energy demand (2007).
- http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.463.7249&rep=rep1&type=pdf
- . Accessed 22 Oct 2018
- Gilbert, B., Graff Zivin, J.: Dynamic salience with intermittent billing: evidence from smart electricity meters (2013).
- http://www.nber.org/papers/w19510
- . Accessed 22 Oct 2018
- Mizobuchi and Takeuchi (2013) The influences of financial and non-financial factors on energy-saving behaviour: a field experiment in Japan (pp. 775-787) https://doi.org/10.1016/j.enpol.2013.08.064
- Fisher, J., Irvine, K.: Reducing household energy use and carbon emissions: the potential for promoting significant and durable changes through group participation. In: IESD PhD Conf. Energy Sustain. Dev., Leicester, pp. 49–57 (2010).
- http://www.iesd.dmu.ac.uk/events/phd_conference_2010/papers/Fisher.pdf
- . Accessed 30 Sept 2018
- Allcott (2011) Social norms and energy conservation (pp. 1082-1095) https://doi.org/10.1016/j.jpubeco.2011.03.003
- Ayres et al. (2013) Evidence from two large field experiments that peer comparison feedback can reduce residential energy usage. J. Law (pp. 992-1022) https://doi.org/10.1093/jleo/ews020
- Delmas et al. (2013) Information strategies and energy conservation behavior: a meta-analysis of experimental studies from 1975 to 2012 61(2013) (pp. 729-739) https://doi.org/10.1016/j.enpol.2013.05.109
- Abrahamse and Steg (2013) Social influence approaches to encourage resource conservation: a meta-analysis (pp. 1773-1785) https://doi.org/10.1016/j.gloenvcha.2013.07.029
- de la Rue du Can, S., McNeil, M., Letschert, V., Shen, B., Sathaye, J.: DSM Electricity Savings potential in the buildings sector in APP countries, Berkeley, CA, USA (2011).
- https://www.osti.gov/servlets/purl/1011507
- . Accessed 17 Nov 2018
- Asensio and Delmas (2015) Nonprice incentives and energy conservation 112(6) (pp. E510-E515) https://doi.org/10.1073/pnas.1401880112
- Asensio and Delmas (2016) The dynamics of behavior change: evidence from energy conservation (pp. 196-212) https://doi.org/10.1016/j.jebo.2016.03.012
- Allcott and Rogers (2014) The short-run and long-run effects of behavioral interventions: experiment evidence from energy conservation (pp. 3003-3037) https://doi.org/10.1257/aer.104.10.3003
- Khan (2019) Household factors and electrical peak demand : a review for further assessment https://doi.org/10.1080/17512549.2019.1575770
- Besagni and Borgarello (2018) The determinants of residential energy expenditure in Italy (pp. 369-386) https://doi.org/10.1016/j.energy.2018.09.108
- Brounen et al. (2012) Residential energy use and conservation: economics and demographics (pp. 931-945) https://doi.org/10.1016/j.euroecorev.2012.02.007
- Longhi (2015) Residential energy expenditures and the relevance of changes in household circumstances (pp. 440-450) https://doi.org/10.1016/j.eneco.2015.03.018
- Filippini and Pachauri (2004) Elasticities of electricity demand in urban Indian households (pp. 429-436) https://doi.org/10.1016/S0301-4215(02)00314-2
- Galvin and Sunikka-Blank (2013) Economic viability in thermal retrofit policies: learning from ten years of experience in Germany (pp. 343-351) https://doi.org/10.1016/j.enpol.2012.11.044
- Bhattacharjee et al. (2014) Identification of elements to control and regulate residential energy consumption (pp. 174-195) https://doi.org/10.1080/17512549.2013.865552
- Monyei and Adewumi (2017) Demand side management potentials for mitigating energy poverty in South Africa (pp. 298-311) https://doi.org/10.1016/j.enpol.2017.09.039
- Monyei and Adewumi (2018) Integration of demand side and supply side energy management resources for optimal scheduling of demand response loads—South Africa in focus (pp. 92-104) https://doi.org/10.1016/j.epsr.2017.12.033
- Li and Pye (2018) Assessing the benefits of demand-side flexibility in residential and transport sectors from an integrated energy systems perspective (pp. 965-979) https://doi.org/10.1016/j.apenergy.2018.06.153
- Yang and Rumsey (1997) Energy conservation in typical Asian countries (pp. 507-521) https://doi.org/10.1080/00908319708908868
- Buchanan et al. (2015) The question of energy reduction: the problem(s) with feedback (pp. 89-96) https://doi.org/10.1016/j.enpol.2014.12.008
- Dietz et al. (2009) Household actions can provide a behavioral wedge to rapidly reduce US carbon emissions (pp. 18452-18456) https://doi.org/10.1073/pnas.0908738106
- Attari et al. (2010) Public perceptions of energy consumption and savings (pp. 16054-16059) https://doi.org/10.1073/pnas.1001509107
- Han et al. (2013) Intervention strategy to simulate energy-saving behaviour of local residents (pp. 706-715) https://doi.org/10.1016/j.enpol.2012.10.031
- Kua and Wong (2012) Lessons for integrated household energy conservation policies from an intervention study in Singapore (pp. 49-56) https://doi.org/10.1016/j.enpol.2012.04.009
- Tilson, D.: Customer centric demand side management : five keys to increase customer adoption and create sustainable behavior (2015).
- https://www.westmonroepartners.com/
- . Accessed 30 Sept 2018
- E.M. Rogers, Diffusion of innovations, 3rd ed., The Free Press, 1983
- Xu et al. (2014) Energy saving alignment strategy: achieving energy efficiency in urban buildings by matching occupant temperature preferences with a building’s indoor thermal environment (pp. 209-219) https://doi.org/10.1016/j.apenergy.2014.02.039
- Sorrell, S.: Mapping rebound effects from sustainable behaviours: key concepts and literature review, Guildford (2010).
- http://sustainablelifestyles.ac.uk/sites/default/files/publicationsdocs/slrg_working_paper_01-10.pdf
- . Accessed 29 Sept 2018
- Sorrell et al. (2009) Empirical estimates of the direct rebound effect: a review (pp. 1356-1371) https://doi.org/10.1016/j.enpol.2008.11.026
- Freire-González (2017) Evidence of direct and indirect rebound effect in households in EU-27 countries (pp. 270-276) https://doi.org/10.1016/j.enpol.2016.12.002
- Deng and Newton (2017) Assessing the impact of solar PV on domestic electricity consumption: exploring the prospect of rebound effects (pp. 313-324) https://doi.org/10.1016/j.enpol.2017.08.035
- Thomas and Azevedo (2013) Estimating direct and indirect rebound effects for U.S. households with input-output analysis. Part 2: Simulation (pp. 188-198) https://doi.org/10.1016/j.ecolecon.2012.12.002
- Freire-González (2011) Methods to empirically estimate direct and indirect rebound effect of energy-saving technological changes in households (pp. 32-40) https://doi.org/10.1016/j.ecolmodel.2011.09.001
- Yu et al. (2013) Evaluating the direct and indirect rebound effects in household energy consumption behavior: a case study of Beijing (pp. 441-453) https://doi.org/10.1016/j.enpol.2013.02.024
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