Scrutiny of Electricity Billing and Supply Data as a Probable Proxy for Economic Activities: A Comprehensive Analysis of Power Consumption of Dhaka, Bangladesh

Keywords

• household electricity consumption
• electricity price elasticity
• load forecasting
• energy policy
• Dhaka
• regulatory intervention
• household economic conditions
• household appliance usage
• consumer behavior

CCDS Authors

Moinul I Zaber, PhD

Moinul I Zaber, PhD

• Director, HCI Wing
• Supervisor, DS Wing

Professor

+2 more affiliations

Department of Computer Science & Engineering

Dhaka University

Published at

ICPR, HCII, JMIR

Research Interests

Computational Social Science, Human-Computer Interaction, Telecommunication Policy

References

1. 1.Kirsten Jenkins, Darren McCauley, Raphael Heffron, Hannes Stephan, Robert Rehner. (2015). Energy justice: A conceptual review. Energy Research & Social Science, 11, 174–182[10.1016/j.erss.2015.10.004]
2. 2.Benjamin K. Sovacool. (2014). What are we doing here? Analyzing fifteen years of energy scholarship and proposing a social science research agenda. Energy Research & Social Science, 1, 1–29[10.1016/j.erss.2014.02.003]
3. 3.L. Suganthi, Anand A. Samuel. (2011). Energy models for demand forecasting—A review. Renewable and Sustainable Energy Reviews, 16(2), 1223–1240[10.1016/j.rser.2011.08.014]
4. 4.Ugur Soytas, Ramazan Sari. (2002). Energy consumption and GDP: causality relationship in G-7 countries and emerging markets. Energy Economics, 25(1), 33–37[10.1016/s0140-9883(02)00009-9]
5. 5.Abul M.M. Masih, Rumi Masih. (1996). Energy consumption, real income and temporal causality: results from a multi-country study based on cointegration and error-correction modelling techniques. Energy Economics, 18(3), 165–183[10.1016/0140-9883(96)00009-6]
6. 6.Joshua Blumenstock, Gabriel Cadamuro, Robert On. (2015). Predicting poverty and wealth from mobile phone metadata. Science, 350(6264), 1073–1076[10.1126/science.aac4420]
7. 7.Christine Liddell, Chris Morris. (2010). Fuel poverty and human health: A review of recent evidence. Energy Policy, 38(6), 2987–2997[10.1016/j.enpol.2010.01.037]
8. 8.Charlotta Mellander, José Lobo, Kevin Stolarick, Zara Matheson. (2015). Night-Time Light Data: A Good Proxy Measure for Economic Activity?. PLoS ONE, 10(10), e0139779[10.1371/journal.pone.0139779]
9. 9.Galip Altinay, Erdal Karagol. (2005). Electricity consumption and economic growth: Evidence from Turkey. Energy Economics, 27(6), 849–856[10.1016/j.eneco.2005.07.002]
10. 10.Md. Shahadat Iqbal, Charisma F. Choudhury, Pu Wang, Marta C. González. (2014). Development of origin–destination matrices using mobile phone call data. Transportation Research Part C Emerging Technologies, 40, 63–74[10.1016/j.trc.2014.01.002]
11. 11.Lucie Middlemiss, Ross Gillard. (2015). Fuel poverty from the bottom-up: Characterising household energy vulnerability through the lived experience of the fuel poor. Energy Research & Social Science, 6, 146–154[10.1016/j.erss.2015.02.001]
12. 12.Michael Xie, Neal Jean, Marshall Burke, David Lobell, Stefano Ermon. (2016). Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1)[10.1609/aaai.v30i1.9906]
13. 13.Ross Ferguson, William Wilkinson, Robert Hill. (2000). Electricity use and economic development. Energy Policy, 28(13), 923–934[10.1016/s0301-4215(00)00081-1]
14. 14.Mary G. Finn. (2000). Perfect Competition and the Effects of Energy Price Increases on Economic Activity. Journal of money credit and banking, 32(3), 400[10.2307/2601172]
15. 15.Jessica E. Steele, Pål Roe Sundsøy, Carla Pezzulo, Victor A. Alegana, Tomas J. Bird, Joshua Blumenstock, Johannes Bjelland, Kenth Engø-Monsen, Yves-Alexandre de Montjoye, Asif M. Iqbal, Khandakar N. Hadiuzzaman, Xin Lu, Erik Wetter, Andrew J. Tatem, Linus Bengtsson. (2017). Mapping poverty using mobile phone and satellite data. Journal of The Royal Society Interface, 14(127), 20160690[10.1098/rsif.2016.0690]
16. 16.André Månsson, Bengt Johansson, Lars J. Nilsson. (2014). Assessing energy security: An overview of commonly used methodologies. Energy, 73, 1–14[10.1016/j.energy.2014.06.073]
17. 17.Fatih Birol, Jan Horst Keppler. (2000). Prices, technology development and the rebound effect. Energy Policy, 28(6-7), 457–469[10.1016/s0301-4215(00)00020-3]
18. 18.Ian Sue Wing. (2007). Explaining the declining energy intensity of the U.S. economy. Resource and Energy Economics, 30(1), 21–49[10.1016/j.reseneeco.2007.03.001]
19. 19.Katarina Grolinger, Alexandra L’Heureux, Miriam A.M. Capretz, Luke Seewald. (2015). Energy Forecasting for Event Venues: Big Data and Prediction Accuracy. Energy and Buildings, 112, 222–233[10.1016/j.enbuild.2015.12.010]
20. 20.Mazbahul Golam Ahamad, A.K.M. Nazrul Islam. (2011). Electricity consumption and economic growth nexus in Bangladesh: Revisited evidences. Energy Policy, 39(10), 6145–6150[10.1016/j.enpol.2011.07.014]
21. 21.Brenda Boardman. (2013). Fixing Fuel Poverty. [10.4324/9781849774482]
22. 22.Jane Falkingham, Ceema Zahra Namazie. (2002). Measuring health and poverty: a review of approaches to identifying the poor. ePrints Soton (University of Southampton)
23. 23.Roselyne Joyeux, Ronald D. Ripple. (2005). Household energy consumption versus income and relative standard of living: A panel approach. Energy Policy, 35(1), 50–60[10.1016/j.enpol.2005.10.012]
24. 24.Malcolm Eames, Miriam Hunt. (2013). Energy justice in sustainability transitions research. Zed Books Ltd[10.5040/9781350219908.ch-003]
25. 25.Lingyun He, Zhihua Ding, Fang Yin, Meng Wu. (2016). The impact of relative energy prices on industrial energy consumption in China: a consideration of inflation costs. SpringerPlus, 5(1), 1001[10.1186/s40064-016-2661-z]
26. 26.Abbas Valadkhani, Alperhan Babacan, Parviz Dabir-Alai. (2014). The impacts of rising energy prices on non-energy sectors in Australia. Economic Analysis and Policy, 44(4), 386–395[10.1016/j.eap.2014.11.005]
27. 27.Md Abu Sayed, Md Maksudur Rahman, Moinul Islam Zaber, Amin Ahsan Ali. (2017). Understanding Dhaka city traffic intensity and traffic expansion using gravity model. , 1–6[10.1109/iccitechn.2017.8281770]
28. 28.Xie, Michael, Jean, Neal, Burke, Marshall, Lobell, David, Ermon, Stefano. (2015). Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping. arXiv (Cornell University)[10.48550/arxiv.1510.00098]

Cited By

1. 1.Ying Liu, Jincan Li, Wanting Zhu, Dongdong Deng, Binji Wu, Xin Wen. (2024). Intelligent Analysis and Prediction of User Electricity Consumption Status Based on Big Data. , 35, 671–676[10.1109/edpee61724.2024.00130]