The Efficiency Leap: A Simulation-Driven Approach toward Ethiopian Energy-Efficient Urban Housing
Research Article  ·  Published: 15 August 2026
Issue cover
Sustainable Intelligent Infrastructure
Volume 2, Issue 2, 2026: 8-24
Research Article Open Access

The Efficiency Leap: A Simulation-Driven Approach toward Ethiopian Energy-Efficient Urban Housing

1 Department of Architecture, Adama Science and Technology University, Adama 1888, Ethiopia
2 Department of Architecture and Planning, Indian Institute of Technology Roorkee, Roorkee 247667, India
* Corresponding Author: Getahun Ayele Tessema, [email protected]
Volume 2, Issue 2
You have full access to this open access article · CC BY 4.0 License

Article Information

Abstract

Enhancing the energy efficiency of urban housing is crucial for improving energy access in Ethiopia, where a persistent gap exists between energy demand and supply. The nationwide Integrated Housing Development Program (IHDP), implemented across diverse climatic zones with limited attention to local context and building energy performance, has inadvertently produced thermally uncomfortable and energy-inefficient urban dwellings. This study employs a scenario-based intelligent energy simulation framework to address this inefficiency by identifying energy-saving opportunities in urban housing, pioneering the smart meter data-driven ClimateStudio-EnergyPlus workflow-validated through machine-readable consumption analytics (R$^2$ = 0.79 in Addis Ababa; 0.64 in Adama) and on-site surveys across temperate highland Addis Ababa and hot-arid Adama. Appliance usage inventory reveals cooking dominance, accounting for 60-62.9% of total loads. Adama's 20% household fan-based thermal coping behavior signals a latent air-conditioning demand projected to surge 31% above baseline in arid lowlands versus 6% in temperate zones as affordability erodes overheating tolerance. Monthly consumption heatmaps reveal unit-size and seasonal interaction effects diverging sharply between cities, with Adama's studio units peaking at approximately 191~kWh/month in the dry season against a stable 150-190~kWh/month range in Addis Ababa. Envelope diagnostics expose a systemic performance gap, wall U-values of 1.61~W/m$^2$K and glazing SHGC of 0.86-0.87 exceeding best-practice targets by three- to fourfold, with Adama's larger glazed area compounding solar heat gain risk in the climate zone least suited to absorb it. Targeting dominant local cooking appliance upgrades yields immediate operational savings of 18-18.9%. Furthermore, these empirical benchmarks recommend region-tailored building envelopes in conjunction with Minimum Energy Performance Standards (MEPS) for cooking appliances, establishing foundational performance data for Ethiopia's unimplemented building codes and informing climate-affordability demand forecasting to achieve policy-aligned efficiency gains.

Graphical Abstract

The Efficiency Leap: A Simulation-Driven Approach toward Ethiopian Energy-Efficient Urban Housing

Keywords

energy efficiency IHDP housing smart meter data analytics intelligent building simulation latent cooling demand climatic zoning

Data Availability Statement

Data will be made available on request.

Funding

This work was supported by the Indian Council for Cultural Relations (ICCR) under Grant JW8107729363962 for the PhD scholarship of the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

AI Use Statement

The authors declare that no generative AI was used in the preparation of this manuscript.

Ethical Approval and Consent to Participate

Not applicable.

References

  1. OECD, African Development Bank, Cities Alliance, & United Cities and Local Governments of Africa. (2025). Africa's Urbanisation Dynamics 2025: Planning for Africa's Urban Expansion. OECD Publishing.
    [CrossRef] [Google Scholar]
  2. Liyew, K. W., Ejigu, N. A., & Habtu, N. G. (2024). Analysis of energy supply, energy policies, and the final energy end-use consumption of the residential sector in Ethiopia. Heliyon, 10(15), e34809.
    [CrossRef] [Google Scholar]
  3. Falchetta, G., Cian, E. D., Pavanello, F., & Wing, I. S. (2024). Inequalities in global residential cooling energy use to 2050. Nature communications, 15(1), 7874.
    [CrossRef] [Google Scholar]
  4. Dagne, S. S., Hirpha, H. H., Tekoye, A. T., Roba, Z. R., & Moisa, M. B. (2025). Quantifying urbanization-induced dynamics of urban sprawl using spatial metrics method in Adama City, Ethiopia. Cogent Social Sciences, 11(1), 2433696.
    [CrossRef] [Google Scholar]
  5. Pavanello, F., De Cian, E., Davide, M., Mistry, M., Cruz, T., Bezerra, P., ... & Lucena, A. F. (2021). Air-conditioning and the adaptation cooling deficit in emerging economies. Nature communications, 12(1), 6460.
    [CrossRef] [Google Scholar]
  6. Hassen, S., Anandarajah, G., & Seifemichael, R. (2023). Behavioral and socio-economic determinants of urban households' investment in energy efficient technologies: evidence from Ethiopia. Frontiers in Energy Research, 11, 1135291.
    [CrossRef] [Google Scholar]
  7. Falchetta, G., & Mistry, M. N. (2021). The role of residential air circulation and cooling demand for electrification planning: Implications of climate change in sub-Saharan Africa. Energy Economics, 99, 105307.
    [CrossRef] [Google Scholar]
  8. Vetter-Gindele, J., Bachofer, F., Braun, A., Uwayezu, E., Rwanyiziri, G., & Eltrop, L. (2023). Bottom-up assessment of household electricity consumption in dynamic cities of the Global South—Evidence from Kigali, Rwanda. Frontiers in Sustainable Cities, 5, 1130758.
    [CrossRef] [Google Scholar]
  9. Tessema, G. A., Chani, P. S., & Rajasekar, E. (2025, August). Analysis of Residential Electricity Consumption in Ethiopian Condominiums: Leveraging Cluster Analysis for Targeted Electrification Interventions. In 2025 IEEE 13th International Conference on Smart Energy Grid Engineering (SEGE) (pp. 89-93). IEEE.
    [CrossRef] [Google Scholar]
  10. Gupta, V., & Deb, C. (2023). Envelope design for low-energy buildings in the tropics: A review. Renewable and Sustainable Energy Reviews, 186, 113650.
    [CrossRef] [Google Scholar]
  11. Tessema, G. A., Chani, P. S., & Rajasekar, E. (2026). Building operational energy saving opportunities: A clustering analysis of Ethiopian urban housing. Energy Strategy Reviews, 63, 102044.
    [CrossRef] [Google Scholar]
  12. Ethiopian Energy Authority (EEA). (2019). Energy Efficiency Program and Activity Plan. Ethiopian Energy Authority. Retrieved from https://rise.esmap.org/sites/default/files/library/ethiopia/Energy%20Efficiency/Ethiopia_Energy%20Efficiency%20Program%20Final%20A4.pdf
    [Google Scholar]
  13. Eludoyin, E. O., Anandarajah, G., Broad, O., Hassen, S., & Seifemichael, R. (2022). Modelling residential electricity demand in Ethiopia: a mixed methods approach. September, 1-18. Retrieved from https://climatecompatiblegrowth.com/publication/eeg-working-paper-modelling-residential-electricity-demand-in-ethiopia-a-mixed-methods-approach/
    [Google Scholar]
  14. Garrett, A., & New, J. R. (2015). Suitability of ASHRAE guideline 14 metrics for calibration. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Available at: https://web.eecs.utk.edu/~jnew1/publications/2016_ASHRAE_G14.pdf
    [Google Scholar]
  15. Makeyaw, A., & Getu, M. (2025). Unlocking Ethiopia's Renewable Energy Potential: Pathways into a Sustainable Future. Journal of Forensic Science and Research, 162-172.
    [CrossRef] [Google Scholar]
  16. Yalew, A. W. (2022). The Ethiopian energy sector and its implications for the SDGs and modeling. Renewable and Sustainable Energy Transition, 2, 100018.
    [CrossRef] [Google Scholar]
  17. Beyene, A. D., Jeuland, M., Sebsibie, S., Hassen, S., Mekonnen, A., Meles, T. H., ... & Klug, T. (2022). Pre-paid meters and household electricity use behaviors: Evidence from Addis Ababa, Ethiopia. Energy Policy, 170, 113251.
    [CrossRef] [Google Scholar]
  18. Weldeghebrael, E. H. (2021). Addis Ababa: city scoping study. African Cities Research Consortium. Available at: https://www.african-cities.org/wp-content/uploads/2021/12/ACRC_Addis-Ababa_City-Scoping-Study.pdf
    [Google Scholar]
  19. Workineh, B. A. (2022). The practice and roles of condominium housing for tackling urban problems in the case of Gondar city, Ethiopia. Heliyon, 8(12).
    [CrossRef] [Google Scholar]
  20. Kang, Y., & Kim, S. (2025). Climate-responsive optimization of phase change materials for energy-efficient building envelopes in diverse climatic regions of Ethiopia. International Journal of Thermophysics, 46(8), 122.
    [CrossRef] [Google Scholar]
  21. Asres, B., Pan, J., Bardhan, R., & Alemayehu, E. (2025). Thermal comfort in affordable housing in Global South: A case of free-running integrated housing development program (IHDP) in Jimma, Ethiopia. Journal of Building Engineering, 101, 111814.
    [CrossRef] [Google Scholar]
  22. Maagøe, V. (2023). Review of Ethiopian energy efficiency policy. Ethiopian-Danish Energy Cooperation, 2023. Retrieved from https://www.scribd.com/document/760013342/Review-of-Ethiopian-Energy-Efficiency-Policy-2023
    [Google Scholar]
  23. Ethiopian Energy Authority. (2019). Energy Efficiency Program and Activity Plan [Directive No.~006]. Retrieved from https://rise.esmap.org/sites/default/files/library/ethiopia/Energy\%20Efficiency/Ethiopia_Directive\%20006_2011-Energy\%20Efficiency\%20Program\%20and\%20Activity\%20Plan.pdf
    [Google Scholar]
  24. Shabunko, V., Lim, C. M., & Mathew, S. (2018). EnergyPlus models for the benchmarking of residential buildings in Brunei Darussalam. Energy and Buildings, 169, 507-516.
    [CrossRef] [Google Scholar]
  25. Crawley, D. B. (2019). Building 12 simulation for policy support. In Building Performance Simulation for Design and Operation (pp. 384-395). Routledge.
    [CrossRef] [Google Scholar]
  26. Crawley, D. B., Lawrie, L. K., Winkelmann, F. C., Buhl, W. F., Huang, Y. J., Pedersen, C. O., ... & Glazer, J. (2001). EnergyPlus: creating a new-generation building energy simulation program. Energy and buildings, 33(4), 319-331.
    [CrossRef] [Google Scholar]
  27. Larsen, L., Yeshitela, K., Mulatu, T., Seifu, S., & Desta, H. (2019). The impact of rapid urbanization and public housing development on urban form and density in Addis Ababa, Ethiopia. Land, 8(4), 66.
    [CrossRef] [Google Scholar]
  28. Tipple, G., & Alemayehu, E. Y. (2014). Stocktaking of the Housing Sector in Sub‐Saharan Africa Part 3: Ethiopia. Affordable Housing Institute, 16(2), 39-55. Available at: https://www.worldbank.org/content/dam/Worldbank/document/Africa/Report/stocktaking-of-the-housing-sector-in-sub-saharan-africa-summary-report.pdf
    [Google Scholar]
  29. Bulti, D. T., & Bogale, E. M. (2025). Seasonal and Multi-Decadal Dynamics of Land Surface Temperature and Urban Heat Island in a Semi-Arid Secondary City: A Case Study of Adama, Ethiopia.
    [CrossRef] [Google Scholar]
  30. Abera, B. (2024). Evaluation of Urban Thermal Environment Variation and Stress Using Remote Sensing Imagery and QGIS for Sustainable Urban Development over Adama City, Ethiopia.
    [CrossRef] [Google Scholar]
  31. Zeleke, B., Kumar, M., & Rajasekar, E. (2022). A novel building performance based climate zoning for Ethiopia. Frontiers in Sustainable Cities, 4, 684148.
    [CrossRef] [Google Scholar]
  32. Jain, N., Burman, E., Stamp, S., Mumovic, D., & Davies, M. (2020). Cross-sectoral assessment of the performance gap using calibrated building energy performance simulation. Energy and Buildings, 224, 110271.
    [CrossRef] [Google Scholar]
  33. Jones, R., Diehl, J. C., Simons, L., & Verwaal, M. (2017, April). The development of an energy efficient electric Mitad for baking injeras in Ethiopia. In 2017 International Conference on the Domestic Use of Energy (DUE) (pp. 75-82). IEEE.
    [CrossRef] [Google Scholar]
  34. Hailu, H., Gelan, E., & Girma, Y. (2021). Indoor thermal comfort analysis: A case study of modern and traditional buildings in hot-arid climatic region of Ethiopia. Urban Science, 5(3), 53.
    [CrossRef] [Google Scholar]

Cite This Article

APA Style
Tessema, G. A., Chani, P. S., & Elangovan, R. (2026). The Efficiency Leap: A Simulation-Driven Approach toward Ethiopian Energy-Efficient Urban Housing. Sustainable Intelligent Infrastructure, 2(2), 8-24. https://doi.org/10.62762/SII.2026.252088
Export Citation
RIS Format
Compatible with EndNote, Zotero, Mendeley, and other reference managers
TY  - JOUR
AU  - Tessema, Getahun Ayele
AU  - Chani, Prabhjot Singh
AU  - Elangovan, Rajasekar
PY  - 2026
DA  - 2026/08/15
TI  - The Efficiency Leap: A Simulation-Driven Approach toward Ethiopian Energy-Efficient Urban Housing
JO  - Sustainable Intelligent Infrastructure
T2  - Sustainable Intelligent Infrastructure
JF  - Sustainable Intelligent Infrastructure
VL  - 2
IS  - 2
SP  - 8
EP  - 24
DO  - 10.62762/SII.2026.252088
UR  - https://www.icck.org/article/abs/SII.2026.252088
KW  - energy efficiency
KW  - IHDP housing
KW  - smart meter data analytics
KW  - intelligent building simulation
KW  - latent cooling demand
KW  - climatic zoning
AB  - Enhancing the energy efficiency of urban housing is crucial for improving energy access in Ethiopia, where a persistent gap exists between energy demand and supply. The nationwide Integrated Housing Development Program (IHDP), implemented across diverse climatic zones with limited attention to local context and building energy performance, has inadvertently produced thermally uncomfortable and energy-inefficient urban dwellings. This study employs a scenario-based intelligent energy simulation framework to address this inefficiency by identifying energy-saving opportunities in urban housing, pioneering the smart meter data-driven ClimateStudio-EnergyPlus workflow-validated through machine-readable consumption analytics (R$^2$ = 0.79 in Addis Ababa; 0.64 in Adama) and on-site surveys across temperate highland Addis Ababa and hot-arid Adama. Appliance usage inventory reveals cooking dominance, accounting for 60-62.9% of total loads. Adama's 20% household fan-based thermal coping behavior signals a latent air-conditioning demand projected to surge 31% above baseline in arid lowlands versus 6% in temperate zones as affordability erodes overheating tolerance. Monthly consumption heatmaps reveal unit-size and seasonal interaction effects diverging sharply between cities, with Adama's studio units peaking at approximately 191~kWh/month in the dry season against a stable 150-190~kWh/month range in Addis Ababa. Envelope diagnostics expose a systemic performance gap, wall U-values of 1.61~W/m$^2$K and glazing SHGC of 0.86-0.87 exceeding best-practice targets by three- to fourfold, with Adama's larger glazed area compounding solar heat gain risk in the climate zone least suited to absorb it. Targeting dominant local cooking appliance upgrades yields immediate operational savings of 18-18.9%. Furthermore, these empirical benchmarks recommend region-tailored building envelopes in conjunction with Minimum Energy Performance Standards (MEPS) for cooking appliances, establishing foundational performance data for Ethiopia's unimplemented building codes and informing climate-affordability demand forecasting to achieve policy-aligned efficiency gains.
SN  - 3067-8137
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 
BibTeX Format
Compatible with LaTeX, BibTeX, and other reference managers
@article{Tessema2026The,
  author = {Getahun Ayele Tessema and Prabhjot Singh Chani and Rajasekar Elangovan},
  title = {The Efficiency Leap: A Simulation-Driven Approach toward Ethiopian Energy-Efficient Urban Housing},
  journal = {Sustainable Intelligent Infrastructure},
  year = {2026},
  volume = {2},
  number = {2},
  pages = {8-24},
  doi = {10.62762/SII.2026.252088},
  url = {https://www.icck.org/article/abs/SII.2026.252088},
  abstract = {Enhancing the energy efficiency of urban housing is crucial for improving energy access in Ethiopia, where a persistent gap exists between energy demand and supply. The nationwide Integrated Housing Development Program (IHDP), implemented across diverse climatic zones with limited attention to local context and building energy performance, has inadvertently produced thermally uncomfortable and energy-inefficient urban dwellings. This study employs a scenario-based intelligent energy simulation framework to address this inefficiency by identifying energy-saving opportunities in urban housing, pioneering the smart meter data-driven ClimateStudio-EnergyPlus workflow-validated through machine-readable consumption analytics (R\$^2\$ = 0.79 in Addis Ababa; 0.64 in Adama) and on-site surveys across temperate highland Addis Ababa and hot-arid Adama. Appliance usage inventory reveals cooking dominance, accounting for 60-62.9\% of total loads. Adama's 20\% household fan-based thermal coping behavior signals a latent air-conditioning demand projected to surge 31\% above baseline in arid lowlands versus 6\% in temperate zones as affordability erodes overheating tolerance. Monthly consumption heatmaps reveal unit-size and seasonal interaction effects diverging sharply between cities, with Adama's studio units peaking at approximately 191~kWh/month in the dry season against a stable 150-190~kWh/month range in Addis Ababa. Envelope diagnostics expose a systemic performance gap, wall U-values of 1.61~W/m\$^2\$K and glazing SHGC of 0.86-0.87 exceeding best-practice targets by three- to fourfold, with Adama's larger glazed area compounding solar heat gain risk in the climate zone least suited to absorb it. Targeting dominant local cooking appliance upgrades yields immediate operational savings of 18-18.9\%. Furthermore, these empirical benchmarks recommend region-tailored building envelopes in conjunction with Minimum Energy Performance Standards (MEPS) for cooking appliances, establishing foundational performance data for Ethiopia's unimplemented building codes and informing climate-affordability demand forecasting to achieve policy-aligned efficiency gains.},
  keywords = {energy efficiency, IHDP housing, smart meter data analytics, intelligent building simulation, latent cooling demand, climatic zoning},
  issn = {3067-8137},
  publisher = {Institute of Central Computation and Knowledge}
}

Article Metrics

Citations
Crossref
0
Scopus
0
Views
35
PDF Downloads
5

Publisher's Note

ICCK stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and Permissions

CC BY Copyright © 2026 by the Author(s). Published by Institute of Central Computation and Knowledge. 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/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
Sustainable Intelligent Infrastructure
Sustainable Intelligent Infrastructure
ISSN: 3067-8137 (Online)
Portico
Preserved at
Portico