• International Journal of Technology (IJTech)
  • Vol 10, No 2 (2019)

Cost Optimum Design of a Tropical Near Zero Energy House (nZEH)

Cost Optimum Design of a Tropical Near Zero Energy House (nZEH)

Title: Cost Optimum Design of a Tropical Near Zero Energy House (nZEH)
Yusuf Latief, Mohammed Ali Berawi, Ario Bintang Koesalamwardi, Leni Sagita, Ayu Herzanita

Corresponding email:

Cite this article as:
Latief, Y., Berawi, M.A., Koesalamwardi, A.B., Sagita, L., Herzanita, A., 2019. Cost Optimum Design of a Tropical Near Zero Energy House (nZEH). International Journal of Technology. Volume 10(2), pp. 376-385

Yusuf Latief Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Mohammed Ali Berawi Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Ario Bintang Koesalamwardi Construction Engineering and Management, Faculty of Engineering, Universitas Agung Podomoro, Jakarta 11470, Indonesia
Leni Sagita Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Ayu Herzanita Department of Civil Engineering, Faculty of Engineering, Universitas Pancasila, Srengseng Sawah, Jagakarsa, South Jakarta 12640, Indonesia
Email to Corresponding Author

Cost Optimum Design of a Tropical Near Zero Energy House (nZEH)

Housing development, as part of economic development, must be supported by energy availability in order to achieve sustainable growth. One of the approaches to supporting renewable energy promotion is to design and build energy efficient housing. However, the optimal design of such buildings faces two conflicting requirements, namely the consideration of cost effectiveness and minimum environmental impact. The high costs of energy efficient buildings, such as the near Zero Energy House (nZEH), are due to the high price of the materials and equipment used, such as photovoltaic (PV) panels, insulation and other supporting materials. Indonesia is situated on the equator and benefits from sunlight throughout the year. Nonetheless, this potential has not been fully realized, as the solar-generated energy technology for housing comes at a high price. Therefore, the objective of this study is to find the cost optimum combination of validated design variables for an nZEH which suit the tropical climate conditions of Indonesia. Experiments and a case study are employed in the study to validate the design variables for an optimum nZEH design, which include building orientation, PV panels, fenestration, and passive design. The study finds that the cost optimum nZEH design achieved 72 percent site-energy savings and 21 percent savings in the total Net Present Value (NPV) of life cycle costs, with insignificant incremental initial construction costs in enhancing the design.


Design optimization; Near Zero Energy House; Sequential search


As its population continues to grow, Indonesia is currently facing increasing demand for housing and electricity production. A by-product of such rapid development is greenhouse gas emissions. The Centre of Energy Studies at the University of Indonesia has projected that these emissions will grow continuously to an alarming level by 2025 (PEUI, 2006) if Indonesia continues to develop a business-as-usual (BAU) scheme. In the Paris Accord 2015, Indonesia signed a commitment to reduce its greenhouse gas emissions by up to 29% by 2030 (United Nations Framework Convention on Climate Change, 2016); however, to date it has only been able to achieve a 1.49% reduction (INDC, 2015). To maintain social welfare by  meeting   the  basic   needs  of   adequate   housing   and  energy   and  continuing to keep the enviromental impact at a minimum level, the development of the housing and energysectors needs innovation.

The energy performance of a building is the key element in reducing greenhouse gas emissions and making energy savings. Improving such performance is a cost-effective solution to overcoming climate change and improving energy security. Energy conservation in the building sector has attracted the interest and concern of the world community with respect to environmental conservation (Koesalamwardi, 2014).

In practice, it is very difficult to achieve zero energy consumption in a building. Buildings that consume just a little more energy than that generated are called near zero energy buildings (nZEBs), while an nZEH is a residential building that consumes a little more energy than it produces. Buildings that can generate energy usually use solar panels on their roofs and facades. By collecting energy from the sun, an nZEH can use its own generated energy and minimize energy consumption from outside sources (Marszal et al., 2011). Indonesia's tropical climate provides the potential for the development of nZEHs integrated with photovoltaic (PV) panels. However, this potential has not been fully explored due to the expensive technology of solar power generation systems (Dhany, 2013).

Reducing energy consumption without compromising living standards, e.g. indoor room temperature and comfort, is an important issue in the building construction industry. In addition, this problem also creates a contradiction for energy-efficient building design, which typically uses expensive materials and technology, and which directly affects the overall cost of construction (Milajic et al., 2013). This requires optimal use of green technology and attention to construction costs, so that energy-efficient building technologies will be economically feasible.

Buildings with high energy performance, such as the nZEH, should also be economically viable. Strategies and solutions are needed to reduce energy consumption for such buildings and to continually provide energy from renewable sources (Milan et al., 2012). In recent years, many energy conservation technologies have been developed, but the use of these tools does not guarantee optimal energy savings. This is because energy consumption is highly dependent on the combination and use of these tools, so these factors should be planned and optimized in order to obtain the best levels of energy saving (Ooka & Komamura, 2009). The purpose of this research is to develop an nZEH design with optimal costs using a sequential search optimization algorithm.


To conclude, this study has determined an nZEH design at optimum cost, using nZEH design variables such as PV panels, azimuth (building orientation), fenestration (window-to-wall ratio), and glazing for windows. The design variables were combined and simulated using sequential search numerical rules, with the help of building performance simulation software. The results show that common construction materials, e.g. concrete hollow bricks and terracotta roof tiles, are suitable and represent low-cost heat insulation materials for tropical houses. Comfortable indoor room temperatures can be achieved with minimal usage of air conditioning, by positioning the house so it is not directly facing the sun, and applying 60 cm eaves and overhangs on all windows. The application of these can also reduce the initial construction cost by not having to use expensive glazing. The optimum window-to-wall ratio, which ranged from 15% to 40%, can provide adequate natural lighting, while minimizing heat radiation from the sun. By applying PV panels, electric consumption can also be reduced significantly. The electric power generated by the PV panels can also be exported to the central power grid, thus cutting electricity bills thanks to the net-metering incentive scheme.

The design optimization algorithm will sequentially search for the optimum combinations, thus generating maximum cost savings. Therefore, the optimization process will also eliminate unnecessary, unsuitable, and/or expensive design variables for tropical climates; for example, boilers, asphalt roof shingles, fiberglass wall insulations and LED lighting. Based on the cost optimum design parameter selection, the incremental construction cost for upgrading the design towards nZEH design concept is less than 5% to the initial construction cost of conventional design. The optimized design of the nZEH shows a significant annual maintenance and operational cost reduction, resulting in a lower NPV of cost compared to the conventional house design of up to 21%.


The authors would like to acknowledge the research grant from the Ministry of Research, Technology and Higher Education Republic of Indonesia (Kemenristekdikti) as funding support for the research project (Hibah Penelitian Unggulan Perguruan Tinggi 2016 Nomor:1181/UN2.R12/HKP.05.00/2016).


Blank, L., Tarquin, A., 2005. Engineering Economy, 6th ed., New York: McGraw-Hill

Boeck, L.D., Audenaert, A., Mesmaeker, L.D, 2013. Improving the Energy Performance of Residential Buildings: A Literature Review. Hubrussel Research Paper, Brussel, Belgia

Bucking, S., Athienitis, A., Zmeureanu, R., O'Brien, W., Doiron, M., 2013a. Design Optimization Methodology for a Near Net Zero Energy Demonstration Home. Concordia University, Montreal, Quebec, Department of Building and Civil & Environmental Engineering, Quebec

Bucking, S., Zmeureanu, R., Athienitis, A., 2013b. An Information Driven Hybrid Evolutionary Algorithm for Optimal Design of a Net Zero Energy House. Solar Energy, Volume (96), pp. 128–139

Couture, T., Gagnon, Y., 2010. An Analysis of Feed-in Tariff Remuneration Models: Implications for Renewable Energy Investment. Energy Policy, Volume 38(2), pp. 955–965

Dhany, R.R., 2013. Ini Alasan Pembangkit Listrik Matahari Sulit Berkembang di RI (This is the Reason Why Solar Power Plant is Difficult to Grow in RI). Available Online at http://finance.detik.com/read/2013/02/22/192004/2177424/1034/ini-alasan-pembangkit-listrik-matahari-sulit-berkembang-di-ri

Hamdy, M., Hasan, A., Siren, K., 2013. A Multi-stage Optimization Method for Cost-optimal and Nearly-Zero-Energy Building Solutions in Line with the EPDB-Recast 2010. Energy and Buildings Volume 56, pp. 189–203

Hartungi, R., Pye, C., 2009. Life Cycle Cost (LCC) for Sustainable Building. Lancashire, UK: University of Central Lancashire

Herubowo, Y., 2017. Perbandingan Penerapan Variabel Desain Near Zero Energy House (nZEH) di Indonesia dengan Negara di Asia Tenggara (Comparison on the Implementation of Near Zero Energy House (nZEH) Design Variable in Indonesia with Other Countries in South East Asia Region). Graduate Program, Universitas Indonesia, Depok, Indonesia

Ihm, P., Krarti, M., 2012. Design Optimization of Energy Efficient Residential Buildings in Tunisia. Building and Environment, Volume 58, pp. 81–90

INDC., 2015. Carbon Brief's Paris Climate Pledge Tracker: INDC Database. Available Online at https://docs.google.com/spreadsheets/d/1LtaBOv70pvXVPDgLUGtTKnSxofjfZy7jx06bTSaMaH4/pubhtml?gid=14385633&single=true, Accessed on January 9, 2018

Kemal, E., 2017. Identifikasi Variabel Desain Konsep Near Zero Energy Housing (nZEH) pada Bangunan Rumah di Daerah Tropis (Identification of Near Zero Energy Housing (nZEH) Design Variables of Residential Buildings in Tropical Climate). Graduate Program, Universitas Indonesia, Depok, Indonesia

Koesalamwardi, A.B., 2014. Desain Optimum Biaya Near Zero Energy House Menggunakan Algoritma Genetika (Cost Optimum Design of Near Zero Energy House using Genetic Algortihm). Master Thesis, Graduate Program, Universitas Indonesia, Depok, Jawa Barat, Indonesia

Latief, Y., Berawi, M.A., Koesalamwardi, A.B., Sagita, L., Petroceany, J., 2017. Defining Design Parameters for Housing Development in Tropical Climates using the Near Zero Energy House (nZEH) Concept. International Journal of Technology. Volume 8(6), pp. 1134–1140

Marszal, A.J., Heiselberg, P., 2011. Life Cycle Cost Analysis of a Multi-storey Residential Net Zero Energy Building. Energy, Volume 36(9), pp. 5600–5609

Marszal, A.J., Heisenberg, P., Bourelle, J.S., Musall, E., Voss, K., Sartori, I., Napolitano, A., 2011. Zero Energy Buildings - A Review of Definitions and Calculation Methodologies. Energy and Buildings, Volume 43(4), pp. 971–979

Milajic, A., Milosevic, P., Belkovic, D., 2013. Optimal Green Building Design using Multi-objective Genetic Algorithm. Reporting for Sustainability, pp. 119–123

Milan, C., Bojesen, C., Nielsen, M.P., 2012. A Cost Optimization Model for 100% Renewable Residential Energy Supply Systems. Energy, Volume 48(1), pp. 118–127

Ooka, R., Komamura, K., 2009. Optimal Design Method for Building Energy Systems using Genetic Algorithms. Building and Environment, Volume 44(7), pp. 1538–1544

PEUI., 2006. Indonesia Energy Outlook and Statistics. (W.W. Purwanto, Ed.) Depok: Pengkajian Energi Universitas Indonesia

Torcellini, P., Pless, S., Deru, M., 2006. Zero Energy Buildings: A Critical Look at the Definition. In: ACEEE Summer Study. Pacific Grove, California: National Renewable Energy Laboratory

United Nations Framework Convention on Climate Change, 2016. United Nations Climate Change. Available Online at https://www.google.com/url?q=http://www4.unfccc.int/ndcregistry/PublishedDocuments/Indonesia%2520First/First%2520NDC%2520Indonesia_submitted%2520to%2520UNFCCC%2520Set_November%2520%25202016.pdf&sa=D&ust=1515471798942000&usg=AFQjCNGCEShKzeOOFZzDHBb4sAeXg7F, Accessed on January 9, 2018

Wang, W., Zmeureanu, R., Rivard, H., 2005. Applying Multi-objective Genetic Algorithms in Green Building Design Optimization. Building and Environment, Volume 40(11), pp. 1512–1525

Wimmer, R., 2013. Adapting Zero Carbon House for Tropical Climate – Passive Cooling Design in the Philippines. In: Proceedings of SB13 Sustainable Buildings, Infrastructure and Communities in Emerging Economies 2013, Manila, 25–27 November, Philippines