Skip to main content

Advertisement

SpringerLink
Log in

Application of the bin weather data for building energy analysis in the tropics

  • Original Article
  • Published:
Energy Efficiency Aims and scope Submit manuscript

Abstract

The present study presents the bin weather data for four cities in the tropical region and its significance in the building energy analysis. The bin weather data for four cities in Malaysia, which are Bayan Lepas, Kuala Terengganu, Senai and Kuching, were generated. The bin weather data are in the range from 18 to 38 °C with 2 °C intervals and tabulated based on six 4-h shifts. Since there is a lack of updated bin weather data in Malaysia, the present paper provides valuable data for engineers and designers to conduct an energy analysis using the bin method in this region. This data may also serve as an important reference for all tropical regions with similar weather characteristics. Energy analysis is an important tool for estimating the energy usage of a building in order to minimize energy wastage and maximize energy efficiency. The significance of applying bin weather data in energy analysis is also investigated using a case simulation. When the mean outdoor temperature of occupied period is used in simulation, the results deviate less than 1.6% from the results with the bin weather data, but the deviation rises up to 16.68% with the use of the annual mean outdoor dry bulb temperature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Abbreviations

BLAST:

Building Loads Analysis and System Thermodynamics

GWP:

Global warming potential

HEED:

Home Energy Efficient Design

HVAC:

Heating, ventilating, and air-conditioning

IES-VE:

Integrated Environmental Solutions – Virtual Environment

ODP:

Ozone depletion potential

TRNSYS:

Transient Systems Simulation Program

References

  • Al-Homoud, M. S. (2001). Computer-aided building energy analysis techniques. Building and Environment, 36, 421–433.

    Article  Google Scholar 

  • Auffhammer, M., & Aroonruengsawat, A. (2011). Simulating the impacts of climate change, prices and population on California’s residential electricity consumption. Climatic Change, 109, 191–210.

    Article  Google Scholar 

  • Brown, M. A., Cox, M., Staver, B., & Baer, P. (2016). Modeling climate-driven changes in US buildings energy demand. Climatic Change, 134, 29–44.

    Article  Google Scholar 

  • Bulut, H., Büyükalaca, O., & Yılmaz, T. (2001). Bin weather data for Turkey. Applied Energy, 70, 135–155.

    Article  Google Scholar 

  • Chau, C., Leung, T., & Ng, W. (2015). A review on life cycle assessment, life cycle energy assessment and life cycle carbon emissions assessment on buildings. Applied Energy, 143, 395–413.

    Article  Google Scholar 

  • Coakley, D., Raftery, P., & Keane, M. (2014). A review of methods to match building energy simulation models to measured data. Renewable and Sustainable Energy Reviews, 37, 123–141.

    Article  Google Scholar 

  • Day, A., Knight, I., Dunn, G., & Gaddas, R. (2003). Improved methods for evaluating base temperature for use in building energy performance lines. Building Services Engineering Research and Technology, 24, 221–228.

    Article  Google Scholar 

  • Ebrahimpour, A., & Maerefat, M. (2010). A method for generation of typical meteorological year. Energy Conversion and Management, 51, 410–417.

    Article  Google Scholar 

  • Fazeli, R., Ruth, M., & Davidsdottir, B. (2016). Temperature response functions for residential energy demand—a review of models. Urban Climate, 15, 45–59.

    Article  Google Scholar 

  • Idchabani, R. 2018. Bin weather data for five climatic zones of Morocco. International Journal of Ambient Energy, 1-8.

  • Jin, Z., Yezheng, W., & Gang, Y. (2006). A stochastic method to generate bin weather data in Nanjing, China. Energy Conversion and Management, 47, 1843–1850.

    Article  Google Scholar 

  • Kreider, J. F., Curtiss, P. S. & Rabl, A. 2009. Heating and cooling of buildings: design for efficiency. CRC Press.

  • Krese, G., Prek, M., & Butala, V. (2012). Analysis of building electric energy consumption data using an improved cooling degree day method. Strojniški vestnik-Journal of Mechanical Engineering, 58, 107–114.

    Article  Google Scholar 

  • Manfren, M., Aste, N., & Moshksar, R. (2013). Calibration and uncertainty analysis for computer models—a meta-model based approach for integrated building energy simulation. Applied Energy, 103, 627–641.

    Article  Google Scholar 

  • Mcquiston, F. C. & Parker, J. D. 2005. Heating, ventilating, and air conditioning: analysis and design.

  • Meng, Q., & Mourshed, M. (2017). Degree-day based non-domestic building energy analytics and modelling should use building and type specific base temperatures. Energy and Buildings, 155, 260–268.

    Article  Google Scholar 

  • METMALAYSIA 2017. Annual Report 2017. In: RAHMAN, R. A. (ed.). Malaysia: Malaysian Meteorological Department.

  • Nguyen, A.-T., Reiter, S., & Rigo, P. (2014). A review on simulation-based optimization methods applied to building performance analysis. Applied Energy, 113, 1043–1058.

    Article  Google Scholar 

  • Noriah, A., & Rakhecha, P. (2001). Probable maximum precipitation for 24 h duration over southeast Asian monsoon region—Selangor, Malaysia. Atmospheric Research, 58, 41–54.

    Article  Google Scholar 

  • Özyurt, Ö., Bakirci, K., Erdoğan, S., & Yilmaz, M. (2009). Bin weather data for the provinces of the Eastern Anatolia in Turkey. Renewable Energy, 34, 1319–1332.

    Article  Google Scholar 

  • Papakostas, K. (1999). Technical note bin weather data of Athens, Greece. Renewable Energy, 17, 265–275.

    Article  Google Scholar 

  • Papakostas, K., Bentoulis, A., Bakas, V., & Kyriakis, N. (2007). Estimation of ambient temperature bin data from monthly average temperatures and solar clearness index. Validation of the methodology in two Greek cities. Renewable Energy, 32, 991–1005.

    Article  Google Scholar 

  • Papakostas, K., Tsilingiridis, G., & Kyriakis, N. (2008). Bin weather data for 38 Greek cities. Applied Energy, 85, 1015–1025.

    Article  Google Scholar 

  • Peng, Z., Jin, Z., Guoqiang, Z., & Yezheng, W. (2009). Generation of ambient temperature bin data of 26 cities in China. Energy Conversion and Management, 50, 543–553.

    Article  Google Scholar 

  • Pérez-Lombard, L., Ortiz, J., & Pout, C. (2008). A review on buildings energy consumption information. Energy and Buildings, 40, 394–398.

    Article  Google Scholar 

  • Pusat, S. (2019). A simple approach to estimate ambient temperature bin data. Energy Efficiency, 12, 1053–1064.

    Article  Google Scholar 

  • Pusat, S., & Ekmekci, I. (2016). A study on degree-day regions of Turkey. Energy Efficiency, 9, 525–532.

    Article  Google Scholar 

  • Pusat, S., Ekmekçi, İ., & Akkoyunlu, M. T. (2015). Generation of typical meteorological year for different climates of Turkey. Renewable Energy, 75, 144–151.

    Article  Google Scholar 

  • Saidur, R. (2009). Energy consumption, energy savings, and emission analysis in Malaysian office buildings. Energy Policy, 37, 4104–4113.

    Article  Google Scholar 

  • Sarak, H., & Satman, A. (2003). The degree-day method to estimate the residential heating natural gas consumption in Turkey: a case study. Energy, 28, 929–939.

    Article  Google Scholar 

  • Schicktanz, M. D., Döll, J., & Fugmann, H. (2014). Calculation of solar gains for solar heating and cooling using the bin-method. Energy Procedia, 48, 1665–1675.

    Article  Google Scholar 

  • Suhaila, J., Deni, S. M., Zin, W. Z. W., & Jemain, A. A. (2010). Trends in Peninsular Malaysia rainfall data during the southwest monsoon and northeast monsoons seasons: 1975-2004. Sains Malaysiana, 39, 533–542.

    Google Scholar 

  • Tangang, F., Juneng, L., & Ahmad, S. (2007). Trend and interannual variability of temperature in Malaysia: 1961–2002. Theoretical and Applied Climatology, 89, 127–141.

    Article  Google Scholar 

  • Wang, Z., Ding, Y., Geng, G., & Zhu, N. (2014). Analysis of energy efficiency retrofit schemes for heating, ventilating and air-conditioning systems in existing office buildings based on the modified bin method. Energy Conversion and Management, 77, 233–242.

    Article  Google Scholar 

  • Yau, Y., & Hasbi, S. (2013). A review of climate change impacts on commercial buildings and their technical services in the tropics. Renewable and Sustainable Energy Reviews, 18, 430–441.

    Article  Google Scholar 

  • Zhao, H.-X., & Magoulès, F. (2012). A review on the prediction of building energy consumption. Renewable and Sustainable Energy Reviews, 16, 3586–3592.

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank the Malaysian Meteorological Department for providing valuable weather data for the present research.

Funding

The authors would like to thank the Daikin Fellowship Grant for funding the project PV018-2016. In addition, special thanks are extended to University of Malaya for providing partial RU Grants GPF004A-2018 and IIRG014A-2019 to the authors for research work to be conducted at University of Malaya.

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Y. H. Yau, C. M. Wong & H. C. Ong

  2. UM-Daikin Laboratory, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Y. H. Yau, C. M. Wong & H. C. Ong

  3. Daikin Research & Development Malaysia Sdn Bhd, Lot 60334, Persiaran Bukit Rahman Putra 3, Taman Perindustrian Bukit Raman Putra, 47000, Sungai Buloh, Selangor, Malaysia

    W. M. Chin

Authors
  1. Y. H. Yau
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. M. Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. H. C. Ong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. W. M. Chin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Y. H. Yau.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yau, Y.H., Wong, C.M., Ong, H.C. et al. Application of the bin weather data for building energy analysis in the tropics. Energy Efficiency 13, 935–953 (2020). https://doi.org/10.1007/s12053-020-09862-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12053-020-09862-8

Keywords

Search

Navigation