Descriptive Review of Energy Performance Evaluation Approaches

Authors

  • Siva Jaganathan Centre for Real Estate Studies, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Abdul Hakim Mohammed Centre for Real Estate Studies, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Mohd Shahril Abdul Rahman Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/sh.v8n4-3.1082

Keywords:

Energy, design, performance, building envelope, simulation, optimization

Abstract

This study address energy performance evaluation uncertainities in design. To achieve energy efficiency in building, designer should incorporate energy performance evaluation approach to foresight energy performance failure during design. The research has  evaluated and compares the capabilities of energy performances evaluation approaches namely computational fluid dynamic approach, optimization algorithm, and coupled approach. Furthermore, descriptive review unveils the practical obstacles and challenges designers encounter during design life cycle and proposes future direction to mitigate inundated energy performance gap.

References

Adeleke, M. H. (2006). An Appraisal of Curriculum Implementation in Nigeria, Lagos: Macus Publication.

Adeyemi, T. O. (2008).The Availability of Teaching Manpower in Technical Colleges in Ondo and Ekiti States, Nigeria: A Comparative Analysis. Middle-

East Journal of Scientific Research, 3(4), 179–189.

Aina, O. (2009). Three Decades of Technical and Vocational Education and Training in Nigeria. Ile-Ife: Obafemi University Press Ltd.

Akuezuilo, E. O. (2007). The New 9-year Basic Science and Technology Curriculum and Challenges of its Implementation. Journal of Curriculum and

Instruction, 6(2): 2–5.

Arbuckle, J. L. (2007). AMOS 16.0 User’s Guide. Spring House. PA: Amos Development Corporation.

Augenbroe, G. (1992). Integrated Building Performance Evaluation In The Early Design Stages. Building and Environment. 27 (2): 149–161.

Bambrook. S. M., A. B. Sproul, D. Jacob. (2011). Design Optimization For A Low Energy Home in Sydney. Energy and Building. 43 (7): 1702 -11.

Brans, J.P., B. Mareschal. (1995). The PROMETHEE VI procedure. How to Differentiate Soft From Hard Multicriteria Problems In The Discrete Case. Journal of Decision Systems. 4 (3): 213–224.

Bouchlaghem, N., (2000). Optimising The Design Of Building Envelopes For Thermal Performance. Automation and Construction. 10: 101-112.

Carmody, J, S. Selkowitz, E. Lee, D. Arasteh, and T. Willmert. 2004. Window Systems for High-Performance Buildings, Norton & Company, New York.

Education for Emergent Globalization, Relevance and Sustainable Economic Development. International Journal of Vocational and Technical Education,

(4), 55–61

Castro Lacouture. D., J. A. Sefair, L. Flórez, A. L. Medaglia. (2009). Optimization Model For The Selection Of Materials Using A LEED-Based Green Building Rating System in Colombia. Build Environ. Building and Environment. [6]: 1162 -70.

Coley, D.A., S. Schukat. (2002). Low-Energy Design: Combining Computer-Based Optimisation And Human Judgment. Building and Environment. 37: 1241–127.

De Wit, S., and G. Augenbroe. (2002). Analysis of Uncertainty in Building Design Evaluations and Its Implications. Energy and Buildings. 34: 951-958

Domínguez-Muñoz, F., J. M. Cejudo-López, and A. Carrillo- Andrés. 2010. Uncertainty in Peak Cooling Load Calculations. Energy and Buildings. 42 (7):

–1018.

Donn. M. 2004. Simulation Of Imagined Realities Environmental Design Decision Support Tools In Architecture. Ph.D. Thesis. School of Architecture, Victoria University, Wellington.

Fesanghary. M., S. Asadi, Z.W. Geem. (2012). Design of Low-Emission And Energy Efficient Residential Buildings Using A Multi-Objective Optimization Algorithm. Building and Environment. 49: 245–50

Foucquier. A., S. Robert, F. Suard, L. Stéphan, A. Jay. (2013). State Of The Art In Building Modelling And Energy Performances Prediction: A Review. Renew Sustainable Energy. 23: 272–88.

Gao, S., Mokhtarian, P. L., and Johnson, R. A. (2008). Non-Normality of Data in Structural Equation Models. Transportation Research Board’s 87th Annual Meeting, January. Washington D.C

Grob, R.F., M. Madjidi. (1997). Commissioning and fault detection of HVAC systems by using simulation models based on characteristic curves, in:

clima-2000 conference, Brussels.

Heiselberg, P., H. Brohus, A. Hesselholt, H. Rasmussen, E. Seinre, and S. Thomas. (2009). Application of Sensitivity Analysis in Design of Sustainable Buildings. Renewable Energy. 34 (9): 2030–2036

Holst J. N. 2003. Using Whole Building Simulation Models And Optimizing Procedures To Optimize Building Envelope Design With Respect To Energy

Consumption And Indoor Environment. Eighth International IBPSA Conference, Eindhoven, Netherlands. In: Proceedings of the Building Simulation.

Hopfe, C., and J. Hensen.(2011). Uncertainty Analysis in Building Performance Simulation for Design Support.†Energy and Buildings. 43 [10]: 2798 –2805.

Hopfe, C., C. Struck, P. Kotek, J. van Schijndel, J. Hensen, and W. Plokker. (2007). Uncertainty Analysis for Building Performance Simulation – A Comparison of Four Tools. Proceedings of the 10th IBPSA Building Simulation Conference. Beijing, China. 1383–1388.

Iassinovski, S., A. Artiba, V. Bachelet, and F. Riane. 2003. Integration of Simulation And Optimization For Solving Complex Decision Making Problems. International of Journal Production and Economics. 85: 3-10.

Nguyen. A., S. Reiter, P. Rigo. (2014). A Review On Simulation-Based Optimization Methods Applied To Building Performance Analysis. Applied Energy. 113: 1043–58.

Mahdavi, A., S. Feurer, A. Redlein, and G. Suter. (2003). An Inquiry Into The Building Performance Simulation Tools Usage By Architects In Austria, Proceedings of the Eighth IBPSA Conference. Eindhoven, Netherlands. 777–784.

Mahdavi, A., S. Feurer, A. Redlein, and G. Suter. (2003). An Inquiry Into The Building Performance Simulation Tools Usage By Architects In Austria, Proceedings of the Eighth IBPSA Conference. Eindhoven, Netherlands. 777–784.

Fisher D. E. , M.J. Witte, J. Glazer. (2001). Energy Plus: Creating A New-Generation Building Energy Simulation Program. Energy and Building. 33: 319–31.

Kim, S. H., and G. Augenbroe. 2013. Uncertainty in Developing Supervisory Demand-Side Controls in Buildings: A Framework and Guidance. Automation in Construction. 35: 28-43.

Rysanek, A., and R. Choudhary.(2013). Optimum Building Energy Retrofits Under Technical and Economic Uncertainty. Energy and Buildings. 57: 324–337.

Wright J, H. Loosemore, R. Farmani. 2002. Optimization of Building Thermal Design And Control By Multi-Criterion Genetic Algorithm. Energy and Buildings. 34 (9): 959-972

Hox, J. J and Bechger, T. M. (1998). An Introduction to Syructural Equation Modeling. Family Science Review, 11, 354–373.

ILO-International Labor Organization. (2008). Recognizing Ability: The Skills and Productivity of Persons with Disabilities. International Labour Office, Skills and Employability Department.-Geneva: ILO, 2008.

James, A., Fraces, L., Elaine, C., Wynn, C., Jim, H. and Jack, W. (2007). Models for Curricular Materials Development: Combining Applied Development

Processes with Theory. Journal of Science Education and Technology, 16(6), 491.

Kennedy, O. O. (2011). Reappraising the Work Skill Requirements for Building Technology Education in Senior Secondary School for Optimum Performance in Nigeria. European Journal of Applied Sciences, 3(2), 46–52.

Kline, R. B. (1998). Principle and Practice of Structural Modeling. New York: Guilford Press.

Mailea, T., V. Bazjanac and M. Fischera. (2012). A Method To Compare Simulated And Measured Data To Assess Building Energy Performance. Building and Environment. 56: 241- 251

McLeish, A. (2002). Employability Skills for Australian Small and Medium Sized Enterprises. Report of the Interviews and Focus Groups with Small and Medium Enterprises.

National Policy of Education. (2004). Federal Republic of Nigeria. Lagos: NERDC Press.

Oduolowu, E. A. (2007). A Comparison of the Universal Basic Education (UBE) Programme in Nigeria and the Grundskola of Sweden. Essays in Education, 20, 90–93.

Olayinka, O. and Oyenuga, O.A. (2010). Integration of Automobile Technological Developments into Nigeria Technical College Motor Mechanics Work Curriculum. Academic Leadership: The Online Journal, 8(2), 1–11.

Oloruntegbe, K. O., Agbayewa, J. O., Adodo, S. O., Adare D., and Laleye, A. M. 2010. Reconceptualization of African Vocational and Technological.

Partners for 21st Century Skills. (2009). P21 Framework Definitions.Available: http://www.p21.org/storage/documents/P21_Framework_Definitions.pdf.

Psacharopoulos, G and Woodhall, M. (1997). Education for Development: An Analysis of Investment Choice. New York Oxford University Press.

Sakamota, A. and Powers, P. A. (1995). Education and the Dual Labour Market for Japanaese Men in American Sociological Review, 60(2), P. 222–246.

Schultz, T. W. (1971). Investment in Human Capital. New York. The Free Press.

Wan-Mohammed, W. A and Yunus, M. H. (2009). The Inculcation of Generic Skills among Juveniles through Technical and Vocational Education. Us-China Education Review, 6(4), 56–61.

Wang, W. 2005. A Simulation-Based Optimization System for Green Building Design. PhD Thesis. Concordia University.

Wang. L., N. H. Wong. (2008). Coupled Simulations For Naturally Ventilated Residential Buildings. Automation in Construction. 17:386–98.

Wang. W., H. Rivard, R. Zmeureanu. 2005. An Object-Oriented Framework For Simulation-Based Green Building Design Optimization With Genetic Algorithms. Advanced Engineering Information. 19(1): 5–23.

Wang. L., P. Mathew, X. Pang. (2012). Uncertainties In Energy Consumption Introduced By Building Operations And Weather For A Medium-Size Office Building. Energy and Building. 53: 152 – 8.

W. Tian, W., P. de Wilde.(2011). Uncertainty and Sensitivity Analysis Of The Performance Of An Air-Conditioned Campus Building In The UK Under

Probabilistic Climate Projections. Automation and Construction. 20: 1096–1109.

Wang Shengwei, Yan Chengchu, Xiao Fu. (2012). Quantitative Energy Performance Assessment Methods For Existing Buildings. Energy and Building. 55:

- 88.

Wetter M, J. Wright. 2004. A Comparison Of Deterministic And Probabilistic Optimization Algorithms For Nonsmooth Simulation-Based Optimization. Building and Environment. 39: 989 - 99.

Wilson, K. (2008). Entrepreneurship and Higher Education. Entrepreneurship Education in Europe. European Foundation for Entrepreneurship Research. P1-9.

Zelenay, K., K. Perepelitza, and D. Lehrer, (2011). High-Performance Facades Design Strategies And Applications in North America and Northern Europe. California Energy Commission, Publication number: CEC-500-99-013

Downloads

Published

2016-12-22

How to Cite

Jaganathan, S., Mohammed, A. H., & Abdul Rahman, M. S. (2016). Descriptive Review of Energy Performance Evaluation Approaches. Sains Humanika, 8(4-3). https://doi.org/10.11113/sh.v8n4-3.1082