Framework for a Simulation Learning Tool to Optimize Green Star Buildings in South Africa

Author:

Pillay Theogan Logan1,Saha Akshay Kumar1ORCID

Affiliation:

1. Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, South Africa

Abstract

The Green Building Council of South Africa specifies nine parameters for energy efficiency in buildings. These parameters are in dynamic systemic interaction with each other and with other building design elements. Therefore, the issue of optimization in terms of the Green Star rating system is a complex problem that defies complete resolution and sustainability. Partial resolution, using algorithmic optimization convergence and simulation techniques, holds potential. The specific problem that this paper confronts is the need for engineers, and others, to be able to assess energy-efficient early design decisions within tight time frames. A proposition is made regarding further developing a “green” simulation learning tool for practitioners. This paper explores the potential of MATLAB and EnergyPlus to create a simulated learning space for green energy optimization. While recognized as being an abstraction from the total set of nine Green Building Council of South Africa parameters, the purpose is to introduce principles that can be extended into a multi-variable, more complex context of multiple sustainability criteria. This paper concludes with a framework for a simulation model that optimizes one of the Green Star criteria of the Green Building Council of South Africa supported by case study data for four, five, and six star rated buildings.

Publisher

MDPI AG

Reference43 articles.

1. WGB Council (2023, September 21). World Green Building Council. Available online: www.worldgbc.org/africa/.

2. Machine learning model for green building design prediction;Sari;IAES Int. J. Artif. Intell. (IJ-AI),2022

3. GBPN (2023, July 25). Buildings for Our Future, “The Deep Path for Closing the Emissions Gap in the Building Sector”. Green Buildings Performance Network. Available online: www.gbpn.org/reports.

4. UNEP (2023, August 12). Towards a Green Economy: Pathways to Sustainable Development and Poverty Eradication. Chapter 9, Buildings: Investing in Energy and Resource Efficiency. United Nations Environment Programme, Sustainable Building and Climate Initiative. Available online: www.unep.org/greeneconomy.

5. Elbeltagi, E., Wefki, H., and Khallaf, R. (2022). Sustainable Building Optimization Model for Early-Stage Design. Buildings, 13.

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