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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.
Pillay et al. (Tue,) studied this question.