A decision support system for sustainable energy supply combining multi-objective and multi-attribute analysis: An Australian case study

• A DSS for sustainable technologies’ design and selection is presented in the paper.
• LCI and impact assessment have been used for initial problem definition.
• Both multi-objective's and multi-attribute's methods are used for CHP plant design and selection.
• DSS is applied to a case study in Kwinana Industrial Area (Perth, Western Australia).

A framework for an energy supply decision support system (DSS) for sustainable plant design and production is presented in this paper, utilising an innovative use of multi-objective and multi-attribute decision-making (MODM, MADM) modelling together with impact assessment (IA) of the emission outputs. The mathematical model has been applied within an eco-industrial park (EIP) setting and includes three steps. First, an assessment of the total EIP emissions' inventory and impacts is conducted; the second step, focusing on the sustainability benefits of combined heating and power (CHP) plants and photovoltaic technologies, developed a multi-objective mathematical model including both economic and environmental objectives in a Pareto-frontier optimisation analysis. Four different scenarios involving combinations of CHP plants (internal combustion engine, gas turbine, micro-turbines and fuel cells) and two types of PV plant (monocrystalline and polycrystalline) were evaluated. The third step utilises a MADM methodology – the analytic hierarchy process (AHP) – for selecting the best alternative among the Pareto-frontier efficient solutions. This model has been applied to a case study of an EIP located in Perth (Kwinana Industrial Area—KIA), Western Australia.