Multi-criteria prioritization of the renewable power plants in Australia using the fuzzy logic in decision-making method (FMCDM)

Abstract

Abstract The presented study focused on developing an innovative decision-making framework to select the best renewable-power-plant technologies, considering comprehensive techno-economic and environmental variables. Due to the favourable conditions, Australia was selected as the case study. A fuzzy-logic method and analytical hierarchy process were applied to prioritize different renewable-energy power plants. The techno-economic factors included levelized cost of energy, initial cost, simple payback time, and operation and maintenance costs along with environmental factors including carbon payback time, energy payback time and greenhouse-gas emissions were used to rank the power plants. The results showed that the capital cost and simple payback time had the highest priority from an economic point of view. In comparison, greenhouse-gas emissions and carbon payback time were the dominant environmental factors. The analysis results provided economic and environmental priority tables for developing different power plants in the current state and a future scenario by 2030. The fuzzy results and pairwise composite matrix of alternatives indicated that the onshore wind, offshore wind, single-axis tracker polycrystalline photovoltaic, single-axis tracker monocrystalline photovoltaic, fix-tilted polycrystalline photovoltaic and fix-tilted monocrystalline photovoltaic scored the highest in the current state. In contrast, by 2030, the single-axis tracker photovoltaic power plants will be the best choice in the future scenario in Australia. Finally, the results were used and analysed to recommend and suggest several policy implementations and future research studies.