Waste-to-energy technology selection: A multi-criteria optimisation approach

Abstract

Waste is the most abundant biomass worldwide for renewable energy and value-added products generation. While technologies for the treatment of multiple waste categories continue to evolve, frameworks that facilitate strategic decision-making within bio-economies are required. Therefore, the aim of this research is to develop a framework that can identify optimal processing route for converting different biomass wastes into valuable products. This study considers five different waste types available in Qatar, including date seed, camel manure, municipal solid waste (MSW), food waste, and sewage sludge. Whereas the investigated technologies include pyrolysis, gasification, and hydrothermal liquefaction (HTL). The three processes were simulated in Aspen Plus® and evaluated in terms of their technical, environmental, and economic performance for the different selected biomass feedstocks. A two-stage optimisation framework was then developed to identify the optimal processing technology for each biomass considering multiple products generation (i.e., syngas, biochar, and bio-oil). Investigating the waste to energy pathways, the presented model maximised net profit and energy generation while minimised the total associated emissions. The model indicated that gasification is the optimal processing technology to achieve higher economic return. While pyrolysis is recommended for the achievement of highest energy return. Nevertheless, HTL exhibited the best environmental performance with the lowest associated emissions. In addition, various wastes such as MSW and food waste are best processed by gasification to fulfil the environmental and economic criteria, while pyrolysis is more energy efficient in processing these wastes. Whereas HTL has been recommended only for high moisture containing biomass like manure and sludge, demonstrating relatively high energy efficiency, but lower economic return relative to gasification and pyrolysis. The presented optimisation framework may provide insights for decision-makers to optimally valorise waste considering national priorities.