Optimal Processing Pathway for Sludge-to-Energy Technologies: A Superstructure Optimization-Based MINLP Model

Abstract

The perception of sewage sludge has been increasingly changing from being a waste, that is a burden to the environment and society, to a useful resource of materials and renewable energy. There are several available technologies at different stages of maturity that aim to convert sludge to energy in the form of electricity and/or fuels. In this study, a decision-making support tool is proposed to help in choosing the optimal pathway for the sludge-to-energy conversion from a techno-economic perspective. The conversion technologies under study are anaerobic digestion, pyrolysis, gasification, incineration, supercritical water oxidation, supercritical water gasification as well as the corresponding dewatering and drying methods for each technology. Different synergies between the available technologies are compared by the formulation of a superstructure optimization problem expressed in a mixed-integer non-linear program (MINLP) model. The applicability of the proposed model is explored via a case study for a hypothetical sludge treatment plant with a capacity of 100 tonnes of dry solids (tDS) per day. The model was solved via BARON solver using GAMS software within a reasonable CPU time of 70 seconds. The case study results show that fast pyrolysis technology, coupled with filter press dewatering and thermal drying as pretreatment steps, show the most promising results with the minimum treatment cost of $180/tDS. Fast pyrolysis converts the sludge to bio-oil that can be used as an alternative fuel after further refining and biochar which can be used for soil amendment or adsorption purposes. The model parameters are subject to uncertainty that was addressed in the sensitivity analysis section of the study. The pyrolysis pathway showed a high degree of robustness in most of the sensitivity scenarios. Anaerobic digestion coupled with fast pyrolysis was chosen as the best energy recovery alternative upon increasing electricity prices. The optimization model proposed in this study can be used as an early screening tool for decision-makers to assess different sludge-to-energy pathways. It can be further extended to account for different feedstocks (co-processing) and to account for environmental constraints (CO2 emissions).