Biogas from anaerobic digestion (AD) of organic waste is a promising renewable energy resource, which can be burned to produce heat and electricity. Research on AD systems has had a tendency to focus on optimising digester operational parameters that maximise biogas yields. However, there are several other components in an AD system which affect overall technical, financial and environmental performances and need wider consideration in AD optimisation studies.This thesis explores the use of multi-objective optimisation of food waste and wastewater AD systems when there are conflicting objectives. A case study approach is taken to evaluate different AD systems and genetic algorithms (GA), in Python, is used to solve the optimisation problems. Three case studies systems are defined: (1) food waste, (2) conventional wastewater and (3) thermally hydrolysed wastewater. Measured data from these systems isused to evaluate the performance of AD models, specifically modified Gompertz, Anaerobic Digestion Model No. 1 (ADM1) and ADM1 coupled with the Transformer Tool. Quantitative data is used to provide information on key system parameters and operating conditions. This is then coupled with qualitative data to better understand the systems and formulate the optimisation problems. From testing different AD models, it is found that the modified Gompertz model performs well when substrate feeding rates and digester operational conditions are consistent. When digester conditions vary with time, ADM1 is better suited and its performance can be further enhanced by coupling it with the Transformer tool. Results from optimisation of the food waste case study show that, when the substrate feeding rate isoptimised, the amount of biogas flared can be reduced by almost 90%. Optimisation of thewastewater case studies highlight the need to optimise parameters other than the biogas yield, especially for newer generation of AD systems, as these systems have multiple components and downstream pathways which affect profit and GHG emissions. For example, when the TH pre-treated wastewater case study is maximised for just biogas yield, it is observed that the profit reduced by 20.3%.This thesis establishes that a large gap still remains between ideal and in-situ performance of AD systems and better optimisation is required to ensure wider deployment of these systems. The research conducted in this project is one of only a few studies that investigates optimisation of AD systems for objective functions other than biogas yield and includes a dynamic digester model to factor varying substrate conditions. The optimisation frameworkhas been demonstrated for improving performance of existing AD systems and can be expanded to assist in design of new systems
Multi-Objective Optimisation of Anaerobic Digestion Systems
Ashraf, R. J. (Author). Jun 2024
Student thesis: Doctoral Thesis › Doctor of Philosophy