‘Hot topic’ – combined energy and process modeling in thermal hydrolysis systems

Abstract

The thermal hydrolysis process (THP) is applied to enhance biogas production in anaerobic digestion (AD), reduce viscosity for improved mixing and dewatering and to reduce and sterilize cake solids. Large heat demands for steam production rely on dynamic effects like sludge throughput, gas availability and THP process parameters. Here, we propose a combined energy and process model suitable to describe the dynamic behaviour of THP in a full-plant context. The process model addresses interactions of THP with operational conditions covered by the AD model obeying mass continuity. Energy conservation is considered in balancing and converting various energy species dominated by thermal heat and calorific energy. The combined energy and process model was then applied on the THP at Blue Plains advanced WWTP (DC Water) to analyse the process and assess potential energy optimizations. It was found that dynamic effects like mismatched steam production and consumption, temporary gas shortages and underloaded units are responsible for energy inefficiencies with losses in electricity-production up to 29%.

A Comprehensive Review on Pretreatment Methods for Enhanced Biogas Production from Sewage Sludge

“…However, this can be offset by producing high-quality biogas and incorporating a Combined Heat and Power (CHP) system. As a result, the heat recovered from the CHP units cooling systems and exhaust gases, cover all the heating needs, and thus, reducing the overall cost of thermal pretreatment application [14,136].…”

A Control Algorithm for the Optimization of Batch Reactor-Based Processes

“…Mathematical modeling is the product of the combination of mathematical theory and practical application, which realizes the mutual transformation between real problems and mathematical problems. This transformation describes practical problems from the perspective of qualitative or quantitative analysis, and provides accurate data and reliable information guidance for practical problems [Aichinger, DeBarbadillo, Al-Omari et al (2019)]. Nowadays, there are many mathematical models, such as static model and dynamic model, distributed parameter model and centralized parameter model, continuous time model and discrete time model, stochastic model and deterministic model, etc.…”