Dynamic energy performance assessment using a digital shadow for sludge incineration in wastewater treatment plants

Abstract

Abstract The rapid growth of the global economy and rising energy costs have underscored the need for efficient energy utilization across various sectors. To address this, we developed a novel data-informed digital shadow framework, enhancing energy management within a closed-loop control system, particularly in wastewater treatment facilities. Our approach centers on reducing biogas consumption in the fluidized bed reactor, a crucial component of the incineration process. The digital shadow simulates the entire incineration section by extracting model parameters for key components, including the furnace, dryer, mixer, and heat exchangers, from both physical models and operational data. System-level simulation was performed in AnyLogic software, integrating analytical calculations with data from positioning sensors. The model was informed by operational plant data and validated against historical system data. Evaluation of five operating scenarios demonstrated the capability of the digital shadow to capture system behavior and support operational decision-making. The evaluation of dynamic energy performance identified the most effective scenario, achieving a 40% reduction in biogas consumption while maintaining furnace operation within the temperature range specified by European standards. These findings demonstrate the effectiveness of the digital shadow approach and highlight its potential to deliver substantial annual cost savings in wastewater sludge incineration systems.