Energy Flexibility in Large Water Resource Recovery Facilities

The thesis addresses the main research topic, ’energy integration within large-scale water resource recovery facilities (WRRFs)’ in three sub-sections of works. The first work investigates integrating peak demand mitigation and future energy pricing structures in process modelling for conventional Water Resource Recovery Facilities (WRRFs). Using the Benchmark Simulation Model (BSM2), it analyzes energy usage and explores flexible control opportunities across flow streams. Reject water scheduling strategies, without additional controls like aeration, achieved 63.4% average peak demand reduction and €10,755 annual energy cost savings for a 100k population equivalent WRRF, maintaining effluent quality. The study emphasises the effectiveness of reject water scheduling in optimizing energy costs under varying electricity tariffs, highlighting its role in mitigating electricity peak demands. This second one introduces a dynamic energy dispatch optimization framework for WRRFs, crucial for their complex energy conversion and recovery processes. Assessing biogas, electricity, and heat potentials across major Irish WRRFs, it uses mixed-integer programming (MIP) to simulate national electricity systems under eight scenarios for 2030. Results show potential €46.35M cost savings, primarily from biogas cogeneration and thermal energy recovery. The framework also reduces carbon emissions, fossil fuel use, startup costs, and external dependency. It suggests WRRFs can enhance energy system sustainability by dynamically dispatching recovered energy, meeting significant power and heat demands during peak periods. This last one addresses challenges faced by WRRFs regarding increasing wastewater loads and regulatory demands. It proposes a demand response strategy through influent load shifting using the BSM2 framework, enhanced with phosphorus precipitation and struvite recovery. Implementing night-time flow equalization shows potential to reduce influent peaks by 16% and improve effluent quality. Results project a 4% reduction in total power demand, 0.5-0.8% enhancement in energy self-sufficiency, and 2% total energy consumption savings. This approach offers a systematic method to optimize WRRF utility capacity, treatment performance, and energy efficiency, crucial for future wastewater management strategies.