High energy consumption is a major barrier to the efficient and environmentally sustainable management of water reuse facilities. This is exacerbated by fluctuating electricity prices and inefficient energy management. This study presents an integrated digital-physical twin framework to maximize the energy efficiency of water reuse processes. The digital twin models can forecast system dynamics and are used to infer optimal control actions, while the physical twin is used to evaluate the proposed control actions in real-world conditions. By leveraging time-of-use electricity pricing and dynamic process adjustments, the proposed framework achieved a 5% reduction in daily electricity costs without compromising system performance. Additionally, it enhances resilience by simulating and mitigating the impact of extreme events such as power disruptions. These findings demonstrate the potential of digital-physical twin integration in improving energy efficiency and sustainability in water reuse systems.