Energy-Optimal Siting of Decentralized Water Recycling Systems.

Decentralized water recycling systems (DWRS) have emerged as a viable option for incrementally augmenting water supply in water-stressed regions, but DWRS are generally more energy-intensive than traditional centralized water treatment systems. When DWRS are deployed incrementally in small batches, the marginal energy intensity (MEI) of water supply quantifies the location-specific energy footprint of centralized water supply and serves as a robust metric measuring the energy implications of replacing centralized supply with DWRS supply. This research develops and applies a MEI-based decision framework that identifies the energy-optimal siting of DWRS to minimize the overall system operational energy consumption given a target fraction of water demand to be met by newly deployed DWRS. In a small benchmark water supply system where the energy intensity of the intended DWRS is 5.3% higher than the current system average energy intensity of centralized supply, we demonstrate that the optimal siting of DWRS to offset 10% of the system-wide water demand reduces the overall system energy consumption by 0.77%. In contrast, the naive and worst-case siting of the same DWRS increases the energy consumption of the overall system by 0.65 and 2.0%, respectively. The proposed MEI-based decision framework is particularly valuable for application in large multi-source systems, where an optimization-based approach is computationally intractable. This study highlights the importance of accounting for both distribution and treatment energy intensity when evaluating new water sources and demonstrates the viability of DWRS as an energy-efficient tool for augmenting water supply.