Design and optimization of a hydrogen integrated Water-Energy-Food nexus under uncertainty

Abstract

This paper presents a two-stage stochastic mixed-integer linear programming (MILP) model for the optimal design and operation of an integrated Power-to-X (P2X) facility within a Water–Energy–Food (WEF) nexus framework. The superstructure encompasses 19 candidate technologies and twelve commodity networks. First-stage decisions fix capacities; second-stage decisions optimize hourly dispatch across 1152 operating hours under renewable uncertainty. Applied to an undeveloped site in Türkiye, the model selects 13 technologies centered on steam methane reforming with 90% carbon capture, chosen for dispatchable flexibility rather than unit cost alone, plus Haber–Bosch synthesis, Sabatier methanation, and 94 MW of rated renewable capacity. The Value of the Stochastic Solution is $12.9M/yr (13.7%), showing that deterministic design underinvests in capacity and omits storage buffers critical for resilience. Downstream operational requirements propagate through the conversion chain, shifting upstream investment by up to 14%.