  Hydrogen-electrical (HE) microgrids are increasingly assuming an important
role on the pathway toward decarbonization of energy and transportation
systems. This paper studies networked HE microgrids planning (NHEMP),
considering a critical but often-overlooked issue, i.e., the demand-inducing
effect (DIE) associated with infrastructure development decisions.
Specifically, higher refueling capacities will attract more refueling demand of
hydrogen-powered vehicles (HVs). To capture such interactions between
investment decisions and induced refueling demand, we introduce a
decision-dependent uncertainty (DDU) set and build a trilevel stochastic-robust
formulation. The upper-level determines optimal investment strategies for HE
microgrids, the lower-level optimizes the risk-aware operation schedules across
a series of stochastic scenarios, and, for each scenario, the middle-level
identifies the "worst" situation of refueling demand within an individual DDU
set to ensure economic feasibility. Then, an adaptive and exact decomposition
algorithm, based on Parametric Column-and-Constraint Generation (PC&CG), is
customized and developed to address the computational challenge and to
quantitatively analyze the impact of DIE. Case studies on an IEEE exemplary
system validate the effectiveness of the proposed NHEMP model and the PC&CG
algorithm. It is worth highlighting that DIE can make an important contribution
to the economic benefits of NHEMP, yet its significance will gradually decrease
when the main bottleneck transits to other system restrictions.
