Economic and resilient planning of hydrogen-enriched power distribution network with mobile hydrogen energy resources - Wang, Tengbo; Dong, Yuchen; Cao, Xiaoyu; Xu, Zhanbo; Gao, Feng; Guan, Xiaohong (International journal of hydrogen energy, 2025)
This paper presents a risk-averse stochastic mixed-integer programming method to support the economic and resilient planning of hydrogen-enriched power distribution network with mobile hydrogen energy resources (MHERs). Our planning formulation holds a two-stage problem structure. The first-stage problem is to minimize the investment cost for optimally siting and configuring stationary distributed energy resources (DERs) and MHERs. In the second-stage, the operational feasibility of planning alternatives is verified subject to a finite support of stochastic scenarios. Besides of the economic assessment, an additional set of recourse problems based on contingency scenarios is involved to reflect the impact of extreme events (e.g., natural disasters or malicious attacks). To evaluate the risk-hedging capability of long-run system operation, a special objective function based on conditional value-at-risk (CVaR) is introduced. Moreover, various on-emergency corrective measures, e.g., energy storage dispatching, MHERs’ dynamic re-routing, and distribution feeders reconfiguration, are considered to enhance the system resilience. Case studies on a 33-bus test distribution network have validated the economic and resilience benefits of the proposed planning method. Through the proper configuration of stationary and mobile DERs, the load curtailment risks can be reduced by more than 75% given similar levels of system expenses. Besides, the inclusion of CVaR objective provides a flexible and quantitative measure for risk controls by tuning key model parameters. •Risk-averse two-stage stochastic programming model for power-hydrogen planning.•Coordination of stationary and mobile energy resources to improve cost efficiency.•Optimal configuration of mobile hydrogen energy resources for resilience enhancement.•CVaR objective to mitigate the load curtailment risks against extreme events.•Validation of economic and resilience benefits on exemplary distribution network.