Resilience-oriented planning for the optimal sizing and pre-positioning of mobile power sources in distribution networks with multiple energy hubs

High-impact, low-probability (HILP) events are arising more frequently than ever before and pose a great challenge to power system resilience. Mobile power sources (MPSs) have been gradually deployed in distribution networks as critical resources towards resilience enhancement owing to their flexibility and mobility in handling the complex coupled power network environment. In addition, as localised energy systems, energy hubs (EHs) have been widely integrated into distribution networks for the effective coordination of various small-size energy sources, which can be used to support resilience enhancement given their advanced control capabilities. Therefore, this paper develops a resilience-oriented planning framework for the optimal sizing and pre-positioning of various MPSs in the power distribution network with multiple EHs. In the planning stage, the optimal sizing of MPSs, including the power capacities of mobile energy storage system (MESS) and mobile emergency generator (MEG) as well as the number of deployed electric vehicles (EVs), is determined for the after-event dispatch. In addition, the pre-positioning of MPSs is implemented, considering possible line outage scenarios. In the post-event stage, coordinated operations of MPSs and EHs are performed towards resilience enhancement. Particularly, routing and scheduling behaviours of each individual MPS are modelled in detail to fully exploit their mobility and flexibility, capturing uncertainty in traffic conditions. Furthermore, a hybrid stochastic-information gap decision theory (IGDT) approach is implemented to handle the uncertainties in line outage, renewable generation, network electricity load and EH electricity and heat loads. Case studies are first carried out based on a modified IEEE 15-bus test system, considering different outage scenarios and risk management strategies. Results demonstrate that the proposed framework achieves system resilience index of 90.43 %, 88.86 % and 92.30 % under the risk-neutral, risk-averse and risk-seeking strategies, respectively. Compared with the case without MPSs and EHs, the proposed method reduces the system cost from £ 668,889.32 to £ 176,138.70 and improves the resilience index from 55.74 % to 90.43 % under the risk-neutral strategy. Furthermore, additional tests on the IEEE 33-bus system validate the effectiveness of the proposed framework for resilience enhancement in larger-scale networks.