Research Specifications

Today’s societies need a sustainable supply of energy more than ever, whereas unseen events challenge the electric power supply. The coordinated operation of a power-gas-transportation system can decrease the effects of such faults in the distribution level. This paper proposes a model predictive control approach for dynamic load restoration in an integrated energy system. The coordination of electric and gas networks besides the mobile energy storage (MES) units provides a novel resilient alternative to serve active and reactive loads. First, the location and time of drastic events are identified as the initialization phase in this paper using a vulnerability analysis by a master–slave problem to find the weak points of the electric grid. Then, a rolling horizon model predictive control-based approach is proposed to make corrective decisions to serve loads. Meanwhile, a new linearization approach for the Weymouth equation has been proposed based on the binary expansion method. The proposed linear resiliency-oriented scheduling problem is tested on IEEE 33-bus and IEEE 69-bus integrated with a seven-node gas distribution grid and a six-station transportation railway. The analysis revealed that the coordination between electric and gas resources minimizes the not-supplied load; MES units act as certain emergency tools to serve the critical loads.