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Abstract This study introduces a strategy for the pre‐allocation and dispatch of mobile power sources (MPSs) within a power‐transportation coupled network, targeting efficient distribution network fault recovery under extreme weather conditions. The strategy incorporates the Dijkstra algorithm and blind number theory to analyse the MPS driving path and generate fault scenarios respectively, considering the effects of extreme weather on traffic capacity and distribution network fault rate. The MPS pre‐allocation model, formulated to minimize the load outage loss, MPS investment, and driving fuel cost, provides a foundation for optimization of the dispatch process. The dispatch optimization model adapts to dynamic information from the power‐transportation coupled network to make decisions on load restoration sequencing and MPS driving path. The effectiveness of the proposed strategy is demonstrated through an application to the IEEE 33‐node distribution system and a corresponding 33‐node transportation network.

Abstract With large‐scale wind farms connected to AC/DC network, the transient stability assessment (TSA) of the power system becomes more and more difficult. Among them, estimating the region of attraction (ROA) of the equilibrium point is a traditional but still challenging problem. Based on the Lyapunov stability theory, this paper proposes a new approach to obtain the enlarged estimation of the ROA. The optimization and updating strategy of shape function in the sum of squares (SOS) optimization problem are studied to reduce the conservatism of estimation result. In the proposed method, the gravitational search algorithm (GSA) is employed to optimize the coefficients of initial shape function to improve estimation performance. Based on the time‐domain simulation (TDS) of expected faults, the fitness value for shape function optimization is calculated using the values of state variables at the fault clearing time and the system stability information. Furthermore, the optimal Lyapunov function is computed by introducing the update condition of shape function and adjusting the iteration strategy of the ROA estimation algorithm. Finally, the proposed method is applied to a two‐machine‐infinite‐bus system and a more complex nine‐bus AC/DC system with wind power. And the effectiveness of the proposed method is verified by comparing with the existing ROA estimation methods.

With the interconnection of large power networks, transient voltage stability of AC/DC power systems has been paid more attention in recent years. To investigate main influence of generating facility, high-voltage direct current (HVDC) and motor load for transient voltage stability, from the perspective of the generalised branch potential energy, the new indexes, and analysis method is proposed here. First, an energy function for AC/DC system is constructed with major dynamic components, namely classical HVDC control systems and motors in third-order model. Accordingly, the influence effects of the above major dynamic elements are investigated based on indexes from the corresponding generalised branch potential energy. With the rule of change in transient potential energy distribution in the network and information in stability margins, an evaluating procedure is established. Here, the judgment of transient voltage stability employs a heuristic energy function method. Finally, simulation tests on three-machine system with a HVDC transmission line are conducted in PSAT package, and the obtained results demonstrate the feasibility and effectiveness of the proposed method.