New energy storage methods based on electrochemistry can not only participate in peak shaving of the power grid but also provide inertia and emergency power support. It is necessary to analyze the planning problem of energy storage from multiple application scenarios, such as peak shaving and emergency frequency regulation. This article proposes an energy storage capacity configuration planning method that considers both peak shaving and emergency frequency regulation scenarios. A frequency response model based on emergency frequency regulation combined with low-frequency load shedding is established, taking into account the frequency safety constraints of the system and the principle of idle time reuse, to establish a bi-level programming model. In the upper-level model, the optimization objective is to minimize the annual operating cost of the system during the planning period, combined with the constraints of power grid operation to plan the energy storage capacity. The lower-level model embeds frequency safety constraints with the optimization objective of minimizing the cost of fault losses. To solve the bi-level optimization problem, the Karush–Kuhn–Tucher (KKT) condition and Big-M method were used to transform the bi-level model into a single-layer linear model. Finally, an improved IEEE RTS-24 system was used for numerical verification. The results show that the method proposed in this article can reasonably plan the capacity of energy storage, improve frequency safety during system operation, and reduce the operating cost of the power grid.

The secure operation of the renewable-integrated power system is affected by extreme weather conditions such as typhoons. In order to meet the operational requirements of the system, it is necessary to dynamically evaluate the resilience of the renewable-integrated power systems based on meteorological forecast information to guide operators to make reasonable risk prevention and control decisions. A rapid assessment method for power system resilience is proposed to address the uncertainty of extreme weather caused by typhoons. First, with a focus on the impact of typhoon disasters on power system components, corresponding failure probability models are constructed by taking typhoon meteorological forecast information as input and considering the uncertainty of typhoon meteorological forecast. Error probability circles and average absolute errors of intensity forecasts are included in the sampling of typhoon scenarios. Second, for the resilience assessment process, the impact increment method is used to reduce the dimensionality of multiple fault state analysis in the power system, and resilience indexes are calculated by screening the contingency set based on depth-first traversal through a backtracking algorithm. The weak links in the power system are identified through sensitivity analysis of load loss. Finally, the effectiveness of the proposed method is verified using the modified IEEE RTS-79 power system.