Optimal configuration of grid-side energy storage considering static security of power system

Abstract

The large-scale access of distributed sources to the grid has brought great challenges to the safe and stable operation of the grid. At the same time, energy storage equipment is of great importance to effectively enhance the consumption of renewable energy and ensure the safe and stable operation of the grid. This paper proposes a method for optimal allocation of grid-side energy storage considering static security, which is based on stochastic power flow analysis under semi-invariant method. Firstly,according to the load, wind power and photovoltaic probability model, a system stochastic power flow model is constructed. Furthermore, the fault probability and fault severity indicators are established from two dimensions of branch power flow and node voltage. And combine the fault probability and severity indicators to establish a static security assessment indicators system. Then, a grid-side energy storage planning model is constructed from the perspective of energy storage operators. Finally, an improved genetic algorithm is used to solve the two-stage planning and operation problem proposed in this paper, and simulation analysis is conducted based on the IEEE-30 node system. The results show that the energy storage configuration considering static security constraints can effectively reduce the fault probability and the severity of fault overlimit. The simulation and case study verify that the proposed energy storage allocation method can effectively improve the static security of the system.

Transient angle stability analysis of maximum Lyapunov exponent based on the key branch response information

“…Based on the measurement information provided by wide area measurement system (WAMS) (Qin et al, 2008), the mode of "realtime decision-making, real-time control" can accurately and efficiently identify the system stability, effectively reduce the chain reaction caused by large disturbances, and have important significance for the safe and stable operation of the power grid (Liu et al, 2013;Tang, 2014;Lin et al, 2016). The research methods based on the network response information include transient energy function method, phase trajectory characteristic analysis method, artificial intelligence method (Tian and Zhao, 2023) and so on. Among them, the Maximum Lyapunov Exponential analysis method based on chaos theory has become research hotspot (Ravikumar and Khaparde, 2018).…”