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,accordin… Show more
“…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).…”
Based on real-time access to response information on wide-area tributaries, in order to assess the system stability more quickly, this paper combines the simplified branch transient transmission capability (sBTTC) index and the largest Lyapunov exponent (MLE). An online identification method for transient power angle stability is proposed. Firstly, the method is based on a two-machine system to study the consistency of the power angle difference between the two ends of the critical branch and the change of the phase difference of the fleet. Secondly, the transient power angle stability problem is transformed into the MLE analysis problem according to the change rule of sBTTC index of the key branch. Then, by combining the characteristics of MLE curve and sBTTC index curve, the transient power angle stability criterion is given. Finally, the proposed method is verified and analysed by simulation examples. The method has strong industrial applicability because it does not need system model, the information source is easy to measure, it has strong anti-noise ability, and it overcomes the defect of the traditional method that needs to set a fixed symbolic observation window.
“…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).…”
Based on real-time access to response information on wide-area tributaries, in order to assess the system stability more quickly, this paper combines the simplified branch transient transmission capability (sBTTC) index and the largest Lyapunov exponent (MLE). An online identification method for transient power angle stability is proposed. Firstly, the method is based on a two-machine system to study the consistency of the power angle difference between the two ends of the critical branch and the change of the phase difference of the fleet. Secondly, the transient power angle stability problem is transformed into the MLE analysis problem according to the change rule of sBTTC index of the key branch. Then, by combining the characteristics of MLE curve and sBTTC index curve, the transient power angle stability criterion is given. Finally, the proposed method is verified and analysed by simulation examples. The method has strong industrial applicability because it does not need system model, the information source is easy to measure, it has strong anti-noise ability, and it overcomes the defect of the traditional method that needs to set a fixed symbolic observation window.
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