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Stochastic Power System Dynamic Simulation Using Parallel-in-Time Algorithm
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DOI：10.1109/ACCESS.2024.3367358.png)
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摘要
En 中文
With increasing grid modernization efforts, future electric grids will be governed by more complex and faster dynamics with the high penetration of new components such as power electronic-based control devices and large renewable resources. These lead to the importance of developing real-time dynamic security assessment under the consideration of uncertainties, whose main tool is time-domain simulation. Though there are many efforts to improve the computational performance of time-domain simulation, its focus has been on the deterministic differential-algebraic equations (DAEs) without modeling uncertainties inherent in power system networks. To this end, this paper investigates large-scale time-domain simulation including effects of stochastic perturbations and ways for its computational enhancement. Particularly, it utilizes the parallel-in-time (Parareal) algorithm, which has shown great potentials, to solve stochastic DAEs (SDAEs) efficiently. A general procedure to compute the numerical solution of SDAEs with the Parareal algorithm is described. Numerical case studies with 10-generator 39-bus system and 327-generator 2383-bus system are performed to demonstrate its feasibility and efficiency. We also discuss the feasibility of employing semi-analytical solution methods, using the Adomian decomposition method, to solve SDAEs. The proposed simulation framework provides a general solution scheme and has the potential for fast and large-scale stochastic power system dynamic simulations.
Keyword:
Stochastic processes
Power system dynamics
Load modeling
Perturbation methods
Time-domain analysis
Uncertainty
Behavioral sciences
Brownian motion
Parallel processing
Differential equations
parallel algorithms
power system dynamics
semi-analytical solution
stochastic differential algebraic equations
time domain simulation
期刊
IF:
3.6
论文数:
9.8W
被引数:
34.1W
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引用论文
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