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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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Abstract
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.
Keywords:
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
Journal
IF:
3.6
Papers:
9.8W
Citations:
34.2W
Organization
Cited Papers
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