Stochastic Power System Dynamic Simulation Using Parallel-in-Time Algorithmopen access
- Authors
- Park, Byungkwon
- Issue Date
- Feb-2024
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- 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
- Citation
- IEEE ACCESS, v.12, pp 28500 - 28510
- Pages
- 11
- Journal Title
- IEEE ACCESS
- Volume
- 12
- Start Page
- 28500
- End Page
- 28510
- URI
- https://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/49261
- DOI
- 10.1109/ACCESS.2024.3367358
- ISSN
- 2169-3536
- Abstract
- 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.
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