Performance and Feature Improvements in Parareal-based Power System Dynamic Simulation

In recent years, a novel Parareal-based approach has been developed for fast transient simulations of large power system interconnections. Parareal belongs to the class of Parallel-in-time algorithms for solution of systems of differential-algebraic equations in parallel over an interval of time. The selection of a reasonably fast and accurate coarse solution is crucial to improve the performance of Parareal algorithm. Semi-analytical solution methods are one promising approach to achieve this goal. They have been investigated, and some preliminary results are presented here. In addition, Parareal-based simulator has been expanded to enable co-simulation with OpenDSS, a widely used open-source distribution system simulator. Preserving the parallel nature of the Parareal approach and taking advantage of the parallel capabilities of the latest versions of OpenDSS, each distribution system can be solved in their entirety on different processors in parallel within the main Parareal simulator. This paper also presents the structure of the transmission and distribution co-simulation and some results with different dynamic models of inverter-based resources in the distribution systems.

[1]  C. Gellings Electric power research institute. , 1983, Environmental science & technology.

[2]  Shijun Liao,et al.  Homotopy Analysis Method in Nonlinear Differential Equations , 2012 .

[3]  Alexander J. Flueck High-fidelity, faster than real-time dynamics simulation , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[4]  Kai Sun,et al.  Application of the adomian decomposition method for semi-analytic solutions of power system differential algebraic equations , 2015, 2015 IEEE Eindhoven PowerTech.

[5]  Michael Starke,et al.  Parareal in Time for Fast Power System Dynamic Simulations , 2016, IEEE Transactions on Power Systems.

[6]  Bin Wang,et al.  Fast power system simulation using semi-analytical solutions based on Pade approximants , 2017, 2017 IEEE Power & Energy Society General Meeting.

[7]  Kai Sun,et al.  Power System Simulation Using the Multistage Adomian Decomposition Method , 2017, IEEE Transactions on Power Systems.

[8]  Kai Sun,et al.  Power system simulation using the multi-stage adomian decomposition method , 2017, 2017 IEEE Power & Energy Society General Meeting.

[9]  Eric Abreut,et al.  Semi-analytical fault-on trajectory simulation and its application in direct methods , 2017, 2017 IEEE Power & Energy Society General Meeting.

[10]  Kai Sun,et al.  Fast Power System Dynamic Simulation Using Continued Fractions , 2018, IEEE Access.

[11]  Xin Yin,et al.  Fault Analysis of Inverter-Interfaced Distributed Generators With Different Control Schemes , 2018, IEEE Transactions on Power Delivery.

[12]  Rui Yao,et al.  Vectorized Efficient Computation of Padé Approximation for Semi-Analytical Simulation of Large-Scale Power Systems , 2019, IEEE Transactions on Power Systems.

[13]  Yang Liu,et al.  Power System Time Domain Simulation Using a Differential Transformation Method , 2019, IEEE Transactions on Power Systems.

[14]  Snehashish Chakraverty,et al.  Advanced Numerical and Semi‐Analytical Methods for Differential Equations , 2019 .

[15]  Gurunath Gurrala,et al.  Application of Multi-Stage Homotopy Analysis Method for Power System Dynamic Simulations , 2019, IEEE Transactions on Power Systems.

[16]  Bin Wang,et al.  A Time–Power Series-Based Semi-Analytical Approach for Power System Simulation , 2018, IEEE Transactions on Power Systems.

[17]  P.K. Sen,et al.  Iteratively-Coupled Co-simulation Framework for Unbalanced Transmission-Distribution System , 2019, 2019 IEEE Milan PowerTech.

[18]  Yang Liu,et al.  Solving Power System Differential Algebraic Equations Using Differential Transformation , 2019, IEEE Transactions on Power Systems.

[19]  Feng Qiu,et al.  Efficient and Robust Dynamic Simulation of Power Systems With Holomorphic Embedding , 2020, IEEE Transactions on Power Systems.