Impact of grid partitioning algorithms on combined distributed AC optimal power flow and parallel dynamic power grid simulation. Issue 25 (9th December 2020)

• Record Type: Journal Article
• Authors: Kyesswa, Michael; Murray, Alexander; Schmurr, Philipp; Çakmak, Hüseyin; Kühnapfel, Uwe; Hagenmeyer, Veit
• Is Part Of: IET generation, transmission & distribution. Volume 14:Issue 25(2020)
• Page Start: 6133
• Page End: 6141
• Publication Date: 2020-12-09
• Subjects: Newton method -- optimisation -- load flow -- IEEE standards -- power grids -- graph theory -- pattern clustering -- parallel algorithms -- power system simulation -- computational complexity; optimal grid partitioning strategy -- spectral clustering -- power system problems -- computational performance -- partitioned OPF‐problem -- augmented Lagrangian based alternating direction inexact Newton method -- partitioned dynamic simulation problem -- partitioned systems -- parallel algorithm -- distributed algorithms -- AC OPF problem -- grid partitioning algorithms -- combined distributed AC optimal power flow -- parallel dynamic power grid simulation -- distributed computing -- power grid simulation algorithms -- power grid partitionings -- parallel computing -- graph theory -- Karlsruhe fast flow partitioner -- KaFFPa -- METIS -- IEEE standard benchmark test networks; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2020.1393
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : The complexity of most power grid simulation algorithms scales with the network size, which corresponds to the number of buses and branches in the grid. Parallel and distributed computing is one approach that can be used to achieve improved scalability. However, the efficiency of these algorithms requires an optimal grid partitioning strategy. To obtain the requisite power grid partitionings, the authors first apply several graph theory based partitioning algorithms, such as the Karlsruhe fast flow partitioner (KaFFPa), spectral clustering, and METIS. The goal of this study is an examination and evaluation of the impact of grid partitioning on power system problems. To this end, the computational performance of AC optimal power flow (OPF) and dynamic power grid simulation are tested. The partitioned OPF‐problem is solved using the augmented Lagrangian based alternating direction inexact Newton method, whose solution is the basis for the initialisation step in the partitioned dynamic simulation problem. The computational performance of the partitioned systems in the implemented parallel and distributed algorithms is tested using various IEEE standard benchmark test networks. KaFFPa not only outperforms other partitioning algorithms for the AC OPF problem, but also for dynamic power grid simulation with respect to computational speed and scalability.