DPLib: A Standard Benchmark Library for Distributed Power System Analysis and Optimization

TL;DR

DPLib is an open-source MATLAB library providing standardized benchmark test cases, a graph-based partitioning toolkit, and distributed optimal power flow solvers to advance research in distributed power system analysis and optimization.

Contribution

It introduces a comprehensive, reproducible benchmark library with partitioning tools and distributed solvers, filling a gap in distributed power system research resources.

Findings

Provides over 20 multi-region test cases.

Includes a graph-based partitioning toolkit.

Validates test cases with distributed OPF solvers.

Abstract

\textit{DPLib} is an open-source MATLAB-based benchmark library created to support research and development in distributed and decentralized power system analysis and optimization. Distributed and decentralized methods offer scalability, privacy preservation, and resilience to single points of failure, making them increasingly important for modern power systems. However, unlike centralized tools such as MATPOWER, no general-purpose, reproducible data library package currently exists for distributed power system studies. DPLib, available at \href{https://github.com/LSU-RAISE-LAB/DPLib.git}{GitHub}, fills this gap by providing a standard power system library featuring over 20 multi-region benchmark test cases of varying sizes, along with a graph-based partitioning toolkit that decomposes any MATPOWER test system into multiple electrically coherent regions. The partitioning toolkit, an easy-to-use MATLAB code, generates standardized \texttt{.mat} and \texttt{.m} files, along with region visualizations for intuitive understanding. We also provide modular, easy-to-use distributed optimal power flow (OPF) solvers: an alternating direction method of multipliers(ADMM)-based DC-OPF solver implemented in YALMIP, and an ADMM-based AC-OPF solver leveraging IPOPT. These solvers validate the generated test systems for distributed optimization applications. Numerical results validate the generated test cases, establishing DPLib as a foundation for reproducible distributed power system research.