Data-driven Power Flow Linearization: Simulation

TL;DR

This paper describes a pair of CAS LaTeX class files, cas-sc.cls and cas-dc.cls, which enable single- and two-column formatting for manuscripts intended for Elsevier submissions, with accompanying templates. It clarifies integration with Elsevier's updated workflow and supports robust front matter management, including author metadata, affiliation handling, and marks for corresponding authors. Practical usage guidance covers mode-driven title pages, long front matter, and the organization of abstract, keywords, and theorem-like environments. The work aims to simplify manuscript preparation, improve formatting consistency across submission channels, and provide a practical resource for authors preparing compliant, publication-ready articles.

Abstract

Building on the theoretical insights of Part I, this paper, as the second part of the tutorial, dives deeper into data-driven power flow linearization (DPFL), focusing on comprehensive numerical testing. The necessity of these simulations stems from the theoretical analysis's inherent limitations, particularly the challenge of identifying the differences in real-world performance among DPFL methods with overlapping theoretical capabilities and/or limitations. The absence of a comprehensive numerical comparison of DPFL approaches in the literature also motivates this paper, especially given the fact that over 95% of existing DPFL studies have not provided any open-source codes. To bridge the gap, this paper first reviews existing DPFL experiments, examining the adopted test scenarios, load fluctuation settings, data sources, considerations for data noise/outliers, and the comparison made so far. Subsequently, this paper evaluates a total of 44 methods, containing over 30 existing DPFL approaches, some innovative DPFL techniques, and several classic physics-driven power flow linearization methods for benchmarking. The evaluation spans various dimensions, including generalizability, applicability, accuracy, and computational efficiency, using various different test cases scaling from 9-bus to 1354-bus systems. The numerical analysis identifies and examines significant trends and consistent findings across all methods under various test cases. It also offers theoretical insights into phenomena like under-performance, failure, excessive computation times, etc. Overall, this paper identifies the differences in the performances of the wide range of DPFL methods, reveals gaps not evident from theoretical discussions, assists in method selection for real-world applications, and provides thorough discussions on open questions within DPFL research, indicating ten potential future directions.