A General Formulation for Evaluating the Performance of Linear Power Flow Models

TL;DR

This paper introduces a comprehensive framework for evaluating and comparing linear power flow models, addressing key questions about their performance bounds, applicability, and optimality in power system analysis.

Contribution

It proposes a general formulation for assessing LPF models, defining their valid range, and analytically identifying the best model, enhancing understanding and selection of LPF methods.

Findings

The proposed framework effectively evaluates LPF model performance.

Case studies demonstrate the superiority of the proposed LPF model.

The framework clarifies factors influencing LPF model accuracy.

Abstract

Linear power flow (LPF) models are essential in power system analysis. Various LPF models are proposed, but some crucial questions are still remained: what is the performance bound (e.g., the error bound) of LPF models, how to know a branch is applicable for LPF models or not, and what is the best LPF model. In this paper, these crucial questions are answered and a general formulation (GF) for evaluating the performance of LPF models is proposed. The GF actually figure out two core difficulties, the one is how to define the definition range of the LPF models, and the second is how to analytically obtain the best LPF model and evaluate the performance of a given LPF model. Besides, the key factors that affect the performance of LPF models are also analyzed through the proposed framework. The case studies compare the proposed LPF model with the DC power flow model, the physical-model-driven LPF model, and the data-driven LPF model, and the results show the effectiveness as well as the superiority of the proposed method.