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Data-driven Power Flow Linearization: Simulation: Evaluation Overview
Authors:
(1) Mengshuo Jia, Department of Information Technology and Electrical Engineering, ETH Zürich, Physikstrasse 3, 8092, Zürich, Switzerland;
(2) Gabriela Hug, Department of Information Technology and Electrical Engineering, ETH Zürich, Physikstrasse 3, 8092, Zürich, Switzerland;
(3) Ning Zhang, Department of Electrical Engineering, Tsinghua University, Shuangqing Rd 30, 100084, Beijing, China;
(4) Zhaojian Wang, Department of Automation, Shanghai Jiao Tong University, Dongchuan Rd 800, 200240, Shanghai, China;
(5) Yi Wang, Department of Electrical and Electronic Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong, China;
(6) Chongqing Kang, Department of Electrical Engineering, Tsinghua University, Shuangqing Rd 30, 100084, Beijing, China.
Table of Links
2. Evaluated Methods
3. Review of Existing Experiments
4. Generalizability and Applicability Evaluations and 4.1. Predictor and Response Generalizability
4.2. Applicability to Cases with Multicollinearity and 4.3. Zero Predictor Applicability
4.4. Constant Predictor Applicability and 4.5. Normalization Applicability
5. Numerical Evaluations and 5.1. Experiment Settings
This paper is available on arxiv under CC BY-NC-ND 4.0 Deed (Attribution-Noncommercial-Noderivs 4.0 International) license.
[4] Active branch flows and nodal voltages are two essential parameters frequently utilized in operation/planning/control models of power systems. The linearization accuracy evaluated by these two factors is thus crucial.
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