@inproceedings{aa3de76c50e84c8d8136626d0144338f,
title = "Solar PV Modeling with Lambert W Function: An Exponential Cone Programming Approach",
abstract = "This paper presents a convex programming formulation to accurately compute the Lambert W-function. This function is widely used in modeling solar PVs, i.e., explicitly modeling the current voltage curve for solar PV performance. Unfortunately, the Lambert W function cannot be expressed by elementary functions and its computation also follows a complex procedure. To address these issues, we propose to leverage the exponential cone model to equivalently cast the computation of Lambert W function as solving a convex optimization problem whose constraints are representable with elementary functions. In other words, the Lambert W function can be exactly computed by means of convex programming without needing its close-form. We validate our results by comparing the accuracy of our proposed method for computing Lambert W function and its applications on modeling current-voltage curves of solar PV and Maximum Power Point Tracking System.",
keywords = "convex optimization, exponential cone, Lambert W function, solar PV modeling",
author = "Hieu Nguyen and Duong Nguyen and Ngo, {Anh Phuong} and Christan Thomas",
note = "Funding Information: This work was supported in part by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525, and in part by the North Carolina A&T State University's College of Engineering Intel Fellowship Program. Funding Information: ACKNOWLEDGEMENT This work was supported in part by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy{\textquoteright}s National Nuclear Security Administration under contract DE-NA0003525, and in part by the North Carolina A&T State University{\textquoteright}s College of Engineering Intel Fellowship Program. Publisher Copyright: {\textcopyright} 2022 IEEE.; 3rd IEEE Kansas Power and Energy Conference, KPEC 2022 ; Conference date: 25-04-2022 Through 26-04-2022",
year = "2022",
doi = "10.1109/KPEC54747.2022.9814756",
language = "English (US)",
series = "2022 IEEE Kansas Power and Energy Conference, KPEC 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 IEEE Kansas Power and Energy Conference, KPEC 2022",
}