Non-Linear Programming Based Optimal Power Flow (N-OPF) for Bulk Transmission Grid: Modeling and Comparative Study

Md Shamim Hasan; Sukumar Kamalasadan

doi:10.1109/IAS54024.2023.10406883

Non-Linear Programming Based Optimal Power Flow (N-OPF) for Bulk Transmission Grid: Modeling and Comparative Study

Md Shamim Hasan
, Sukumar Kamalasadan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Optimal power flow is generally formulated as a non-convex and non-linear programming (NLP) problem. Traditionally, the OPF problem is solved in transmission systems through approximations and/or relaxation techniques. Such methods lead to infeasible and inaccurate solutions. This paper provides a numerical analysis of the performance of different NLP OPF formulations, such as the Interior Point Method (IPM), Sequential Quadratic Programming (SQP), and Alternating Direction Method of Multipliers (ADMM) in terms of, feasibility, optimality, and scalability. The performances are evaluated using small (IEEE 9 bus and 14 bus), medium (IEEE 30 bus, 39 bus, and 57 bus), and large (IEEE 118 bus) test cases.

Original language	English
Title of host publication	2023 IEEE Industry Applications Society Annual Meeting, IAS 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350320169
DOIs	https://doi.org/10.1109/IAS54024.2023.10406883
State	Published - 2023
Externally published	Yes
Event	2023 IEEE Industry Applications Society Annual Meeting, IAS 2023 - Nashville, United States Duration: Oct 29 2023 → Nov 2 2023

Publication series

Name	2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

Conference

Conference	2023 IEEE Industry Applications Society Annual Meeting, IAS 2023
Country/Territory	United States
City	Nashville
Period	10/29/23 → 11/2/23

Funding

This article is based upon work supported in part by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technology Office Award Number DE-EE0008774. The authors are with the Energy Production and Infrastructure Center (EPIC) and the Department of Electrical and Computer Engineering of the University of North Carolina at Charlotte, Charlotte, NC 28223, USA. (e-mail: [email protected]; [email protected]).

Keywords

Alternating Direction Method of Multipliers (ADMM)
Bus Injection Model
Interior Point Method (IPM)
Optimal power flow (OPF)
Sequential Quadratic Programming (SQP)

Access to Document

10.1109/IAS54024.2023.10406883

Cite this

Hasan, M. S., & Kamalasadan, S. (2023). Non-Linear Programming Based Optimal Power Flow (N-OPF) for Bulk Transmission Grid: Modeling and Comparative Study. In 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023 (2023 IEEE Industry Applications Society Annual Meeting, IAS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IAS54024.2023.10406883

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title = "Non-Linear Programming Based Optimal Power Flow (N-OPF) for Bulk Transmission Grid: Modeling and Comparative Study",

abstract = "Optimal power flow is generally formulated as a non-convex and non-linear programming (NLP) problem. Traditionally, the OPF problem is solved in transmission systems through approximations and/or relaxation techniques. Such methods lead to infeasible and inaccurate solutions. This paper provides a numerical analysis of the performance of different NLP OPF formulations, such as the Interior Point Method (IPM), Sequential Quadratic Programming (SQP), and Alternating Direction Method of Multipliers (ADMM) in terms of, feasibility, optimality, and scalability. The performances are evaluated using small (IEEE 9 bus and 14 bus), medium (IEEE 30 bus, 39 bus, and 57 bus), and large (IEEE 118 bus) test cases.",

keywords = "Alternating Direction Method of Multipliers (ADMM), Bus Injection Model, Interior Point Method (IPM), Optimal power flow (OPF), Sequential Quadratic Programming (SQP)",

author = "Hasan, \{Md Shamim\} and Sukumar Kamalasadan",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023 ; Conference date: 29-10-2023 Through 02-11-2023",

year = "2023",

doi = "10.1109/IAS54024.2023.10406883",

language = "English",

series = "2023 IEEE Industry Applications Society Annual Meeting, IAS 2023",

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Hasan, MS & Kamalasadan, S 2023, Non-Linear Programming Based Optimal Power Flow (N-OPF) for Bulk Transmission Grid: Modeling and Comparative Study. in 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023. 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023, Nashville, United States, 10/29/23. https://doi.org/10.1109/IAS54024.2023.10406883

Non-Linear Programming Based Optimal Power Flow (N-OPF) for Bulk Transmission Grid: Modeling and Comparative Study. / Hasan, Md Shamim; Kamalasadan, Sukumar.
2023 IEEE Industry Applications Society Annual Meeting, IAS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE Industry Applications Society Annual Meeting, IAS 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Optimal power flow is generally formulated as a non-convex and non-linear programming (NLP) problem. Traditionally, the OPF problem is solved in transmission systems through approximations and/or relaxation techniques. Such methods lead to infeasible and inaccurate solutions. This paper provides a numerical analysis of the performance of different NLP OPF formulations, such as the Interior Point Method (IPM), Sequential Quadratic Programming (SQP), and Alternating Direction Method of Multipliers (ADMM) in terms of, feasibility, optimality, and scalability. The performances are evaluated using small (IEEE 9 bus and 14 bus), medium (IEEE 30 bus, 39 bus, and 57 bus), and large (IEEE 118 bus) test cases.

AB - Optimal power flow is generally formulated as a non-convex and non-linear programming (NLP) problem. Traditionally, the OPF problem is solved in transmission systems through approximations and/or relaxation techniques. Such methods lead to infeasible and inaccurate solutions. This paper provides a numerical analysis of the performance of different NLP OPF formulations, such as the Interior Point Method (IPM), Sequential Quadratic Programming (SQP), and Alternating Direction Method of Multipliers (ADMM) in terms of, feasibility, optimality, and scalability. The performances are evaluated using small (IEEE 9 bus and 14 bus), medium (IEEE 30 bus, 39 bus, and 57 bus), and large (IEEE 118 bus) test cases.

KW - Alternating Direction Method of Multipliers (ADMM)

KW - Bus Injection Model

KW - Interior Point Method (IPM)

KW - Optimal power flow (OPF)

KW - Sequential Quadratic Programming (SQP)

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M3 - Conference contribution

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Hasan MS, Kamalasadan S. Non-Linear Programming Based Optimal Power Flow (N-OPF) for Bulk Transmission Grid: Modeling and Comparative Study. In 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE Industry Applications Society Annual Meeting, IAS 2023). doi: 10.1109/IAS54024.2023.10406883

Non-Linear Programming Based Optimal Power Flow (N-OPF) for Bulk Transmission Grid: Modeling and Comparative Study

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