Abstract
Typically, optimal power flow (OPF) analysis in a power grid is a nonlinear and non-convex problem. While analyzing OPF in a centralized manner in modern large power systems, nonlinearity generates a computational burden for OPF analysis, and due to the non-convexity, global optimality is not always guaranteed. Therefore, OPF models utilize approximations and/or relaxation techniques. However, these approximated/relaxed strategies can potentially result in solutions that are not feasible or not exact. Therefore, researchers have leaned toward distributed or decentralized approaches to address these challenges. In this article, a comprehensive and definitive study of different centralized and distributed OPF methods has been thoroughly investigated. This paper presents a qualitative and quantitative assessment of the effectiveness of various formulations of OPF analysis. The analysis illustrates the feasibility, optimality, convergence time, convergence behavior, and scalability of the different OPF models in different test networks spanning 9-bus to 2736-bus transmission systems.
| Original language | English |
|---|---|
| Pages (from-to) | 4328-4341 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Industry Applications |
| Volume | 61 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2025 |
| Externally published | Yes |
Funding
This work supported in part by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) through Solar Energy Technology Office under Award DEEE0008774.
Keywords
- Optimal power flow (OPF)
- and alternating direction method of multipliers (ADMM)
- convex OPF
- interior point method (IPM)
- second-order conic programming (SOCP)
- semi-definite programming (SDP)
- sequential quadratic programming (SQP)