USING SECOND-ORDER CONE PROGRAMMING-BASED ITERATIVE METHOD FOR LOAD FLOW ANALYSIS IN MESHED POWER TRANSMISSION NETWORKS

Đỗ Minh Hồng; Phạm Năng Văn; Nguyễn Thị Hoài Thu

doi:10.34238/tnu-jst.10686

USING SECOND-ORDER CONE PROGRAMMING-BASED ITERATIVE METHOD FOR LOAD FLOW ANALYSIS IN MESHED POWER TRANSMISSION NETWORKS

About this article

Received: 01/07/24 Revised: 01/08/24 Published: 01/08/24

Authors

1. Do Minh Hong, School of Electrical and Electronic Engineering - Hanoi University of Science and Technology
2. Pham Nang Van , School of Electrical and Electronic Engineering - Hanoi University of Science and Technology
3. Nguyen Thi Hoai Thu, School of Electrical and Electronic Engineering - Hanoi University of Science and Technology

Abstract

Power transmission networks are often designed and operated as meshed topologies. The power flow equations of these networks are nonlinear. They are typically solved using iterative methods such as Newton-Raphson. This research introduces an iterative method for analyzing power flow in meshed power transmission networks using second-order cone programming (SOCP). The proposed approach is extended from the SOCP procedure for radial electrical networks by adding constraints for the voltage phase angle on each branch in the transmission network. Simultaneously, the proposed SOCP method integrates the power flow equations into optimization problems. Therefore, optimization formulation using the proposed SOCP model is convex, and the globally optimal solution is attained. The proposed SOCP model is evaluated on a power transmission network with six buses and IEEE thirty buses using the GAMS programming language and the CPLEX commercial software. The computational results indicate that, in comparison to the standard Newton-Raphson approach, the solution of the suggested methodology has a very small error, which can be entirely disregarded in real-world applications.

Keywords

Power transmission networks; Meshed power networks; Load flow analysis; Second-order cone programming (SOCP); Optimization methods

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DOI: https://doi.org/10.34238/tnu-jst.10686

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