Showing 2 results for Shayegani Akmal
Mohammad Abouhosseini Darzi, Mohammad Mirzaie, Amir Abbas Shayegani Akmal, Ebrahim Rahimpour,
Volume 21, Issue 3 (September 2025)
Abstract
Bushings are one of the most important components of electrical equipment such as power transformers, reactors, capacitors. Most of the installed bushings have Oil-Immersed Paper (OIP) insulation structure. Bushing failure is caused by various reasons such as poor manufacturing process, overloading and also poor installation process, but moisture ingress is one of the main reasons of OIP bushing defect during its operation. In this paper, the electric field distribution of OIP bushings in multiple situations are simulated and effects of moisture distribution are analyzed. The simulations are stablished in polluted and clean surfaces of the studied bushing and done by COMSOL Multiphysics Software. The results show that non-uniform moisture distribution has a significant effect on electric fields of OIP insulation. This effect strongly increases with increasing the pollution on the external insulator of the bushing.
Ali Esmaeilvandi, Mohammad Hamed Samimi, Amir Abbas Shayegani Akmal,
Volume 22, Issue 1 (March 2026)
Abstract
This paper introduces an improved multi-conductor transmission line (MTL) model for transformers' high-frequency transient and frequency response analysis, overcoming limitations in traditional models that fail to capture complex electromagnetic interactions during high-frequency events, such as lightning strikes and switching operations. The model accurately reflects real-world transformer behaviors under transient conditions by integrating particle swarm optimization (PSO) for efficient parameter estimation and incorporating frequency-dependent losses. The combined use of PSCAD and Python minimizes computational overhead, enabling high-fidelity simulations closely aligned with experimental transformer data. Validation against real transformer measurements demonstrates the model’s reliability in capturing high-frequency responses, essential for transformer diagnostics. This novel approach offers a practical tool for studying transformer frequency response analysis, which is an important tool in transformer diagnosis.
