Rahman A. Prasojo, Muhammad R. Zainal, Galuh P.C. Handani, Muhammad F. Hakim, Bustani H. Wijaya, Sherif S.M. Ghoneim, Karar Mahmoud, Matti Lehtonen, Mohamed M.F. Darwish
Medium Voltage (MV) distribution substations are vital infrastructure in electrical power networks, yet condition-based maintenance practices for these systems remain underdeveloped compared to transmission-level assets. This study introduces a structured diagnostic framework to support maintenance prioritization in MV substations by aggregating diverse technical indicators into a unified condition score. The proposed model integrates data from field inspections, online monitoring, and laboratory testing across multiple substation components—such as MV fuses, lightning arresters, distribution transformers, and LV panels. Diagnostic parameters are individually scored based on operational standards, while the relative importance of each parameter is established using the Analytic Hierarchy Process (AHP), informed by expert input. The framework was applied to 695 MV substations within an Indonesian utility, producing health index scores that guided condition-based categorization. Results show that 567 substations were in good condition (HI > 80), while 128 were classified as requiring closer monitoring. Case studies of representative substations demonstrated a strong alignment between the health index outcomes and actual field conditions. The multi-parameter approach was particularly effective in identifying issues that would be overlooked in single-variable assessments. Compared to conventional methods, this model supports more holistic decision-making for asset maintenance and replacement planning. Its scalable structure and adaptability to different datasets make it a valuable tool for utility operators aiming to improve reliability and optimize resource allocation in distribution networks. © 2025
Department of Electrical Engineering, Politeknik Negeri Malang, Malang, 65141, Indonesia; UP3 Surabaya Utara, PT PLN (Persero), Surabaya, Indonesia; Department of Electrical Engineering, College of Engineering, Taif University, Taif, 21944, Saudi Arabia; Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan, 81542, Egypt; Department of Electrical Engineering and Automation, Aalto University, Espoo, FI-00076, Finland; Department of Engineering Sciences in the Electrical Field, Constanta Maritime University, Constanta, 900663, Romania; Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo, 11629, Egypt