Study on Advanced Maintenance Strategies and Asset Management for Substation Equipment in Japan: Investigation of Recent Technologies for Advance Maintenance Strategies

Study on the advanced maintenance strategies and the asset management for the substation equipment is enthusiastically taken in place in Japan by the engineers from utilities and manufactures. This work is a part of the ETRA (Electric Technology Research Association) in Japan, where most of the Japanese utilities and manufactures cooperate with each other to address various issues that need to be improved or overcome for upwards of 80 years. The following working groups are organized in this study; “Investigation of the transition of substation equipment quantity, trend analysis of failures“, “Analysis of the degradation mechanisms of substation equipment and investigation of maintenance strategy
$\prime$
, “Investigation of recent technologies for advance maintenance strategies” and “Survey and research on asset management methods for strategic investment judgments”. This paper describes achievement of “Investigation of recent technologies for advance maintenance strategies”. In the first step, from the questionnaire to Japanese substation engineers from utilities and manufactures and investigation of technical literatures and papers, we summarized result of needs against further advanced maintenance and the technology for advanced maintenance work with recent technologies (hereafter referred to as “advanced maintenance technology”). Next, we describe future prospects for advanced maintenance work, based on the utilization status and future trends of maintenance work for substation equipment with advanced maintenance technologies developed and introduced in Japan. Finally, we report the consideration chart needed until implementation of advanced maintenance technology, and works needed each step of chart (considering some conditions for technical application and cost-effectiveness, design / development, field verification, construction new maintenance models).