# Life Cycle Cost Estimation and Analysis of Transformers Based on Failure Rate
## 1 Introduction  
With the dynamic advancement of the social economy, electricity has emerged as a pivotal energy source intricately tied to the essential well-being of the national economy and the sustenance of both economic progress and the welfare of the populace. Major power companies shoulder the responsibility of upholding national energy security, fostering the recovery of the real economy, and enhancing the overall quality of life [1]. With the rapid development of power system infrastructure, the requirements for power equipment are also increasing. The traditional equipment management method only focuses on immediate benefits, resulting in poor efficiency in equipment asset management. This model is not suitable for the needs of contemporary development [2]. The novel power equipment management technology focuses on the operation status of the entire life cycle. The life cycle is defined as the time interval between the product concept stage and the product disposal stage, which refers to the time interval between the entire process of product conception, design, manufacturing, installation, commissioning, operation, maintenance, repair, and scrapping [3]. Hence, this innovative power equipment asset management technology has broad prospects in various application scenarios. Substation equipment occupies a critical role within the power grid system, where both its safety and economic considerations hold paramount significance. Among the most important power equipment is the power transformer. The investment decision on power transformers directly bears on the investment cost, social benefits, and competitiveness of power companies in the face of market-oriented reform. As the power sector invests in the construction of substations, the financial aspect becomes a crucial factor alongside safety considerations [4]. Consequently, there is a collective effort from engineering personnel, scholars, and experts to tirelessly explore and research optimal solutions for substation equipment management. The rapid economic growth in China has led to a substantial increase in electricity consumption for both industrial production and daily life. This surgein demand necessitates the expansion of the power grid, resulting in a proportional growth in substation equipment and its associated facilities [5]. The ongoing energy transition has changed the architecture of electricity networks in ways such that conventional power transformers are not able to cope with the new required functionalities. Solid-state transformers (SSTs) have emerged as a superior alternative to conventional transformers and are regarded as the building block of the future smart grid. [PERSON] [6] analyzed and summarized the future trends and challenges of SST technology being more widely implemented in the power grid. [PERSON] [7] discussed the application and recent applications of SSTs as a substitute for low-frequency transformer (LFTs), and explored the future challenges of the real-time implementation of SSTs and proposed research directions. [PERSON] [8] focused on researching high-frequency transformers in solid-state transformers, especially the steps of designing and optimizing high-frequency transformers and their equivalent models based on the required characteristics. The efficient management of substation equipment not only demands the implementation of effective technical monitoring and analysis of the equipment, but also necessitates judicious management strategies and economically prudent personnel allocation to optimize cost savings. The advancement in transformer condition-based maintenance, and the scientific and economic management of transformers are intricately linked to the examination of transformer failure rates and the analysis of the life cycle cost of transformers [9]. Electric power construction not only needs to consider the initial construction cost of the project, but also needs to comprehensively consider the operation and maintenance costs [10].