Time Series Forecasting Case Study on Risk-Based Asset Integrity Management for Low-Voltage Failures of Power Distribution Systems

Abstract

The concept of risk assessment is an important tool in the asset integrity management of power distribution systems. This manuscript presents a risk-based asset integrity management (RBAIM) methodology for the optimization of power distribution assets using a time series analysis approach. This approach deals with time series forecasting on risk assessment for low-voltage-level (400/230 V) failures using the Python programming language and considering historical low-voltage (LV) fuse failure data from a case study over 44 months, starting from 2019. The proposed approach is deployed in a power distribution utility located in a densely populated area of Colombo district, Sri Lanka. The authors proposed a methodical approach for the identification of priority components for asset maintenance and repair ranking based on the risk index percentage value to enhance the predictiveness of potential defects and estimate the risk of potential failures. The results show that the proposed time series forecasting methodology for RBAIM is useful for power distribution utility asset owner organizations for continuous monitoring, the evaluation of asset conditions, and the implementation of proper maintenance and repair strategies to enable assets to perform at their optimal level. The proposed RBAIM methodology enables practicing engineers to assure the asset integrity of power distribution utilities.

Keywords

• asset integrity management
• low voltage failures
• power distribution systems
• RBAIM
• risk assessment
• time series forecasting