Smart asset integrity management in power distribution

On Tuesday, 14 October 2025, Sakura R. H. Attanayake successfully defended her doctoral thesis.

Published Updated on
En gruppe mennesker samlet på en disputas.

Sakura R. H. Attanayake's research introduces a cutting-edge, data-driven framework for asset integrity management in power distribution systems, offering innovative solutions to challenges posed by aging infrastructure, rising electricity demand, and growing sustainability expectations.

Thesis: Enhancing Asset Integrity Management of Power Distribution Systems using Artificial Intelligence driven Risk and Reliability Assessment

Supervised by Professor R. M. Chandima Ratnayake (main supervisor) and Professor Tore Markeset (co-supervisor), the project combines advanced analytics, artificial intelligence, and international best practices to support safer, more reliable, and cost-effective electricity distribution.

Transforming infrastructure integrity in energy systems

Power distribution networks form the backbone of modern electricity delivery. However, many suffer from aging components and reactive maintenance practices. This doctoral research seeks to modernise asset integrity management through:

  1. Digital processes for asset data management
  2. AI-based methods for risk prediction and failure forecasting
  3. Intelligent decision-support systems for asset integrity prioritization
  4. Alignment with international standards and sustainability frameworks
  5. Empirical validation through real-world case studies

Grounded in practice, powered by data

The study adopts an action research methodology, integrating theoretical reasoning with practical application. Case studies conducted at the Ceylon Electricity Board (CEB) in Sri Lanka demonstrate how the developed methods lead to reduced downtime, improved forecasting accuracy, and more efficient use of resources.

Advanced tools and methodologies

The research integrates several advanced tools, including:

  • Supervised machine learning, digitalized Weibull analysis, and ARIMA models
  • Fuzzy logic-based resilience modelling
  • Analytic Hierarchy Process (AHP) aligned with the NORSOK Z-008 standard
  • Circular economy frameworks based on ISO standards

The models were developed using Python, MATLAB, and other digital tools. Validation involved both technical performance data and stakeholder input.

Global relevance and future opportunities

While focused on Sri Lanka’s power infrastructure, the framework provides scalable insights for utility providers worldwide. It lays a foundation for future work in automation, software development, and application of asset integrity management principles across other sectors such as water, transport, and telecommunications.

Ms. Attanayake’s successful defense highlights the University of Stavanger’s dedication to sustainability-driven, high-impact engineering research.