Smart operations for low-emission maintenance vessels at offshore wind farms

Abstract

This thesis investigates the efficiency of maintenance operations for offshore wind farms (OWFs) using mathematical programming. The aim is to find cost-effective solutions focusing on implementing hybrid battery technology in maintenance vessels. The developed model optimises short-term maintenance schedules to enhance the profitability and competitiveness of OWFs in the energy market.

The research examines the impact of green maritime technologies on the profitability of maintenance operations. It compares traditional diesel-powered vessels with low-emission hybrid vessels, evaluating their economic impact. A column generation-based algorithm identifies the best routes and schedules for maintenance tasks, considering factors such as technician availability, battery limits, charging schedules, and time constraints.

The results indicate that using low-emission vessels with offshore charging stations can significantly reduce operational costs and increase profitability in maintenance operations. This thesis provides insights into running OWFs and the benefits of low-emission technologies. It supports global efforts to reduce greenhouse gas emissions and shift to green energy sources while addressing economic considerations.