Offshore Wind Farm Maintenance Scheduling Optimization
Globally optimal maintenance scheduling considering production loss and maintenance cost; productized with Shanghai Electric
Project Overview
Every offshore maintenance trip is expensive — too early wastes it, too late means downtime. This system builds a globally optimal maintenance model that weighs production loss against maintenance cost.
Research Objectives
Production-loss-aware maintenance window optimization
Joint scheduling of routes, vessels and crews
Automatic generation of globally cost-optimal schedules
Methodology
A global optimal maintenance model with mixed-integer optimization formulation and solution algorithms.
Key Results
Productized and deployed with Shanghai Electric
Published in Journal of Intelligent & Fuzzy Systems and E3S
Case featured in the books Industrial Big Data and Industrial AI
Related Publications
An intelligent system for off-shore wind farm maintenance scheduling optimization considering turbine production loss, Journal of Intelligent & Fuzzy Systems, 2019
Real-Time Optimization of Production Operations