New paper on a bi-level multi-agent system for optimal scheduling of predictive maintenance interventions
Our paper proposing a bi-level multi-agent system for optimal scheduling of predictive maintenance interventions has just been accepted for publication in the journal Reliability Engineering & System Safety and is available under open access.
We propose a bi-level multi-agent decision support system for the generation maintenance decision of power grids in an electricity market in the context of predictive maintenance. The aim of the generation maintenance decision is to minimize the generation cost while maximizing the system reliability. The proposed framework integrates a central coordination system, i.e. the transmission system operator, and distributed agents representing power generation units that act to maximize their profit and decide about the optimal maintenance time slots while ensuring the energy balance. To solve the coordination problem, we propose a negotiation algorithm using an incentive signal to coordinate the agents’ and the central system’s decisions, such that all the agents’ decisions can be accepted by the central system.
The Chair of Intelligent Maintenance Systems focuses on developing intelligent algorithms to improve performance, reliability and availability of complex industrial assets and making the maintenance more cost efficient. For more information visit our webpage