A distributed combinatorial optimisation heuristic for the scheduling of energy resources represented by self-interested agents. (2017)

• Record Type: Journal Article
• Authors: Hinrichs, Christian; Sonnenschein, Michael
• Is Part Of: International journal of bio-inspired computation. Volume 10:Number 2(2017)
• Page Start: 69
• Page End: 78
• Publication Date: 2017
• Subjects: heuristic -- distributed optimisation -- combinatorial optimisation -- scheduling -- energy resources -- energy markets -- day-ahead -- smart grid -- virtual power plants -- VPPs -- multi-agent systems -- self-interested agents -- self-organisation -- convergence -- termination -- proof; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

Abstract

The aggregation of controllable distributed energy resources (DER) to virtual power plants (VPPs) forms a possible integration path for DER in future energy systems. The authors present a fully distributed scheduling heuristic for VPPs. The approach is realised by representing each participant of a VPP by a self-interested agent. Both the global, operator-driven scheduling objective of a VPP as well as arbitrary individual local objectives of the agents are integrated efficiently in a fully distributed coordination paradigm. Convergence and termination of the heuristic are proven in the presence of unreliable environments, e.g., with communication delays.