Title: A distributed combinatorial optimisation heuristic for the scheduling of energy resources represented by self-interested agents

Authors: Christian Hinrichs; Michael Sonnenschein

Addresses: Department of Computing Science, University of Oldenburg, D-26111 Oldenburg, Germany ' Department of Computing Science, University of Oldenburg, D-26111 Oldenburg, Germany

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.

Keywords: 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.

DOI: 10.1504/IJBIC.2017.085895

International Journal of Bio-Inspired Computation, 2017 Vol.10 No.2, pp.69 - 78

Received: 15 Nov 2014
Accepted: 25 Nov 2015
Published online: 18 Aug 2017 *

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