Affiliations: DAI Labor / Technische Universität Berlin, Berlin, Germany | Department of Computer Science and Engineering, University of Minnesota, 4-192 EE/CS Building, 200 Union Street S.E., Minneapolis, MN 55455-0159, USA
Correspondence:
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Corresponding author: Dr. Benjamin Hirsch, Director Competence Center Agent Core Technologies, Dai Labor / TU Berlin, Ernst-Reuter-Platz 7, 10587 Berlin, Germany. Tel.: +49 30 31474025; Fax: +49 30 31474003; E-mail: [email protected].
Abstract: There is a lot of effort directed toward realizing the power network of the future. The future power network is expected to depend on a large number of renewable energy resources connected directly to the low and medium voltage power network. Demand side management (DSM) is an important element for reaching this goal. Demand side management is concerned with actions that reshape the energy consumption pattern for the end-users during peak time or during times when consumption exceeds generation. To control and coordinate the operation of the network with these new characteristics efficiently and with a certain degree of reliability, intelligent coordination approaches are required. The intermittency and variability of renewable energy resources, the large number of distributed consumption and generation units, and the local operation constraints for these units should be considered when designing the appropriate control and coordination systems. Agent-based systems are proposed and being implemented to control and coordinate the operation of different entities inside the future power network. By using agent technology we can satisfy the local constraints of different entities while simultaneously satisfying global goals by using coordination approaches for coordinating and adapting the agents' actions. Approaches developed rely on two control types for altering demand: price-based control (indirect control) and direct-load control. In this survey article we review previously and currently developed agent-based coordination approaches that depend on direct-load control for matching supply and demand in the power network of the future.
Keywords: Supply and demand matching, multi-agent systems, market and non-market algorithms
