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Advisor(s)
Abstract(s)
Environmental concerns and the shortage in the fossil
fuel reserves have been potentiating the growth and
globalization of distributed generation. Another resource that
has been increasing its importance is the demand response,
which is used to change consumers’ consumption profile,
helping to reduce peak demand. Aiming to support small
players’ participation in demand response events, the
Curtailment Service Provider emerged. This player works as an
aggregator for demand response events. The control of small
and medium players which act in smart grid and micro grid
environments is enhanced with a multi-agent system with
artificial intelligence techniques – the MASGriP (Multi-Agent
Smart Grid Platform). Using strategic behaviours in each
player, this system simulates the profile of real players by using
software agents. This paper shows the importance of modeling
these behaviours for studying this type of scenarios. A case study
with three examples shows the differences between each player
and the best behaviour in order to achieve the higher profit in
each situation.
Description
Keywords
Artificial Intelligence Demand Response Micro Grid Multi-agent Simulation Smart Grid
Citation
Publisher
IEEE