Power conversion for sustainable energy production and distribution is one of the most active areas, since efficient power conversion is required at every level of energy supply chain, from the producer to the consumer. Even more, the demand of energy efficient and reliable power conversion is further strengthened by the current evolution towards intelligent energy networks, i.e. smart grids, which facilitate the pervasive integration and deployment of renewable energy sources. In the state of the art, Smart Grids electrical energy generation is based on the load demand. When switching to renewable energy sources, this scheme becomes problematic because sources are not always available on demand, unless a large costly storage capacity is introduced; moreover energy cost for user during the day peak hours becomes very expensive for end users. A cheaper solution is to match the load demand with the instantaneously available power and amount of stored energy. In this paper, a new matchmaking solution based on Multi Agent System and Game Theory has been developed and implemented, optimizing the Smart Grid energy management and consequently reducing costs for end users. © 2014 IEEE.
A novel matchmaking algorithm for smart grid applications
Spata M. O.
Primo
;
2014-01-01
Abstract
Power conversion for sustainable energy production and distribution is one of the most active areas, since efficient power conversion is required at every level of energy supply chain, from the producer to the consumer. Even more, the demand of energy efficient and reliable power conversion is further strengthened by the current evolution towards intelligent energy networks, i.e. smart grids, which facilitate the pervasive integration and deployment of renewable energy sources. In the state of the art, Smart Grids electrical energy generation is based on the load demand. When switching to renewable energy sources, this scheme becomes problematic because sources are not always available on demand, unless a large costly storage capacity is introduced; moreover energy cost for user during the day peak hours becomes very expensive for end users. A cheaper solution is to match the load demand with the instantaneously available power and amount of stored energy. In this paper, a new matchmaking solution based on Multi Agent System and Game Theory has been developed and implemented, optimizing the Smart Grid energy management and consequently reducing costs for end users. © 2014 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
