A deregulated energy market is a typical scenario in which software agents are used for simulation and/or application purposes. Agents act on behalf of end users, thus implying the necessity of being aware of multiple aspects connected to the distribution of electricity. These aspects refer to outside world variables like weather, stock market trends, location of the users etc. therefore an architecture highly context aware is needed. We propose a web service integration in which agents contracting energy will automatically retrieve data to be used in adaptive and collaborative aspects, an explicative example, misrepresented by the retrieval of weather forecasting, that provides input on ongoing demand and data for the predicted availability(in case of photovoltaic or wind powered environments). The challenge lies in how to correctly use data coming from different sources, since these information are crucial for user profiling and balancing in the short-term contracts in the Smart Grid.
A Context-aware Agent-based Approach for Deregulated Energy Market / Capodieci, Nicola; Alsina, Emanuel Federico; Cabri, Giacomo. - STAMPA. - (2012), pp. 16-21. (Intervento presentato al convegno 21st IEEE International WETICE Conference, WETICE 2012 tenutosi a Toulouse, fra nel June 25-27) [10.1109/WETICE.2012.15].
A Context-aware Agent-based Approach for Deregulated Energy Market
CAPODIECI, NICOLA;ALSINA, EMANUEL FEDERICO;CABRI, Giacomo
2012
Abstract
A deregulated energy market is a typical scenario in which software agents are used for simulation and/or application purposes. Agents act on behalf of end users, thus implying the necessity of being aware of multiple aspects connected to the distribution of electricity. These aspects refer to outside world variables like weather, stock market trends, location of the users etc. therefore an architecture highly context aware is needed. We propose a web service integration in which agents contracting energy will automatically retrieve data to be used in adaptive and collaborative aspects, an explicative example, misrepresented by the retrieval of weather forecasting, that provides input on ongoing demand and data for the predicted availability(in case of photovoltaic or wind powered environments). The challenge lies in how to correctly use data coming from different sources, since these information are crucial for user profiling and balancing in the short-term contracts in the Smart Grid.Pubblicazioni consigliate
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