Identifying prosumer’s energy sharing behaviours for forming optimal prosumer-communities
|dc.identifier.citation||Rathnayaka, A.J. Dinusha and Potdar, Vidyasagar M. and Hussain, Omar and Dillon, Tharam. 2011. Identifying prosumer’s energy sharing behaviours for forming optimal prosumer-communities, in IEEE International Conference on Cloud and Service Computing (CSC), Dec 12-14 2011. Hong Kong, China: IEEE.|
Smart Grid (SG) achieves bidirectional energy and information flow between the energy user and the utility grid, allowing energy users not only to consume energy, but also to generate the energy and share with the utility grid or with other energy consumers. This type of energy user who consumes energy and who also can generate the energy is called the “prosumer”. The sustainability of the SG energy sharing process heavily depends on its participating prosumers, making prosumer participation and management schemes crucial within the energy sharing approaches. The contribution of this article is twofold. First, this article introduces a novel concept of participating and managing the prosumers in the SG energy sharing process in the form of virtual communities, which involves with computation, software, data access, and storage services that do not need end-prosumer knowledge of the physical location and system configuration. Here, the community of prosumers can collectively increase the amount of power to be auctioned or bought offering higher bargaining power, thereby settling for a higher price per kilowatt in long-term. The initial step to build an effective prosumer-community is the identification of those prosumers who would be suitable to make efficient prosumer communities. This leads the necessity of identifying parameters that influence the energy sharing behaviours of prosumers. The second contribution of this article is that, this comprehensively analyses the different parameters influencing the prosumer’s energy sharing behaviours and thus presents multi-agent architecture for optimal prosumer-community formation.
|dc.publisher||IEEE Computer Society|
|dc.subject||multi agent system|
|dc.title||Identifying prosumer’s energy sharing behaviours for forming optimal prosumer-communities|
|dcterms.source.title||Proceedings of the IEEE international conference on cloud and service computing (CSC 2011)|
|dcterms.source.series||Proceedings of the IEEE international conference on cloud and service computing (CSC 2011)|
|dcterms.source.conference||IEEE International Conference on Cloud and Service Computing (CSC 2011)|
|dcterms.source.conference-start-date||Dec 12 2011|
|dcterms.source.conferencelocation||Hong Kong, China|
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|curtin.department||Digital Ecosystems and Business Intelligence Institute (DEBII)|