Emerging smart grids have promising potentials to make energy management more efficient than currently possible in today's power grids. Integration of small scale renewables, distributed charging of electrical vehicles and virtual power stations are some of the technological innovations made possible by smart grids. Besides these technological aspects, smart grids also have a clear social component: consumers and small producers can together form energy communities. Such communities can be based on shared geographical location. They can also form based on shared values. This paper assumes that online social networks can be used to form virtual energy communities with shared values such as sustainability and social cohesion, sharing energy. We present an exploratory study on the creation and evolution of Smart Grid Social Networks using an agent-based simulation model. Initial simulation experiments show that in this context a large community with members that are occasionally active forms a better predictor for successful energy communities than a smaller community of very active users.

Social networking for Smart Grid users

Miorandi, Daniele;
2015-01-01

Abstract

Emerging smart grids have promising potentials to make energy management more efficient than currently possible in today's power grids. Integration of small scale renewables, distributed charging of electrical vehicles and virtual power stations are some of the technological innovations made possible by smart grids. Besides these technological aspects, smart grids also have a clear social component: consumers and small producers can together form energy communities. Such communities can be based on shared geographical location. They can also form based on shared values. This paper assumes that online social networks can be used to form virtual energy communities with shared values such as sustainability and social cohesion, sharing energy. We present an exploratory study on the creation and evolution of Smart Grid Social Networks using an agent-based simulation model. Initial simulation experiments show that in this context a large community with members that are occasionally active forms a better predictor for successful energy communities than a smaller community of very active users.
2015
978-1-4799-8069-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/310417
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