Wednesday, May 22, 2013

Integrating Households into the Smart Grid

On May 20th 2013 we attended the first IEEE Workshop on Modeling and Simulation of Cyber-Physical Energy Systems. The workshop was collocated with the fourth International Conference on Future Energy Systems (ACM e-Energy), to be held in Berkeley on May 22th, 23th and 24rd.

The topics presented were very variegated. In the first session the papers were mostly concerning simulations of building or system-scale aspects in the grid (distribution, market, power flow modeling). The opening presentation was given by Kyle Anderson from Stanford University, presenting the GridSpice simulator, a cloud-based simulation tool which relies on multiple agents to run different existing simulation tools (MATPOWER and GridLab-D) and mantain the overall simulation consistence with a central coordinator. It also provides a RESTful interface to access the simulation, so that it can be integrated in third-part applications.

In the second session more applied and variegated aspects were presented.
We opened this session with the paper "Integrating Households into the Smart Grid". It deals with the problem of device and data interoperability created by the highly heterogeneous ecosystem of digital devices present in homes. In the paper we discuss requirements that should be addressed when copying with such a complex network. We show that an architecture based on REST webservices and linked data streams would be able to tackle this complexity. Applications can access the data through a uniform interface consisting in specific APIs and standardized query languages, as well as agreed ontologies for the specific use case.

The following presentation surveyed existing ontologies for smart home and smart energy systems and was held by Marco Grassi from Università Politecnica delle Marche. This completed the device and data interoperability issues and gave the audience a complete overview of this side of the smart grid.
The following presentations dealt with security aspects of the grid, such as detecting spoofing attacks on power grid GPS sensors. Also, multi-agent algorithms and control schemes were proposed for various aspects involving cyber-physical energy systems (i.e., resource bargaining, model-predictive control, coordination of power flow controllers).


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