Nespoli, Lorenzo and Giusti, Alessandro and Vermes, Nicola and Derboni, Marco and Rizzoli, Andrea Emilio and Gambardella, Luca Maria and Medici, Vasco (2016) Distributed demand side management using electric boilers. Computer Science - Research and Development. pp. 1-13. ISSN 1865-2034
Full text not available from this repository.Abstract
Demand side management is a promising approach towards the integration of renewable energy sources in the electric grid, which does not require massive infrastructural investments. In this paper, we report the analysis of the performance of a demand side management algorithm for the control of electric boilers, developed within the context of the GridSense project. GridSense is a multi-objective energy management system that aims at decreasing both the end user energy costs and the congestions on the local feeder. The latter objective is minimized exploiting the existent correlation between the voltage measured at the connection point to the grid and the power flow measured at the low voltage transformer. The algorithm behavior has been firstly investigated by means of simulation, using typical water consumption profiles and a simplified thermodynamic model of the electric boiler. The simulation results show that the algorithm can effectively shift the boiler’s electric consumption based on voltage and price profiles. In the second phase, we analyzed the results from a pilot project, in which the GridSense units were controlling the boilers of four households, located in the same low voltage grid.
| Item Type: | Scientific journal article, Newspaper article or Magazine article |
|---|---|
| Uncontrolled Keywords: | Demand side management; Decentralized energy manager; Smart grid |
| Subjects: | Engineering > General engineering > General engineering not elsewhere classified Computer sciences > Information systems > Intelligent & expert systems Computer sciences > Artificial intelligence > Machine learning > Automated reasoning |
| Department/unit: | Dipartimento ambiente costruzioni e design > Istituto sostenibilità applicata all'ambiente costruito Dipartimento tecnologie innovative > Istituto Dalle Molle di studi sull’intelligenza artificiale USI-SUPSI |
| Depositing User: | Lorenzo Nespoli |
| Date Deposited: | 05 Sep 2016 07:20 |
| Last Modified: | 19 Sep 2016 08:58 |
| URI: | http://repository.supsi.ch/id/eprint/7687 |
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