Shams, Farshad and Tribastone, Mirco Power Trading Coordination in Smart Grids Using Dynamic Learning and Coalitional Game Theory. In: Quantitative Evaluation of Systems.12th International Conference, QEST 2015, Madrid, Spain, September 1-3, 2015, Proceedings. Lecture Notes in Computer Science (9259). Springer, pp. 54-69. ISBN 978-3-319-22264-6 (2015)
Full text not available from this repository.Abstract
In traditional power distribution models, consumers acquire power from the central distribution unit, while “micro-grids” in a smart power grid can also trade power between themselves. In this paper, we investigate the problem of power trading coordination among such micro-grids. Each micro-grid has a surplus or a deficit quantity of power to transfer or to acquire, respectively. A coalitional game theory based algorithm is devised to form a set of coalitions. The coordination among micro-grids determines the amount of power to transfer over each transmission line in order to serve all micro-grids in demand by the supplier micro-grids and the central distribution unit with the purpose of minimizing the amount of dissipated power during generation and transfer. We propose two dynamic learning processes: one to form a coalition structure and one to provide the formed coalitions with the highest power saving. Numerical results show that dissipated power in the proposed cooperative smart grid is only 10% of that in traditional power distribution networks.
| Item Type: | Book Section |
|---|---|
| Identification Number: | https://doi.org/10.1007/978-3-319-22264-6_4 |
| Additional Information: | SCOPUS ID: 2-s2.0-84944753708; WOS Accession Number: WOS:000363574600006 |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Research Area: | Computer Science and Applications |
| Depositing User: | Caterina Tangheroni |
| Date Deposited: | 06 Oct 2016 16:05 |
| Last Modified: | 06 Oct 2016 16:05 |
| URI: | http://eprints.imtlucca.it/id/eprint/3580 |
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