eprintid: 3580
rev_number: 6
eprint_status: archive
userid: 69
dir: disk0/00/00/35/80
datestamp: 2016-10-06 16:05:16
lastmod: 2016-10-06 16:05:16
status_changed: 2016-10-06 16:05:16
type: book_section
metadata_visibility: show
creators_name: Shams, Farshad
creators_name: Tribastone, Mirco
creators_id: 
creators_id: mirco.tribastone@imtlucca.it
title: Power Trading Coordination in Smart Grids Using Dynamic Learning and Coalitional Game Theory
ispublished: pub
subjects: QA76
divisions: CSA
full_text_status: none
note: SCOPUS ID: 2-s2.0-84944753708; WOS Accession Number: WOS:000363574600006
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.
date: 2015
date_type: published
series: Lecture Notes in Computer Science
number: 9259
publisher: Springer
pagerange: 54-69
id_number: doi:10.1007/978-3-319-22264-6_4
refereed: TRUE
isbn: 978-3-319-22264-6
issn: 0302-9743
book_title: Quantitative Evaluation of Systems.12th International Conference, QEST 2015, Madrid, Spain, September 1-3, 2015, Proceedings
official_url: http://doi.org/10.1007/978-3-319-22264-6_4
citation:   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)