A leader-followers model of power transmission capacity expansion in a market driven environment
Paolo Pisciella (),
Marida Bertocchi and
Maria Vespucci
Computational Management Science, 2016, vol. 13, issue 1, 87-118
Abstract:
We introduce a model for analyzing the upgrade of the national transmission grid that explicitly accounts for responses given by the power producers in terms of generation unit expansion. The problem is modeled as a bilevel program with a mixed integer structure in both upper and lower level. The upper level is defined by the transmission company problem which has to decide on how to upgrade the network. The lower level models the reactions of both power producers, who take a decision on new facilities and power output, and Market Operator, which strikes a new balance between demand and supply, providing new Locational Marginal Prices. We illustrate our methodology by means of an example based on the Garver’s 6-bus Network. Copyright Springer-Verlag Berlin Heidelberg 2016
Keywords: Power network expansion planning; Generation expansion; Bilevel programming; $$k$$ k -th Best algorithm (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1007/s10287-014-0223-9 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:comgts:v:13:y:2016:i:1:p:87-118
Ordering information: This journal article can be ordered from
http://www.springer. ... ch/journal/10287/PS2
DOI: 10.1007/s10287-014-0223-9
Access Statistics for this article
Computational Management Science is currently edited by Ruediger Schultz
More articles in Computational Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().