Modelling demand response in organized wholesale energy markets. (2nd September 2016)
- Record Type:
- Journal Article
- Title:
- Modelling demand response in organized wholesale energy markets. (2nd September 2016)
- Main Title:
- Modelling demand response in organized wholesale energy markets
- Authors:
- Ferris, Michael C.
Liu, Yanchao - Abstract:
- Abstract : We propose a bi-level optimization model for demand response in organized wholesale energy markets. In this model, the lower level performs the economic dispatch of energy and generates the price and the upper level minimizes the total amount of demand response subject to a net benefit requirement. In an economic sense, demand response is a trade of 'consuming rights' instead of a sale of energy. Therefore it must be traded separately from the energy market. Although a bi-level optimization model is very hard to solve in general, we demonstrate that realistic power networks have characteristics that can be exploited to reduce the effective size of the problem instance. In particular, we transform the nonconvex net benefit test constraint to an equivalent linear form, and reformulate the nonconvex complementarity conditions of doubly bounded variables using SOS2 constraints. For realistic instances of the MPEC, we employ a three-phase approach that exploits the fast local solution from a nonlinear programming solver as well as LP-based bound strengthening within a mixed integer/SOS2 formulation. The model is tested against various data cases and settings, and generates useful insight for demand response dispatch operations in practice.
- Is Part Of:
- Optimization methods and software. Volume 31:Number 5(2016)
- Journal:
- Optimization methods and software
- Issue:
- Volume 31:Number 5(2016)
- Issue Display:
- Volume 31, Issue 5 (2016)
- Year:
- 2016
- Volume:
- 31
- Issue:
- 5
- Issue Sort Value:
- 2016-0031-0005-0000
- Page Start:
- 1064
- Page End:
- 1088
- Publication Date:
- 2016-09-02
- Subjects:
- bi-level program -- mixed integer program -- energy market -- demand response
Mathematical optimization -- Periodicals
Algorithms -- Periodicals
519.7 - Journal URLs:
- http://www.tandfonline.com/toc/goms20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/10556788.2016.1177527 ↗
- Languages:
- English
- ISSNs:
- 1055-6788
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6275.120000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2102.xml