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A Bilevel Model for Optimal Bidding and Offering of Flexible Load Aggregator in Day-Ahead Energy and Reserve Markets
- Source :
- IEEE Access, Vol 6, Pp 67799-67808 (2018)
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- With the development of smart grid and active distribution network, the flexible load recourse would play a key role in the electricity market. In this paper, we proposed a framework that the distributed storage energy systems, electric vehicles, and temperature control loads are aggregated in the flexible load aggregator, trading in day-ahead energy and reserve markets. The framework is modeled as a bilevel optimization model. In the propose model, the operation problem of the FLA is modeled in upper-level problem, which is to maximize the profit of the aggregator. The biding and offering strategic of Gencos and flexible load aggregator in the independent system operator are presented in lower-level problem, which aim at improving the social benefits. Karush–Kuhn–Tucker and dual theory are used to transform the nonlinear bilevel problem to a mixed-integer linear programming of single-level model. Finally, the numerical studies based on modifying PJM-5bus power system, showing the effectiveness of the proposed framework and bilevel model.
- Subjects :
- Mathematical optimization
flexible load aggregator
Bilevel optimization model
General Computer Science
Linear programming
Computer science
020209 energy
02 engineering and technology
computer.software_genre
Bilevel optimization
Energy storage
News aggregator
Electric power system
Distributed data store
0202 electrical engineering, electronic engineering, information engineering
Electricity market
General Materials Science
General Engineering
Bidding
Electricity generation
Smart grid
lcsh:Electrical engineering. Electronics. Nuclear engineering
lcsh:TK1-9971
computer
day-ahead energy and reserve markets
offering and biding strategic
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....7364fc3238a0331e8085e5698b428412
- Full Text :
- https://doi.org/10.1109/access.2018.2879058