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Optimal Bidding Strategy for a Strat...

ProQuest Information and Learning Co.

Optimal Bidding Strategy for a Strategic Power Producer Using Mixed Integer Programming.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Optimal Bidding Strategy for a Strategic Power Producer Using Mixed Integer Programming./
Author:	Sadat, Sayed Abdullah.
Description:	1 online resource (55 pages)
Notes:	Source: Masters Abstracts International, Volume: 56-03.
Contained By:	Masters Abstracts International56-03(E).
Subject:	Electrical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9781369689310

Optimal Bidding Strategy for a Strategic Power Producer Using Mixed Integer Programming.
Sadat, Sayed Abdullah.

Optimal Bidding Strategy for a Strategic Power Producer Using Mixed Integer Programming. - 1 online resource (55 pages)

Source: Masters Abstracts International, Volume: 56-03.

Thesis (M.S.E.E.)

Includes bibliographical references

The thesis focuses on a mixed integer linear programming (MILP) formulation for a bi-level mathematical program with equilibrium constraints (MPEC) considering chance constraints. The particular MPEC problem relates to a power producer's bidding strategy: maximize its total benefit through determining bidding price and bidding power output while considering an electricity pool's operation and guessing the rival producer's bidding price. The entire decision-making process can be described by a bi-level optimization problem. The contribution of our thesis is the MILP formulation of this problem considering the use of chance constrained mathematical program for handling the uncertainties.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369689310Subjects--Topical Terms:

596380
Electrical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Optimal Bidding Strategy for a Strategic Power Producer Using Mixed Integer Programming.
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020 $a 9781369689310
035 $a (MiAaPQ)AAI10260941
035 $a (MiAaPQ)usf:13954
035 $a AAI10260941
040 $a MiAaPQ $b eng $c MiAaPQ
099 $a TUL $f hyy $c available through World Wide Web
100 1 $a Sadat, Sayed Abdullah. $3 1182865
245 1 0 $a Optimal Bidding Strategy for a Strategic Power Producer Using Mixed Integer Programming.
264 0 $c 2017
300 $a 1 online resource (55 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 56-03.
500 $a Adviser: Lingling Fan.
502 $a Thesis (M.S.E.E.) $c University of South Florida $d 2017.
504 $a Includes bibliographical references
520 $a The thesis focuses on a mixed integer linear programming (MILP) formulation for a bi-level mathematical program with equilibrium constraints (MPEC) considering chance constraints. The particular MPEC problem relates to a power producer's bidding strategy: maximize its total benefit through determining bidding price and bidding power output while considering an electricity pool's operation and guessing the rival producer's bidding price. The entire decision-making process can be described by a bi-level optimization problem. The contribution of our thesis is the MILP formulation of this problem considering the use of chance constrained mathematical program for handling the uncertainties.
520 $a First, the lower-level poor operation problem is replaced by Karush-Kuhn-Tucker (KKT) optimality condition, which is further converted to an MILP formulation except a bilinear item in the objective function. Secondly, duality theory is implemented to replace the bilinear item by linear items. Finally, two types of chance constraints are examined and modeled in MILP formulation. With the MILP formulation, the entire MPEC problem considering randomness in price guessing can be solved using off-shelf MIP solvers, e.g., Gurobi. A few examples and a case study are given to illustrate the formulation and show the case study results.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 596380
650 4 $a Industrial engineering. $3 679492
655 7 $a Electronic books. $2 local $3 554714
690 $a 0544
690 $a 0546
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of South Florida. $b Electrical Engineering. $3 845643
773 0 $t Masters Abstracts International $g 56-03(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10260941 $z click for full text (PQDT)

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