Title :
Optimization based bidding strategies in the deregulated market
Author :
Zhang, Daoyuan ; Wang, Yajun ; Luh, Peter B.
Author_Institution :
Ascend Commun. Inc., Wallingford, CT, USA
fDate :
8/1/2000 12:00:00 AM
Abstract :
With the deregulation of electric power systems, market participants are facing an important task of bidding energy to an independent system operator (ISO). This paper presents a model and a method for optimization-based bidding and self-scheduling where a utility bids part of its energy and self-schedules the rest as in New England. The model considers ISO bid selections and uncertain bidding information of other market participants. With appropriately simplified bidding and ISO models, closed-form ISO solutions are first obtained. These solutions are then plugged into the utility´s bidding and self-scheduling model which is solved by using Lagrangian relaxation. Testing results show that the method effectively solves the problem with reasonable amount of CPU time
Keywords :
electricity supply industry; power system economics; scheduling; Lagrangian relaxation; New England; deregulated market; electric power systems deregulation; independent system operator; optimization based bidding strategies; self-scheduling; uncertain bidding information; Closed-form solution; Cost function; Game theory; ISO; Lagrangian functions; Linear programming; Optimization methods; Power system modeling; Pricing; Testing;
Journal_Title :
Power Systems, IEEE Transactions on