Application of actor-critic learning algorithm for optimal bidding problem of a GenCo
DSpace at IIT Bombay
View Archive InfoField | Value | |
Title |
Application of actor-critic learning algorithm for optimal bidding problem of a GenCo
|
|
Creator |
GAJJAR, GR
KHAPARDE, SA NAGARAJU, P SOMAN, SA |
|
Subject |
markov processes
optimization algorithms learning game theory |
|
Description |
The optimal bidding for Genco in a deregulated power market is an involved task. The problem is formulated in the framework of Markov decision process (MDP), a discrete stochastic optimization method. When the time span considered is 24 h, the temporal difference method becomes attractive for application. The cumulative profit over the span is the objective function to be optimized. The temporal difference technique and actor-critic learning algorithm are employed. An optimal strategy is devised to maximize the profit. The market-clearing system is included in the formulation. Simulation cases of three, seven, and ten participants are considered and the obtained results are discussed.
|
|
Publisher |
IEEE
|
|
Date |
2008-11-24T05:40:23Z
2011-11-25T16:03:15Z 2011-12-26T13:05:24Z 2011-12-27T05:52:12Z 2008-11-24T05:40:23Z 2011-11-25T16:03:15Z 2011-12-26T13:05:24Z 2011-12-27T05:52:12Z 2003 |
|
Type |
Article
|
|
Identifier |
IEEE Transactions on Power Engineering Review 18(1), 11-18
0885-8950 http://dx.doi.org/10.1109/TPWRS.2002.807041 http://hdl.handle.net/10054/131 http://dspace.library.iitb.ac.in/xmlui/handle/10054/131 |
|
Language |
en_US
|
|