| dc.contributor.author |
Jagathy Raj, V P |
|
| dc.contributor.author |
Jasmin, E A |
|
| dc.contributor.author |
Imthias Ahamed, T P |
|
| dc.date.accessioned |
2014-08-04T09:53:38Z |
|
| dc.date.available |
2014-08-04T09:53:38Z |
|
| dc.date.issued |
2010-05 |
|
| dc.identifier.uri |
http://dyuthi.cusat.ac.in/purl/4489 |
|
| dc.description |
International J. of Recent Trends in Engineering and Technology, Vol. 3, No. 3, May 2010 |
en_US |
| dc.description.abstract |
Unit Commitment Problem (UCP) in power
system refers to the problem of determining the on/ off
status of generating units that minimize the operating cost
during a given time horizon. Since various system and
generation constraints are to be satisfied while finding the
optimum schedule, UCP turns to be a constrained
optimization problem in power system scheduling.
Numerical solutions developed are limited for small systems
and heuristic methodologies find difficulty in handling
stochastic cost functions associated with practical systems.
This paper models Unit Commitment as a multi stage
decision making task and an efficient Reinforcement
Learning solution is formulated considering minimum up
time /down time constraints. The correctness and efficiency
of the developed solutions are verified for standard test
systems |
en_US |
| dc.description.sponsorship |
CUSAT |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
ACEEE |
en_US |
| dc.subject |
Unit Commitment |
en_US |
| dc.subject |
reinforcement learning, |
en_US |
| dc.subject |
Q learning |
en_US |
| dc.title |
Reinforcement Learning Solution for Unit Commitment Problem Considering Minimum Start Up and Shut Down Times |
en_US |
| dc.type |
Article |
en_US |