| dc.contributor.author |
Jagathy Raj, V P |
|
| dc.contributor.author |
Jasmin, E A |
|
| dc.contributor.author |
Imthias Ahamed, T P |
|
| dc.date.accessioned |
2014-08-06T04:47:53Z |
|
| dc.date.available |
2014-08-06T04:47:53Z |
|
| dc.date.issued |
2009-12-28 |
|
| dc.identifier.uri |
http://dyuthi.cusat.ac.in/purl/4494 |
|
| dc.description |
Advances in Computing, Control, & Telecommunication Technologies, 2009. ACT'09. International Conference on |
en_US |
| dc.description.abstract |
Unit commitment is an optimization task in electric
power generation control sector. It involves scheduling the
ON/OFF status of the generating units to meet the load demand
with minimum generation cost satisfying the different constraints
existing in the system. 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 task and Reinforcement Learning solution is formulated
through one efficient exploration strategy: Pursuit method. 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 |
IEEE |
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 through pursuit method |
en_US |
| dc.type |
Article |
en_US |