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Please use this identifier to cite or link to this item: http://purl.org/purl/4489

Title: Reinforcement Learning Solution for Unit Commitment Problem Considering Minimum Start Up and Shut Down Times
Authors: Jagathy Raj, V P
Jasmin, E A
Imthias Ahamed, T P
Keywords: Unit Commitment
reinforcement learning,
Q learning
Issue Date: May-2010
Publisher: ACEEE
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
Description: International J. of Recent Trends in Engineering and Technology, Vol. 3, No. 3, May 2010
URI: http://dyuthi.cusat.ac.in/purl/4489
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