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Murray, J.J., Cox, C.J., Lendaris, G.G. and Saeks, R. (2002) Adaptive Dynamic Programming. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 32, 140-153. http://dx.doi.org/10.1109/TSMCC.2002.801727

has been cited by the following article:

• TITLE: Extended Sequential Truncation Technique for Adaptive Dynamic Programming Based Security-Constrained Unit Commitment with Optimal Power Flow Constraints

  AUTHORS: Danli Long, Hua Wei

  KEYWORDS: Power System Operation and Planning; Priority Order; Adaptive Dynamic Programming; Unit Commitment

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.2 No.4, April 23, 2014

  ABSTRACT: Considering the economics and securities for the operation of a power system, this paper presents a new adaptive dynamic programming approach for security-constrained unit commitment (SCUC) problems. In response to the “curse of dimension” problem of dynamic programming, the approach solves the Bellman’s equation of SCUC approximately by solving a sequence of simplified single stage optimization problems. An extended sequential truncation technique is proposed to explore the state space of the approach, which is superior to traditional sequential truncation in daily cost for unit commitment. Different test cases from 30 to 300 buses over a 24 h horizon are analyzed. Extensive numerical comparisons show that the proposed approach is capable of obtaining the optimal unit commitment schedules without any network and bus voltage violations, and minimizing the operation cost as well.