NDLI: An iterative deepening genetic algorithm for scheduling of direct load control

Content Provider	IEEE Xplore Digital Library
Author	Leehter Yao Wen-Chi Chang Rong-Liang Yen
Copyright Year	1969
Abstract	A modified genetic algorithm (GA) called iterative deepening GA (IDGA) is proposed in this paper to optimize the scheduling of direct load control (DLC) strategies. The control strategy (or scheduling) arranged by the IDGA not only sheds the load so that the load required to be shed at each sampling interval is individually satisfied, but it also minimizes the shedding load so that the utility company's revenue loss due to DLC is minimized. The scheduling obtained by the proposed IDGA tends to level off the accumulated shedding time of each load group, avoiding customers' complaints about fairness of shedding time. IDGA is composed of a master GA and a sequence of slave GAs. As the master GA evaluates a status combination, it iteratively calls upon a slave GA at each of the following time steps, evaluating possible forward status combinations. With an iteratively deepening search scope, IDGA is able to find a satisfactory suboptimal scheduling.
Sponsorship	IEEE Power Engineering Society
Starting Page	1414
Ending Page	1421
Page Count	8
File Size	265295
File Format	PDF
ISSN	08858950
Volume Number	20
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-08-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms Load flow control Radio control Master-slave Load management Air conditioning Switches Power generation Dynamic programming Dynamic scheduling load management Air conditioner direct load control (DLC) genetic algorithm (GA)
Content Type	Text
Resource Type	Article
Subject	Energy Engineering and Power Technology Electrical and Electronic Engineering

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