NDLI: A Lagrangian Decomposition Algorithm for Optimal Emergency Voltage Control

Content Provider	IEEE Xplore Digital Library
Author	Beccuti, A.G. Demiray, T.H. Andersson, G. Morari, M.
Copyright Year	1969
Abstract	Voltage control problems typically involve large networks comprising diverse components extending over considerable areas and interconnecting different grids and operators. To deal with such systems, there has been over the past few years a steadily increasing interest in model predictive/optimal control techniques as a viable solution. In such a setting, it is essential to be able to coordinate the control actions among the various grids while preserving sensitive local system data that regional operators are often not willing to disclose. In view of these discordant factors, centralized and decentralized control schemes, respectively, yield advantages and drawbacks: the former require global system data to be accessible whereas the latter may prove to be difficult to effectively implement or might achieve suboptimal performance. The present paper therefore proposes a centralized control scheme that is solved however in a distributed fashion through a Lagrangian decomposition algorithm, thus reaping the benefits of both approaches: the control problem is global, therefore intrinsically more reliable and comprehensive, but only local information is employed to achieve the overall optimum control input. The computational delay associated with the additional iterations required by the algorithm is shown to be viable for the considered application and can furthermore be inherently accounted for within the proposed optimal control scheme.
Sponsorship	IEEE Power Engineering Society
Starting Page	1769
Ending Page	1779
Page Count	11
File Size	1713982
File Format	PDF
ISSN	08858950
Volume Number	25
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lagrangian functions Voltage control Optimal control Control systems Centralized control Automatic control Laboratories Predictive models Power system dynamics Power system stability predictive control Optimization methods power system dynamic stability
Content Type	Text
Resource Type	Article
Subject	Energy Engineering and Power Technology Electrical and Electronic Engineering

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