NDLI: A novel approach to the optimal planning of flexible active distribution networks

Content Provider	IEEE Xplore Digital Library
Author	MacDonald, R.A. Ault, G.W. McDonald, J.R.
Copyright Year	2010
Description	Author affiliation: Institute for Energy and the Environment, University of Strathclyde, UK (MacDonald, R.A.; Ault, G.W.; McDonald, J.R.)
Abstract	This paper introduces a novel approach to the task of identifying an optimal plan for electrical distribution networks, a problem which is set to increase in complexity as distribution networks shift away from a relatively “passive” operational regime, towards a future of flexible, dynamically controlled networks. Such a shift in the fundamental operational philosophy of distribution networks will render conventional network planning and design techniques inadequate. What would previously have been seen as an optimal network design, may be far from optimal for an actively managed distribution network. This paper identifies the shortcomings of traditional network planning optimization techniques, and introduces a novel approach, using Stochastic Programming techniques to hedge against the uncertainties which exist in long-term network planning problems. It is argued that the approach proposed will be able to integrate new technologies and systems which will enable network flexibility into the planning optimization task. A key idea discussed is that a flexible planning approach provides a highly valuable counter to the growing levels of uncertainty faced by distribution system planners (e.g. renewable generation, demand side measures and more active distribution networks).
Starting Page	1
Ending Page	5
File Size	1327924
Page Count	5
File Format	PDF
ISBN	9781424468232
e-ISBN	9780947649449
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-01
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	The University of Strathclyde
Subject Keyword	Uncertainty Stochastic Programming Optimal control Stochastic processes Probabilistic Study Active Network Management Smartgrids Distribution Planning Technology planning Counting circuits
Content Type	Text
Resource Type	Article

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