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A new methodology for power systems flexibility evaluation

descriptionPublicationkeyboard_double_arrow_right Conference object , Article 01 Jun 2005 Italy Publisher:IEEEJournal:2005 IEEE Russia Power Tech

Authors: CAPASSO, Alfonso; FALVO, Maria Carmen; LAMEDICA, Regina; LAURIA, Stefano; S. Scalcino;

doi: 10.1109/ptc.2005.4524644

handle: 11573/232342

A new methodology for power systems flexibility evaluation

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Abstract

In a free-market scenario, power system planning is affected by a significant degree of uncertainty about time and location of generating assets expansion. The paper contains a methodology for the evaluation of the flexibility, defined as the attitude of the transmission system to adapt, quickly and with limited costs, to every change, from the initial planning conditions, with a particular regard to the changes in generation. The method provides new global and local flexibility indices, based on technical and economical parameters, defined as Technical Uncertainty Scenarios Flexibility Index (T-USFI) and Technical Economical Uncertainty Scenarios Flexibility Index (TE-USFI). The T-USFI computation segment of methodology has been tested on simple networks.

Country

Italy

Related Organizations

Sapienza University of Rome
Italy
Roma Tre University
Italy

Keywords

flexibility; genetic algorithms; montecarlo method; open-access; power system planning; uncertainty

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	37
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average