Possibilistic-scenario Model for DG Impact Assessment on Distribution Networks in an Uncertain Environment
|Title:||Possibilistic-scenario Model for DG Impact Assessment on Distribution Networks in an Uncertain Environment||Authors:||Soroudi, Alireza||Permanent link:||http://hdl.handle.net/10197/6176||Date:||Aug-2012||Online since:||2014-11-18T15:35:50Z||Abstract:||The distribution network operators (DNOs) are responsible for securing a diverse and viable energy supply for their customers so the technical and economical impacts of distributed generation (DG) units are of great concerns. Traditionally, the DNOs try to maximize the technical performance of the distribution network, but it is evident that the first step in optimizing a quantity is being able to calculate it. The DG investment/operation which is performed by distributed generation operators/owners (DGOs) (under unbundling rules) has made this task more complicated. This is mainly because the DNO is faced with the uncertainties related to the decisions of DG investors/operators where some of them can be probabilistically modeled while the others are possibilistically treated. This paper proposes a hybrid possibilistic-probabilistic DG impact assessment tool which takes into account the uncertainties associated with investment and operation of renewable and conventional DG units on distribution networks. This tool would be useful for DNOs to deal with the uncertainties which some of them can be modeled probabilistically and some of them are described possibilistically. The proposed method has been tested on a test system and a large-scale real distribution network to demonstrate its strength and flexibility.||Type of material:||Journal Article||Publisher:||Institute of Electrical and Electronics Engineers||Journal:||IEEE Transactions on Power Systems||Volume:||27||Issue:||3||Start page:||1283||End page:||1293||Copyright (published version):||2012 Institute of Electrical and Electronics Engineers||Keywords:||Distributed generation; Fuzzy sets; Stochastic approximation; Uncertainty; Risk analysis; Wind energy||DOI:||10.1109/TPWRS.2011.2180933||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Electrical and Electronic Engineering Research Collection|
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