A possibilistic-probabilistic tool for evaluating the impact of stochastic renewable and controllable power generation on energy losses in distribution networks - A case study
|Title:||A possibilistic-probabilistic tool for evaluating the impact of stochastic renewable and controllable power generation on energy losses in distribution networks - A case study||Authors:||Soroudi, Alireza
|Permanent link:||http://hdl.handle.net/10197/6207||Date:||Jan-2011||Online since:||2014-11-26T09:53:32Z||Abstract:||This paper proposes a hybrid possibilistic–probabilistic evaluation tool for analyzing the effect of uncertain power production of distributed generations (DGs) on active losses of distribution networks. The considered DG technologies are gas and wind turbines. This tool is useful for distribution network operators (DNOs) when they are faced with uncertainties which some of them can be modeled probabilistically and some of them are described possibilistically. The generation pattern of DG units changes the flow of lines and this will cause change of active losses which DNO is responsible for compensating it. This pattern is highly dependent on DG technology and also on decisions of DG operator which is an entity other than DNO. For wind turbines, this pattern is described using a weibull probability distribution function (PDF) for wind speed along with the power curve of the wind turbine but for other controllable DG technologies like gas turbines, it is not an easy job to provide a PDF to describe the generation schedule. On the other hand, the values of loads cannot be always described using a PDF so the possibilistic (fuzzy) description can be helpful in such cases. In order to demonstrate the effectiveness of the proposed tool, it is applied to a realistic distribution system and the results are analyzed and discussed.||Type of material:||Journal Article||Publisher:||Elsevier||Journal:||Renewable and Sustainable Energy Reviews||Volume:||15||Issue:||1||Start page:||794||End page:||800||Copyright (published version):||2010 Elsevier||Keywords:||Distributed generation; Fuzzy; Uncertainty; Active losses; Monte Carlo simulation||DOI:||10.1016/j.rser.2010.09.035||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Electrical and Electronic Engineering Research Collection|
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