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A possibilistic-probabilistic tool for evaluating the impact of stochastic renewable and controllable power generation on energy losses in distribution networks-A case study

Soroudi, A ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1016/j.rser.2010.09.035
  3. Abstract:
  4. 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
  5. Keywords:
  6. Active losses ; Fuzzy ; Uncertainty ; Active loss ; Distributed generation ; Fuzzy ; Monte Carlo Simulation ; Computer simulation ; Distributed parameter networks ; Distributed power generation ; Distribution functions ; Electric load loss ; Energy dissipation ; Galerkin methods ; Monte Carlo methods ; Probability density function ; Wind power ; Wind turbines ; Weibull distribution
  7. Source: Renewable and Sustainable Energy Reviews ; Volume 15, Issue 1 , 2011 , Pages 794-800 ; 13640321 (ISSN)
  8. URL: http://www.sciencedirect.com/science/article/pii/S1364032110003229