Application of RBF neural networks and unscented transformation in probabilistic power-flow of microgrids including correlated wind/PV units and plug-in hybrid electric vehicles-Reference-Cited by-同舟云学术

Application of RBF neural networks and unscented transformation in probabilistic power-flow of microgrids including correlated wind/PV units and plug-in hybrid electric vehicles

Published:2017-03 Issue: Volume:72 Page:51-68
ISSN:1569-190X
Container-title:Simulation Modelling Practice and Theory
language:en
Short-container-title:Simulation Modelling Practice and Theory

Author:

Baghaee Hamid Reza^ORCID,Mirsalim Mojtaba,Gharehpetian G.B.^ORCID,Talebi H.A.

Publisher

Elsevier BV

Subject

Hardware and Architecture,Modelling and Simulation,Software

Reference70 articles.

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3. Performance improvement of multi-DER microgrid for small and large-signal disturbances and nonlinear loads: novel complementary control loop and fuzzy controller in a hierarchical droop-based control scheme;Baghaee;IEEE Syst. J.,2016

4. Three phase AC/DC power-flow for balanced/unbalanced microgrids including wind/solar, droop-controlled and electronically-coupled distributed energy resources using RBF neural networks;Baghaee;IET Power Electron.,2016

5. An Islanding microgrid power sharing approach using enhanced virtual impedance control scheme;He;IEEE Trans. Power Electron.,2013

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