Fuzzy unscented transform for uncertainty quantification of correlated wind/PV microgrids: possibilistic–probabilistic power flow based on RBFNNs

Author:

Baghaee Hamid Reza1,Mirsalim Mojtaba1,Gharehpetian Gevork B.1,Talebi Heidar Ali1

Affiliation:

1. Electrical Engineering DepartmentAmirkabir University of TechnologyTehranIran

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Reference66 articles.

1. A new current limiting strategy and fault model to improve fault ride‐through capability of inverter interfaced DERs in autonomous microgrids;Baghaee H.R.;Sustain. Energy Technol. Assess.,2017

2. 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 H.R.;IEEE Syst. J.,2016

3. Multi-objective optimal power management and sizing of a reliable wind/PV microgrid with hydrogen energy storage using MOPSO

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 H.R.;IET Power Electron.,2016

5. Real‐time verification of new controller to improve small/large‐signal stability and fault ride‐through capability of multi‐DER microgrids

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