A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources-Reference-Cited by-同舟云学术

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A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources

Published:2015-08 Issue: Volume:152 Page:71-82
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Quan Hao,Srinivasan Dipti,Khambadkone Ashwin M.,Khosravi Abbas

Funder

National Research Foundation

Australian Research Council

Centre for Intelligent Systems Research

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference46 articles.

1. Wind power prediction by a new forecast engine composed of modified hybrid neural network and enhanced particle swarm optimization;Amjady;IEEE Trans Sustain Energy,2011

2. Incorporating wind generation and load forecast uncertainties into power grid operations;Makarov,2010

3. Fuzzy MILP unit commitment incorporating wind generators;Venkatesh;IEEE Trans Power Syst,2008

4. A fuzzy-optimization approach for generation scheduling with wind and solar energy systems;Liang;IEEE Trans Power Syst,2007

5. An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation;Niknam;Appl Energy,2012

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