Accommodating high penetrations of pevs and renewable dg considering uncertainties in distribution systems

IEEE Transactions on Power Systems

Volumn 29, Issue 1, 2014, Pages 259-270

  Shaaban, Mostafa F ^a   El Saadany, E F ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Distributed power generation; electric vehicles; emissions; genetic algorithms; Monte Carlo methods; probability density function

Indexed keywords

DISTRIBUTION SYSTEMS; MINIMIZE GREENHOUSE GAS EMISSIONS; MIXED-INTEGER NONLINEAR PROGRAMMING; MULTI-OBJECTIVE PLANNING; NON-DOMINATED SORTING GENETIC ALGORITHMS; PLUG-IN ELECTRIC VEHICLES; RENEWABLE DISTRIBUTED GENERATIONS; SYSTEM OPERATING POINTS;

ALGORITHMS; DISTRIBUTED POWER GENERATION; ELECTRIC VEHICLES; GENETIC ALGORITHMS; GREENHOUSE GASES; MONTE CARLO METHODS; NONLINEAR PROGRAMMING; PARTICULATE EMISSIONS; PROBABILITY DENSITY FUNCTION; UNCERTAINTY ANALYSIS;

PROBLEM SOLVING;

EID: 84891547986     PISSN: 08858950     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPWRS.2013.2278847     Document Type: Article

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