@inproceedings{2cd87ed7051f4e95a2a8792bdfe719c5,
title = "Towards a real-time Energy Management System for a Microgrid using a multi-objective genetic algorithm",
abstract = "This paper proposes a real-time Energy Management System (EMS) for a low voltage (LV) Microgrid (MG). The system operation consists in solving the Unit Commitment (UC) and Economic Load Dispatch (ELD) simultaneously for 24 hours ahead at every 15-minute period. This operation is formulated as a multi-objective optimization problem where the minimization of operational cost, total emissions and power losses is simultaneously pursued using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). In this algorithm, crossover and mutation operators were improved with respect to existing approaches to achieve an adequate characterization of the energy management problem and a good algorithm performance. Simulation studies have outlined that, in fact, the NSGA-II can be used as a real-time optimization tool providing a good-quality Pareto front to operate optimally the MG in a limited time of 15 minutes.",
keywords = "economic dispatch, Energy management system, evolutionary algorithm, microgrid, multi-objective optimization, non-dominating sorting genetic algorithm, unit commitment",
author = "Vergara, {Pedro P.} and Ricardo Torquato and {Da Silva}, {Luiz C.P.}",
year = "2015",
doi = "10.1109/PESGM.2015.7285956",
language = "English",
series = "IEEE Power and Energy Society General Meeting",
publisher = "IEEE",
booktitle = "2015 IEEE Power and Energy Society General Meeting, PESGM 2015",
address = "United States",
note = "IEEE Power and Energy Society General Meeting, PESGM 2015 ; Conference date: 26-07-2015 Through 30-07-2015",
}
