Towards a real-time energy management system for a Microgrid using a multi-objective genetic algorithm

Pedro P. Vergara; Ricardo Torquato; Luiz C.P. Da Silva

doi:10.1109/PESGM.2015.7285956

Towards a real-time energy management system for a Microgrid using a multi-objective genetic algorithm

Pedro P. Vergara
, Ricardo Torquato
, Luiz C.P. Da Silva

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

38 Citations (Scopus)

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.

Original language	English
Title of host publication	2015 IEEE Power and Energy Society General Meeting, PESGM 2015
Place of Publication	Piscataway
Publisher	IEEE Computer Society
Number of pages	5
ISBN (Electronic)	978-1-4673-8040-9
DOIs	https://doi.org/10.1109/PESGM.2015.7285956
Publication status	Published - 30 Sept 2015
Externally published	Yes
Event	2015 IEEE Power and Energy Society General Meeting, PESGM 2015 - Sheraton Denver Downtown Hotel, Denver, United States Duration: 26 Jul 2015 → 30 Jul 2015 http://www.pes-gm.org/2015/

Conference

Conference	2015 IEEE Power and Energy Society General Meeting, PESGM 2015
Abbreviated title	PESGM 2015
Country/Territory	United States
City	Denver
Period	26/07/15 → 30/07/15
Other	"Powering Up the Next Generation"
Internet address	http://www.pes-gm.org/2015/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

economic dispatch
Energy management system
evolutionary algorithm
microgrid
multi-objective optimization
non-dominating sorting genetic algorithm
unit commitment

Access to Document

10.1109/PESGM.2015.7285956

Cite this

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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",

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language = "English",

booktitle = "2015 IEEE Power and Energy Society General Meeting, PESGM 2015",

publisher = "IEEE Computer Society",

address = "United States",

note = "2015 IEEE Power and Energy Society General Meeting, PESGM 2015, PESGM 2015 ; Conference date: 26-07-2015 Through 30-07-2015",

url = "http://www.pes-gm.org/2015/",

}

Vergara, PP, Torquato, R & Da Silva, LCP 2015, Towards a real-time energy management system for a Microgrid using a multi-objective genetic algorithm. in 2015 IEEE Power and Energy Society General Meeting, PESGM 2015., 7285956, IEEE Computer Society, Piscataway, 2015 IEEE Power and Energy Society General Meeting, PESGM 2015, Denver, Colorado, United States, 26/07/15. https://doi.org/10.1109/PESGM.2015.7285956

Towards a real-time energy management system for a Microgrid using a multi-objective genetic algorithm. / Vergara, Pedro P.; Torquato, Ricardo; Da Silva, Luiz C.P.
2015 IEEE Power and Energy Society General Meeting, PESGM 2015. Piscataway: IEEE Computer Society, 2015. 7285956.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Towards a real-time energy management system for a Microgrid using a multi-objective genetic algorithm

AU - Vergara, Pedro P.

AU - Torquato, Ricardo

AU - Da Silva, Luiz C.P.

PY - 2015/9/30

Y1 - 2015/9/30

N2 - 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.

AB - 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.

KW - economic dispatch

KW - Energy management system

KW - evolutionary algorithm

KW - microgrid

KW - multi-objective optimization

KW - non-dominating sorting genetic algorithm

KW - unit commitment

UR - https://www.scopus.com/pages/publications/84956861509

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DO - 10.1109/PESGM.2015.7285956

M3 - Conference contribution

AN - SCOPUS:84956861509

BT - 2015 IEEE Power and Energy Society General Meeting, PESGM 2015

PB - IEEE Computer Society

CY - Piscataway

T2 - 2015 IEEE Power and Energy Society General Meeting, PESGM 2015

Y2 - 26 July 2015 through 30 July 2015

ER -

Towards a real-time energy management system for a Microgrid using a multi-objective genetic algorithm

Abstract

Conference

UN SDGs

Keywords

Access to Document

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