2015 IEEE Power &Amp; Energy Society General Meeting 2015
DOI: 10.1109/pesgm.2015.7285956
|View full text |Cite
|
Sign up to set email alerts
|

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 algorit… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
7
0

Year Published

2018
2018
2022
2022

Publication Types

Select...
5
4
1

Relationship

0
10

Authors

Journals

citations
Cited by 31 publications
(11 citation statements)
references
References 14 publications
0
7
0
Order By: Relevance
“…Moreover, in [138], NSGA-II is applied to the controller of the inverters of distributed generators with inner and outer control loops to seamless transition operation between grid-connected and islanding mode. In [139][140][141][142] the more applications of NSGA-II are presented.…”
Section: C32 Direct Aooroachmentioning
confidence: 99%
“…Moreover, in [138], NSGA-II is applied to the controller of the inverters of distributed generators with inner and outer control loops to seamless transition operation between grid-connected and islanding mode. In [139][140][141][142] the more applications of NSGA-II are presented.…”
Section: C32 Direct Aooroachmentioning
confidence: 99%
“…Versatility to find several members of the Pareto optimal set in a single performance of the algorithm High computational cost [107,108] Non-dominated sorting genetic algorithm II (NSGA-II)…”
Section: Global Criterionmentioning
confidence: 99%
“…The proposed controller minimized the grid fluctuations while keeping the state of charge (SOC) of the battery storage within a secure range (Arcos-Aviles et al, 2018). Vergara et al introduced a real-time EMS based on a no-dominated sorting Genetic algorithm, where the crossover and mutation parameters were adapted in order to achieve higher performances (Vergara et al 2015). Ahmad Eid et al (2021) improved marine predator algorithm (MPA) to control the active and reactive power injected into two standard distribution test systems and to minimize system losses.…”
Section: Introductionmentioning
confidence: 99%