Co-Optimization of Reliability and Resilience in Hybrid Microgrids

This paper proposes the optimal sizing of standalone microgrid hybrid renewable energy resources (HRES), considering the minimization of the levelized cost of energy (LCOE), and maximizing the reliability and resilience of microgrids using a puma optimizer (PO). PO is an optimization algorithm with special mechanisms for the exploration and exploitation phases as well as a hyper-heuristic for phase change that enables the algorithm to balance both phases and adapt to the nature of the problem. hybrid microgrid comprising PV, battery storage, and diesel generators. The results of the simulation obtained by PO were compared with the particle swarm optimization technique (PSO). PSO frequently has the tendency to converge too quickly and can become stuck in local minima. On the other hand, the Puma optimizer uses sophisticated exploration methods and exploitation strategies to increase its resilience to local optima and raise the possibility of finding global solutions. This indicates that the PO has better performance in global search and optimization than PSO.

Authors

Institutions

Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/mepcon63025.2024.10850189
Citations
1
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Co-Optimization of Reliability and Resilience in Hybrid Microgrids

Sherif Helmy, M A Abdel-Rahman, Mazlan Abdul Wahid
1 citations
Microgrid Control and Optimization
0.33
article

Co-Optimization of Reliability and Resilience in Hybrid Microgrids

Sherif Helmy, M A Abdel-Rahman, Mazlan Abdul Wahid
article en
1 citations

Abstract

This paper proposes the optimal sizing of standalone microgrid hybrid renewable energy resources (HRES), considering the minimization of the levelized cost of energy (LCOE), and maximizing the reliability and resilience of microgrids using a puma optimizer (PO). PO is an optimization algorithm with special mechanisms for the exploration and exploitation phases as well as a hyper-heuristic for phase change that enables the algorithm to balance both phases and adapt to the nature of the problem. hybrid microgrid comprising PV, battery storage, and diesel generators. The results of the simulation obtained by PO were compared with the particle swarm optimization technique (PSO). PSO frequently has the tendency to converge too quickly and can become stuck in local minima. On the other hand, the Puma optimizer uses sophisticated exploration methods and exploitation strategies to increase its resilience to local optima and raise the possibility of finding global solutions. This indicates that the PO has better performance in global search and optimization than PSO.

Ain Shams University (EG), Military Technical College (EG)
Openalex Percentile: Top 37%
Microgrid Control and Optimization
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Co-Optimization of Reliability and Resilience in Hybrid Microgrids — Sherif Helmy, M A Abdel-Rahman, et al. · (2024) | TGRS Research Map | TGRS