Evidence map›Paper›PMID 39905168›Full record

ArticleScientific reports2025

Optimal multiobjective design of an autonomous hybrid renewable energy system in the Adrar Region, Algeria.

Abderrahmane Mehallou, Benalia M'hamdi, Abderrahmane Amari, Madjid Teguar, Abdelaziz Rabehi, Mawloud Guermoui, Amal H Alharbi, El-Sayed M El-Kenawy, Doaa Sami Khafaga

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Abderrahmane MehallouApplied Automation and Industrial Diagnostics Laboratory (LAADI), Ziane Achour University of Djelfa, 17000, Djelfa, Algeria.
Benalia M'hamdiApplied Automation and Industrial Diagnostics Laboratory (LAADI), Ziane Achour University of Djelfa, 17000, Djelfa, Algeria.
Abderrahmane AmariZiane Achour University of Djelfa, 17000, Djelfa, Algeria.
Madjid TeguarLaboratoire de Recherche en Electrotechnique, Ecole Nationale Polytechnique, El Harrach, 16200, Algiers, Algeria.
Abdelaziz RabehiLaboratory of Telecommunications and Smart Systems Faculty of Sciences and Technologies, University of Djelfa, 17000, Djelfa, Algeria. rab_ehi@hotmail.fr.
Mawloud GuermouiLaboratory of Telecommunications and Smart Systems Faculty of Sciences and Technologies, University of Djelfa, 17000, Djelfa, Algeria.
Amal H AlharbiDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
El-Sayed M El-KenawySchool of ICT, Faculty of Engineering, Design and Information & Communications Technology (EDICT), Bahrain Polytechnic, PO Box 33349, Isa Town, Bahrain.
Doaa Sami KhafagaDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.

Funding

Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. PNURSP2025R754
6 · The paper itself

Abstract

Extended power outages are not only a nuisance but a critical problem in the modern world, which demands a continuous supply of decent quality electricity. Hybrid renewable energy systems (HRES) within a microgrid (MG) play an important role in delivering energy to rural and off-grid areas and avoiding potential power outages. This research describes an in-depth study of the three phases, design, optimization, and performance analysis of a stand-alone hybrid microgrid for a residential area in a remote area in the province of Adrar in southern Algeria. The system is composed of photovoltaic (PV) modules and a wind turbine, a set of batteries as an energy storage unit, a diesel generator as a backup energy source, and an inverter. This paper investigates four recent methodologies based on Multi-objective Particle Swarm Optimization (MOPSO), Multi-objective Ant Lion Optimizer (MOALO), Multi-objective Dragonfly Algorithm (MODA), and Multi-objective Evolutionary Algorithm (MOGA) to identify the optimal sizing of a microgrid (MG) integrated with hybrid renewable energy sources (RES). The proposed methods are carried out to select the optimal system size, which is a multi-objective problem involving the minimization of the annual cost of electricity (COE), and the loss of power supply probability (LPSP) simultaneously. To achieve this, the proposed methods are combined with energy management strategy (EMS) rules that coordinate energy flows between the various system components. The findings reveal that the MOPSO method has the most efficient hybrid renewable configuration with an annual generation cost of electricity (COE) of 0.2520 $/kWh and loss of power supply probability (LPSP) of 9.164%, which dominates the performance of MOALO (COE of 0.1625$/kWh and LPSP of 8.4872%), MOGA (COE of 0.1577$/kWh and LPSP of 10%), and MODA (COE of 0.02425$/kWh and LPSP of 7.8649%). Furthermore, a sensitivity analysis is performed for the effect that COE variants may have on the design variables.

Indexed as

Energy management strategyHybrid energy systemMicrogridMult objective optimizationRenewable energy

Identifiers

PMID39905168
PMCPMC11794690

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.