Evidence map›Paper›PMID 39910161›Full record

ArticleScientific reports2025

A modified energy management strategy for PV/diesel hybrid system to reduce diesel consumption based on artificial protozoa optimizer.

Rania G Mohamed, Amal A Hassan, Shady H E Abdel Aleem

Abstract read
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Rania G MohamedDepartment of Electrical Engineering, Institute of Aviation Engineering and Technology, Giza, 12658, Egypt.ORCID http://orcid.org/0000-0002-6394-3829
Amal A HassanDepartment of Photovoltaic Cells, Electronics Research Institute, Cairo, 11843, Egypt. amal.elramly@eri.sci.eg.ORCID http://orcid.org/0000-0003-4828-1668
Shady H E Abdel AleemDepartment of Electrical Engineering, Institute of Aviation Engineering and Technology, Giza, 12658, Egypt.ORCID http://orcid.org/0000-0003-2546-6352

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The photovoltaic (PV)/diesel hybrid system (PV/D-HS) combines solar PV panels with a diesel generator (DG) to meet energy demands, especially in industrial operations. This study introduces an improved energy management strategy designed to optimize the performance of PV/D-HS by reducing diesel consumption, increasing solar energy utilization, and minimizing environmental impact. The strategy dynamically manages power distribution between the PV panels and the DG, adapting to changing solar conditions and energy demands. Doing so reduces the system's reliance on diesel, improves operational efficiency, and supports the integration of cleaner energy sources. Simulation results show significant improvements over traditional approaches: carbon emissions decreased from 62 kg/day with a standalone diesel generator to 38 kg/day, representing a 38% reduction. The solar energy fraction (SEF) increases from 12 to 35%, a 23% improvement in solar energy utilization. These results demonstrate the potential of the proposed strategy to enhance sustainability by lowering greenhouse gas emissions, reducing dependence on fossil fuels, and advancing global efforts to combat climate change. In addition to environmental benefits, the approach reduces operational costs and improves the system's reliability, making it a practical solution for industrial energy needs.

Indexed as

Artificial protozoa optimizerDiesel generatorsHybrid systemModified energy management strategyMulti-objective optimizationPhotovoltaic

Identifiers

PMID39910161
PMCPMC11799208

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.