ArticleScientific reports2026
Optimal distributed generation allocation considering renewable and load uncertainties.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The integration of distributed generation (DG) into electrical networks offers technical and environmental benefits, including reduced power losses, improved voltage stability, and enhanced reliability. Improper DG placement or sizing, however, can degrade network performance. This study addresses optimal DG allocation under uncertainty, focusing on voltage profiles and stability indices in distribution networks. Variations in photovoltaic (PV) and wind turbine (WT) generation due to solar irradiance and wind speed are considered. Seven optimization algorithms-FVIM, SBO, SCSO, PSO, WOA, ALO, and Harmony Optimization-are applied and compared. Two DG types (active power only and active-reactive power) and a hybrid scenario with capacitor banks are analyzed. The IEEE-33 bus network is used as a test system. Results show reductions in total annual cost ($7.654 M → $2.614 M), voltage deviations (38.376 p.u. → 10.826 p.u.), and power losses (4043.462 kW → 2500.466 kW). Minimum voltage improved from 0.9065 to 0.9538 p.u. WOA achieves the lowest overall cost ($2,614,363), followed by PSO ($2,648,914) and FVIM ($2,699,308). FVIM demonstrates consistent technical performance, with total VDDT of 11.3144 p.u., VSIT of 730.6071, minimum bus voltage of 0.9527 p.u., and total active/reactive losses of 2789.703 kW and 2029.58 kVAr, maintaining a strong balance between economic and operational objectives.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.