PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 19, 2026Journal of Dynamic Systems Measurement and Control0 citations

Impact of Thermal Mismatch on Photovoltaic Module Performance: A Novel Modeling Approach And Configuration Analysis

View Full Paper
IFImed FazaaTBTaoufik BrahimRARiadh Abdelati

Key Points

  • To investigate how uneven temperature affects the performance of photovoltaic modules using various electrical configurations.
  • Developed a novel mathematical approach to model thermal gradients.
  • Analyzed performance for series, parallel, series-parallel, and parallel-series configurations.
  • Conducted experimental validation to compare simulation results.
  • Hybrid configurations (series-parallel and parallel-series) exhibit higher tolerance to thermal mismatches.
  • Significant reduction in power loss observed with proper thermal management.
  • Experimental validation aligns well with simulation outcomes.

Abstract

Abstract This study addresses the effects of uneven temperature distribution on the performance of photovoltaic (PV) modules in series, parallel, series-parallel, and parallel-series electrical configurations. This comprehensive and extensive work presents a new mathematical approach that models thermal gradients caused on by environmental or structural factors. In comparison to pure series or parallel connections, the results indicate that hybrid configurations, in particular, series-parallel and parallel-series, show a higher tolerance to temperature mismatches. In large-scale PV installations, where perfect thermal uniformity is uncommon, the results emphasize the significance of thermal management and configuration selection in reducing power loss from localized heating. Experimenatl validation is carried out showing a good agrremeent with the current simulation model.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Fazaa et al. (2026) studied this question.

synapsesocial.com/papers/6996a887ecb39a600b3ef5b6https://doi.org/10.1115/1.4071138
Ask AI
Helpful
Bookmark
Share
View Full Paper