Long-term seasonal and interannual performance of a residential photovoltaic system in a temperate continental climate
Bibliographic record
Abstract
This study presents a comprehensive performance evaluation of a residential photovoltaic (PV) system located in Târlungeni, Braşov County, Romania, monitored over a 29-month period from January 2023 to May 2025. The 6.48 kWp system comprises 16 Canadian Solar HiKu6 Mono PERC 405 W modules (module efficiency 20.7%) configured in an East-West orientation and connected to a Huawei SUN 2000-5KTL-M0 inverter (maximum efficiency 98.4%). The analysis focuses on seasonal variations and interannual trends in energy production, self-consumption rates, and grid dependency patterns. Data extracted from the Huawei FusionSolar energy management platform reveals a significant increase in solar yield from 47.18 kWh in January 2023 (during the system commissioning phase with partial operational period) to 286.76 kWh in January 2025, reflecting full system maturity. Seasonal patterns show peak solar production of 654.83 kWh in August 2023, with substantial monthly variation driven by climate dynamics typical of temperate continental regions. The self-consumption rate averaged 27%–36% across the monitoring period, while energy independence levels ranged from 17%–22% in winter months to 50%–58% in summer months. Grid dependency followed inverse patterns, with winter months requiring 77%–82% grid import versus 42%–48% in summer. The coefficient of variation for monthly solar yield was 52%, reflecting high seasonal variability characteristic of the temperate continental climate. These findings provide valuable insights for residential PV system planning in temperate continental climates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".