Techno–economic–environmental feasibility study of a photovoltaic system in northern part of Iran including a two-stage multi-string inverter with DC–DC ZETA converter and a modified P&O algorithm
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Inverters play a significant role in the configuration of grid-connected photovoltaic (PV) systems. The perturb-and-observe (P&O) algorithm is a common method to derive the maximum power from grid-connected inverters; however, the possibility of losing maximum power due to sudden changes in radiation is a significant drawback of this control strategy. To overcome this barrier, the two-stage multi-string inverter using the ZETA DC–DC converter and a novel P&O algorithm has been proposed to increase the efficiency of these systems. The proposed inverter has been simulated in MATLAB/SIMULINK software. To investigate the performance of the proposed inverter, technical, environmental and economic feasibility studies have been performed for the construction of a 5-kW PV power plant in a northern city of Iran (Sari) using the RETScreen software developed by Natural Resources Canada. On the other hand, most feasibility studies for power-plant construction are based on the concept of inverter peak efficiency, which leads to non-optimal system design due to the short operation duration of the inverter at this value. However, the weighted European efficiency has been used in the feasibility study for more accurate computations. Moreover, the performance of the proposed inverter is compared to that of a two-stage multi-string inverter using a conventional P&O algorithm and the single-stage (central) inverter. The simulation results indicated that the proposed inverter injects 7.6 MW of power into the grid per year. Moreover, it prevents the emission of 88 tons of CO2 (over 20 years), which is equivalent to saving 1883.5 litres of gasoline per year.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it