Cost Analysis and Cost Reduction Opportunities of Residential PV System in the Japan
Bibliographic record
Abstract
Since the start of the Feed-in Tariff Program in July 2012, the PV market in Japan has been growing and annual installed capacity reached 10.8 GW in 2015. Newly installed PV capacity in 2016 is estimated to be 8.6 GW. While the majority segments of the new capacity are commercial, industrial and utility scale application, installed capacity of residential application remains relative low at around 0.9 GW in 2016. With the reduction of Feed-in tariff level, installation cost for residential PV system decreased from 472 Yen/W in the 2012 to 363 Yen/kW (USD 3.15/W) in the third quarter of 2016. However, cost is still higher level in comparison with Germany, Australia and other countries. It is observed that soft cost of residential PV system is one of the major factors for higher cost. In this paper, reasons behind higher cost is analyzed based on residential cost breakdown based on hearings, supply chain survey. This paper also analyze the future cost reduction opportunities by the policy change and other factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".