An Iterative Approach to Improve PV Hosting Capacity for a Remote Community
Bibliographic record
Abstract
Remote communities are largely supplied by diesel generating plants. With weak grid and sparse communities over a large geographical area, photovoltaic distributed generation (PVDG) with battery energy storage systems (BESS) can be a viable alternative to grid upgrade while reducing dependence on fossil fuel based generation. This paper presents results of a research study for improving the hosting capacity of distribution systems in remote communities in the northwestern part of Canada. The proposed iterative approach seeks to exploit untapped potential of existing grid infrastructure along with the four-quadrant operation of BESS to maximize the feeder's hosting capacity. The proposed approach uses the headroom of overvoltage limit made available by several voltage regulators in the remote feeder to increase its hosting capacity by as much as 25%. Based on simulations with annual load profiles and site- specific PV generation profiles, it is shown that BESS can further improve the feeder hosting capacity by up to 60% with reactive power support. A comparison is also drawn between the options of grid-upgrade versus the use of BESS for improving hosting capacity. Three BESS technologies are compared with their cost metric for this application.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".