Optimal Allocation of ESS in Distribution Systems With a High Penetration of Wind Energy
Bibliographic record
Abstract
Environmental concerns and fuel cost uncertainties associated with the use of conventional energy sources have resulted in rapid growth in the amount of wind energy connected to distribution grids. However, based on Ontario's standard offer program (SOP), the utility has the right to curtail (spill) wind energy in order to avoid any violation of the system constraints. This means that any increase in wind energy production over a specific limit might be met with an increase in the wind energy curtailed. In spite of their cost, energy storage systems (ESSs) are considered to be a viable solution to this problem. This paper proposes a methodology for allocating an ESS in a distribution system with a high penetration of wind energy. The ultimate goal is to maximize the benefits for both the DG owner and the utility by sizing the ESS to accommodate all amounts of spilled wind energy and by then allocating it within the system in order to minimize the annual cost of the electricity. In addition, a cost/benefit analysis has been conducted in order to verify the feasibility of installing an ESS from the perspective of both the utility and the DG owner.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".