Firm Power generation 2023 PVPS
Bibliographic record
Abstract
Grid-connected solar power generation, either dispersed or centralized, has developed and grown at the margin of a core of dispatchable and baseload conventional generation. As the penetration of this variable resource increases, the management of the underlying core gradually becomes more complex and costly.The challenge ahead for grid-connected solar is to evolve beyond the margin and the context of underlying conventional generation management. The present report focuses on the challenge of displacement of the underlying conventional generation core by proposing to transform intermittent variable renewable energy (VRE) resources such as solar and wind1 into firm, i.e. effectively dispatchable power generation.Substantiated by in-depth case studies, this report infers that, almost anywhere on the planet, nearly 100% VRE power grids firmly supplying clean power and meeting demand 24/365 are not only possible but would be economically viable, provided that VRE resources are optimally transformed from unconstrained run-of-the weather generation into firm generation. VREs are then capable of entirely displacing all conventional sources economically (provided now emerging grid-forming inverter technology resolves any grid frequency and stability issues resulting from the displacement of conventional rotating power generation). The variable-to- firm transformation enablers include energy storage, the optimum blending of VREs and other renewable resources, geographic dispersion, and supply/demand flexibility. Most importantly this transformation entails overbuilding (see below) and operationally curtailing the VREs ─ a strategy we term applying implicit storage. This strategy ensures acceptable total VRE production costs, which include both generation and grid integration cost.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.140 | 0.051 |
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".