The threat of economic grid defection in the U.S. with solar photovoltaic, battery and generator hybrid systems
Bibliographic record
Abstract
Solar photovoltaic (PV) costs have dropped rapidly making PV the fastest growing and least expensive electricity source. Grid-tied PV systems owned by prosumers currently dominate the market primarily due to historical net metering. As utility rate structures shift away from net metering, increase unavoidable costs or restrict grid access, solar prosumers have an increasingly economic path to grid defection. These trends coupled with increasing grid electricity costs and decreases in both PV and battery costs, have made economic grid defection and utility death spirals salient issues. To evaluate the economics and realistic potential of grid defection, this study evaluates eighteen case studies across the U.S. to assess the profitability of grid defection across different irradiation zones using hybrid PV-diesel generator-battery systems. The results show that grid defection is already economically advantageous in some solar-rich locations that have high electric rates. Rate structures and policy, however, can be used to encourage solar-prosumers to remain on the grid rather than grid defect. Utilities that have rate structures that discourage on-grid PV systems, however, may unintentionally incentivize grid defection. If consumers feel that inflation will be high for a long period of time they may use off-grid PV systems as economic hedges. Overall, the results of this study and the clear trends in economic and technical development indicate that regulators must consider mass economic grid defection of PV-diesel generator-battery systems as a near-term possibility and design rate structures to encourage solar producers to remain on the grid to prevent utility death spirals.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".