Financial Viability of Residential Photovoltaic and Battery Systems in Californias
Bibliographic record
Abstract
Using a battery on a household level has become easier after the launch of Tesla’s Powerwall. Storing electricity during daytime’s PV overproduction or charging the battery during night with an attractive tariff is the most prominent applications. This paper explores the economic impact of the usage of residential battery storage combined with solar photovoltaics (PV) based on real load data from Northern California, USA. A data-driven, deterministic model to benchmark electricity cost savings for single households is presented and the financial viability of such systems is scrutinized for California. Our results indicate that under current capacity and price points, battery systems have limited financial viability and have a payback period exceeding 20 years in most cases. We deepen our analysis and compare the results of our deterministic model to that of a stochastic model to demonstrate that for an hourly time resolution the deterministic model provides an adequate benchmark for estimating cost (within 3%) savings with a short (1/60th) computation time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".