Analysis of Key Performance Indicators for Local Electricity Markets’ Design
Why this work is in the frame
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Bibliographic record
Abstract
Local electricity markets (LEMs) are investigated as a solution to provide consumers and prosumers the opportunity to have control over their electricity-related choices and make savings on their energy bills. This work analyzes market design factors, such as the number of update intervals per trading slot, the production-to-consumption (PtC) ratio, and pricing scenarios that influence the performance of an LEM. The decentralized autonomous area agent (D3A) has been used for running LEM simulations under the German regulatory framework. The results of the simulations compared using self-sufficiency, the share of market savings, and the average buying rate revealed that the performance of an LEM is highly dependent on the market design factors. Also, bidding strategy affects the performance of an LEM compared to the share of the local generation. The results imply that LEM can provide better incentives for both prosumers and consumers by providing them with the opportunity to trade their excess generation at prices higher than the feed-in tariff and lower their regular electricity tariff, respectively. With only a 20% reduction in average buying rate, it is also evident that LEMs provide a great opportunity for keeping smaller PV systems active after their 20 years of fixed remuneration under a state-sponsored incentive scheme in Germany.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 it