Exploiting Modelica and the OpenIPSL for University Campus Microgrid Model Development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The need for modeling different aspects of microgrid design and operation has seen the development of various tools over time for different analysis purposes. In this study, Modelica has been adopted as the language of choice to construct a University Campus Microgrid model, utilizing the Modelica Standard Library and the OpenIPSL library. This paper explores the advantages of utilizing Modelica for campus microgrid modeling, emphasizing its benefits and unique features. Modelica features, such as the use of record structures and replaceable templates prove to be particularly advantageous for the modeling task, enabling flexibility and efficiency in the modeling process. Furthermore, comprehensive validation tests are conducted to ensure the accuracy and reliability of sub-systems (e.g. specific power generator systems), before assembling the microgrid network model as a whole. The results demonstrate the efficacy of Modelica in accurately modeling and simulating microgrids, highlighting its potential for advancing microgrid research and development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it