Active power control of smart grids Using Plug-in Hybrid Electric Vehicle
Bibliographic record
Abstract
In conventional power systems, due to lack of communication, power sharing between generators is based on their capacities and economical power flow would not be applied. So, this would be led to rise of fuel consumption and reduced efficiency. For solving this smart micro grid with communication platform is defined. This micro grid consists of load, Plug-in Hybrid Electric Vehicle (PHEV), and Auxiliary Power Unit (APU). APU works in voltage-frequency mode and its role is to fix the voltage and frequency of micro grid. Whereas, PHEVs work in power injection mode and produce power based on the set points that are defined for them. These set points which indicate the contribution of each PHEV in producing power are defined by an economical power flow in a control center known as Central Power Management (CPM). The PHEVs are connected to the Point of Common Coupling (PCC) through Voltage Source Inverters (VSI). Since the active power flow depends on the deference between angles of inverter output voltage and PCC voltage, by controlling this angle deference, active power will be controlled. By comparing the proposed smart method with conventional method, through simulations in MATLAB/Simulink environment, it will be approved smart method is more economical.
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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 | 0.000 | 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 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".