An Optimized Frequency Control of Green Energy Integrated Microgrid Power System using Modified SSO Algorithm
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Bibliographic record
Abstract
Abstract This paper proposes a modified sperm swarm optimization (MSSO) technique for automatic load frequency control (ALFC) of bio and renewable energy (RE) integrated Microgird (MG) system. A chaotic search based on a one-dimensional (1D) chaotic map is adopted to intensify the exploitation and exploration characteristics of sperm swarm optimization algorithm. The proposed MSSO technique is used to tune the gains of proportional integral derivative controller to regulate the frequency of MG system through minimization of integral time absolute error of frequency deviation. The effectiveness of the technique is evaluated in terms of steady state and transient performance indices for the response of frequency and power deviation. In addition, to validate the robustness, a sensitivity analysis is carried out under varying load condition, change in system parameter, and real-time variation in RE sources. The results obtained for the aforementioned cases show that the proposed MSSO tuned technique outperforms other techniques (Salp swarm algorithm, Particle swarm optimization, and sperm swarm optimization) in terms of steady state and transient indices. The real-time implementation of proposed controller for MG system is validated in Hardware-in-loop analysis with its stability analysis in frequency domain.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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