Control Strategies for a Shared Diesel Generator in an Off-Grid Hybrid Power System for Urban Areas in Pakistan
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Bibliographic record
Abstract
This paper presents control strategies for a hybrid off-grid power system serving an urban residential neighborhood in Pakistan, integrating solar photovoltaic (PV) generation, battery storage, and a shared diesel generator. The primary objective is to ensure power reliability and prevent generator overloading in a multi-household configuration. The system was initially optimized for component sizing and cost using HOMER Pro, followed by the development of a detailed dynamic model in MATLAB Simulink/Simscape. Building on this foundation, two complementary control schemes are designed: one for load distribution among the houses and another for battery bank charging. Simulation results demonstrate that the proposed controls stabilize the load supply—ensuring that the diesel generator consistently maintains single-phase voltage around 220 V while sharing a 2kW load per house without exceeding its capacity—and facilitate efficient battery charging on a common 48 V Direct Current (DC) bus. The diesel generator is time-shared across seven households, delivering approximately 9.65 A Root Mean Square (RMS) per active phase, which prevents overloading and ensures continuous power availability. The batteries are charged in a balanced manner whenever solar energy is insufficient, preserving system autonomy. By sharing the diesel generator, the system reduces battery size requirements, thereby lowering both capital and operational costs. This work offers a scalable, cost-effective control strategy for a PV–diesel–battery hybrid microgrid, providing a viable solution to Pakistan’s urban energy shortages.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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