ArticleScientific reports2026
Improved dung beetle optimized MPPT with novel FOTPIDn(1 + PD) control in grid connected PV for optimal power sharing.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The increasing demand for clean and sustainable energy has led to the widespread adoption of photovoltaic (PV) systems. This method proposes a novel bio-inspired control methodology to increase the performance of grid-connected PV systems under different climatic conditions. The article introduces a maximum power point tracking (MPPT) technique based on an improved dung beetle optimization (IDBO) algorithm for efficient power extraction and inverter management. For the population diversity, the IDBO algorithm uses a multi-strategy mechanism, like Fuch chaotic mapping. The N-Filter, a one plus proportional derivative (1 + PD) controller, and a fractional order tilt proportional integral derivative (FOTPID) controller are designed to improve the inverter’s performance even more. The difficulties in adjusting the controller setting in a non-linear and erratic grid tied PV system are addressed by the suggested hybrid controller. The IDBO algorithm optimizes the inverter control parameters to minimize direct current (DC) link voltage error and total harmonic distortion (THD) in output voltage and current. The simulation outcomes exhibit that the proposed approach expressively improves the power quality and dynamic response under varying environmental conditions. During the irradiance variation, the system attains a steady state power output of 7723.613W, with a peak power of 7741.121 W at 0.397 s, a settling time of 0.049 s, and a minimal overshoot of 0.22%. Under the temperature variation, the steady state output reached 7007.978 W with a peak response time of 0.088 s, settling time of 0.216 s, and an overshoot of 8.316%. This work also provide the mean squared error (MSE) of 0.046, root mean squared error (RMSE) of 0.215 and mean absolute error (MAE) of 0.175. This result confirms the supremacy of the proposed IDBO algorithm optimized control strategy in maintaining system stability, reducing DC-link voltage error, minimizing THD, and improving the overall performance of the grid connected PV system.
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