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[5, 2024] 

Journal of Electrical Engineering, Vol 75, 5 (2024) 351-362, https://doi.org/10.2478/jee-2024-0043

Improving primary frequency response in photovoltaic systems using hybrid inertia and intelligent control techniques

Chaouki Messasma – Seif Eddine Chouaba – Bilal Sari – Abdallah Barakat – Luis C. Félix-Herrán

   Low inertia poses a significant challenge to the widespread integration of photovoltaic (PV) systems into the grid, particularly affecting frequency stability. This paper addresses this challenge by proposing an advanced hybrid inertia (AHI) approach, characterized by the integration of real and virtual inertia, combined with the application of intelligent control techniques, to enhance the primary frequency response of a PV system. Internal inertia is provided by a synchronous generator (SG) acting as a compensator, while virtual inertia is generated through a real-time deloading strategy in the PV plant. The AHI is implemented on an isolated grid, utilizing various intelligent control techniques to improve frequency stability. The intelligent techniques employed include genetic algorithms (GA) and fuzzy logic controllers (FLC), which do not require mathematical modeling. This allows them to overcome the nonlinear dynamics of the PV plant and the uncertainties associated with climatic changes. These techniques are applied to the nonlinear components on the generator side, including the governor loop, DC-DC converter loop, and power reserve injection management loop. A frequency fluctuation scenario, induced by generating power perturbations in the proposed system, demonstrates and validates the improvement in frequency stability achieved by the HI and intelligent techniques. All tests are conducted using MATLAB Simulink. Various simulation results show a significant improvement in frequency stability through the incorporation of HI and intelligent control techniques.

Keywords: photovoltaics (PV), synchronous generator (SG), DC-DC boost converter, advanced hybrid inertia (AHI), virtual inertia control (VIC), genetic algorithm (GA), fuzzy logic controller (FLC)


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