An advanced intelligent MPPT control strategy based on the imperialist competitive algorithm and artificial neural networks

Ncir, Noamane; Akchioui, Nabil El

doi:10.1007/s12065-023-00838-y

Cited by 4 publications

(1 citation statement)

References 63 publications

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“…Various MPPT algorithms are used for photovoltaic and wind systems control, such as the imperialist competitive algorithm and artificial neural networks [45], [46], and other studies based on MPPT control [47,48].…”

Section: Integration Of Vrementioning

confidence: 99%

VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene

Tadjeddine,

Bendelhoum,

Bendjillali

et al. 2023

EAI Endorsed Trans Energy Web

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The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system.

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