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 9 publications

(2 citation statements)

References 63 publications

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“…Jouili et al 31 presented the most promising technology now in use: a brushless DC motor with a fuel cell stack known as a “PEMFC.” The DC/DC boost circuit of the PEMFC was designed with a powerful “maximum power point tracking” algorithm to improve its performance. Ncir and Akchioui, 32 presented that one of the most difficult components of producing science is developing a reliable optimization control method that can manage a variety of nonlinear system challenges.…”

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

Enhancing performance of interleaved KY converter control in single phase grid‐tied PV systems: A hybrid approach

Shobha,

Narmadhai

2024

Optim Control Appl Methods

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This paper proposes a hybrid COA‐QNN approach for an interleaved KY converter with closed‐loop control for a single‐phase grid‐connected photovoltaic (PV) system. The proposed strategy combines both Cheetah Optimizer algorithm (COA) and Quantum Neural Network (QNN), and it is commonly named the COA‐QNN technique. The interleaved KY converter is connected in the converter side. The primary goal of the COA‐QNN technique is to enhance PQ while maximizing PV electricity being transferred to the grid. The proposed COA is utilized to identify the optimal closed‐loop controller enhancements for on‐grid solar photovoltaic systems. The QNN is used to predict the optimal control parameter. The PV‐interleaved KY converter is managed by a predictive control mechanism to carry out both tasks of PQ enhancement. By then the COA‐QNN technique is implemented on the MATLAB platform and compared with existing methods. Finally, the proposed method shows better results in all methods, such as GWO, FF optimization and combined GWO‐FF.

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Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

Enhancing performance of interleaved KY converter control in single phase grid‐tied PV systems: A hybrid approach

Shobha,

Narmadhai

2024

Optim Control Appl Methods

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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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Optimal Fuzzy-Genetic Self-tuning for Tracking Photovoltaic Peak Power

Douiri,

Chermite

2024

Lecture Notes in Computer Science

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

Cited by 9 publications

References 63 publications

Enhancing performance of interleaved KY converter control in single phase grid‐tied PV systems: A hybrid approach

Enhancing performance of interleaved KY converter control in single phase grid‐tied PV systems: A hybrid approach

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

Optimal Fuzzy-Genetic Self-tuning for Tracking Photovoltaic Peak Power

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