MPPT Using Adaptive Genetic-Fuzzy Logic Control for Wind Power System

Alaoui, Chakib; Saikouk, Hajar; Bakouri, Anass

doi:10.1007/978-3-030-73882-2_162

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…In a stand-alone PV system, Metaheuristic techniques are used to optimize FLC [22]. The PV efficiency is further improved by the research work on Firefly Optimization Algorithm [23][24][25][26], Gray Wolf Algorithm [27][28][29], Grasshopper Algorithm [30], Ant Colony Optimization algorithm [30], Genetic Optimization Algorithm [32,33] and many other algorithms, optimization techniques are also used in the optimal selection of FLC parameters [34]. Ultra-innovative algorithms for determining the output step size and tracking the MPP, have been used in many popular articles such as in [35], the authors have used the cuckoo search algorithm for MPPT.…”

Section: Introductionmentioning

confidence: 99%

Optimized Fuzzy Controller Based on Cuckoo Optimization Algorithm for Maximum Power-Point Tracking of Photovoltaic Systems

et al. 2022

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The performance of a photovoltaic (PV) array depends on temperature, radiation, shading and load size. Conventional maximum power point tracking (MPPT) methods have acceptable efficiencies under uniform conditions (irradiance = 1000 W/m 2 and temprature = 25 °C), but in dynamic weather conditions, load changes, and also in partial shading conditions due to the presence of several local maximum power points (MPP) in the P-V characteristic, the conventional tracking method does not work well in finding the main MPP. To extract maximum power in all conditions, many algorithms have been proposed, all of which have limitations in terms of convergence speed, output power ripple and efficiency. This research proposes an optimized Fuzzy Logic Controller (FLC) based on the Cuckoo Optimization Algorithm (COA) for MPPT under uniform conditions, dynamic weather conditions, partial shading and under load changes. Finally, the research compared the simulation results with four other popular methods. According to the simulation observations and the result, COA-FLC overcomes the mentioned limitations such as low convergence speed, output power ripple and low tracking efficiency in all conditions. Simulations are performed with MATLAB / Simulink software.

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Section: Introductionmentioning

confidence: 99%

Optimized Fuzzy Controller Based on Cuckoo Optimization Algorithm for Maximum Power-Point Tracking of Photovoltaic Systems

et al. 2022

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Artificial Intelligence-based MPPT Techniques in Wind Energy Systems: A Literature Review

Belkhiri,

Ajaamoum,

Cherifi

et al. 2023

2023 3rd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)

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Hybrid Optimized Fuzzy Pitch Controller of a Floating Wind Turbine with Fatigue Analysis

Serrano

Sierra-García

Santos

2022

JMSE

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Floating offshore wind turbines (FOWTs) are systems with complex and highly nonlinear dynamics; they are subjected to heavy loads, making control with classical strategies a challenge. In addition, they experience vibrations due to wind and waves. Furthermore, the control of the blade angle itself may generate vibrations. To address this issue, in this work we propose the design of an intelligent control system based on fuzzy logic to maintain the rated power of an FOWT while reducing the vibrations. A gain scheduling incremental proportional–derivative fuzzy controller is tuned by genetic algorithms (GAs) and combined with a fuzzy-lookup table to generate the pitch reference. The control gains optimized by the GA are stored in a database to ensure a proper operation for different wind and wave conditions. The software Matlab/Simulink and the simulation tool FAST are used. The latter simulates the nonlinear dynamics of a real 5 MW barge-type FOWT with irregular waves. The hybrid control strategy has been evaluated against the reference baseline controller embedded in FAST in different environmental scenarios. The comparison is assessed in terms of output power and structure stability, with up to 23% and 33% vibration suppression rate for tower top displacement and platform pitch, respectively, with the new control scheme. Fatigue damage equivalent load (DEL) of the blades has been also estimated with satisfactory results.

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MPPT Using Adaptive Genetic-Fuzzy Logic Control for Wind Power System

Cited by 3 publications

References 12 publications

Optimized Fuzzy Controller Based on Cuckoo Optimization Algorithm for Maximum Power-Point Tracking of Photovoltaic Systems

Optimized Fuzzy Controller Based on Cuckoo Optimization Algorithm for Maximum Power-Point Tracking of Photovoltaic Systems

Artificial Intelligence-based MPPT Techniques in Wind Energy Systems: A Literature Review

Hybrid Optimized Fuzzy Pitch Controller of a Floating Wind Turbine with Fatigue Analysis

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