Comparative Study of Optimization Techniques for Renewable Energy System

Khan, Mohammad Junaid; Mathew, Lini

doi:10.1007/s11831-018-09306-8

Cited by 17 publications

(3 citation statements)

References 69 publications

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“…Amongst the various AI-based optimization techniques, MHAs have proven their accuracy and higher computation efficiency when compared with the other conventional optimization techniques [7]. Therefore, MHAs have been adopted to get the optimum solutions for several engineering problems such as power systems problems, as presented in [95][96][97][98][99][100][101][102][103][104]. Besides, depending on the no freelunch theory [105], many researchers have utilized various algorithms for accurate and effective investigation of the polarization characteristics of the PEMFC, as reported in [5,7,16,57].…”

Section: Mhas For Pemfc's Model Parameters Identificationmentioning

confidence: 99%

Computational Techniques Based on Artificial Intelligence for Extracting Optimal Parameters of PEMFCs: Survey and Insights

Ashraf

Abdellatif

Elkholy

et al. 2022

Arch Computat Methods Eng

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For the sake of precise simulation, and proper controlling of the performance of the proton exchange membrane fuel cells (PEMFCs) generating systems, robust and neat mathematical modelling is crucially needed. Principally, the robustness and precision of modelling strategy depend on the accurate identification of PEMFC’s uncertain parameters. Hence, in the last decade, with the noteworthy computational development, plenty of meta-heuristic algorithms (MHAs) are applied to tackle such problem, which have attained very positive results. Thus, this review paper aims at announcing novel inclusive survey of the most up-to-date MHAs that are utilized for PEMFCs stack’s parameter identifications. More specifically, these MHAs are categorized into swarm-based, nature-based, physics-based and evolutionary-based. In which, more than 350 articles are allocated to attain the same goal and among them only 167 papers are addressed in this effort. Definitely, 15 swarm-based, 7 nature-based, 6 physics-based, 2 evolutionary-based and 4 others-based approaches are touched with comprehensive illustrations. Wherein, an overall summary is undertaken to methodically guide the reader to comprehend the main features of these algorithms. Therefore, the reader can systematically utilize these techniques to investigate PEMFCs’ parameter estimation. In addition, various categories of PEMFC’s models, several assessment criteria and many PEMFC commercial types are also thoroughly covered. In addition to that, 27 models are gathered and summarized in an attractive manner. Eventually, some insights and suggestions are presented in the conclusion for future research and for further room of improvements and investigations.

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Section: Mhas For Pemfc's Model Parameters Identificationmentioning

confidence: 99%

Computational Techniques Based on Artificial Intelligence for Extracting Optimal Parameters of PEMFCs: Survey and Insights

Ashraf

Abdellatif

Elkholy

et al. 2022

Arch Computat Methods Eng

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“…Indeed, the turbine electrical control is essential in order to produce the maximum power during medium and low wind speeds (speed is lower than the nominal one) by applying calculation techniques of the optimal operating point or algorithms of the search for this desired point. In the literature, there are several methods of tracking the maximum power point for wind turbines MPPT (Asri et al, 2019; Khan and Mathew, 2018; Kumar and Chatterjee, 2016; Kumari and Aggarwal, 2019). The commands in speed or power and torque are the main research techniques of maximum power.…”

Section: Introductionmentioning

confidence: 99%

Maximum power point tracking control of wind energy conversion system driving a permanent magnet synchronous generator: Comparative study

et al. 2020

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A wind energy conversion system needs a maximum power point tracking strategy. In the literature, several works have interested in the search for a maximum power point. Generally, their goals are to optimize the rotation speed or the machine torque and the direct current–direct current or the alternating current–direct current duty cycle switchers. This work presents a comparative study between two maximum power point tracking strategies of a wind energy conversion system. The model of the system is studied and developed. It includes a permanent magnet synchronous generator, a diode rectifier and a three-cell direct current–direct current converter. The direct current–direct current is controlled in order to generate the wind maximum power using the tip speed ratio strategy and optimal torque strategy. The effectiveness of the used strategies control scheme is proved by simulation results using MATLAB/Simulink.

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“…Several MPPT methods have been described for photovoltaic (PV) systems [4] and wind turbine (WT) systems [5], including Hill-climbing like Perturb and Observe (P&O), incremental conductance (INC), short-circuit fractional current (SCFC), open-circuit fractional voltage (OCFV) FL, Neural Network (NN), current sweep (CS), Ripple correlation control (RCC), drop control of the DC-Link condenser, maximization of current / load voltage and sliding mode control (SMC). Such methods provide an effective way to solve the MPPT problem but vary widely in sensed parameters, complexity, hardware implementation, convergence speed [6].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Based Maximum Power Point Tracking Controller for Fuel Cell System

Khan¹

2019

EJEE

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Due to the used of fuel cell (FC) system that produces low pollution, low noise, and high efficiency. Though, an FC's voltage-current response is nonlinear, resulting in only one operating point maximizing the output power given a set of operating conditions. In this paper, a comparative analysis is discussed using a smart controller with the Maximum Power Point Tracking (MPPT) of the Proton Exchange Membrane FC (PEMFC) power system. This paper analyzed the electrical characteristics of PEMFC with regard to the fuel flow rate using FL and conventional perturb and observe (P&O) MPPT techniques. In Matlab/Simulink software and analysis system performance, the proposed system with FL based MPPT controller was modelled under smart control and then optimal power with variable fuel rate. The resulting waveforms were evaluated and demonstrate the system's effectiveness.

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Comparative Study of Optimization Techniques for Renewable Energy System

Cited by 17 publications

References 69 publications

Computational Techniques Based on Artificial Intelligence for Extracting Optimal Parameters of PEMFCs: Survey and Insights

Computational Techniques Based on Artificial Intelligence for Extracting Optimal Parameters of PEMFCs: Survey and Insights

Maximum power point tracking control of wind energy conversion system driving a permanent magnet synchronous generator: Comparative study

Artificial Intelligence Based Maximum Power Point Tracking Controller for Fuel Cell System

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