Energy performance investigation of nanofluid‐based concentrated photovoltaic /
            <scp>thermal‐thermoelectric</scp>
            generator hybrid system

Lekbir, Abdelhak; Hassani, Samir; Mekhilef, Saad; Saidur, R.; Ghani, Mohd Ruddin Ab; Gan, Chin Kim

doi:10.1002/er.6436

Cited by 34 publications

(12 citation statements)

References 47 publications

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“…Nanofluids as cooling fluids in the PVT-TE collectors are important to improve heat transfer properties compared to conventional fluids [39][40][41][42][43][44][45]. The influence of nanofluid use in hybrid PV-TE was performed by Wu et al [39].…”

Section: Introductionmentioning

confidence: 99%

Comparative investigation of concentrated photovoltaic thermal-thermoelectric with nanofluid cooling

Rejeb

Shittu

et al. 2021

Energy Conversion and Management

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Section: Introductionmentioning

confidence: 99%

Comparative investigation of concentrated photovoltaic thermal-thermoelectric with nanofluid cooling

Rejeb

Shittu

et al. 2021

Energy Conversion and Management

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“…Considering Equation (7), the position for i th creature, except that of the first one, is reliant on the position from (i − 1) th agent M t x i and the best one (M t best ). While the manta ray creatures recognize the position of the plankton spot, they amalgamate, forming long chains, then swim in the direction of the prey in a spiral shape, and towards the manta ray in front of them.…”

Section: Mrfo Algorithmmentioning

confidence: 99%

“…TEGs do not require any greenhouse gases to operate, and do not have restrictions on fuels that can be used to generate the needed heat. Lately, various applications have been presented for TEG systems [4,5] and/or by amalgamating them with distinct sources [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification of Optimized Fractional Maximum Power Point Tracking for Thermoelectric Generation Systems Using Manta Ray Foraging Optimization

et al. 2021

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Thermoelectric generation systems (TEGSs) are used to convert temperature difference and heat flow into DC power based on the Seebeck theorem. The basic unit of TEGS is the thermoelectric module (TEM). TEGSs have gained increasing interest in the research fields of sustainable energy. The output power from TEM is mostly reliant on differential temperature between the hot and cold sides of the TEM added to the value of the load. As such, a robust MPPT strategy (MPPTS) is required to ensure that the TEGS is operating near to the MPP while varying the operating conditions. Two main drawbacks may occur in the conventional MPPTSs: low dynamic response, such as in the incremental resistance (INR) method, and oscillations around MPP at steady state, such as in the hill climbing (HC) method. In the current research work, an optimized fractional MPPTS is developed to improve the tracking performance of the TEGS, and remove the two drawbacks of the conventional MPPTSs. The proposed strategy is based on fractional order control (FOC). The main advantage of FOC is that it offers extra flexible time and frequency responses of the control system consent for better and robust performance. The optimal parameters of the optimized fractional MPPTS are identified by a manta ray foraging optimization (MRFO). To verify the robustness of the MRFO, the obtained results are compared with ten other algorithms: particle swarm optimization; whale optimization algorithm; Harris hawks optimization; heap-based optimizer; gradient-based optimizer; grey wolf optimizer; slime mould algorithm; genetic algorithm; seagull optimization algorithm (SOA); and tunicate swarm algorithm. The maximum average cost function of 4.92934 kWh has been achieved by MRFO, followed by SOA (4.5721 kWh). The lowest STD of 0.04867 was also accomplished by MRFO. The maximum efficiency of 99.46% has been obtained by MRFO, whereas the lowest efficiency of 74.01% was obtained by GA. Finally, the main findings proved the superiority of optimized fractional MPPTS compared with conventional methods for both steady-state and dynamic responses.

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“…Recently, several applications have been introduced for TEG systems 9,10 and/or through combining them with different sources. [11][12][13] Recently, significant advancements in TE devices have been found. Hence, increased efficiency is obtained due to the improved materials and geometry of TE systems.…”

Section: Introductionmentioning

confidence: 99%

A MPPT based on optimized FLC using manta ray foraging optimization algorithm for thermo‐electric generation systems

Aly

Rezk

2021

Int J Energy Res

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Energy performance investigation of nanofluid‐based concentrated photovoltaic / thermal‐thermoelectric generator hybrid system

Cited by 34 publications

References 47 publications

Comparative investigation of concentrated photovoltaic thermal-thermoelectric with nanofluid cooling

Comparative investigation of concentrated photovoltaic thermal-thermoelectric with nanofluid cooling

Parameter Identification of Optimized Fractional Maximum Power Point Tracking for Thermoelectric Generation Systems Using Manta Ray Foraging Optimization

A MPPT based on optimized FLC using manta ray foraging optimization algorithm for thermo‐electric generation systems

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