Novel model and maximum power tracking algorithm for thermoelectric generators operated under constant heat flux

Torrecilla, Marcos Compadre; Montecucco, Andrea; Siviter, Jonathan; Knox, Andrew R.; Strain, Andrew

doi:10.1016/j.apenergy.2019.113930

Cited by 16 publications

(4 citation statements)

References 37 publications

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“…19,20 The perturb & observe (P&O) and hill climbing (HC) MPPT methods represent the commonly applied MPPT controllers for TEG systems in the literature. [21][22][23] The P&O operates in alternating manner for the TEG set point through continuously observing whether the outputted TEG power is increasing or decreasing. Afterward, it decides the operating duty cycle decision with increase/decrease in accordance by fixed step from the current values.…”

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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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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“…Hill climbing (HC), and perturb and observe tracking (P&O) are the frequently used approaches for TEG systems in the literature [9][10][11], thanks to their simplicity in implementation. The main drawback of such approaches is the high fluctuations around the MPP at steady-state condition.…”

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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“…MPPT algorithms used in TEG energy harvesting systems are the same ones applied in PV systems, notably the P&O algorithm, 13‐15 the incremental conductance (IC) algorithm, 15,16 for hybrid MPPT algorithms. Some researchers have made a Hybrid MPPT Algorithm Based on Fractional Short‐Circuit Current Measurement with P&O algorithm which decides intelligently the disconnecting time of the photovoltaic array to measure the short‐circuit current and improve the power ripples of the conventional technique and some other algorithm which is proposed for a constant heat flux 17 . Recently, research studies and algorithmic models have been presented to deal with the problems resulting from irridation of PV systems, and fluctuations in temperature in TEG energy harvesting systems.…”

Section: Introductionmentioning

confidence: 99%

A new maximum power point tracking algorithm based on power differentials method for thermoelectric generators

Yahya

Alomari

2020

Int J Energy Res

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Summary This study uses a new maximum power point tracking (MPPT) algorithm for Thermoelectric Generator (TEG) devices. The MPPT algorithm appears as an essential solution due to the nature and the variation characteristics of the TEG devices under certain conditions. In this paper, the power differentials‐maximum power point tracking (PD‐MPPT) algorithm is proposed to control the boost converter by measuring the output power of TEG devices at both the start and finishing points of the power curve along with making a comparison of these two measured power points. The priority is given to the highest power point until the maximum power point is achieved, and Kalman Filter has been applied to eliminate the oscillation generated from the TEG system. This algorithm does not require any extra circuit to measure the short‐circuit current or the open‐circuit voltage because there is no disconnection between the TEG and the load. The hardware implementation of the power differentials algorithm is demonstrated under steady‐state conditions. Moreover, the PD‐MPPT is an effective and applicable algorithm applied to grab the maximum power point from the Photovoltaics PVs and TEGs systems. The practical experiment is conducted using the “STM32f429” microcontroller to implement the algorithm. During the experiments, the change in the duty cycles is observed. The experimental results show that the PD‐MPPT algorithm performs better under a steady‐state and has the ability to track the maximum power point accurately.

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Novel model and maximum power tracking algorithm for thermoelectric generators operated under constant heat flux

Cited by 16 publications

References 37 publications

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

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

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

A new maximum power point tracking algorithm based on power differentials method for thermoelectric generators

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