A Hybrid Photovoltaic-Fuel Cell for Grid Integration With Jaya-Based Maximum Power Point Tracking: Experimental Performance Evaluation

Padmanaban, Sanjeevikumar; Priyadarshi, Neeraj; Holm‐Nielsen, Jens Bo; Hossain, Eklas; Azam, Farooque

doi:10.1109/access.2019.2924264

Cited by 125 publications

(35 citation statements)

References 37 publications

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“…The simultaneous optimal network reconfiguration and capacitor bank placement is studied in [14], [15]. The integration of capacitors and renewable energy sources into the distribution systems is analyzed in [16]. In [17], distributed generators (DGs) and capacitor placement are optimized through weight improved particle swarm optimization (WIPSO) algorithm and gravitational search algorithm (GSA).…”

Section: Introductionmentioning

confidence: 99%

A Two-Loop Hybrid Method for Optimal Placement and Scheduling of Switched Capacitors in Distribution Networks

et al. 2020

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This paper presents a method to find the optimal size and place of the switched capacitors using a hybrid optimization algorithm. The objective function includes the active and reactive power of power plants, the capital and maintenance costs of capacitor banks, and the cost of active and reactive power losses in distribution lines and transformers. The impact of the load model on the optimal sizing and placement of switched capacitors is studied using three different scenarios: In the first scenario, all loads are voltage-dependent; in the second scenario, only a portion of loads are voltage-dependent; in the third scenario, all loads are voltage-independent. The proposed hybrid algorithm incorporates an outer and two inner optimization layers. The outer layer is executed by a genetic algorithm (GA), while the inner layer is performed by a GA, an exchange market algorithm (EMA), or a particle swarm optimization (PSO). The performance of GA-GA, GA-EMA, and GA-PSO hybrid schemes are compared on an IEEE 33-bus test system. Moreover, IEEE 33-bus and 69-bus networks are used to verify the effectiveness of proposed hybrid scheme against the gravitational search algorithm (GSA), a combination of PSO and GSA (PSOGSA), cuckoo search algorithm (CSA), teaching learning-based optimization (TLBO), and flower pollination algorithm (FPA). The results highlight the advantage of the proposed hybrid optimization scheme over the other optimization algorithms. INDEX TERMS Exchange market algorithm (EMA), genetic algorithm (GA), particle swarm optimization (PSO), radial distribution system (RDS), switched capacitors.

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Section: Introductionmentioning

confidence: 99%

A Two-Loop Hybrid Method for Optimal Placement and Scheduling of Switched Capacitors in Distribution Networks

et al. 2020

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“…Moreover, artificial neural network (ANN) based variable step size INC MPPT method has been presented for enhancing the outputted power of FCs in [26]. The JAYA optimization has been proposed for controlling MPPT for hybrid photovoltaic (PV)/FC/ultra-capacitor grid tied systems in [27].…”

Section: Introductionmentioning

confidence: 99%

A Differential Evolution-Based Optimized Fuzzy Logic MPPT Method for Enhancing the Maximum Power Extraction of Proton Exchange Membrane Fuel Cells

Aly

Rezk

2020

IEEE Access

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Recently, fuel cells (FCs) have found vast employment in several applications. However, unique maximum power point tracking (MPPT) exists for each set of operating condition for the efficient operation of FCs. Therefore, this paper presents a differential evolution optimization algorithm (DEOA)based optimized fuzzy-logic (OFLC) MPPT method for enhancing the maximum power extraction of FCs. The various settings for the membership functions (MFs) of the input and output variables are optimized in the proposed method. Thence, more degree-of-freedom can be employed for accurate and fast tracking of the optimal power point of the proton exchange membrane FCs (PEMFCs). Whereas, existing MPPT methods in the literature for FC applications suffer from decreased degree-of-freedom for optimizing their performance, and lack of adaptivity, which obstructs their suitability for the wide operating range of FCs. The superiority and performance effectiveness of the proposed OFLC MPPT method have been validated and compared with the most prevalent techniques in the literature. Moreover, the robustness and sensitivity of the proposed OFLC MPPT method have been tested at various step changes in the water content of membrane and various temperature changes. Moreover, the proposed design of the suggested OFLC MPPT is general and it can be implemented on low-cost microcontrollers. The results verify the superior performance of the proposed OFLC MPPT method from the accurate and fast MPPT extraction, smooth output power with low ripple, and simplicity of the design point of views. INDEX TERMS Differential Evolution Optimization Algorithm (DEOA), fuel cell (FC), fuzzy logic control (FLC), maximum power point tracking.

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“…In addition to standalone PGS, MPPT techniques can also be applied to grid-integrated PV systems [19][20][21][22], hybrid renewable energy systems [23][24][25][26], PV water pumping system [27,28] and Internet of Things [15]. In [19][20][21][22], fuzzy particle swarm optimization MPPT method [19], modified sine-cosine optimized algorithm [20], hybrid adaptive neuro-fuzzy inference system and artificial bee colony algorithm [21], and adaptive neuro-fuzzy inference system-particle swarm optimization-based hybrid MPPT technique [22] have been successfully applied to gridintegrated PV systems to achieve fast convergence and high accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…In [19][20][21][22], fuzzy particle swarm optimization MPPT method [19], modified sine-cosine optimized algorithm [20], hybrid adaptive neuro-fuzzy inference system and artificial bee colony algorithm [21], and adaptive neuro-fuzzy inference system-particle swarm optimization-based hybrid MPPT technique [22] have been successfully applied to gridintegrated PV systems to achieve fast convergence and high accuracy. In [23][24][25][26], a firefly asymmetrical fuzzy logic controller based unified MPPT hybrid controller, hybrid fuzzy particle swarm optimization-based MPPT approach, Jaya-based MPPT method, and Lyapunov controller are utilized in PV-Wind-Fuel Cell hybrid system [23], hybrid PV-wind system [24] and PV-Fuel Cell systems [25,26] to achieve high efficiency and stable operation. Besides, hybrid artificial neural network-fuzzy logic control tuned flower pollination algorithm [27] and hybrid gravitational search algorithm-particle swarm optimization based MPPT method [28] are adopted for MPP tracking in PV water pumping systems.…”

Section: Introductionmentioning

confidence: 99%

A Fast and Efficient Maximum Power Tracking Combining Simplified State Estimation With Adaptive Perturb and Observe

et al. 2020

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This paper proposes a fast and efficient maximum power tracking approach, which synthesizes simplified model-based state estimation (SMSE) with adaptive alpha perturb-and-observe (α-P&O) method, to further raise the capability and efficacy of maximum power point (MPP) tracking (MPPT). Only any two sampling points, in the first stage, on the operating characterization curve are needed to estimate the irradiance and temperature based on SMSE. In the second phase, the operation point is moved directly to the operating voltage command (OVC) derived from the fitting relationship between the voltages at MPP under various insolation intensities, and then the α-P&O method takes over the next tracking to pinpoint the exact MPP. Performances are demonstrated through simulations and experiments. Experimental results reveal that tracking accuracies exceed 99.2 % in all test scenarios. Comparing with conventional and variable step-size P&O methods, the tracking time is shortened by 84.6 % and 76.0 %, improvement of 1.26 % and 0.03 % in tracking accuracy can also be achieved, and the tracking energy loss is reduced by 68.0 % and 52.7 %, respectively. INDEX TERMS Maximum power point tracking, photovoltaic generation system, perturb and observe, state estimation.

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A Hybrid Photovoltaic-Fuel Cell for Grid Integration With Jaya-Based Maximum Power Point Tracking: Experimental Performance Evaluation

Cited by 125 publications

References 37 publications

A Two-Loop Hybrid Method for Optimal Placement and Scheduling of Switched Capacitors in Distribution Networks

A Two-Loop Hybrid Method for Optimal Placement and Scheduling of Switched Capacitors in Distribution Networks

A Differential Evolution-Based Optimized Fuzzy Logic MPPT Method for Enhancing the Maximum Power Extraction of Proton Exchange Membrane Fuel Cells

A Fast and Efficient Maximum Power Tracking Combining Simplified State Estimation With Adaptive Perturb and Observe

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