A Prediction Model-Guided Jaya Algorithm for the PV System Maximum Power Point Tracking

Huang, Chao; Yeung, Ryan Shun-Cheung; Zhang, Zijun; Chung, Henry Shu-Hung; Bensoussan, Alain

doi:10.1109/tste.2017.2714705

Cited by 187 publications

(79 citation statements)

References 30 publications

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“…In order to obtain the optimally fitted parameter vector, Jaya algorithm is introduced to obtain the solution of this optimization problem. Compared with other popular heuristic search algorithms, including PSO algorithm and Genetic algorithm, Jaya algorithm provides the supreme performance in both constraint and unconstraint benchmark problems, 15,[17][18][19] and objective functions of these problems demonstrate different characteristics. Algorithm 1 illustrates the mechanism of Jaya algorithm.…”

Section: Four-parameter Logistic Modelmentioning

confidence: 99%

Wind turbine generation performance monitoring with Jaya algorithm

et al. 2019

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Summary Wind turbine (WT) power curves effectively reflect the generation performance of WTs and depict the relationship between the wind speed and the WT power output. This paper aims at developing an effective method for learning the intrinsic representations of WT power curves, which are robust to external environmental changes. Based on the obtained representations, WT generation performance is monitored. In the proposed approach, data of the supervisory control and data acquisition (SCADA) system is employed to derive the representations. Parametric models of WT power curves are developed using the two‐parameter and four‐parameter logic models. The parameters of these model are identified via Jaya algorithm. To detect the changes of WT power curve model parameters over different time, multivariate control charts are employed. The effectiveness of the proposed WT generation performance monitoring approach is validated based on SCADA data collected from real commercial WTs.

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Section: Four-parameter Logistic Modelmentioning

confidence: 99%

Wind turbine generation performance monitoring with Jaya algorithm

et al. 2019

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“…In addition, many works have investigated the effect of partial shading conditions (PSC) on the extracted PV energy, always with the aim of improving the PV system efficiency. As a result, several GMPPT techniques have been proposed in the literature to make PV systems working at the actual best efficiency under PSC [8][9][10][11][12][13]. On the other hand, to validate the performance of these techniques, it is necessary to test them before implementation.…”

Section: Introductionmentioning

confidence: 99%

Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm

Chalh¹,

Hammoumi²,

Motahhir³

et al. 2020

Energies

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The real implementation of the maximum power point tracking (MPPT) controllers for the photovoltaic (PV) systems is still a big challenge for researchers working in this field. Often, they use simulation tools to assess the performance of their MPPT algorithms before actual implementation. In this context, this paper aims to propose a trusted simulation of a PV system designed under Proteus software. The proposed PV simulator can be used to verify and evaluate the performance of MPPT algorithms with a closer approximation to the real implementation. The main advantage of this model that it contains a real microcontroller, as can be found in reality, so that same code for the MPPT algorithm used in the simulation will be used in real implementation. In contrast, when using (Powersim Software) PSIM or Matlab/Simulink, the code of the algorithm must be rewritten once the real experiment begins, because these tools don't provide a microcontroller or an electronic board in which our algorithm can be implemented and tested in the same way as the real experiment. After this section, a modified Hill-Climbing (HC) algorithm is introduced. The proposed algorithm can avoid the drift problem posed by conventional HC under a fast variation in insolation. The simulation results show that this method presents good performance in terms of efficiency (99.21%) and response time (10 ms), which improved by 1.2% and 70 ms respectively compared to the conventional HC algorithm.

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“…, nominal temperature; N P , number of PV parallel cells; N s , number of PV series cells; I sc , PV module short circuit current; R L , resistive load; I 0 , reverse saturation current; R s , series resistance (Ω) of PV cell; R sh , shunt resistance (Ω) of PV cell; K I , temperature coefficient; V t , thermal voltage; ΔT = T act. 3,9 More recently, further schemes have been developed such as optimized dP-P&O, 10 S-Jaya, 11 fast MPPT, 12 and DMPPT. ; T act , actual temperature; DC, direct current; MPPT, maximum power point trackers; P&O, perturb and observe have inspired, permitted, and even subsidized the established low cost and high efficient PV generating system.…”

Section: Introductionmentioning

confidence: 99%

“…[1][2][3] The main purpose of utilization maximum power point trackers (MPPT) algorithm is to adjust the effective working point of PV panels on their maximum power. In recent research era, many MPPT algorithm strategies are very popular, 1,[3][4][5][6][7][8][9][10][11][12][13] such as the perturb and observe (P&O), 5 hill-climbing, 6 incremental conductance (Inc. Cond.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development and implementation of modified MPPT algorithm for boost converter‐based PV system under input and load deviation

Jana

Kumar

Mishra

et al. 2019

Int Trans Electr Energ Syst

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Summary This paper presents a modified‐maximum power point tracking (M‐MPPT)‐based application of boost converter to extract the power from photovoltaic (PV) module under the variable solar irradiance and load disturbances. The perturb and observe (P&O)‐based MPPT algorithm suffers from an inherent drift in case of an increment in solar irradiance. This drift is observed during the variation in duty cycle under rapid increment in solar irradiance. Modified drift avoidance P&O‐based MPPT is developed to reject the drift effect by incorporating the current (dI) variation in the algorithm along with the power (dP) and voltage (dV) variation, respectively. The proposed novel drift avoidance P&O M‐MPPT algorithm for boost converter is implemented and compared with the conventional P&O algorithm. The drift free performance is demonstrated for the proposed scheme with adaptive duty cycle (ΔD) technique. The simulation study is carried out in MATLAB/Simulink to predict the performance under variations in solar irradiance and load change. Furthermore, the experimental prototype is used to validate the simulation‐based results. The proposed schemes are implemented using the dSPACE 1104. The steady state and transient results are showing the reduction in time to achieve the maximum power by the proposed technique successfully. The real time results are successfully validating the same theoretical findings in this work.

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A Prediction Model-Guided Jaya Algorithm for the PV System Maximum Power Point Tracking

Cited by 187 publications

References 30 publications

Wind turbine generation performance monitoring with Jaya algorithm

Wind turbine generation performance monitoring with Jaya algorithm

Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm

Development and implementation of modified MPPT algorithm for boost converter‐based PV system under input and load deviation

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