A Novel Spline Model Guided Maximum Power Point Tracking Method for Photovoltaic Systems

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

doi:10.1109/tste.2019.2923732

Cited by 26 publications

(10 citation statements)

References 32 publications

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“…being the power to track the DC-link voltage reference as: (11) where e vdc (k) = (v'MPP(k)) 2 -(vdc(k)) 2 , kc vdc is the DC voltage control loop gain, k1 vdc and k2 vdc are defined as a function of the sampling time (Ts) and integrative time (Ti vdc ) as: 12 1 , 1 22…”

Section: ) Power Controlmentioning

confidence: 99%

A Novel Global Maximum Power Point Tracking Method Based on Measurement Cells

Morales¹,

Rohten²,

Garbarino³

et al. 2022

IEEE Access

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Solar power generation has become a solution to mitigate the severe effects on the everyday higher prices of fossil fuels. Additionally, renewable energies operation -as solar-results in a non-polluting way to supply energy, being of special interest into highly contaminated cities and/or countries. The solar energy efficiency injection system is known to be high and mainly due to the power converters effectiveness, which is over of 95% for low and medium voltage. However, this efficiency is reduced when the solar array is partially shaded because traditional maximum power point tracking (MPPT) algorithms are not able to find the maximum power point (MPP) under irregular radiation. This work presents a new algorithm to find the global MPP (GMPP) based upon two MPPTs algorithms used regularly in uniform solar condition (USC), these are the Measuring Cell (MC) and the Perturb and Observe (P&O) methods. The MC ensures to find the surroundings of every local MPP (LMPP) faster and then choose among them the surroundings of the GMPP. Once the surroundings of GMPP are found, the P&O is used to get closer to the GMPP but reducing the DC voltage oscillation to zero hence overcoming the main issue of the P&O. Thus, the proposed algorithm finds the GMPP in two main steps and eliminates the oscillations around the GMPP in steady state, despite the utilization of the P&O. The algorithm is detailed mathematically, illustrated by means of a block diagram, and validated in simulated and experimental results.

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Section: ) Power Controlmentioning

confidence: 99%

A Novel Global Maximum Power Point Tracking Method Based on Measurement Cells

Morales¹,

Rohten²,

Garbarino³

et al. 2022

IEEE Access

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“…The vector modulation approach has the following advantages relative to the traditional modulation technique,  Instant coverage of required switching processes;  Simplified control algorithm;  Maximum voltage transfer coefficient without adding third harmonic components;  No synchronization requirement with input voltage. In addition, the proposed switching algorithm can reduce the number of switching devices involved in the switching process relative to conventional switching strategies [1], [2]. It should be noted that since the modulation strategy is defined directly in terms of the amplitude and phase angle of the output, this method is applicable to highly efficient drive systems.…”

Section: E Space Vector Modulationmentioning

confidence: 99%

“…It is known that the disadvantage of the photovoltaic system is the low power output of solar radiation due to changes in environmental conditions. A cheap and virtual solution for converting solar energy is to track the maximum power point (MPP) of the solar photovoltaic (PV) panel and generate the utmost output power from the PV panel [2][3][4][5][6]. Maximum power point tracking (MPPT) technology has become very fashionable in solar-based systems and, in fact, is the standard technology for autonomous or grid-connected inverters.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Standalone Three-Phase Photovoltaic System with SPWM and SVPWM Techniques

Saravanan*,

Sivakumaran

2020

IJITEE

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Maximum power point tracking is a method employed to produce the utmost power available from the photovoltaic module. To date, many algorithms for maximum power point tracking technique had been stated, every with its own capabilities. In this paper, a Luo converter with high-voltage conversion gain is employed to track photovoltaic panels at maximum power and to step up the voltage to a higher level. This work also aims to validate the performance of the maximum power point tracking system with Luo converter which utilizes incremental conductance techniques. Space vector modulation and sinusoidal pulse width modulations are the control techniques employed to control the three-phase voltage source converter. In order to measure the overall performance indices of the proposed system, a simulation is carried out in MATLAB / Simulink environment.

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“…Driven by the advanced innovations in metaheuristic optimization, different variants have been employed in the MPPT problem, like ant colony optimization algorithm [ 21 ], particle swarm optimization [ 22 ], and differential evaluation [ 23 ]. Further metaheuristic based approaches for the MPPT control of PV involve cuckoo Search Algorithm [ 24 ], Jaya optimizer [ 25 ], and spline model guided MPPT method [ 26 ]. Other methods exploit the common methods and AI techniques as hybrid MPPT control systems [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic

Ali

Mahmoud

Lehtonen

et al. 2021

Sensors

122

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This paper addresses the improvement of tracking of the maximum power point upon the variations of the environmental conditions and hence improving photovoltaic efficiency. Rather than the traditional methods of maximum power point tracking, artificial intelligence is utilized to design a high-performance maximum power point tracking control system. In this paper, two artificial intelligence-based maximum power point tracking systems are proposed for grid-connected photovoltaic units. The first design is based on an optimized fuzzy logic control using genetic algorithm and particle swarm optimization for the maximum power point tracking system. In turn, the second design depends on the genetic algorithm-based artificial neural network. Each of the two artificial intelligence-based systems has its privileged response according to the solar radiation and temperature levels. Then, a novel combination of the two designs is introduced to maximize the efficiency of the maximum power point tracking system. The novelty of this paper is to employ the metaheuristic optimization technique with the well-known artificial intelligence techniques to provide a better tracking system to be used to harvest the maximum possible power from photovoltaic (PV) arrays. To affirm the efficiency of the proposed tracking systems, their simulation results are compared with some conventional tracking methods from the literature under different conditions. The findings emphasize their superiority in terms of tracking speed and output DC power, which also improve photovoltaic system efficiency.

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A Novel Spline Model Guided Maximum Power Point Tracking Method for Photovoltaic Systems

Cited by 26 publications

References 32 publications

A Novel Global Maximum Power Point Tracking Method Based on Measurement Cells

A Novel Global Maximum Power Point Tracking Method Based on Measurement Cells

Simulation of Standalone Three-Phase Photovoltaic System with SPWM and SVPWM Techniques

Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic

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