Simulation and Hardware Implementation of Incremental Conductance MPPT With Direct Control Method Using Cuk Converter

Safari, Amin; Mekhilef, Saad

doi:10.1109/tie.2010.2048834

Cited by 943 publications

(399 citation statements)

References 28 publications

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“…Several MPPT algorithms heva been proposed in the litherature to extract the maximum energy from PV modules. One of them is the well-known incremental conductance (IncCond) algorithm [20,21]. This method consists in the regulation of the PV voltage according to the MPP voltage reference.…”

Section: A Mppt Control Of Pv Generatormentioning

confidence: 99%

Section: A Mppt Control Of Pv Generatormentioning

confidence: 99%

“…At each iteration, the PV voltage reference is adjusted based on the comparison of the incremental conductance (dI/dV) of the PV source with the negative instantaneous conductance (-I/V). The position of the operating point with respect to the MPP on the PV power curve is known based on the following equation [20]:The IncCond method is simple and easy to implement. But, the convergence speed and the steady state power oscillations depend mainly on the size of the step change in the reference voltage.…”

mentioning

confidence: 99%

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Adaptive Neural Network-Based Control of a Hybrid AC/DC Microgrid

Chettibi

Mellit

Sulligoi

et al. 2016

IEEE Trans. Smart Grid

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-In this paper, the behavior of a grid-connected hybrid AC/DC Microgrid has been investigated. Different Renewable Energy Sources -photovoltaics modules and a wind turbine generator -have been considered together with a Solid Oxide Fuel Cell and a Battery Energy Storage System. The main contribute of this work is the design and the validation of an innovative online-trained artificial neural network based control system for a hybrid microgrid. Adaptive Neural Networks are used to track the Maximum Power Point of renewable energy generators and to control the power exchanged between the Front-End Converter and the electrical grid. Moreover, a fuzzy logic based Power Management System is proposed in order to minimize the energy purchased from the electrical grid. The operation of the hybrid microgrid has been tested in the Matlab/Simulink environment under different operating conditions. The obtained results demonstrate the effectiveness, the high robustness and the self-adaptation ability of the proposed control system. OWADAYS, the wide diffusion of distributed RES presents a new scenario for the regulation of distribution networks and the availability of new technologies for storage systems encourages their use in power systems [1]. In general, a hybrid AC/DC MG integrates different Distributed Generators (e.g. solar power sources, wind power generators, cogenerators, etc.), a energy storage system and a number of AC and DC loads. A FEC can interface the MG with the electric grid and can operate either in a grid-connected or islanded mode. The use of a PMS is crucial to optimize the power flow through the different components of the MG and the exchange of energy with the electric grid. Moreover, since the power produced by RESs depends on the climatic conditions, MPPT algorithms are needed in order to harvest the maximum available energy. The intermittent nature of RESs with the time-varying loads demand make the use of advanced control structures fundamental in order to make the operation of the MG reliable, economic, and secure under different operating conditions. The MG must also guarantee a high quality power supply to both local loads and electrical grid. Index TermsMany works have focused on hybrid microgrids and have proposed a number of control schemes for different mode of operations [2]- [8]. A multiagent-based energy management system to optimizes the economic operation of a MG is presented in [2]. A reactive power sharing algorithm in hierarchical droop control is developed in [3]. A novel coordinated voltage control scheme with islanding capability for a MG is proposed in [4]. adapt to uncertainties and they can be used also when the model of the system to be controlled is not available. Recently, the NNs with the learning capability are widely applied for the control of complex power systems. In [9], a back-propagation NN is applied for the real-time estimation of the wind speed. A novel discrete-time NN controller for the control of DC distribution system is designed in [10]. In [11], a...

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Section: A Mppt Control Of Pv Generatormentioning

confidence: 99%

Section: A Mppt Control Of Pv Generatormentioning

confidence: 99%

mentioning

confidence: 99%

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Adaptive Neural Network-Based Control of a Hybrid AC/DC Microgrid

Chettibi

Mellit

Sulligoi

et al. 2016

IEEE Trans. Smart Grid

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“…The Ćuk converter has low switching losses and the highest efficiency of non-isolated DC-DC converters. Ćuk converters can also provide a better output-current characteristic due to the inductor in the output stage [40]. The input/output relation of the Ćuk converter is given by Equations (10) and (11):…”

Section: Rmo Based Mpptmentioning

confidence: 99%

Efficient Photovoltaic System Maximum Power Point Tracking Using a New Technique

et al. 2016

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Abstract:Partial shading is an unavoidable condition which significantly reduces the efficiency and stability of a photovoltaic (PV) system. When partial shading occurs the system has multiple-peak output power characteristics. In order to track the global maximum power point (GMPP) within an appropriate period a reliable technique is required. Conventional techniques such as hill climbing and perturbation and observation (P&O) are inadequate in tracking the GMPP subject to this condition resulting in a dramatic reduction in the efficiency of the PV system. Recent artificial intelligence methods have been proposed, however they have a higher computational cost, slower processing time and increased oscillations which results in further instability at the output of the PV system. This paper proposes a fast and efficient technique based on Radial Movement Optimization (RMO) for detecting the GMPP under partial shading conditions. The paper begins with a brief description of the behavior of PV systems under partial shading conditions followed by the introduction of the new RMO-based technique for GMPP tracking. Finally, results are presented to demonstration the performance of the proposed technique under different partial shading conditions. The results are compared with those of the PSO method, one of the most widely used methods in the literature. Four factors, namely convergence speed, efficiency (power loss reduction), stability (oscillation reduction) and computational cost, are considered in the comparison with the PSO technique.

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“…However, the conventional incremental conductance method determines the Slope of PV curve by varying the converter duty cycle in fixed or variable step size until the MPP is achieved. In this way, oscillation under rapidly changing solar irradiance is reduced with greater efficiency but due to complicated algorithm speed is slow [6,24].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Incremental Conductance MPPT with Simple Moving Voltage Average Method for Distributed PV System

Ali¹,

Li²,

He³

2016

TOEEJ

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Abstract:In order to harvest photovoltaic energy efficiently, several methods exist, yet most of them failed to address the issues related to extract the maximum power under rapidly changing solar irradiance conditions. In conventional incremental conductance, large step size reduces tracking time but oscillation remains around maximum power point (MPP). However, small step size reduces the oscillation but results in slower tracking speed. This paper proposes a simple moving voltage average (SMVA) technique in conjunction with fixed step direct control incremental conductance (INC) maximum power point tracking (MPPT) method in order to reduce the photovoltaic (PV) generated voltage (V PV ) fluctuation and power losses under mismatching solar irradiance conditions in distributed PV system. Theoretical analysis and the simulation results revealed that the proposed SMVA technique provides fast and accurate tracking under mismatching irradiance conditions. Also, it significantly improves the voltage stability because of extremely small |dP/dV| around MPP as compared to the conventional fixed step direct control incremental conductance MPPT method. Finally, results show that the proposed method is suitable for distributed PV system under intermittent weather conditions not only in terms of voltage stability but also in overall system efficiency.

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Simulation and Hardware Implementation of Incremental Conductance MPPT With Direct Control Method Using Cuk Converter

Cited by 943 publications

References 28 publications

Adaptive Neural Network-Based Control of a Hybrid AC/DC Microgrid

Adaptive Neural Network-Based Control of a Hybrid AC/DC Microgrid

Efficient Photovoltaic System Maximum Power Point Tracking Using a New Technique

Performance Analysis of Incremental Conductance MPPT with Simple Moving Voltage Average Method for Distributed PV System

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