No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Design of a Backstepping-Controlled Boost Converter for MPPT in PV Chains
... They are better suited than traditional techniques for improving reaction period, tracking efficiency, and minimizing overshoot in the period of transition, as well as oscillation associated with the MPP due to irradiation and/or temperature fluctuations [10]. (FL) is currently utilized for monitoring the MPP of solar power plants since it is resilient, relatively straightforward to develop, and requires no expertise in a specific model [11]. In this article, theoretical representations of solar energy systems and DC-DC conversion devices are utilized to analyze the FL-based MPPT approach. ...
A maximum power point tracking (MPPT) control procedure constructed based on the Artificial intelligence optimization algorithm is proposed. A mathematical model of photovoltaic cells was established under varying light intensity and ambient temperature. Maximal power tracking control for iterative search using an artificial intelligence (AI) optimization technique Excellent, the artificial intelligence-based MPPT algorithm's principle is presented. Simulation results it shows that the artificial intelligence algorithm can faster and exactly track the maximum power point and remains stable, and compared to Perturb and Observe algorithm under dynamic shadow conditions and artificial intelligence MPPT control method, which has higher tracking accuracy and faster convergence speed. Faster and smaller oscillation amplitude, which is the best response to sunlight conditions for photovoltaic maximum power point tracking technology Flexibility. Using Matlab/Simulink software to build a simulation model of an independent photovoltaic system. It controls variables by keeping the temperature continuous and changes the light intensity to simulate different lighting environments. The identical comparison was conducted between all based MPPT methods such as the fuzzy control approach, demonstrating that the fuzzy control based technique exhibits higher results in terms of efficiency.
... However, the need for prior knowledge regarding uncertainty bounds is still a major drawback of sliding mode control. To ensure global asymptotic stability of the closed-loop system, a nonlinear controller based on Lyapunov method was introduced in [9] and a backstepping controller using Lyapunov function was proposed in [10] for a DC/DC boost power converter. Although the controllers demonstrating satisfactory dynamic performance, their calculations and implementation are complex and challenging. ...
... This inaccuracy can lead to unstable operation of the power converter once the control loop is closed. As a solution to instability problems and ineffective performance, several robust non-linear controllers have been proposed, such as predictive control [3], [4], intelligent control [5], [6], Sliding Mode Control (SMC) [7]- [9], and Back-Stepping (BS) [10]- [13]. These controls provide a fast transient response time and robustness. ...
This paper introduces two improved control algorithms for DC-DC converters. The first one is called “Non-Adaptive Modified Back-Stepping Control” (M-BSC) and the second one is called “Adaptive Modified Back-Stepping Control” (AM-BSC). Both the proposed control schemes allow one to increase the robustness to load and input voltage variations and make the DC-DC converter less sensitive to disturbances concerning the control algorithms available in the literature. The control aims to keep the output voltage at the desired value despite any changes that may occur during its operation. As a case study, the proposed control techniques have been applied to a DC-DC Buck converter. To validate the theoretical results and evaluate the performance of the proposed control algorithms, numerical simulations with four different scenarios have been analyzed: nominal operating conditions, load variations, output voltage tracking, and input voltage variations. The simulation results highlight the good performance of the proposed control algorithms compared to other classical algorithms, improving both the stationary error and the response time.
... Among these approaches, sliding mode of first order are developed and compared to the fuzzy logic (FL) MPPT controller in [15]. However, Backstepping and sliding mode [16][17][18][19][20], neurofuzzy and backstepping [21], passivity-based nonlinear control [22] are nonlinear approaches which provide good stability of the regulated plant. However, these methods inherit important steady state error. ...
The most recent research challenge in sustainable photovoltaic (PV) energy is to maintain a high efficiency of PV arrays. Our contribution in this issue is reducing the power loss caused by environmental condition change and parametric variations. A non linear recursive Backstepping maximum power point tracking (MPPT) controller based on an adjusted variable step Perturb and Observe (P&O) algorithm (VS-Backstepping) is proposed to gather the maximum power with fast converge time from the PV system. The trade off between the high accuracy and the fast tracking speed cannot be realized through single MPPT techniques. Thus this work combines two individual MPPT controllers. However, the accuracy for finding the maximum power is highly related to the part of MPP tracking control using the Backstepping approach as well as the rapidity to reach the MPP is managed with the adjusted variable step P&O algorithm. To further evaluate the effectiveness of the proposed method (VS-Backstepping), simulation and experimental results on a commercial PV panel are presented and compared to an individual fixed step P&O algorithm and a variable step P&O (VS-P&O) controller.
... To obtain the optimal reference voltage, the P&O algorithm is used to extract the maximum energy from the photovoltaic generator. A non-linear BSC aims to track this reference voltage of the photovoltaic generator by regulating the duty cycle µ of the NIBB [17]. BSC being a recursive control law, the calculation of the control law must be done in several steps. ...
... This operation is performed by means of a very efficient controller adaptive backstepping (ABSC), the basic idea of this later is used to design stable controls with a recursive methodology. It must stabilize the origin of a system by means of closed loop control laws and using Lyapunov functions to ensure the stability of the system [1][2][3][4]. ...
Maximum power point tracking (MPPT) is necessary to achieve an optimal exploitation of photovoltaic (PV) system. This paper presents a novel voltage-oriented MPPT (VO-MPPT) method, where the conventional perturb and observe (P&O) algorithm is combined with the proposed external voltage control based on an adaptive integral derivative sliding mode (AIDSM). It is designed with new sliding surface, in addition, the derivative and integral terms are chosen to eliminate the overshoot during fast changes in solar irradiation and to minimize the steady-state fluctuation. Furthermore, an adaptation mechanism is joined to adjust the controller gains under each irradiation level. The proposed MPPT is tested and compared with the most widely used MPPT methods by simulations using MATLAB/Simulink and real time hardware in the loop (HIL) implementation. The results obtained with the proposed MPPT show excellent dynamic performance under fast irradiation changes.
This contribution considers an improved control scheme for three-phase two-stage grid-tied photovoltaic (PV) power systems based on integral sliding mode control (ISMC) theory. The proposed control scheme consists of maximum power point tracking (MPPT), DC-Link voltage regulation and grid current synchronization. A modified voltage-oriented maximum power point tracking (VO-MPPT) method based on ISMC theory is proposed for design of an enhanced MPPT under irradiation changes. Moreover, a novel DC-Link voltage controller based on ISMC theory is proposed to achieve good regulation of DC-Link voltage over its reference. To inject the generated PV power into the grid with high quality, a voltage-oriented control based on space vector modulation (SVM) and ISMC (VOC-ISMC-SVM) has been developed to control the grid current synchronization. Numerical simulations are performed in a MATLAB/SimulinkTM (R2009b, MathWorks, Natick, MA, USA) environment to evaluate the proposed control strategy. In comparison with conventional control schemes, the developed control strategy provides an accurate maximum power point (MPP) tracking with less power oscillation as well as a fast and an accurate DC-Link regulation under varying irradiation conditions. Moreover, the transfer of the extracted power into the grid is achieved with high quality.
This paper focuses on the control of three phase dual-stage grid connected photovoltaic (PV) system. The control objective is to generate the maximum power from PV arrays under irradiation changes and transfer it into the grid, in addition to the reactive power demanded by the grid operator while providing high grid current quality. A quick and accurate control method based on variable step size incremental conductance and predictive current control (VS-INC/PCC) is proposed and applied to the first stage (DC-DC Boost converter) in order to achieve a quick maximum power point tracking MPPT with less power oscillations. Furthermore, a voltage-oriented control based on both predictive control strategy and space vector modulation SVM (PS-VOC) is applied to the second stage (Two-level inverter) whose objective is to control the d-q axis grid currents. The proposed system is simulated using Matlab/Simulink and Simpower packages. As results, the proposed MPPT provides a quick and accurate tracking with significant oscillation reduction at the MPP under irradiation changes in comparison with the conventional methods. Besides, the injection of the extracted PV power and the reactive power demanded by the grid operator are provided with high current quality due to the capability of the proposed PS-VOC control method.
Maximum power point tracking (MPPT) techniques play an essential role in efficiency improvement of photovoltaic systems. The present paper deals with the development of an enhanced MPPT algorithm in order to achieve maximum power point for any climatic conditions. The method under study is composed of two advanced approaches: a modified perturb and observe (MPO) algorithm based on a fuzzy logic controller for ensuring an optimal output of photovoltaic current and a model predictive current controller. The MPO algorithm is implemented with minimum rules to reduce the computational burden. The proposed MPPT is discussed, verified, and compared through simulations under the MATLAB/Simulink™ environment, which presents a high dynamic performance under various conditions. Furthermore, a hardware validation using a dSPACE DS 1104 board is built in order to test and to assess, in real-time, the proposed MPPT.
Tracking the maximum power point (MPP) has a great interest in the study of photovoltaic (PV) systems. This task is very difficult due to the non linearity of PV current-voltage characteristics which are dependent on the temperature and irradiation conditions. The sliding mode control (SMC) based MPPT with two different step sizes designed for Boost-type DC/DC converter method is investigated in this paper. The robustness of the proposed controller is tested under rapidly changing solar radiations. The SMC based MPPT is compared to perturb and observe (P&O) method and to incremental conductance (IncCond) method. The PV-MPPT system is simulated by Matlab/Simulink environment and verified by practical implementation within DS1104 R&D controller board. The simulation and experimental results are satisfactory and demonstrate that the new SMC can follow the PV peak power at different operating conditions with best performance.
The world is fast becoming a global village due to the increasing daily requirement of energy by all population across the world while the earth in its form cannot change. The need for energy and its related services to satisfy human social and economic development, welfare and health is increasing. Returning to renewables to help mitigate climate change is an excellent approach which needs to be sustainable in order to meet energy demand of future generations. The study reviewed the opportunities associated with renewable energy sources which includes: Energy Security, Energy Access, Social and Economic development, Climate Change Mitigation, and reduction of environmental and health impacts. Despite these opportunities, there are challenges that hinder the sustainability of renewable energy sources towards climate change mitigation. These challenges include Market failures, lack of information, access to raw materials for future renewable resource deployment, and our daily carbon footprint. The study suggested some measures and policy recommendations which when considered would help achieve the goal of renewable energy thus to reduce emissions, mitigate climate change and provide a clean environment as well as clean energy for all and future generations.
The output power induced in the photovoltaic modules depends on solar radiation and temperature of the solar cells. Therefore, to maximize the efficiency of the renewable energy system, it is necessary to track the maximum power point of the PV array. This paper proposes a new method of maximum power point tracking using fuzzy logic for photovoltaic system. It uses a sampling measure of the PV array power and voltage then determines an optimal increment required to have the optimal operating voltage which permits maximum power tracking. This method carries high accuracy around the optimum point when compared to the conventional perturbation and observation algorithm then it assures fast and fine tracking. The system is composed a solar panel, a DC/DC converter, batteries storage and resistive load. A simulation study is presented under variable weather conditions. The obtained results are presented and discussed
This paper presents a control of three phase two-stage grid-connected photovoltaic (PV) system based on predictive control strategy. The main goals are: extract the maximum power point (MPP) delivered by PV arrays under irradiation variations and to inject it into the network with a high grid current quality. MPPT current oriented loop based on predictive control strategy is proposed and applied into the first stage (DC–DC Boost converter) in order to achieve high performance tracking. Furthermore, a Voltage oriented control based on predictive control strategy and space vector modulation SVM (VOC-PC-SVM) is applied into the second stage (Tow-level inverter) in order to control the grid currents. The proposed system is simulated using Matlab/Simulink and Simpower system packages. The obtained results prove that the proposed control strategy provides high performance control in term of MPP tracking and grid current quality under irradiation variations in accordance with international standards (IEEE-519).
According to the characteristics of photovoltaic (PV) array and the prevailing maximum power tracking control methods, a controlling algorithm of the maximum power point tracking (MPPT) based on the fuzzy algorithm, variable step-size perturbation observing, was proposed in this paper. The method is divided into two stages in the view of the error and the error rate of the system, the first step is to apply perturb and observe (P&O)-arithmetic which sets up a larger step-size and get close to the maximum power point as fast as possible. On this basis, the second step is to utilize the variable step-size to close the maximum power point as precise as possible and get the optimum. The estimating of the working status, which can respond to the variance of the environment, was introduced into the system, and the fast tracking performance and the stability in photovoltaic system were inproved.
The world is fast becoming a global village due to the increasing daily requirement of energy by all population across the world while the earth in its form cannot change. The need for energy and its related services to satisfy human social and economic development, welfare and health is increasing. Returning to renewables to help mitigate climate change is an excellent approach which needs to be sustainable in order to meet energy demand of future generations. The study reviewed the opportunities associated with renewable energy sources which includes: Energy Security, Energy Access, Social and Economic development, Climate Change Mitigation, and reduction of environmental and health impacts. Despite these opportunities, there are challenges that hinder the sustainability of renewable energy sources towards climate change mitigation. These challenges include Market failures, lack of information, access to raw materials for future renewable resource deployment, and our daily carbon footprint. The study suggested some measures and policy recommendations which when considered would help achieve the goal of renewable energy thus to reduce emissions, mitigate climate change and provide a clean environment as well as clean energy for all and future generations.
The contents of the book are a review of dynamical systems,the principal stability and boundedness results on metric spaces, specialized stability and boundedness results on metric spaces, applications to discrete-event systems, stability results for finite-dimensional dynamical systems, applications to the stability of finite-dimensional dynamical systems, and stability results for infinite-dimensional systems. Each chapter ends with three final sections: Notes and References, Problems, and Bibliography; these sections are welcome additions that provide insights and perspectives beyond the main content of the chapters. This second edition provides more emphasis on the stability of discrete-event and hybrid systems than the first edition [1] (see [2] for an earlier review), and it emphasizes the use of non-monotonic Lyapunov functions, which the authors developed in their recent research publications. In the Preface, the authors motivate the introduction of non-monotonic Lyapunov functions; this generalization is used to derive a general form of Lyapunov stability results. Further, in the case that the Lyapunov functions are monotonic, standard Lyapunov stability results are obtained. In practice, this extension is primarily motivated by discrete event and hybrid dynamical systems. These new features add significant material to the first edition. This new edition of the book provides a scholarly and comprehensive view of Lyapunov stability that should be accessible to mathematically inclined graduate students and to many researchers in the control field. It is a welcome addition to the published literature.
Maximum power point tracking (MPPT) techniques are used in photovoltaic (PV) systems to extract maximum power from the PV module. There are number of techniques available in literature. In this paper, an adaptive P&O MPPT algorithm is proposed using conventional perturb and observe (P&O) and fractional short circuit current (FSCC) methods. P&O method is widely used because of its low-cost and ease of implementation. The P&O method oscillates close to maximum power point (MPP), when atmospheric conditions are constant or slowly varying. However, when irradiance and temperature are changing rapidly, this method fails to track MPP with rapid speed. In order to consider rapidly varying atmospheric conditions an adaptive control algorithm is proposed, by measuring the short circuit current at different irradiance levels and temperatures. In this proposed method current perturbation is considered instead of voltage perturbation. The proposed method has faster dynamics and improved stability compared to the conventional P&O method. The effectiveness of proposed MPPT algorithm is verified using digital simulations.
With the rapid growth of photovoltaic (PV) systems, stringent standards are envisaged to ensure the safe and efficient generation of power. Therefore, the performance of maximum power point tracking (MPPT) element in PV system under dynamic environmental conditions is very crucial. Hence, this paper evaluates the performance of perturb and observe (P&O) and incremental conductance (IC) MPPT technique on the basis of European Efficiency Test, EN 50530, which is specifically devised for the dynamic performance of PV system. Both techniques are implemented in direct control structure and buck–boost converter is used as MPPT converter. Experiments are conducted using a custom designed PV array simulator. Results reveal that both methods yield almost equivalent dynamic MPPT efficiency. However, in average, the performance of IC method is found to be slightly better that gives 98.5% efficiency compare to 98.3% in P&O. It is also seen that the performance of IC method is very sensitive to its perturbation size, especially at low insolation levels.
This paper shows that the performance of the perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is improved when the electronic converter is correctly controlled. A linearized photovoltaic (PV) array model is used to obtain the transfer function of the electronic converter and to design a voltage compensator for the converter input voltage. A buck converter is used in this work.
In this paper a current controller is used to reject the 100-Hz oscillation of the voltage of the photovoltaic field taking place in any grid connected system. With respect to the classical linear voltage control the current-based sliding-mode approach ensures a wider regulation band but, unfortunately, in presence of a fast irradiance variation the sliding conditions might be violated, so that the operating point, which should be the maximum power point, might not be the expected one. In order to prevent such a drawback, an appropriate voltage compensation loop is used to interface the current-based sliding mode with the Maximum Power Point Tracking algorithm. Simulation and experimental results confirm the goodness of the proposed algorithm.
A new fuzzy-logic controller for maximum power point tracking of photovoltaic (PV) systems is proposed. PV modeling is discussed. Conventional hill-climbing maximum power-point tracker structures and features are investigated. The new controller improves the hill-climbing search method by fuzzifying the rules of such techniques and eliminates their drawbacks. Fuzzy-logic-based hill climbing offers fast and accurate converging to the maximum operating point during steady-state and varying weather conditions compared to conventional hill climbing. Simulation and experimentation results are provided to demonstrate the validity of the proposed fuzzy-logic-based controller.
This paper focuses on the problem of controlling DC-to-DC switched power converter of Boost type. The system nonlinear feature is coped with by resorting to the backstepping control approach. Both adaptive and nonadaptive versions are designed and shown to yield quite interesting tracking and robustness performances. A comparison study shows that backstepping nonlinear controllers perform as well as passivity- based controllers. For both the choice of design parameters proves to be crucial to ensure robustness with respect to load resistance variations. From this viewpoint, adaptive backstepping controllers are more interesting as they prove to be less sensitive to design parameters.
An alternative approach to modeling pulsewidth-modulated (PWM)
DC/DC converters out of basic converter units (BCUs) is presented in
this paper. Typical PWM DC/DC converters include the well-known buck,
boost, buck-boost, Cuk, Zeta, and Sepic. With proper reconfiguration,
these converters can be represented in terms of either buck or boost
converter and linear devices, thus, the buck and boost converters are
named BCUs. The PWM converters are, consequently, categorized into buck
and boost families. With this categorization, the small-signal models of
these converters are readily derived in terms of h parameter (for buck
family) and g parameter (for boost family). Using the proposed approach,
not only can one find a general configuration for converters in a
family, but one can yield the same small-signal models as those derived
from the direct state-space averaging method. Additionally, modeling of
quasi-resonant converters and multiresonant converters can be simplified
when adopting the proposed approach
« Backstepping based control of PWM DC-DC boost power converters », in Industrial Electronics
- H Fadil
- F Giri
H. El Fadil et F. Giri, « Backstepping based control of PWM DC-DC
boost power converters », in Industrial Electronics, 2007. ISIE 2007.
IEEE International Symposium on, 2007, p. 395-400.
- H K Khalil
- J W Grizzle
H. K. Khalil et J. W. Grizzle, Nonlinear systems, vol. 3. Prentice hall
Upper Saddle River, NJ, 2002.