scholarly journals Practical Implementation of the Backstepping Sliding Mode Controller MPPT for a PV-Storage Application

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3539 ◽  
Author(s):  
Marwen Bjaoui ◽  
Brahim Khiari ◽  
Ridha Benadli ◽  
Mouad Memni ◽  
Anis Sellami

This study presents a design and an implementation of a robust Maximum Power Point Tracking (MPPT) for a stand-alone photovoltaic (PV) system with battery storage. A new control scheme is applied for the boost converter based on the combination of the adaptive perturb and observe fuzzy logic controller (P&O-FLC) MPPT technique and the backstepping sliding mode control (BS-SMC) approach. The MPPT controller design was used to accurately track the PV operating point to its maximum power point (MPP) under changing climatic conditions. The presented MPPT based on the P&O-FLC technique generates the reference PV voltage and then a cascade control loop type, based on the BS-SMC approach is used. The aims of this approach are applied to regulate the inductor current and then the PV voltage to its reference values. In order to reduce system costs and complexity, a high gain observer (HGO) was designed, based on the model of the PV system, to estimate online the real value of the boost converter’s inductor current. The performance and the robustness of the BS-SMC approach are evaluated using a comparative simulation with a conventional proportional integral (PI) controller implemented in the MATLAB/Simulink environment. The obtained results demonstrate that the proposed approach not only provides a near-perfect tracking performance (dynamic response, overshoot, steady-state error), but also offers greater robustness and stability than the conventional PI controller. Experimental results fitted with dSPACE software reveal that the PV module could reach the MPP and achieve the performance and robustness of the designed BS-SMC MPPT controller.

Author(s):  
Taouni Abderrahim ◽  
Touati Abdelwahed ◽  
Majdoul Radouane

The energy produced using a photovoltaic (PV) is mainly dependent on weather factors such as temperature and solar radiation. Given the high cost and low yield of a PV system, it must operate at maximum power point (MPP), which varies according to changes in load and weather conditions. This contribution presents an improved maximum power point tracking (MPPT) controllers of a PV system in various climatic conditions. The first is a sliding mode MPPT that designed to be applied to a buck converter in order to achieve an optimal PV array output voltage. The second MPPT is based on the incremental conductance algorithm or Perturb-and-Observe algorithm. It provides the output reference PV voltage to the sliding mode controller acting on the duty cycle of the DC-DC converter. Simulation is carried out in SimPower toolbox of Matlab/Simulink. Simulation results confirm the effectiveness of the sliding mode control MPPT under the parameter variation environments and shown that the controllers meet its objectives.


Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7806
Author(s):  
Mohamed Derbeli ◽  
Cristian Napole ◽  
Oscar Barambones ◽  
Jesus Sanchez ◽  
Isidro Calvo ◽  
...  

This article contains a review of essential control techniques for maximum power point tracking (MPPT) to be applied in photovoltaic (PV) panel systems. These devices are distinguished by their capability to transform solar energy into electricity without emissions. Nevertheless, the efficiency can be enhanced provided that a suitable MPPT algorithm is well designed to obtain the maximum performance. From the analyzed MPPT algorithms, four different types were chosen for an experimental evaluation over a commercial PV system linked to a boost converter. As the reference that corresponds to the maximum power is depended on the irradiation and temperature, an artificial neural network (ANN) was used as a reference generator where a high accuracy was achieved based on real data. This was used as a tool for the implementation of sliding mode controller (SMC), fuzzy logic controller (FLC) and model predictive control (MPC). The outcomes allowed different conclusions where each controller has different advantages and disadvantages depending on the various factors related to hardware and software.


2018 ◽  
Vol 7 (4.35) ◽  
pp. 457
Author(s):  
M. I. Iman ◽  
M. F. Roslan ◽  
Pin Jern Ker ◽  
M. A. Hannan

This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utilized as PV system. Three different MPPT algorithms were implemented in the converter. The result obtained from the converter was analyzed and compared to find the best algorithm to be used to identify the point in which maximum power can be achieve in a PV system. The objective is to reduce the time taken for the tracking of maximum power point of PV application system and minimize output power oscillation. The simulation was done by using MATLAB/Simulink with DC-DC Boost converter. The result shows that FLC method with PSO has achieved the fastest response time to track MPP and provide minimum oscillation compared to conventional P&O and FLC techniques.


2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Fernando Lessa Tofoli ◽  
Dênis de Castro Pereira ◽  
Wesley Josias de Paula

The generation of electricity from photovoltaic (PV) arrays has been increasingly considered as a prominent alternative to fossil fuels. However, the conversion efficiency is typically low and the initial cost is still appreciable. A required feature of a PV system is the ability to track the maximum power point (MPP) of the PV array. Besides, MPP tracking (MPPT) is desirable in both grid-connected and stand-alone photovoltaic systems because the solar irradiance and temperature change throughout the day, as well as along seasons and geographical conditions, also leading to the modification of theI×V(current versus voltage) andP×V(power versus voltage) curves of the PV module. MPPT is also justified by the relatively high cost of the energy generated by PV systems if compared with other sources. Since there are various MPPT approaches available in the literature, this work presents a comparative study among four popular techniques, which are the fixed duty cycle method, constant voltage (CV), perturb and observe (P&O), and incremental conductance (IC). It considers different operational climatic conditions (i.e., irradiance and temperature), since the MPP is nonlinear with the environment status. PSIM software is used to validate the assumptions, while relevant results are discussed in detail.


Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2228
Author(s):  
Carlos Restrepo ◽  
Nicolas Yanẽz-Monsalvez ◽  
Catalina González-Castaño ◽  
Samir Kouro ◽  
Jose Rodriguez

Among all the conventional maximum power point tracking (MPPT) techniques for a photovoltaic (PV) system that have been proposed, incremental conductance (INC) and perturb and observe (P&O) are the most popular because of their simplicity and ease of implementation. However, under partial shading conditions (PSCs), these MPPT algorithms fail to track the global maximum power point (GMPP) and instead converge into local maximum power points (LMPPs), resulting in considerable PV power loss. This paper presents a new hybrid MPPT technique combining the artificial bee colony (ABC) and P&O algorithms named ABC-P&O. The P&O technique is used to track the MPP under uniform irradiance, and only during irradiance variations is the ABC algorithm employed. The effectiveness of the proposed hybrid algorithm at tracking the GMPP, under both uniform and nonuniform irradiance conditions, was assessed by hardware-in-the-loop (HIL) tests employed by a dc–dc boost converter. Then, the ABC-P&O strategy was applied to obtain the voltage reference for the outer PI control loop, which provided the current reference to the discrete-time sliding-mode current control. The ABC-P&O algorithm has a reasonable computational cost, allowing the use of a commercial, low-priced digital signal controller (DSC) with outer voltage and inner current control loops. Many challenging tests validated that the proposed ABC-P&O technique converges fast to the GMPP with high efficiency and superior performance under different PSCs.


2021 ◽  
Vol 19 ◽  
pp. 598-603 ◽  
Author(s):  
C.B. Nzoundja Fapi ◽  
◽  
P. Wira ◽  
M. Kamta ◽  

To substantially increase the efficiency of photovoltaic (PV) systems, it is important that the Maximum Power Point Tracking (MPPT) system has an output close to 100%.This process is handled by MPPT algorithms such as Fractional Open-Circuit Voltage (FOCV), Perturb and Observe (P&O), Fractional Short-Circuit Current (FSCC), Incremental Conductance (INC), Fuzzy Logic Controller (FLC) and Neural Network (NN) controllers. The FSCC algorithm is simple to be implemented and uses only one current sensor. This method is based on the unique existence of the linear approximation between the Maximum Power Point (MPP) current and the short-circuit current in standard conditions. The speed of this MPPT optimization technic is fast, however this algorithm needs to short-circuit the PV panel each time in order to obtain the short circuit current. This process leads to energy losses and high oscillations. In order to improve the FSCC algorithm, we propose a method based on the direct detection of the shortcircuit current by simply reading the output current of the PV panel. This value allows directly calculating the short circuit current by incrementing or decrementing the solar irradiation. Experimental results show time response attenuation, little oscillations, power losses reduction and better MPPT accuracy of the enhanced algorithm compared to the conventional FSCC method.


2018 ◽  
Vol 12 (1) ◽  
pp. 34-38
Author(s):  
Halil Erol ◽  
Mahmut Uçman

The Power-Voltage characteristic of a photovoltaic (PV) array exhibits non-linear behaviour when exposed to uniform solar irradiance. Maximum Power Point (MPP) tracking is challenging due to the varying climatic conditions in a solar PV system. Moreover, the tracking algorithm becomes more complicated due to the presence of multiple peaks in the power voltage characteristics under the condition of partial shading. This research is devoted to the Stochastic Beam Search (SBS) based algorithm and Stochastic Hill Climbing (SHC) for a maximum power point tracking (MPPT) at a partial shading condition in the PV system. To give a partial shading effect over the entire array of a PV system, a mast is placed in front of the modules. The modules in the array are connected in such a way that one does not need to rewire the electrical connection during the rearrangement of modules. It is validated that the power generation performance of an array under a moving shading condition is increased. Furthermore, it is observed that the SHC method outperforms the SBS method in the MMP tracking.


Sign in / Sign up

Export Citation Format

Share Document