Modeling of Buck Converter Models in MPPT using PID and FLC

PV has become universal for power utility applications in comparison to conventional technologies when it comes to economic competitiveness. As the efficiency of solar PV panel is low, it becomes mandatory to extract maximum power from the PV panel at any given period of time. Maximum Power and efficiency in Photovoltaics can be improved by Maximum Power Point tracking even under distributed temperature and irradiance functions. The paper attempts to compare two different Buck converter models based on predictive control. The two converter models using State space differential equation and direct component in MATLAB/SIMULINK are optimized through PID and FLC to obtain increased gain and desired converter output. A PV system connected with Buck converter using an intelligent controller (FLC) for extracting maximum power at different environmental conditions is proposed and the results are compared with conventional PID controller

On Improved PSO and Neural Network P&O Methods for PV System under Shading and Various Atmospheric Conditions

This article analyzes and compares the integration of two different maximum power point tracking (MPPT) control methods, which are tested under partial shading and fast ramp conditions. These MPPT methods are designed by Improved Particle Swarm Optimization (IPSO) and a combination technique between a Neural Network and the Perturb and Observe method (NN-P&amp;O). These two methods are implemented and simulated for photovoltaic systems (PV), where various system responses, such as voltage and power, are obtained. The MPPT techniques were simulated using the MATLAB/Simulink environment. A comparison of the performance of the IPSO and NN-P&amp;O algorithms is carried out to confirm the best accomplishment of the two methods in terms of speed, accuracy, and simplicity.</p

Support Vector Machine for Photovoltaic System Efficiency Improvement

Photovoltaic panels are promising source for renewable energy. They serve as a clean source of electricity by converting the radiation coming from the sun to electric energy. However, the amount of energy produced by the photovoltaic panels is dependent on many variables including the irradiation and the ambient temperature, leading to nonlinear characteristics. Finding the optimal operating point in the photovoltaic characteristic curve and operating the photovoltaic panels at that point ensures improved system efficiency. This paper introduces a unique method to improve the efficiency of the photovoltaic panel using Support Vector Machines. The dataset, which is obtained from a real photovoltaic setup in Spain, include temperature, radiation, output current, voltage and power for a period of one year. The results obtained show that the system is capable of accurately driving the photovoltaic panel to produce optimal output power for a given temperature and irradiation levels

Predictive control of power electronics converters in renewable energy systems

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A maximum power point tracking scheme for a 1kw stand-alone solar energy based power supply

This paper elucidates one of the tracking schemes for a photovoltaic (PV) systems using Cuk converter operating in discontinuous inductor current mode (DICM) as an interface. A method for efficiently maximizing the output power of a solar panel supplying a load or battery bus under varying meteorological conditions is investigated and results presented therein. The incremental conductance (InCond) method of maximum power point tracking (MPPT) using the Cuks dc to dc converter operating in a discontinuous inductor current mode (DICM) was modeled and studied in relation to PV system interface. Also, laboratory setup was implemented based on the model. This was the main objective of the research. Similarly, the PV simulator was also modeled alongside with Cuk converter operating in DICM. MATLAB/SIMULINK software was used to carry out simulation test. With the incremental conductance method, the problem of sustained oscillation around the maximum power point of the solar panel which is the usual characteristic of the perturbation and observation method is essentially absent. The result disclosed that the power available for the load when MPPT was applied was 1.1 kW which gives a tolerance of 0.1% to the load it powers. But without MPPT, the available power is 0.9 kW using the same number of PV panels and batteries as back up. Hence, MPPT has 17.65% edge in power delivery over non-MPPT PV powered energy supply. An experimental prototype of a 1kW, 230V, 50Hz stand-alone solar based power supply with the incremental conductance scheme was successfully implemented using PIC 16F877 microcontroller, tested and results presented therein. The experimental results agreed with the simulated results.Keywords: Maximum Power point tracking, Cuk converter, Photovoltaic system, PIC 16F877A micro-controller, inverter, batteries

A novel P&OT-Neville’s interpolation MPPT scheme for maximum PV system energy extraction

Photovoltaic (PV) system posses an optimal operating pointing, termed as Maximum Power Point (MPP). Using Maximum Power Point Tracking (MPPT) algorithm, MPP of PV system has to be tracked continuously in any climatic conditions. In general, traditional Perturb and Observe (P&OT) MPP tracker is widely used among existing controllers. But, P&OT fails to harvest maximum power from solar panel, in addition oscillations around MPP results in low efficiency of the PV system. The contradiction involved in the traditional controller can be addressed as P&OT operates with a fixed step size. Hence, with large step size MPP can be reached quickly but the magnitude of oscillations around MPP are high. Similarly, when P&OT operated with tiny step size magnitude of oscillations can be reduced at the same time PV system consumes much time to reach MPP. In order to eliminate the contradiction involved with traditional MPPT scheme and effectively optimize PV system energy, this paper put forwards a hybrid MPPT scheme based on P&OT and Neville interpolation. The proposed scheme is executed in two stages. In the first stage, P&OT is operated with a large step size till the voltage reaches near to maximum point. In the second stage, Neville interpolation is used to find the maximum power point. The performance of the proposed scheme is compared with Golden Section Search (GSS) and P&OT MPPT controllers. With the proposed scheme the convergence time required to reach MPP is improved greatly. Experimental prototype is designed and developed to verify the performance of the proposed scheme. Experimental and simulation results provide enough evidence to show superiority of the proposed scheme. Article History: Received December 15th 2017; Received in revised form July 16th 2018; Accepted September 12th 2018; Available online How to Cite This Article: Bhukya, M. N. and Kota, V. R. (2018) A Novel PandOT-Neville’s Interpolation MPPT Scheme for Maximum PV system energy extraction. International Journal of Renewable Energy Development, 7(3), 251-262 https://dx.doi.org/10.14710/ijred.7.3.251-2

Discrete time modeling and control of DC/DC switching converter for solar energy systems

Distributed generation networks including micro grids benefit from solar cells that are controlled by dc-dc converters. In this research a nonlinear discrete-time model for a buck converter tied to a solar system is derived with unknown internal dynamics. Then, adaptive neural network (NN) controller is employed to enhance stability of dc-dc converter connected to grid-tie inverter (GTI) in the presence of power system disturbances. The NN weights are tuned online by using a novel update law. By using Lyapunov techniques, all signals can be shown to be uniformly ultimately bounded (UUB). In addition, the interaction of the converter with the GTI is investigated to assure stability of the entire interconnected system while the GTI is controlled via a novel stabilizer similar to power system stabilizer (PSS). The proposed nonlinear discrete-time converter controller along with the GTI, equipped with PSS, is simulated in Matlab Simulink environment. The results have highlighted the effectiveness of the proposed modeling and controller design

Parallel-Connected Solar PV System to Address Partial and Rapidly Fluctuating Shadow Conditions

Solar photovoltaic (PV) arrays in portable applications are often subject to partial shading and rapid fluctuations of shading. In the usual series-connected wiring scheme, the residual energy generated by partially shaded cells either cannot be collected (if diode bypassed) or, worse, impedes collection of power from the remaining fully illuminated cells (if not bypassed). Rapid fluctuation of the shading pattern makes maximum power point (MPP) tracking difficult; generally, there will exist multiple local MPPs, and their values will change as rapidly as does the illumination. In this paper, a portable solar PV system that effectively eliminates both of the aforementioned problems is described and proven. This system is capable of simultaneously maximizing the power generated by every PV cell in the PV panel. The proposed configuration consists of an array of parallel-connected PV cells, a low-input-voltage step-up power converter, and a simple wide bandwidth MPP tracker. Parallel-configured PV systems are compared to traditional series-configured PV systems through both hardware experiments and computer simulations in this paper. Study results demonstrate that, under complex irradiance conditions, the power generated by the new configuration is approximately twice that of the traditional configuration. The solar PV system can be widely used in many consumer applications, such as PV vests for cell phones and music players