INCREMENTAL CONDUCTANCE MPPT TECHNIQUE WITH BOOST CONVERTER

ABSTRACTThis paper presents the modelling, simulation and hardware implementation of the incremental conductance (INC) maximum power point tracking (MPPT) algorithm. The extraction of maximum power from the solar photovoltaic system was made by integrating the PV module with a DC–DC converter and utilising the MPPT algorithm. In this work, the INC MPPT algorithm is practically implemented on an Arduino Uno board to track the maximum power point (MPP) and also simulated in Matlab/Simulink under the same environmental conditions. The performance of the INC algorithm was also compared with the conventional Perturb and Observe (P&O) MPPT algorithm. The experimental and simulation results are provided for both MPPT techniques. Matlab/Simulink was used for simulation studies.

This paper presents the analysis and operation of a grid connected photovoltaic (PV)energy conversion system with an Adaptive Neuro-Fuzzy Inference System (ANFIS)based maximum power point tracking (MPPT)algorithm. Particle swarm optimization is used to train the membership functions while the least squares algorithm is used to update the consequent parameters of the ANFIS with changing operating condition of PV solar system. The MPPT algorithm maximizes conversion efficiency by adjusting the duty cycle of the buck boost converter to change the output voltage of the solar panel and hence achieving the maximum panel output power for a given set of environmental conditions. The ANFIS is trained by using a hybrid algorithm implementing least squares estimator and particle swarm optimization with data obtained by operating the system using the Perturb and Observe (P&O)MPPT algorithm. The performance of the proposed ANFIS based MPPT algorithm is validated in simulation using MATLAB/Simulink at different operating conditions. It is proven that the designed ANFIS based MPPT scheme achieves a very fast response with little oscillations while transferring maximum power from solar panel to the grid line as compared to the conventional P&O based MPPT scheme.

An on-line MPPT algorithm for rapidly changing illuminations of solar arrays

Due to the Randomness and fluctuation of the photovoltaic (PV) system, Maximum Power Point Tracking (MPPT) algorithm is employed to ensure the maximum power extraction from PV arrays, when it is connected to the grid. The previous studies have indicated that the MPPT algorithm is one of the main causes of interharmonics emission in PV systems. The MPPT algorithm parameters such as perturbation step size inevitably have a strong impact on the interharmonics in the current injected to the grid. In general, a smaller MPPT perturbation step size will reduce the interharmonics emission level, but it will result in poor tracking performance of the MPPT algorithm. Thus, there is a trade-off between the MPPT efficiency and the interharmonics emission in PV system. In this paper, an interharmonics suppression scheme with variable step size MPPT algorithm was proposed. In the suppression scheme, two voltage values near by the MPPT voltage and two tracking step size are preset. When the dc-link voltage of PV is between the two preset voltage values, it means that the PV power near its MPP and the smaller perturbation step size implemented in the MPPT algorithm. Otherwise, the bigger perturbation step size is employed. It can greatly reduce interharmonics emission level and maintain the MPPT efficiency. Simulations have been carried out to verify the effectiveness of the suppression scheme.

Currently, Photovoltaic (PV) energy is the most important energy resource in electrical power applications around the world since it is inexhaustible, clean and pollution free. As the output power from the PV arrays changing with solar irradiance and temperature, so it is necessary to operate the photovoltaic (PV) system at the maximum power point (MPP) to increase the power extraction from the solar panel. For this effective operation and maximum power extraction from a PV system, Maximum power point tracking (MPPT) algorithm plays a vital role by operating the PV energy system near the MPP. In this work, amongst several existing well established MPPT algorithms, the open voltage (OV) based algorithm is chosen for simulation of a PV system using Matlab / Simscape. As maximum power point (MPP) can be attained with a certain amount of load from the PV power system, so load matching is an important concept of MPPT algorithms. Here, the performances of this open voltage (OV) based algorithm method is evaluated for different values of solar radiation and battery was used as load to see the charging performance for the algorithm.

PV irrigation systems have begun to be used intensively today, as energy needs increase. In Partially Shaded Conditions (PSC), the efficiency of the PV system decreases significantly, and traditional Maximum Power Point Tracking (MPPT) algorithms become insufficient. On the other hand, traditional MPPT algorithms require sensors to measure the current and voltage of the PV system. In this study, a sensorless hybrid MPPT algorithm is proposed to reduce system costs and enable operation without the need for PV system data. A simulation study was conducted in the MATLAB/Simulink environment to examine the PV system. The proposed algorithm has been tested under four different PSC scenarios. PV system power, motor speed, and currents were examined under each condition. The high maximum power tracking performance of the proposed algorithm is demonstrated through simulation results. In the steady state, the lowest MPPT efficiency was 95.66%, whereas the highest MPPT efficiency was 99.9%. The MPPT algorithm completed in less than 2 seconds, with the first stage taking 1.3 seconds to reach most of the maximum PV system power. The second stage of the MPPT algorithm was used to achieve maximum power in a narrower area.

Extracting maximum power available from photovoltaic arrays requires the system operating at the maximum power point (MPP). Therefore, finding the MPP is necessary for efficient operation of PV arrays. The MPP changes with multiple environmental factors, mainly temperature and irradiance. Traditionally, the incremental conductance technique with fixed step size was used to find the MPP, which suffers from a trade-off between speed of convergence and accuracy. In this work, we propose an incremental conductance maximum power point tracking (MPPT) algorithm with a variable step size, which adaptively changes the step size after each iteration based on how far away the current operating point is from a new MPP. This mitigates the aforementioned trade-off drastically by achieving faster convergence speed without the loss of accuracy. A series of simulations involving variations in temperature and irradiance were performed using MATLAB, and the speed of convergence and accuracy were compared with the traditional IC technique.

This Harnessing energy from the abundant and free sunlight is now a days a hot-topic among the research community. The availability of cheap solar modules has made it possible to harvest solar energy with better efficiency. The nature of solar modules is nonlinear and therefore the process of impedance matching is essential. The proper impedance matching ensures extraction of the maximum power from solar PV module. Several algorithms are reported in literatures that are used to operate the DC-DC converter around MPP. Maximum power point tracking (MPPT) algorithm acting an significant part in photovoltaic (PV) power generating system because it exploit the output power from a PV generating set for a various climatically conditions. This paper suggested a new modified work for MPPT of PV energy gathering system by using the optimized novel fuzzy logic controller (FLC). In the optimized FLC method, the membership functions tune automatically. In this paper MATLAB simulation effort shows with MPPT controller, a zero voltage and zero current dc to dc buck-boost Luo converter feeding a battery load is achieved. The results demonstrate that the suggested novel rule FLC MPPT in the photovoltaic generating system is valid.

Due to the nature of unpredicted wind speed, determining the optimal generator speed to extract the maximum available wind power at any wind speed is essential. Therefore, it is significant to include an intelligent controller that can track the maximum peak regardless of wind speed. This paper describes the design and development of particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm to variable-speed fixed-pitch wind turbines. Other than the electrical power subjected to maximization, the proposed algorithm does not need any additional sensor. In addition, the MPPT algorithm does not require any prior knowledge of the wind energy system. Unlike the conventional search optimization method, PSO-based MPPT algorithm produces almost negligible oscillations at the maximum power once the true peak is located. In short, the proposed MPPT is simple, flexible, accurate and efficient in maximum wind power tracking. In this work, MATLAB/Simulink simulation package is used to simulate the performance of the proposed MPPT algorithm.

This paper presents modelling and simulation of artificial neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) algorithm for PV system with modified SEPIC converter. The conventional existing MPPT methods are having major drawbacks of high oscillations at maximum power point and low efficiency due to uncertain nature of solar radiation and temperature. These mentioned problems can be solved by the proposed adaptive (ANFIS)-based MPPT. The proposed work involves ANFIS and modified single ended primary inductor converter (SEPIC) to extract maximum power from PV panel. The results obtained from proposed methodology are compared with other MPPT algorithms such as perturb and observe (P&O), incremental conductance (INC) and radial basis function network (RBFN). The improvement in voltage rating of modified SEPIC is compared with conventional SEPIC converter. The result confirms the superiority of the proposed system.

Solar panels are a renewable energy power plant that uses sunlight as its main energy source. The power generated by solar panels are determined by the size of the solar panels, solar radiation and temperature. The power of the solar panels is also determined by the output voltage of the solar panels. To get the maximum output power at any time, it is necessary to adjust the output voltage of the solar panel. This study proposes controlling the maximum output power of solar panels, also known as maximum power point tracking (MPPT) by adjusting the output voltage of the solar panels using a buck converter. The buck converter output voltage regulation at the maximum power point of the solar panel is designed with the Perturbation and Observation (PO) algorithm which is implemented using an Arduino Mega 2560. This MPPT control system is applied to 4x50 Watt-Peak (WP) solar panels which are connected in parallel. The experimental results show that the proposed MPPT control system with the PO algorithm has worked well as expected. This can be seen from the output power generated by the solar panels already around the maximum power point at any change in solar radiation and temperature.

This paper deals with analysis of a photovoltaic panel array characteristics by considering partial shading effects and modeling of perturb and observe MPPT (Maximum Power Point Tracking) algorithm applied boost convertor using Matlab/Simulink. Performance of a photovoltaic (PV) array is affected by temperature, solar insolation, shading and array configuration. Analysis of photovoltaic array characteristics plays an important role in developing an algorithm based devices for Maximum power point tracking (MPPT). Such devices play an important role in efficient usage of available solar energy. The analyzer developed in command window reads panel temperature, irradiance and number of cells exposed to light and generates corresponding PV characteristics. Maximum power point tracking algorithm is used to generate pulse width modulated signal for boost convertor thus extracting the maximum power from the solar PV module and transferring that power to the load. Perturb and observes algorithm is used, which is the simplest algorithm for implementation.

In this study, an intelligent system that quickly and accurately determines a PV array’s maximum power point by using an artificial neural network is discussed. Maximum Power Point Tracking (MPPT) algorithms for solar photovoltaic (PV) systems are being developed so that we can capture maximum power from varying irradiance (sunlight) and temperature to ensure maximum output power. In this work, two methods of such MPPT techniques are discussed and compared using the same standalone PV system. Two algorithms, the perturb and observe (P&O) and artificial neural network (ANN), are explored and contrasted. Both these methods are used to extract the maximum output power from the PV array and then are compared to determine the better and more efficient option in terms of time consumed to execute the algorithm and the efficiency at which the power is extracted. The simulations required for this project are designed, coded, and executed in MATLAB environment. The ANN has a noticeably better responsiveness when compared to P&O.

A photovoltaic generator exhibits nonlinear voltage-current characteristics and its maximum power point varies with solar radiation and cell temperature. A Dc/Dc power converter is used to match the photovoltaic system to the load and to operate the PV (photo voltaic) cell array at maximum power point. Maximum Power Point Tracking (MPPT) is a process which tracks one maximum power point from PV array input, varying the ratio between the voltage and current delivered to get the most power it can. There are different techniques proposed with lot of algorithms are being used in the MPPT controller to extract the maximum power. It is very difficult for the photo voltaic designers, researchers and academic experts to select a particular MPPT technique for a particular application which requires the background knowledge and comparative features of various MPPT algorithms. This paper will be avaluable source for those who work in the photo voltaic generation, so its objective is to review the main MPPT algorithms in practice and analyzes the merits and demerits with various factors.

Analysis and enhancement of PV efficiency with incremental conductance MPPT technique under non-linear loading conditions