Jubaer Ahmed

A Modified P&O Maximum Power Point Tracking Method With Reduced Steady-State Oscillation and Improved Tracking Efficiency

This paper proposes a method to reduce the steadystate oscillation and to mitigate the probability of losing the tracking direction of the perturb and observed (P&O)-based maximum power point tracking (MPPT) for PV system. The modified scheme retains the conventional P&O structure, but with a unique technique to dynamically alter the perturbation size. At the same time, a dynamic boundary condition is introduced to ensure that the algorithm will not diverge from its tracking locus. The modified P&O is simulated in MATLAB Simulink and its performance is benchmarked using the standard MPPT efficiency ηM P P T calculation. Furthermore, the proposed concept is validated experimentally using a buck-boost converter, fed by a solar PV array simulator (PVAS). Based on the EN 50530 dynamic irradiance tests, the proposed method achieved an average ηMP P T almost 1.1% higher than the conventional P&O when irradiance changes slowly and about 12% higher under fast change of irradiance.

An Improved Method to Predict the Position of Maximum Power Point During Partial Shading for PV Arrays

For a photovoltaic (PV) system, it is widely assumed that the peaks of a partially shaded P-V curve are located at the multiples of 0.8Voc, where Voc is the open-circuit voltage of the PV module. However, this assumption - known as the of 0.8Voc model for partial shading - is not necessarily true. If the same model is used to design the maximum power point tracker (MPPT), it is very likely that the algorithm will scan the wrong region of the P-V curve and, hence, an incorrect global peak detection. This paper attempts to prove the inadequacy of the 0.8Voc model when the number of modules in the string increases. Further, the work suggests a simple relationship to predict the correct position of the peaks. It is found that for a string of 20 modules (Voc of 400 V), the maximum deviation between the actual and computed peak is less than 3 V, while for the 0.8Voc model, the deviation reaches up to 50 V. In addition, using the proposed method, the MPPT efficiency can be improved by approximately 2%.

An adaptive P&O MPPT using a sectionalized piece-wise linear P-V curve

This paper describes the adaptive perturb and observe (P&O) MPPT controller based on a sectionalized piece-wise linearization of the P-V curve. The algorithm divides the curve into three non-uniform sections, depending on the location of the maximum power point (MPP). Furthermore, the step size (M) is varied linearly according to the slope of the P-V curve. This results in high tracking speed and reduced steady state oscillations, along with rapid adjustment for the change in weather conditions. The proposed algorithm is implemented using a unidirectional buck-boost DC/DC converter. The model is simulated in MATLAB® Simulink environment for validation. Its efficiency is found to be higher than the conventional P&O MPPT with the fixed step size.

An Enhanced Adaptive P&O MPPT for Fast and Efficient Tracking Under Varying Environmental Conditions

This paper proposes an enhanced adaptive perturb and observe (EA-P&O) maximum power point tracking (MPPT) algorithm for the photovoltaic system. The objective is to mitigate the limitations of the conventional P&O namely, the steady-state oscillation, diverged tracking direction, and inability to detect the global peak during partial shading. A smart oscillation detection scheme and a dynamic boundary condition resolve the first two problems, respectively. Meanwhile, an intelligent prediction method is designed to ensure that the global peak is always correctly tracked. Another feature is the open-circuit voltage is determined without using sensors. The proposed idea is verified using MATLAB simulations by imposing stringent dynamic irradiance and partial shading tests. Moreover, an experimental validation is carried out using a buck–boost converter in conjunction with dSpace DS1104 DSP board. The performance of the algorithm is compared with four prominent MPPT techniques: first, the artificial bee colony; second, modified incremental conduction; third, cuckoo search; and fourth, the hybrid ant colony optimization-P&O. The results show that the proposed method tracks the global peak successfully under distinctive patterns of partial shading, when other algorithms fail occasionally. On top of that, it improves the tracking speed by two to three times, while efficiency is maintained over 99%.

The application of soft computing techniques to improve the performance of maximum power point tracker for PV system during partial shading

Partial shading is a phenomenon, whereby, certain spots of the photovoltaic (PV) array are shaded, while other parts are left uniformly irradiated. It is caused by the shadow that originates from the obstruction of tall building, chimney, tree, telecom tower and utility power lines. Due to its significant influence in reducing the energy yield, partial shading has attracted considerable interest-particularly for the building integrated PV (BIPV) system in urban areas. For large PV power plant, the primary concern is shading due to the passing cloud. For economic and technological reasons, researchers concentrate on maximizing the energy yield during partial shading by adding more intelligence to the maximum power point tracking (MPPT) algorithm of the inverter. Improvement can be achieved in various ways, but recently, the soft computing (SC) techniques have been extensively applied to enhance the efficiency of the MPPT. In view of the growing importance of this issue, this keynote paper will deliberate on six important SC-based MPPT techniques proposed in literature. The main discussions will be on the technological aspects, merits/drawbacks and their comparative performance. It is envisaged that this paper would be a valuable reference source for those who require more information to design an improved MPPT for their inverters.

Comparative study of software and hardware solutions for partial shading in PV system

The energy yield of the PV system is reduced significantly due to partial shading. To mitigate this problem, two approaches, namely the software and hardware solutions are introduced by many researchers. However, no effort thus far has been made to compare their performances. This paper carries out the evaluation of the particle swarm optimization (software solution) and the energy recovery circuit (hardware solution), by subjecting them to various partial shading conditions. The results are benchmarked with the conventional perturb and observe method. It is found that the hardware approve exhibits higher energy yield. However, this is archived with the expense of additional components.