scholarly journals Numerical Performance Evaluation of Solar Photovoltaic Water Pumping System under Partial Shading Condition using Modern Optimization

Mathematics ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 1123 ◽  
Author(s):  
Arfaoui ◽  
Rezk ◽  
Al-Dhaifallah ◽  
Elyes ◽  
Abdelkader
Keyword(s):  
Maximum Power ◽  
Solar Photovoltaic ◽  
Matlab Simulation ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Pumping System ◽  
Water Pumping ◽  
Voltage Curve ◽  
Perturb And Observe ◽  
Power Point

Renewable energy is an attractive solution for water pumping systems particularly in isolated regions where the utility grid is unavailable. An attempt is made to improve the performance of solar photovoltaic water pumping system (SPVWPS) under partial shading condition. Under this condition, the power versus voltage curve has more than one maximum power point (MPP), which makes the tracking of global MPP not an easy task. Two MPP tracking (MPPT) strategies are proposed and compared for tracking MPP of SPVWPS under shading condition. The first method is based on the classical perturb and observe (P&O) and the other method is based on a Salp Swarm Algorithm (SSA). Based on extensive MATLAB simulation, it is found that the SSA method can provide higher photovoltaic (PV) generated power than the P&O method under shading condition. Consequently, the pump flowrate is increased. But, under normal distribution of solar radiation, both MPPT techniques can extract the maximum power but SSA is considered a time-consuming approach. Moreover, SSA is compared with particle swarm optimization (PSO) and genetic algorithm (GA). The obtained results ensure the superiority of SSA compared with PSO and GA. SSA has high successful rate of reaching true global MPP.

scholarly journals An Enhanced Adaptive Perturb and Observe Technique for Efficient Maximum Power Point Tracking Under Partial Shading Conditions

2020 ◽  
Vol 10 (11) ◽  
pp. 3912 ◽  
Author(s):  
Altwallbah Neda Mahmod Mohammad ◽  
Mohd Amran Mohd Radzi ◽  
Norhafiz Azis ◽  
Suhaidi Shafie ◽  
Muhammad Ammirrul Atiqi Mohd Zainuri
Keyword(s):  
High Performance ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Suggested Technique ◽  
Perturb And Observe ◽  
Power Point ◽  
Different Levels

In this paper, we propose enhanced adaptive step size Perturb and Observe (P&O) maximum power point tracking (MPPT) with properly organized comparison sequences which lead to achieving the actual maximum power point (MPP) effectively in the presence of partial shading conditions, taking into account the optimization of all aspects of high-performance MPPT to be novel, simpler, fast, and accurate, with the best efficiency reaching up to almost 100%. In this study, the proposed algorithm, along with a boost converter, was designed and simulated in MATLAB/Simulink to validate the performance of the suggested technique. Four different levels of partial shading conditions were considered for system examination: weak, moderate, and two different levels of strong shading. Each case was applied separately first and then combined in a sequence arrangement to provide robust and comprehensive testing which can provide a guaranteed assessment of the proposed algorithm. The performance of the suggested technique is discussed and compared with that of conventional P&O and conventional incremental conductance (IC) MPPT techniques. The failure of the conventional techniques to work efficiently in the presence of partial shading conditions was observed from the simulation results. Meanwhile, the success of the proposed technique and its high performance were clearly confirmed under partial shading conditions with no increase in complexity or convergence time.

scholarly journals Optimization of Maximum Power Point Tracking Flower Pollination Algorithm for a Standalone Solar Photovoltaic System

2020 ◽  
Vol 39 (2) ◽  
pp. 267-278
Author(s):  
Muhammad Mateen Afzal Awan ◽  
Tahir Mahmood
Keyword(s):  
Weather Conditions ◽  
Maximum Power ◽  
Flower Pollination Algorithm ◽  
Global Maximum ◽  
Solar Photovoltaic ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Flower Pollination ◽  
Multiple Power ◽  
Power Point

Modern-day world is facing problems such as, electricity generation deficiency, mounting energy demand, GHG (Greenhouse Gas) emissions, reliability and soaring prices. To resolve these issues, sustainable and renewable energy resources like SPV (Solar Photovoltaic) would be quite helpful. In this regard, the extraction of maximum power from SPV array in PSC (Partial Shading Weather Conditions) remains a challenge. Creation of multiple power peaks in the P-V (Power-Voltage) curve of a PV array due to partial shading, makes it difficult to track GMPP (Global Maximum Power Point) out of multiple power peaks known as LMPP (Local Maximum Power Points). Conventional algorithms are not able to perform in any condition other than UWC (Uniform Weather Condition). Nature inspired SC (Soft Computing) algorithms efficiently track the GMPP in PSC. The top performing SC algorithm named, FPA (Flower Pollination Algorithm) presents an efficient solution for GMPP tracking in PSCs. In this paper, the efficiency, accuracy and tracking speed of FPA algorithm is optimized. Comparison of the proposed OFPA (Optimized Flower Pollination Algorithm) and the existing FPAs is performed for zero shading condition, weak PSC, strong PSC, and changing weather conditions. In zero shading conditions, improvement of 0.7% in efficiency and 33% in tracking speed is achieved. In weak shading conditions, improvement of 0.97% in efficiency and 32.2% in tracking speed is achieved. In strong shading conditions, improvement of 0.24% in efficiency and 30.6% in tracking speed is achieved. OFPA is also tested for changing weather conditions (entering from Case-1 to Cae-3) and it retains its outstanding performance in the changing weather conditions. Simulations are performed in MATLAB/Simulink.

scholarly journals GA-SMC Technique for Photovoltaic Systems under Non-Homogenous Meteorological Conditions

2020 ◽  
Vol 9 (5) ◽  
pp. 1481-1487
Keyword(s):  
Sliding Mode ◽  
Maximum Power ◽  
Reference Voltage ◽  
Global Maximum ◽  
Sliding Mode Controller ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Hybrid Controller ◽  
Voltage Curve ◽  
Power Point

When the photovoltaic sources are subjected to the partial shading (PS) effect, the PV modules are consequently subjected to the different levels of the irradiation. Indeed, when the phenomenon of the partial shading occurs, the Power-Voltage curve of the PV panel presents several points of maximum power. These points are divided between local and global, where the global maximum point presents the superior maximum, and the local maximum points present the inferior maximums compared to the global one. In fact, the classical Maximum Power Point Tracking (MPPT) techniques can not distinguish the global maximum power point, but can track only the first maximum found at the right hand of the Power-Voltage curve. Thus, in some cases, the classical techniques can cause the high drop of power. To solve this issue, this paper proposes a new approach based on the genetic algorithm (GA), because of its ability to optimize the solar panels’ output power production under the PSC. This optimization method is combined with the robust Sliding Mode Controller (SMC). Here, the GA is used in order to locate and generate the reference voltage corresponding to the global maximum power. While the sliding mode controller is used in order to track the reference voltage by acting on the duty cycle of the SEPIC converter. To examine the performance of the proposed method, the comparison with some hybrid controller, which are P&O-SMC, P&O-BSC, INC-BSC and INC-SMC, is performed. The results show the tracking performances of the proposed method, which are the accuracy and rapidity. Moreover, the results illustrates the ability of the proposed hybrid controller to detect the partial shading and to distinguish the Global Maximum Power Point.

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