Effect of partial shading in grid connected solar PV system with FL controller

This paper presents a fast and simple algorithm to extract the maximum power under non-uniform weather from the photovoltaic (PV) based generation systems. The proposed algorithm’s three stages are the scanning stage, the tracking stage, the detecting and avoiding the hidden points stage. The hidden points are caused by a transition between the global maximum power point (GMPP) and a local maximum power point (LMPP) when the partial shading conditions (PSCs) are changed. This transition cannot be observed by monitoring only the power difference of the PV generation system. Simulation results with comparisons to other algorithms developed for global maximum power point tracking (GMPPT) under PSCs are provided to clarify and show the effectiveness of the proposed GMPPT algorithm. The average tracking speed of the proposed algorithm is two times faster than the compared MPPT algorithms, with about 2% more power generated with no additional cost. Moreover, the proposed GMPPT algorithm is implemented in real-time using National Instruments (NI) CompactRIO in field-programmable gate array (FPGA) mode to confirm the applicability of the proposed work.

Section: Pv Based Power Generation Systems 21 Pv Based Power Generati...mentioning

confidence: 99%

An algorithm to extract the maximum power from the PV-based generation systems under non-uniform weather

Smadi

AL-Ramaden

2022

“…The suggested technique evaluates the system's performance using partial shading. Due to the existence of impediments in the proximity of PV systems deployed in an urban context, it is normal for the installation to experience some shading [22], [23]. The influence of shading will also be determined by a number of parameters, including the kind of PV module, bypass diode setup, string configuration, and the form of the shadow.…”

Section: Partial Shading Condition On the Performance Of Photovoltaic Systemsmentioning

confidence: 99%

Improving the performance of photovoltaic module during partial shading using ANN

Hashim

Kareem²,

Al‐Azzawi

et al. 2021

Photovoltaic (PV) panels have drawback of having their peak power reduced when clouds or shade are present. Furthermore, it is only available while the sun shine. Nearby structures, plants, bird droppings, and other obstacles shade operating photovoltaic (PV) devices, effectively reducing the incident solar radiation produced by the modules. When these PV panels are exposed to partial shading, their power efficiency is reduced. A neural network with a kind of artificial neural network is used in the suggested hybrid method (ANN). The key focus of this article is to use environmental effects dependent on partial shading to get the maximum performance from a solar system. The suggested hybrid solution is tested in the MATLAB/Simulink working platform using partial shading test cases, and the efficiency is compared to other approaches. Additionally, the best options for the suggested procedure, current, voltage, and power are examined.

“…Recent studies were interested in the effect of partial shading on the energy efficiency of a GPV and its impact on the functioning of the photovoltaic system to be studied [17], [18]. This phenomenon has pushed researchers [19]- [24] to use methods and algorithms to maximize power delivered by the GPV. In our previous work [25] using the classical 'P&O' alogrithm for rechrche of the MPPT of a photovoltaic generator under partial shading for different irradiation values and a constant temperature for a configuration of one hundred series/parallel photovoltaic modules divided into three groups (G1 to G3) each subjected to different shade levels in  ISSN: 2088-8694 Figure 1.…”

Section: Simulation Of a Gpv Under Partial Shadingmentioning

confidence: 99%

Comparison between classical ‘P&O’ algorithm and FLC of MPPT for GPV under partial shading

Abdelaziz

Abdelkrim

Merah

2021

When the GPV is under partial shading, several peaks appear in the characteristic P-V, namely a GMP and one or more local maximums. The classical algorithm ‘P&O’ MPPT cannot converge on the GMP for low irradiation values and is trapped by tracking down a LMP so making the algorithm ineffective making the algorithm ineffective, in this case under 200 W/m². An alternative objective function is developed to optimize the performance of the FLC by selecting the appropriate gains using PSO. In this simulation the GPV is composed of one hundred modules grouped parallel series (10x10) and subjected to partial shading. The proposed FLC provides better performance for GMP tracking for the chosen shade configuration selected.