A performance evaluation model of a high concentration photovoltaic module with a fractional open circuit voltage-based maximum power point tracking algorithm

Implementation of a modified circuit reconfiguration strategy in high concentration photovoltaic modules under partial shading conditions

Model for the prediction of the maximum power of a high concentrator photovoltaic module

Performance characterization of the optical elements of a high concentration photovoltaic (HCPV) module equipped with point-focus Fresnel lens as the concentrator, a plano concave lens as the secondary optical element and multileg homogeniser capable of uniformly distributing incoming rays onto four multi-junction solar cells have been investigated in this paper. To minimise the optical losses, the application of a singlelayer of Anti-Reflective Coating (ARC) on the optical elements was done, to investigate the effect this had on the optical efficiency of the HCPV module. A ray tracing technique using COMSOL Multiphysics was implemented to evaluate the optical performance of HCPV module. It was determined that the optical efficiency of the system without any ARC being applied was at 79.12% which increased by just under 3% to 81.87% when an ARC was applied to only the multi-leg homogeniser. Subsequently, by applying the ARC to the plano concave lens alone produced a further $\approx 2.7 \%$ increase in the optical efficiency to 84.61%. Finally, the highest increase in optical efficiency was observed when both the multi-leg homogeniser and plano concave lens had an ARC applied to them producing an optical efficiency of 87.48%. This shows that applying an ARC to the optical elements produces an increase of over 8% in the optical efficiency of the HCPV module.

The performance of perovskite solar cells (PSCs) has been improved throughout the years. These photovoltaic (PV) cells can be used to power Internet of Things (IoT) devices for indoor applications. A perovskite PV energy harvesting system with a stand-by battery that continuously powers an IoT device is developed in this work. The battery is required to complement the PSCs when the latter have difficulties in power delivery during low or no irradiance. The performance of the energy harvesting circuit as well as the battery charge and discharge scenarios are investigated. Voltage matching between the PSC and the battery is achieved by a boost converter. The PSC energy harvesting system uses fractional open-circuit voltage (FOCV) based maximum power point tracking (MPPT), which utilizes a Sample and Hold (S&H) circuit. The FOCV technique is based on a comparison of the perovskite PV open circuit voltages and the maximum power points. For each irradiance level, the maximum power point is unique, and this work uses a light-dependent resistor (LDR) to adjust the scaling constant in MPPT. Case studies include various scenarios under 1000 lux fluorescent light and 1 sun irradiance as well as a consideration of different battery states.

Spectrally corrected direct normal irradiance based on artificial neural networks for high concentrator photovoltaic applications

Temperature uniformity enhancement of densely packed high concentrator photovoltaic module using four quadrants microchannel heat sink

Determination of the current–voltage characteristics of concentrator systems by using different adapted conventional techniques

This paper reviews the existing models, connection schemes and maximum power point tracking (MPPT) methods of PV arrays. The partial shading causes significant power losses. It is very difficult to maintain uniform irradiance over the entire PV array, especially for rooftop or building-integrated PV systems. The aspects such as connection scheme of PV array, shading pattern and maximum power point tracking (MPPT) techniques, etc., decide the power generated by the PV array. The conventional MPPT methods are only capable of reaching maximum power point (MPP) in identical insolation situations. Hence, conventional MPP tracking becomes inept due to the existence of several peaks in the P-V characteristics. There are different global maximum power point (GMPP) tracking techniques available in the literature that operate in partial shading scenarios. The reconfiguration of the PV array reduces the number of multiple peaks. This reduction in several peaks makes conventional MPP tracking techniques competent even under partial shading conditions with low implementation complexity and higher tracking speed. This paper can assist scientists in choosing a precise objective-based PV module model, connection schemes and MPP tracking methods out of numerous schemes available in the literature.

This paper discusses the approach taken by Concentrating Technologies (CT), Spectrolab, and Arizona Public Service (APS) to demonstrate a High Concentration Photovoltaic (HCPV) module using Spectrolab's GaInP/GaInAs/Ge triple-junction solar cells. This module is currently connected to an inverter, feeding electricity into the grid at the Solar Test & Research (STAR) facility of APS in Tempe, AZ. Although the module output is small, under 1 kW AC, it is the world's first demonstration of a grid-connected utility module using the same triple-junction solar cell technology that have been used to power satellites and other spacecrafts. This paper also discusses the next steps required to increase module efficiency and enhance its reliability. The economics of the MJ receivers in the context of this module are also discussed.

International audience

Performance of multi-junction cells due to illumination distribution across the cell surface

The increasing demand for energy and the environmental impact from the excessive use of fossil fuels has increased the interest in the renewable research. Solar energy is increasingly becoming an area of interest to researchers due to its abundance source and accessibility. This can be achieved by utilizing photovoltaic (PV) panels. Nevertheless, due to PV nonlinear characteristics, maximum power point tracking (MPPT) algorithm are applied. Many MPPT techniques and improvement have been reported in the literature. In this paper, the impact of temperature and irradiation on the performance of proportionality constants in both fractional open circuit voltage (FOCV) MPPT and fractional short circuit current (FSCC) MPPT techniques are explored. Normally in these algorithms the irradiation effect is solely considered. However, the obtained results show that the value of these constants can be re-tuned for better energy harvesting when both the temperature and the irradiation change.

Solar photovoltaic (PV) system contributes a significant role in meeting power requirements and helps the decentralization of power generation and distribution. The output of the individual photovoltaic module depends on local temperature and irradiance. Since the variation of these parameters depends on the environmental factors, it is difficult to obtain maximum power in all instances. The maximum power point tracking (MPPT) technique is used for tracking the maximum power available at a particular instant. This paper presents the maximum power extraction from a photovoltaic system using Artificial Intelligence (AI) techniques. AI based methods provide a fast dynamic response with high accuracy and mitigate the effects of partial shading. A comparative study is performed for various AI based MPPT techniques such as Fuzzy, Artificial Neural Network (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS). PV module output is interfaced with the resistive load through the Z-Source inverter (ZSI). The ZSI boost the input voltage and provides an AC output voltage. The AI based MPPT techniques have been investigated with conventional Z-source Inverter (ZSI) and Switched Inductor Z-Source inverter (SL-ZSI). A simple boost control technique is employed to control, both conventional and SL Z-source inverter. The performance of the system is verified using MATLAB Simulink.

Hybrid maximum power point tracking techniques: A comparative survey, suggested classification and uninvestigated combinations

A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics