Solar Irradiance Measurements Using Smart Devices: A Cost-Effective Technique for Estimation of Solar Irradiance for Sustainable Energy Systems

Effects of Receiver Parameters on Solar Flux Distribution for Triangle Cavity Receiver in the Fixed Linear-Focus Fresnel Lens Solar Concentrator

The objective of the study is to investigate and optimize the solar flux uniformity of a fixed linear-focus Fresnel lens solar concentrator using a triangle cavity receiver. The effects of receiver parameters including the vertical distance from the cavity opening plane to the Fresnel lens f, receiver internal surface absorptivity αab, end reflection plane reflectivity ρr, solar declination angle δ and solar angle ω on the uniformity factor (UF) of a triangle cavity receiver were carried out. The effects of receiver parameters are evaluated with a significance test of critical factors. The results showed that the increase in f and δ would result in an increase in the UF. The average UF with f = 600, 625, 650, 675 and 700 mm, respectively, are 0.5030, 0.5858, 0.6337, 0.6576 and 0.6784 for ω in range of 0–60°. Moreover, the UF increases as αab decreases when other receiver parameters are constant for the δ of 0–8°. The ρr has a limited effect on the UF until δ becomes relatively larger and ω becomes relatively smaller. Furthermore, ω effects are most significant on the UF, followed by δ, f and αab. Setting a suitable f is the most economical and effective way to improve the UF.

Parameter Extraction of Photovoltaic Module Using Tunicate Swarm Algorithm

In the renewable energy sector, the extraction of parameters for solar photovoltaic (PV) cells is a widely studied area of research. Parameter extraction is a non-linear complex optimization problem for solar PV cells. In this research work, the authors have implemented the Tunicate swarm algorithm (TSA) to estimate the optimized value of the unknown parameters of a PV cell/module under standard temperature conditions. The simulation results have been compared with four different, pre-existing optimization algorithms: gravitational search algorithm (GSA), a hybrid of particle swarm optimization and gravitational search algorithm (PSOGSA), sine cosine (SCA), and whale optimization (WOA). The comparison of results broadly demonstrates that the TSA algorithm outperforms the existing optimization algorithms in terms of root mean square error (RMSE) and convergence rate. Furthermore, the statistical results confirm that the TSA algorithm is a better algorithm in terms of average robustness and precision. The Friedman ranking test is also carried out to demonstrate the competency and reliability of the implemented approach.

Design and Implementation of Fuzzy Compensation Scheme for Temperature and Solar Irradiance Wireless Sensor Network (WSN) on Solar Photovoltaic (PV) System

Photovoltaic (PV) systems need measurements of incident solar irradiance and PV surface temperature for performance analysis and monitoring purposes. Ground-based network sensor measurement is preferred in many near real-time operations such as forecasting and photovoltaic (PV) performance evaluation on the ground. Hence, this study proposed a Fuzzy compensation scheme for temperature and solar irradiance wireless sensor network (WSN) measurement on stand-alone solar photovoltaic (PV) system to improve the sensor measurement. The WSN installation through an Internet of Things (IoT) platform for solar irradiance and PV surface temperature measurement was fabricated. The simulation for the solar irradiance Fuzzy Logic compensation (SIFLC) scheme and Temperature Fuzzy Logic compensation (TFLC) scheme was conducted using Matlab/Simulink. The simulation result identified that the scheme was used to compensate for the error temperature and solar irradiance sensor measurements over a variation temperature and solar irradiance range from 20 to 60 °C and from zero up to 2000 W/m². The experimental results show that the Fuzzy Logic compensation scheme can reduce the sensor measurement error up to 17% and 20% for solar irradiance and PV temperature measurement.

A review on the ability of smartphones to detect ultraviolet (UV) radiation and their potential to be used in UV research and for public education purposes

The effects of ultraviolet (UV) radiation on life on Earth have continuously been the subject of research. Over-exposure to UV radiation is harmful, but small amounts of exposure are required for good health. It is, therefore, crucial for humans to optimise their own UV exposure and not exceed UV levels that are sufficient for essential biological functions. Exceeding those levels may increase risk of developing health problems including skin cancer and cataracts. Smartphones have been previously investigated for their ability to detect UV radiation with or without additional devices that monitor personal UV exposure, in order to maintain safe exposure times by individuals. This review presents a comprehensive overview of the current state of smartphones' use in UV radiation monitoring and prediction. There are four main methods for UV radiation detection or prediction involving the use smartphones, depending on the requirements of the user: devoted software applications developed for smartphones to predict UV Index (UVI), wearable and non-wearable devices that can be used with smartphones to provide real-time UVI, and the use of smartphone image sensors to detect UV radiation. The latter method has been a growing area of research over the last decade. Built-in smartphone image sensors have been investigated for UV radiation detection and the quantification of related atmospheric factors (including aerosols, ozone, clouds and volcanic plumes). The overall practicalities, limitations and challenges are reviewed, specifically in regard to public education. The ubiquitous nature of smartphones can provide an interactive tool when considering public education on the effects and individual monitoring of UV radiation exposure, although social and geographic areas with low socio-economic factors could challenge the usefulness of smartphones. Overall, the review shows that smartphones provide multiple opportunities in different forms to educate users on personal health with respect to UV radiation.