Performance investigation of state-of-the-art metaheuristic techniques for parameter extraction of solar cells/module.

One of the greatest challenges for widespread utilization of solar energy is the low conversion efficiency, motivating the needs of developing more innovative approaches to improve the design of solar energy conversion equipment. Solar cell is the fundamental component of a photovoltaic (PV) system. Solar cell's precise modelling and estimation of its parameters are of paramount importance for the simulation, design, and control of PV system to achieve optimal performances. It is nontrivial to estimate the unknown parameters of solar cell due to the nonlinearity and multimodality of search space. Conventional optimization methods tend to suffer from numerous drawbacks such as a tendency to be trapped in some local optima when solving this challenging problem. This paper aims to investigate the performance of eight state-of-the-art metaheuristic algorithms (MAs) to solve the solar cell parameter estimation problem on four case studies constituting of four different types of PV systems: R.T.C. France solar cell, LSM20 PV module, Solarex MSX-60 PV module, and SS2018P PV module. These four cell/modules are built using different technologies. The simulation results clearly indicate that the Coot-Bird Optimization technique obtains the minimum RMSE values of 1.0264E-05 and 1.8694E-03 for the R.T.C. France solar cell and the LSM20 PV module, respectively, while the wild horse optimizer outperforms in the case of the Solarex MSX-60 and SS2018 PV modules and gives the lowest value of RMSE as 2.6961E-03 and 4.7571E-05, respectively. Furthermore, the performances of all eight selected MAs are assessed by employing two non-parametric tests known as Friedman ranking and Wilcoxon rank-sum test. A full description is also provided, enabling the readers to understand the capability of each selected MA in improving the solar cell modelling that can enhance its energy conversion efficiency. Referring to the results obtained, some thoughts and suggestions for further improvements are provided in the conclusion section.

Correction: Enhanced energy harvester performance by a tension annealed carbon nanotube yarn at extreme temperatures.

Correction for 'Enhanced energy harvester performance by a tension annealed carbon nanotube yarn at extreme temperatures' by Xinghao Hu et al., Nanoscale, 2022, 14, 16185-16192, https://doi.org/10.1039/D2NR05303A.

Enhanced energy harvester performance by a tension annealed carbon nanotube yarn at extreme temperatures.

Carbon nanotube (CNT) yarns generate electrical energy when they were stretched in an electrolyte, and they have been exploited for diverse applications such as self-powered sensors and human health monitoring systems. Here we improved the capacitance change and harvester performance of a coiled CNT yarn by using an incandescent tension annealing process (ITAP). When undergoing stretching cycles at 1 Hz, a coiled ITAP yarn can produce 2.5 times peak electrical power and 1.6 times output voltage than that of a neat CNT yarn. Electrochemical analysis shows that the capacitance of the ITAP yarn decreased by 20.4% when it was stretched to 30% strain. Microstructure results demonstrate that the large capacitance change may result from the densified electrochemical surface by the ITAP. Moreover, the potential of the zero charge (PZC) of ITAP yarns was shifted to a more negative value than that of the neat CNT yarn, which means that more charges were injected into the ITAP yarn once it was immersed in an electrolyte. Thus, the large capacitance change and initial injected charge are two main reasons for enhancing the harvester performance of the ITAP yarn. In addition, by annealing a twisted CNT yarn before it was coiled, we further increased the output peak power density to 170 W kg-1 at a strain of 55%.

The Effects of Cogging Torque Reduction in Axial Flux Machines.

An axial flux permanent magnet single-rotor generator has good potential in various applications that require high efficiency, prolonged service life, as well as low mass and dimensions. However, the effect of cogging torque diminishes generator efficiency and flexibility of functionality. The effect of cogging torque arises because of a small air gap between the stator teeth and the rotor. In this article, we suggest that shifting the opposite teeth of the stator to the optimal angle can reduce the effect of cogging torque. A special axial flux permanent magnet generator is developed to choose the optimal disposition of the permanent magnet and stator teeth in the frame. The impact of the optimal angle on the cogging torque, output power, and generator efficiency is investigated. This analytical study with experimental testing proves that the optimal angle between opposite teeth can significantly decrease cogging torque and improve output power and efficiency. The results show that cogging torque decreases significantly (4-5 times) at an optimal angle of 7.5° as compared with that of other angles, although magnetic flux and output power decline slightly but efficiency increases.