Graphene-related materials (GRMs) such as graphene quantum dots (GQDs), graphene oxide (GO), reduced graphene oxide (rGO), graphene nanoribbons (GNRs), and so forth have recently emerged as photovoltaic (PV) materials due to their nanodimensional structure and outstanding properties such as high electrical and thermal conductivity, large specific surface, and unique combination of mechanical strength and flexibility. They can be a crucial part of transparent electrodes, hole/electron transport materials, and active layers in organic solar cells (OSCs). Besides their role in charge extraction and transport, GRMs act as device protectors against environmental degradation through their compact bidimensional structure and offer good durability. This review briefly presents the synthesis methods of GRMs and describes the current progress in GRM-based OSCs. PV parameters (short circuit current, open circuit voltage, power conversion efficiency, and fill factor) are summarized and comparatively discussed for the different structures. The efficiency recently surpassed 15% for an OSC incorporating polymer-modified graphene as a transparent electrode. The long-term stability of OSCs incorporating GRMs is also discussed. Finally, conclusions and the outlook for future investigation into GRM-based devices for PVs are presented.

Solar energy penetration has been on the rise worldwide during the past decade, attracting a growing interest in solar power forecasting over short time horizons. The increasing integration of these resources without accurate power forecasts hinders the grid operation and discourages the use of this renewable resource. To overcome this problem, Virtual Power Plants (VPPs) provide a solution to centralize the management of several installations to minimize the forecasting error. This paper introduces a method to efficiently produce intra-day accurate Photovoltaic (PV) power forecasts at different locations, by using free and available information. Prediction intervals, which are based on the Mean Absolute Error (MAE), account for the forecast uncertainty which provides additional information about the VPP node power generation. The performance of the forecasting strategy has been verified against the power generated by a real PV installation, and a set of ground-based meteorological stations in geographical proximity have been used to emulate a VPP. The forecasting approach is based on a Long Short-Term Memory (LSTM) network and shows similar errors to those obtained with other deep learning methods published in the literature, offering a MAE performance of 44.19 W/m² under different lead times and launch times. By applying this technique to 8 VPP nodes, the global error is reduced by 12.37% in terms of the MAE, showing huge potential in this environment.

In this work, a fiber‐based optical powering (or power‐by‐light) system capable of providing more than 1 W is developed. The prototype was used in order to power a shunt regulator for controlling the activation and deactivation of solar panels in satellites. The work involves the manufacture of a light receiver (a GaAs multiple photovoltaic converter (MPC)), a power conditioning block, and a regulator and the implementation and characterization of the whole system. The MPC, with an active area of just 3.1 mm², was able to supply 1 W at 5 V with an efficiency of 30%. The maximum measured device efficiency was over 40% at an input power (P_in) of 0.5 W. Open circuit voltage over 7 V was measured forP_inover 0.5 W. A system optoelectronic efficiency (including the optical fiber, connectors, and MPC) of 27% was measured at an output power (P_out) of 1 W. AtP_out = 0.2 W, the efficiency was as high as 36%. The power conditioning block and the regulator were successfully powered with the system. The maximum supplied power in steady state was 0.2 W, whereas in transient state, it reached 0.44 W. The paper also describes the characterization of the system within the temperature range going from −70 to +100 °C. Copyright © 2011 John Wiley & Sons, Ltd.

Poly(3-hexylthiophene) (P3HT) is one of the most attractive polymeric donor materials used in organic solar cells because of its high electrical conductivity and solubility in various solvents. However, its carrier mobility is low when compared to that of inorganic semiconductors; hence, the incorporation of appropriate nanomaterials to improve its electrical mobility and optical properties are pursued. In this work, a review of the changes in electrical conductivity, bandgap, hole collection properties and carrier mobility of P3HT when adding graphene (G) is presented. The main aim is to assess how the addition of different G contents influences the optical constants: refractive index (n) and extinction coefficient (k). The values of n and k as a function of the wavelength for six P3HT/G nanocomposites with G loadings in the range of 0.1–5 wt% have been fitted to two different models, Forouhi Bloomer and Cauchy, showing very good agreement between the experimental and the theoretical values. Furthermore, a rule of mixtures was successfully applied to calculate n using mass fraction instead of volume fraction, with errors lower than 6% for all the nanocomposites studied.

In this work, the complex refractive indexes of seven PEDOT:PSS samples, three with isotropic behavior and four with optical anisotropy, were determined. For the anisotropic samples, the ordinary and extraordinary components of the refractive index were described. The effect of the film thickness, measurement technique and preparation method on the extinction coefficient (k) and refractive index (n) of each sample was also discussed. Important differences (up to 20% in the average n) were found among the samples investigated. In most anisotropic films, the mean value of the extraordinary component was between 7 and 10% higher than that of the ordinary. In the three isotropic films, the average k rose when the film thickness increased. Moreover, the different sets of refractive index data were fitted to three different models: the original Forouhi–Bloomer model, the Liu (2007) model and the revised version of the Forouhi–Bloomer model (2019). In general, Liu’s model gave better results, with small errors in n and k (<7.81 and 4.68%, respectively, in all the cases). However, this model had seven fitting parameters, which led to significantly longer computation time than the other two models. The influence of the differences in the measurement of the complex refractive index on the simulation of the optical properties of PEDOT:PSS multilayers was discussed. The results showed that n must be known precisely to accurately calculate the light absorption in a multilayer, without ignoring the isotropic or anisotropic behavior of the material or the influence of the layer thickness on its optical properties. This study aids in the development of simulation and optimization tools that allow understanding the optical properties of PEDOT:PSS films for their potential applications in organic optoelectronic devices, such as organic solar cells.