Individual yield nowcasting for residential PV systems

Due to the inherent uncertainty in photovoltaic (PV) energy generation, an accurate power forecasting is essential to ensure a reliable operation of PV systems and a safe electric grid. Machine learning (ML) techniques have gained popularity on the development of this task due to its increased accuracy. Most literature, however, focuses only...

Introducing a comprehensive physics-based modelling framework for tandem and other PV systems

We introduce a novel simulation tool capable of calculating the energy yield of a PV system based on its fundamental material properties and using self-consistent models. Thus, our simulation model can operate without measurements of a PV device. It combines wave and ray optics and a dedicated semiconductor simulation to model the...

Achieving 23.83% conversion efficiency in silicon heterojunction solar cell with ultra-thin MoO_x hole collector layer via tailoring (i)a-Si:H/MoO_x interface

Thin films of transition metal oxides such as molybdenum oxide (MoO_x) are attractive for application in silicon heterojunction solar cells for their potential to yield large short-circuit current density. However, full control of electrical properties of thin MoO_x layers must be mastered to obtain an efficient hole...

Effect of Climate on Photovoltaic Yield Prediction Using Machine Learning Models

Machine learning is arising as a major solution for the photovoltaic (PV) power prediction. Despite the abundant literature, the effect of climate on yield predictions using machine learning is unknown. This work aims to find climatic trends by predicting the power of 48 PV systems around the world, equally divided into four climates. An...

Strategy to mitigate the dipole interfacial states in (i)a-Si:H/MoO_x passivating contacts solar cells

Molybdenum oxide (MoO_x) is attractive for applications as hole-selective contact in silicon heterojunction solar cells for its transparency and relatively high work function. However, the integration of MoO_x stacked on intrinsic amorphous silicon (i)a-Si:H layer usually exhibits some issues that are still not fully...