Academic Articles & Research Papers

A Hybrid Power Plant Based on Renewables and Electrochemical Energy Storage and Generation Systems for Decentralized Electricity Supply of the Northern Territories

The goal of this paper is to present hybrid power plant based on photovoltaic panels, wind turbine and electrochemical energy storage and generation systems for decentralized power supply of the customers located remotely in northern territ...

Kinetic Photovoltaic Facade System Based on a Parametric Design for Application in Signal Box Buildings in Switzerland

This study aims to produce renewable energy by applying a solar-energy-harvesting architectural design using solar panels on the facade of a building. To install as many solar panels as possible on the building elevation, the Signal Box auf...

Research on a Comprehensive Performance Analysis Method for Building-Integrated Photovoltaics Considering Global Climate Change

Building-integrated photovoltaics (BIPVs) represent a pivotal technology for enhancing the utilization of renewable energy in buildings. However, challenges persist, including the lack of integrated design models, limited analytical dimensi...

Experimental study of a novel contact-based pose detection approach for digital twin-driven high-precision micro assembly

This study presents a comprehensive study of a novel Contact-Based Pose Estimation Method (CBPEM) for enhancing precision in robotic assembly processes within digital twin frameworks. Conventional pose detection methods, such as laser and c...

Bandgap engineering of CuGaS(2)–CuInS(2) heterostructures for efficient thin-film photovoltaics.

Digital Twins in Solar Farms: An Approach through Time Series and Deep Learning

The generation of electricity through renewable energy sources increases every day, with solar energy being one of the fastest-growing. The emergence of information technologies such as Digital Twins (DT) in the field of the Internet of Thi...

Data-driven performance prediction of polymer solar cells using multi-layer perceptron with Bayesian hyperparameter tuning

Polymer solar cells (PSCs) rely on labor-intensive trial-and-error experiments to optimize power conversion efficiency (PCE), due to complex coupling of molecular electronic properties, blend morphology and fabrication parameters. This work...

Machine learning for advanced energy materials

The screening of advanced materials coupled with the modeling of their quantitative structural-activity relationships has recently become one of the hot and trending topics in energy materials due to the diverse challenges, including low su...

The challenge of studying perovskite solar cells’ stability with machine learning

Perovskite solar cells are the most dynamic emerging photovoltaic technology and attracts the attention of thousands of researchers worldwide. Recently, many of them are targeting device stability issues–the key challenge for this technolog...

A physics-informed spatiotemporal graph neural network for photovoltaic power forecasting and micro-anomaly localization

Accurate power forecasting and precise fault diagnosis are critical for the reliable operation of large-scale photovoltaic systems. However, existing data-driven models often fail to capture complex spatiotemporal dependencies and lack phys...

Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids

Electricity grids have become an essential part of daily life, even if they are often not noticed in everyday life. We usually only become particularly aware of this dependence by the time the electricity grid is no longer available. Howeve...