Related papers: Scaling Analysis in a Multi-Energy System
The application of big data is one of the significant features of integrated smart energy. Applying it to the file management of integrated smart energy projects is of great significance for improving the efficiency of project management…
A combination of recent numerical and theoretical advances are applied to analyze the scaling behaviour of the site-diluted Ising model in two dimensions, paying special attention to the implications for multiplicative logarithmic…
Smart grids technologies are enablers of new business models for domestic consumers with local flexibility (generation, loads, storage) and where access to data is a key requirement in the value stream. However, legislation on personal data…
While renewable energies are achieving parity around the globe, efforts to reach higher solar cell efficiencies becomes ever more difficult as they approach the limiting efficiency. The so-called third generation concepts attempt to break…
Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become…
Understanding quantitative relationships between urban elements is crucial for a wide range of applications. The observation at the macroscopic level demonstrates that the aggregated urban quantities (e.g., gross domestic product) scale…
The ongoing transformation of the European energy landscape, driven by the integration of renewable energy sources, digital technologies, and decentralized systems, requires a high degree of interoperability across diverse components and…
Nowadays, collaborative modeling performed by multiple stakeholders is gaining a growing interest in both academia and practice. However, it poses a set of research challenges, such as large and complex models management, support for…
Now we live in an era of big data, and big data applications are becoming more and more pervasive. How to benchmark data center computer systems running big data applications (in short big data systems) is a hot topic. In this paper, we…
As one of the most pressing challenges of the 21st century, global climate change demands a host of changes across four critical energy infrastructures: the electric grid, the natural gas system, the oil system, and the coal system.…
Machine learning (ML) has seen tremendous advancements, but its environmental footprint remains a concern. Acknowledging the growing environmental impact of ML this paper investigates Green ML, examining various model architectures and…
Resource-scale quantification of energy in water supplies is a basis for regional-scale governance of water systems and national- and global-scale assessments of the "water-energy-emission" nexus. But a physically based approach for this…
Climate change has become a major problem for humanity in the last two decades. One of the reasons that caused it, is our daily energy waste. People consume electricity in order to use home/work appliances and devices and also reach certain…
Resilience describes a system's ability to function under disturbances and threats. Many critical infrastructures, including smart grids and transportation networks, are large-scale complex systems consisting of many interdependent…
We show that scaling arguments are very useful to analyze the dynamics of periodically modulated noisy systems. Information about the behavior of the relevant quantities, such as the signal-to-noise ratio, upon variations of the noise…
In order to understand controlling a complex system, an estimation of the required effort needed to achieve control is vital. Previous works have addressed this issue by studying the scaling laws of energy cost in a general way with…
The ongoing process of smart grid digitalisation is increasing the volume of automated information exchange across distributed energy systems. This has driven the development of new information and data models when existing models fail to…
We address the quantum dynamics of a system composed of a qubit globally coupled to a many-body system characterized by short-range interactions. We employ a dynamic finite-size scaling framework to investigate the out-of-equilibrium…
The common thread that characterizes energy efficient mobility systems for smart cities is their interconnectivity which enables the exchange of massive amounts of data; this, in turn, provides the opportunity to develop a decentralized…
This systematic literature review examines the critical challenges and solutions related to scalability and maintainability in Machine Learning (ML) systems. As ML applications become increasingly complex and widespread across industries,…