The smart grid concept is introduced to accelerate the operational efficiency and enhance
the reliability and sustainability of power supply by operating in self-control mode to find and …

The increased digitalisation and monitoring of the energy system opens up numerous
opportunities to decarbonise the energy system. Applications on low voltage, local networks …

Indoor heating and cooling systems largely influence the power demand of residential
buildings and can play a significant role in the Demand Side Management for energy …

In the smart grid era, high granular data play an important role in providing an enormous
amount of information for industry and commerce, both temporally and spatially. With …

Recently, a large number of distributed photovoltaic (PV) power generations have been
connected to the power grid, which resulted in an increased fluctuation of the net load …

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 …

As the access to consumption data available in household smart meters is now very
common in several developed countries, this kind of information is assuming a providential …

The Kernel ridge regression (KRR) model aims to find the hidden nonlinear structure in raw
data. It makes an assumption that the noise in data satisfies the Gaussian model. However, it …

The smart grid concept is introduced to accelerate the operational efficiency and enhance
the reliability and sustainability of power supply by operating in self-control mode to find and …

How to effectively handle heterogeneous data sources is one of the main challenges in the
design of large-scale research computing platforms to collect, analyze and integrate data …