One of the most significant sales moments of the year is coming up. Everyone is preparing for this moment by loading warehouses, reinforcing teams in physical shops, reviewing e-commerce, data management, pricing, and picking or lead time to meet the expected demand. But are we doing it correctly?
The opening of new wind farms and installing wind turbines with greater capacity have made wind energy the technology with the most remarkable installed capacity at the national level. In parallel to the development of these machines, the different aspects of the design process of wind farms have also been studied, to ensure that the actual electricity generation of these installations during their operation is as close as possible to their nominal value.
In a single-price electricity market, a utility can - and should - work to optimise its energy sales. In this post, we will look at how artificial intelligence improves the decision-making process and can in the context of electricity markets.
Artificial Intelligence to Fight Fake News Collaboration with UPM, UOV and baobab soluciones, supported by RIS3, for the research and development of a public tool for the detection of fake news.
The industrial sector has always worked to reduce energy costs in production processes. At times when the price of energy is very high, this is even more important and can often lead to factory shutdowns while waiting for prices to fall.
As you have been able to read in several posts we have published, our work consists, among others, of the development of mathematical models, machine learning models and even visual computing or language understanding models.
The energy transition towards renewable energies is inevitable nowadays, and in this process, advanced and predictive analytics play a vital role for its correct implementation in electricity networks
In Industry 4.0 context and, in general, the 4.0 world, appear products and services whose organisation poses extremely complex problems. Dealing with them well or badly can be the difference between a profitable business and an unprofitable one.
The first step in developing an optimisation solution is to find out where there is a suitable scenario to work on, where and why a business process is lacking, and what are those indications that will help us to focus the shot, to bet on projects that will be clear winners.
While energy mix and technology improvements are the most influential aspects of power generation, advanced, predictive, and prescriptive analytics can play an important role in getting more out of existing or future installations.