Modelling hydrogen production from biomass pyrolysis for energy systems using machine learning techniques.

In the context of Industry 4.0, hydrogen gas is becoming more significant to energy feedstocks in the world. The current work researches a novel artificial smart model for characterising hydrogen gas production (HGP) from biomass composition and the pyrolysis process based on an intriguing approach that uses support vector machines (SVMs) in conjunction with the artificial bee colony (ABC) optimiser.

Modelling energy performance using a new hybrid DE/MARS-based approach for fossil-fuel thermal power stations.

Despite their environmental impact, fossil-fuel power plants are still commonly used due to their high capacity and relatively low cost compared to renewable energy sources. The aim of this paper is to assess the performance of such energy systems as a key element within a fossil-fuel energy supply network. The methodology relies on fossil-fuel power plant modelling to define an optimal energy management level.

Energy potential of residue from wood transformation industry in the central metropolitan area of the Principality of Asturias (northwest Spain).

The development of modern cities favours the formation of metropolitan zones with urban and industrial areas. The central metropolitan area (CMA) of the Principality of Asturias (northwest Spain), takes up 9.6% of the territory and represents 78% of its population.