Computational Models Development and Demand Response Application for Smart Grids

This paper focuses on computational models development and its applications on demand response, within smart grid scope. A prosumer model is presented and the corresponding economic dispatch problem solution is analyzed. The prosumer solar radiation production and energy consumption are forecasted by artificial neural networks. The existing demand response models are studied and a computational tool based on fuzzy clustering algorithm is developed and the results discussed. Consumer energy management applications within the InovGrid pilot project are presented. Computation systems are developed for the acquisition, monitoring, control and supervision of consumption data provided by smart meters, allowing the incorporation of consumer actions on their electrical energy management. An energy management system with integration of smart meters for energy consumers in a smart grid is developed.

Determinants of European tourism demand in a demographic ageing society

This study identifies the senior European tourists determinants that explained their decisions to go on holidays. The empirical study was conducted among European tourists by applying a logit model. The model intends to explain the determinants related to the decision to go on holidays since the probability of a senior European tourist taking holidays in a country depends on a mix of motives as previous travel experience and demographic characteristics. Policy and theoretical implications are derived for contributing to the discussion between demographic variables and tourism demand choice patterns.

Rice development and water demand under drought stress imposed at distinct growth stages.

2016