Renewable generation and demand response integration in micro-grids: development of a new energy management and control system

The aim of this research resides in the development of an energy management and control system (EMCS) to control a micro-grid based on the use of renewable generation and demand resources to introduce the application of demand response concepts to the management of micro-grids in order to effectively integrate the demand side as an operation resource for the grid and improve energy efficiency of the elements. As an additional result, the evaluation of reductions in the total amount of CO2 emitted into the atmosphere due to the improvement of the energy efficiency of the system is assessed.Álvarez, C.; Escrivá-Escrivá, G.; Alcázar-Ortega, M. (2013). Renewable generation and demand response integration in micro-grids: development of a new energy management and control system. Energy Efficiency. 6(2):695-706. doi:10.1007/s12053-013-9207-9S69570662Alcázar-Ortega, M. 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Practice Induces Function-Specific Changes in Brain Activity

Practice can have a profound effect on performance and brain activity, especially if a task can be automated. Tasks that allow for automatization typically involve repeated encoding of information that is paired with a constant response. Much remains unknown about the effects of practice on encoding and response selection in an automated task.To investigate function-specific effects of automatization we employed a variant of a Sternberg task with optimized separation of activity associated with encoding and response selection by means of m-sequences. This optimized randomized event-related design allows for model free measurement of BOLD signals over the course of practice. Brain activity was measured at six consecutive runs of practice and compared to brain activity in a novel task.Prompt reductions were found in the entire cortical network involved in encoding after a single run of practice. Changes in the network associated with response selection were less robust and were present only after the third run of practice.This study shows that automatization causes heterogeneous decreases in brain activity across functional regions that do not strictly track performance improvement. This suggests that cognitive performance is supported by a dynamic allocation of multiple resources in a distributed network. Our findings may bear importance in understanding the role of automatization in complex cognitive performance, as increased encoding efficiency in early stages of practice possibly increases the capacity to otherwise interfering information