Examining User Perceptions of Brain-Computer Interfaces for Practical Applications: An Exploratory Study

The idea of controlling technology with your thoughts only is becoming reality with the emergence of consumer-grade Brain-Computer Interfaces (BCI). Understanding how regular users perceive this innovative way of controlling their devices is crucial, as it offers a more seamless and intuitive method of interacting with technology. Despite the improving capabilities and smaller form factor of BCI, its potential usage by non-medical users remains largely unexplored. In this research, we address this gap in a mixed-methods approach. In (n=26) qualitative interviews we explore users’ perception of BCI technology and identify its impact on users’ attitudinal and behavioral outcomes. Our findings reveal that users consider their perception as a cyborg and the device\u27s functionality when deciding on their intention to interact with BCI, dependent whether BCI used for individual or organizational interaction. We employ a pre-study (n=189) and multiple experimental studies to empirically triangulate and quantify findings from qualitative interviews

A review on the complementarity of renewable energy sources: Concept, metrics, application and future research directions

Global and regional trends indicate that energy demand will soon be covered by a widespread deployment of renewable energy sources. However, the weather and climate driven energy sources are characterized by a significant spatial and temporal variability. One of the commonly mentioned solutions to overcome the mismatch between demand and supply provided by renewable generation is a hybridization of two or more energy sources into a single power station (like wind-solar, solar-hydro or solar-wind-hydro). The operation of hybrid energy sources is based on the complementary nature of renewable sources. Considering the growing importance of such systems and increasing number of research activities in this area this paper presents a comprehensive review of studies which investigated, analyzed, quantified and utilized the effect of temporal, spatial and spatiotemporal complementarity between renewable energy sources. The review starts with a brief overview of available research papers, formulates detailed definition of major concepts, summarizes current research directions and ends with prospective future research activities. The review provides a chronological and spatial information with regard to the studies on the complementarity concept

The Sensitivity of Power System Expansion Models

Power system expansion models are a widely used tool for planning powersystems, especially considering the integration of large shares of renewableresources. The backbone of these models is an optimization problem, whichdepends on a number of economic and technical parameters. Although theseparameters contain significant uncertainties, the sensitivity of power systemmodels to these uncertainties is barely investigated. In this work, we introduce a novel method to quantify the sensitivity ofpower system models to different model parameters based on measuring theadditional cost arising from misallocating generation capacities. The value ofthis method is proven by three prominent test cases: the definition of capitalcost, different weather periods and different spatial and temporal resolutions.We find that the model is most sensitive to the temporal resolution. Fur-thermore, we explain why the spatial resolution is of minor importance andwhy the underlying weather data should be chosen carefully

Spatial representation of temporal complementarity between three variable energy sources using correlation coefficients and compromise programming

Renewable energy sources have shown remarkable growth in recent times in terms of their contribution to sustainable societies. However, integrating them into the national power grids is usually hindered because of their weather-dependent nature and variability. The combination of different sources to profit from their beneficial complementarity has often been proposed as a partial solution to overcome these issues. Thus, efficient planning for optimizing the exploitation of these energy resources requires different types of decision support tools. A mathematical index for assessing energetic complementarity between multiple energy sources constitutes an important tool for this purpose, allowing a comparison of complementarity between existing facilities at different planning stages and also allowing a dynamic assessment of complementarity between variable energy sources throughout the operation, assisting in the dispatch of power supplies. This article presents a method for quantifying and spatially representing the total temporal energetic complementarity between three different variable renewable sources, through an index created from correlation coefficients and compromise programming. The method is employed to study the complementarity of wind speed, solar radiation and surface runoff on a monthly scale using continental Colombia as a case study during the year of 2015