Computer-based monitoring platform for renewable energy systems: Four experimental application cases using NI LabVIEW

Sustainability and responsible environmental behaviour constitute a vital premise in the development of the humankind. In fact, during last decades, the global energetic scenario is evolving towards a scheme with increasing relevance of Renewable Energy Sources (RES) like photovoltaic, wind, biomass and hydrogen. Furthermore, hydrogen is an energy carrier which constitutes a mean for long-term energy storage. The integration of hydrogen with local RES contributes to distributed power generation and early introduction of hydrogen economy. Intermittent nature of many of RES, for instance solar and wind sources, impose the development of a management and control strategy to overcome this drawback. This strategy is responsible of providing a reliable, stable and efficient operation of the system. To implement such strategy, a monitoring system is required.The present paper aims to contribute to experimentally validate LabVIEW as valuable tool to develop monitoring platforms in the field of RES-based facilities. To this aim, a set of real systems successfully monitored is exposed.

Analysis of Dyscalculia Evidences through Artificial Intelligence Systems

Dyscalculia is usually perceived of as a specific learning difficulty for mathematics or, more appropriately, arithmetic. Because definitions and diagnoses of dyscalculia are in their infancy and sometimes are contradictory. However, mathematical learning difficulties are certainly not in their infancy and are very prevalent and often devastating in their impact. Co-occurrence of learning disorders appears to be the rule rather than the exception. Co-occurrence is generally assumed to be a consequence of risk factors that are shared between disorders, for example, working memory. However, it should not be assumed that all dyslexics have problems with mathematics, although the percentage may be very high, or that all dyscalculics have problems with reading and writing. Because mathematics is very developmental, any insecurity or uncertainty in early topics will impact on later topics, hence to need to take intervention back to basics. However, it may be worked out in order to decrease its degree of severity. For example, disMAT, an app developed for android may help children to apply mathematical concepts, without much effort, that is turning in itself, a promising tool to dyscalculia treatment. Thus, this work will focus on the development of a Decision Support System to estimate children evidences of dyscalculia, based on data obtained on-the-fly with disMAT. The computational framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, grounded on a Case-based approach to computing, that allows for the handling of incomplete, unknown, or even self-contradictory information.

Determination of a Mean Solar Radiation Year and of a Typical Meteorological Year for the region of Funchal in the Madeira Island

This paper presents the determination of a mean solar radiation year and of a typical meteorological year for the region of Funchal in the Madeira Island, Portugal. The data set includes hourly mean and extreme values for air temperature, relative humidity and wind speed and hourly mean values for solar global and diffuse radiation for the period 2004-2014, with maximum data coverage of 99.7%. The determination of the mean solar radiation year consisted, in a first step, in the average of all values for each pair hour/day and, in a second step, in the application of a five days centred moving average of hourly values. The determination of the typical meteorological year was based on Finkelstein-Schafer statistics, which allows to obtain a complete year of real measurements through the selection and combination of typical months, preserving the long term averages while still allowing the analysis of short term events. The typical meteorological year validation was carried out through the comparison of the monthly averages for the typical year with the long term monthly averages. The values obtained were very close, so that the typical meteorological year can accurately represent the long term data series. The typical meteorological year can be used in the simulation of renewable energy systems, namely solar energy systems, and for predicting the energy performance of buildings.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.