Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Electricity Markets Simulation: MASCEM Contributions to the Challenging Reality

Electricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in sophisticated tools very helpful under this context. Some simulation tools have already been developed, some of them very interesting. However, at the present state it is important to go a step forward in Electricity Markets simulators as this is crucial for facing changes in Power Systems. This paper explains the context and needs of electricity market simulation, describing the most important characteristics of available simulators. We present our work concerning MASCEM simulator, presenting its features as well as the improvements being made to accomplish the change and challenging reality of Electricity Markets.

Ethernet-based systems: contributions to the holistic analysis

A number of characteristics are boosting the eagerness of extending Ethernet to also cover factory-floor distributed real-time applications. Full-duplex links, non-blocking and priority-based switching, bandwidth availability, just to mention a few, are characteristics upon which that eagerness is building up. But, will Ethernet technologies really manage to replace traditional Fieldbus networks? To this question, Fieldbus fundamentalists often argue that the two technologies are not comparable. In fact, Ethernet technology, by itself, does not include features above the lower layers of the OSI communication model. Where are the higher layers that permit building real industrial applications? And, taking for free that they are available, what is the impact of those protocols, mechanisms and application models on the overall performance of Ethernetbased distributed factory-floor applications? In this paper we provide some contributions that may pave the way towards providing some reasonable answers to these issues.

Constructing and Using Multimodal Narratives to Research in Science Education: Contributions Based on Practical Classroom

This study deals with the problem of how to collect genuine and useful data about science classroom practices, and preserving the complex and holistic nature of teaching and learning. Additionally, we were looking for an instrument that would allow comparability and verifiability for teaching and research purposes. Given the multimodality of teaching and learning processes, we developed the multimodal narrative (MN), which describes what happens during a task and incorporates data such as examples of students’ work.

Contributions for best practices in social recruitment: pilot study in the Northern Region of Portugal

Recruitment is based on a conglomerate of techniques and procedures put in place to attract qualified. The recruitment process has suffered changes, becoming even more sophisticated, involving a whole organisation and a whole community. A new source of recruitment has emerged with the use of online social networks using facilitators in its development and usage, allowing the search for candidates to be fast, cheap and "global". In Portugal, the information available and studies conducted into this phenomenon are still irrelevant, with little reported on the importance of online social recruitment. The purpose of this article is to contribute to what is understood by the professional process of recruitment through online social media by recruitment companies in the Northern Region of Portugal, analysing the use of online media by recruitment professionals, facilitator support tools and the associated best practices.