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.

Mobi_System: A Personal Travel Assistance for Electrical Vehicles in Smart Cities

In this work it is proposed the design of a mobile system to assist car drivers in a smart city environment oriented to the upcoming reality of Electric Vehicles (EV). Taking into account the new reality of smart cites, EV introduction, Smart Grids (SG), Electrical Markets (EM), with deregulation of electricity production and use, drivers will need more information for decision and mobility purposes. A mobile application to recommend useful related information will help drivers to deal with this new reality, giving guidance towards traffic, batteries charging process, and city mobility infrastructures (e. g. public transportation information, parking places availability and car & bike sharing systems). Since this is an upcoming reality with possible process changes, development must be based on agile process approaches (Web services).

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

An intelligent tutoring approach to support students and technicians in electrical installation design

Designing electric installation projects, demands not only academic knowledge, but also other types of knowledge not easily acquired through traditional instructional methodologies. A lot of additional empirical knowledge is missing and so the academic instruction must be completed with different kinds of knowledge, such as real-life practical examples and simulations. On the other hand, the practical knowledge detained by the most experienced designers is not formalized in such a way that is easily transmitted. In order to overcome these difficulties present in the engineers formation, we are developing an Intelligent Tutoring System (ITS), for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students.

Adaptable control for electrical generation at irregural wind speeds

The main aims of this work are the development and the validation of one generic algorithm to provide the optimal control of small power wind generators. That means up to 40 kW and blades with fixed pitch angle. This algorithm allows the development of controllers to fetch the wind generators at the desired operational point in variable operating conditions. The problems posed by the variable wind intensity are solved using the proposed algorithm. This is done with no explicit measure of the wind velocity, and so no special equipment or anemometer is required to compute or measure the wind velocity.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

Information and communication technologies in education – a web-based intelligent tutoring system on teaching and learning electrical project

Electrical activity is extremely broad and distinct, requiring by one hand, a deep knowledge on rules, regulations, materials, equipments, technical solutions and technologies and assistance in several areas, as electrical equipment, telecommunications, security and efficiency and rational use of energy, on the other hand, also requires other skills, depending on the specific projects to be implemented, being this knowledge a characteristic that belongs to the professionals with relevant experience, in terms of complexity and specific projects that were made.

A web-based intelligent tutoring system on teaching and learning electrical project

The Information and Communication Technology (ICT) provide new strategies for disseminating information and new communication models in order to change attitudes and human behaviour concerning to education. Nowadays the internet is crucial as a means of communication and information sharing. To education or tutorship will be required to use ICT, supported on the internet, to establish the communication of teacher-student and student-student, disseminating the content of the subjects, and as a way of teaching and learning process. This paper presents an intelligent tutor that aims to be a tool to support teaching and learning in the field of the electrical engineering project.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Impact of Sahara dust transport on Cape Verde atmospheric element particles

The objectives of this study were to (1) conduct an elemental characterization of airborne particles sampled in Cape Verde and (2) assess the influence of Sahara desert on local suspended particles. Particulate matter (PM10) was collected in Praia city (14°94'N; 23°49'W) with a low-volume sampler in order to characterize its chemical composition by k0-INAA. The filter samples were first weighed and subsequently irradiated at the Portuguese Research Reactor. Results showed that PM10 concentrations in Cape Verde markedly exceeded the health-based air quality standards defined by the European Union (EU), World Health Organization (WHO), and U.S. Environmental Protection Agency (EPA), in part due to the influence of Sahara dust transport. The PM10 composition was characterized essentially by high concentrations of elements originating from the soil (K, Sm, Co, Fe, Sc, Rb, Cr, Ce, and Ba) and sea (Na), and low concentrations of anthropogenic elements (As, Zn, and Sb). In addition, the high concentrations of PM measured in Cape Verde suggest that health of the population may be less affected compared with other sites where PM10 concentrations are lower but more enriched with toxic elements.

Recursos hidrominerais dos Açores: hidrogeologia e avaliação do potencial sócioeconómico

Tese de Doutoramento, Geologia (Hidrogeologia), 17 de Dezembro de 2013, Universidade dos Açores.

Structural, electrical and magnetic studies of Co:SnO2 and (Co,Mo):SnO2 films prepared by pulsed laser deposition

Here we report on the structural, optical, electrical and magnetic properties of Co-doped and (Co,Mo)-codoped SnO2 thin films deposited on r-cut sapphire substrates by pulsed laser deposition. Substrate temperature during deposition was kept at 500 degrees C. X-ray diffraction analysis showed that the undoped and doped films are crystalline with predominant orientation along the [1 0 1] direction regardless of the doping concentration and doping element. Optical studies revealed that the presence of Mo reverts the blue shift trend observed for the Co-doped films. For the Co and Mo doping concentrations studied, the incorporation of Mo did not contribute to increase the conductivity of the films or to enhance the ferromagnetic order of the Co-doped films. (C) 2012 Elsevier B.V. All rights reserved.

In vitro exposure of acer negundo pollen to atmospheric levels of SO2 and NO2: effects on allergenicity and germination

In the last years, a rising trend of pollen allergies in urban areas has been attributed to atmospheric pollution. In this work, we investigated the effects of SO2 and NO2 on the protein content, allergenicity, and germination rate of Acer negundo pollen. A novel environmental chamber was assembled to exposure pollen samples with SO2 or NO2 at two different levels: just below and two times the atmospheric hour-limit value acceptable for human health protection in Europe. Results showed that protein content was lower in SO2- exposed pollen samples and slightly higher in NO2-exposed pollen compared to the control sample. No different polypeptide profiles were revealed by SDSPAGE between exposed and nonexposed pollen, but the immunodetection assays indicated higher IgE recognition by all sera of sensitized patients to Acer negundo pollen extracts in all exposed samples in comparison to the nonexposed samples. A decrease in the germination rate of exposed in contrast to nonexposed pollen was verified, which was more pronounced for NO2-exposed samples. Our results indicated that in urban areas, concentrations of SO2 and NO2 below the limits established for human protection can indirectly aggravate pollen allergy on predisposed individuals and affect plant reproduction.

Integration of biomonitoring and instrumental techniques to assess the air quality in an industrial area located in the coastal of Central Asturias, Spain

Throughout the world, epidemiological studies were established to examine the relationship between air pollution and mortality rates and adverse respiratory health effects. However, despite the years of discussion the correlation between adverse health effects and atmospheric pollution remains controversial, partly because these studies are frequently restricted to small and well-monitored areas. Monitoring air pollution is complex due to the large spatial and temporal variations of pollution phenomena, the high costs of recording instruments, and the low sampling density of a purely instrumental approach. Therefore, together with the traditional instrumental monitoring, bioindication techniques allow for the mapping of pollution effects over wide areas with a high sampling density. In this study, instrumental and biomonitoring techniques were integrated to support an epidemiological study that will be developed in an industrial area located in Gijon in the coastal of central Asturias, Spain. Three main objectives were proposed to (i) analyze temporal patterns of PM10 concentrations in order to apportion emissions sources, (ii) investigate spatial patterns of lichen conductivity to identify the impact of the studied industrial area in air quality, and (iii) establish relationships amongst lichen conductivity with some site-specific characteristics. Samples of the epiphytic lichen Parmelia sulcata were transplanted in a grid of 18 by 20 km with an industrial area in the center. Lichens were exposed for a 5-mo period starting in April 2010. After exposure, lichen samples were soaked in 18-MΩ water aimed at determination of water electrical conductivity and, consequently, lichen vitality and cell damage. A marked decreasing gradient of lichens conductivity relative to distance from the emitting sources was observed. Transplants from a sampling site proximal to the industrial area reached values 10-fold higher than levels far from it. This finding showed that lichens reacted physiologically in the polluted industrial area as evidenced by increased conductivity correlated to contamination level. The integration of temporal PM10 measurements and analysis of wind direction corroborated the importance of this industrialized region for air quality measurements and identified the relevance of traffic for the urban area.

Analysis of polycyclic aromatic hydrocarbons in atmospheric particulate samples by microwaveassisted extraction and liquid chromatography

A methodology based on microwave-assisted extraction (MAE) and LC with fluorescence detection (FLD) was investigated for the efficient determination of 15 polycyclic aromatic hydrocarbons (PAHs) regarded as priority pollutants by the US Environmental Protection Agency and dibenzo(a,l)pyrene in atmospheric particulate samples. PAHs were successfully extracted from real outdoor particulate matter (PM) samples with recoveries ranging from 81.4±8.8 to 112.0±1.1%, for all the compounds except for naphthalene (62.3±18.0%) and anthracene (67.3±5.7%), under the optimum MAE conditions (30.0 mL of ACN for 20 min at 110ºC). No clean-up steps were necessary prior to LC analysis. LOQs ranging from 0.0054 ng/m3 for benzo( a)anthracene to 0.089 ng/m3 for naphthalene were reached. The validated MAE methodology was applied to the determination of PAHs from a set of real world PM samples collected in Oporto (north of Portugal). The sum of particulate-bound PAHs in outdoor PM ranged from 2.5 and 28 ng/m3.