Training control centers' operators in incident diagnosis and power restoration using intelligent tutoring systems

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

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.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

An architecture for ambient intelligent environments

This paper presents the proposal of an architecture for developing systems that interact with Ambient Intelligence (AmI) environments. This architecture has been proposed as a consequence of a methodology for the inclusion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Systems Research for Ambient Intelligence). The ISyRAmI architecture considers several modules. The first is related with the acquisition of data, information and even knowledge. This data/information knowledge deals with our AmI environment and can be acquired in different ways (from raw sensors, from the web, from experts). The second module is related with the storage, conversion, and handling of the data/information knowledge. It is understood that incorrectness, incompleteness, and uncertainty are present in the data/information/knowledge. The third module is related with the intelligent operation on the data/information/knowledge of our AmI environment. Here we include knowledge discovery systems, expert systems, planning, multi-agent systems, simulation, optimization, etc. The last module is related with the actuation in the AmI environment, by means of automation, robots, intelligent agents and users.

Inexact restoration approaches to solve mathematical program with complementarity constraints

Mathematical Program with Complementarity Constraints (MPCC) finds applica- tion in many fields. As the complementarity constraints fail the standard Linear In- dependence Constraint Qualification (LICQ) or the Mangasarian-Fromovitz constraint qualification (MFCQ), at any feasible point, the nonlinear programming theory may not be directly applied to MPCC. However, the MPCC can be reformulated as NLP problem and solved by nonlinear programming techniques. One of them, the Inexact Restoration (IR) approach, performs two independent phases in each iteration - the feasibility and the optimality phases. This work presents two versions of an IR algorithm to solve MPCC. In the feasibility phase two strategies were implemented, depending on the constraints features. One gives more importance to the complementarity constraints, while the other considers the priority of equality and inequality constraints neglecting the complementarity ones. The optimality phase uses the same approach for both algorithm versions. The algorithms were implemented in MATLAB and the test problems are from MACMPEC collection.

Numerical experiments with a modified regularization scheme for mathematical programs with complementarity constraints

On this paper we present a modified regularization scheme for Mathematical Programs with Complementarity Constraints. In the regularized formulations the complementarity condition is replaced by a constraint involving a positive parameter that can be decreased to zero. In our approach both the complementarity condition and the nonnegativity constraints are relaxed. An iterative algorithm is implemented in MATLAB language and a set of AMPL problems from MacMPEC database were tested.

Electrochemical immunosensor for multiplexed detection of food-borne pathogens using nanocrystal bioconjugates and MWCNT screen-printed electrode

Bacterial food poisoning is an ever-present threat that can be prevented with proper care and handling of food products. A disposable electrochemical immunosensor for the simultaneous measurements of common food pathogenic bacteria namely Escherichia coli O157:H7 (E. coli), campylobacter and salmonella were developed. The immunosensor was fabricated by immobilizing the mixture of anti-E. coli, anticampylobacter and anti-salmonella antibodies with a ratio of 1:1:1 on the surface of the multiwall carbon nanotube-polyallylamine modified screen printed electrode (MWCNT-PAH/SPE). Bacteria suspension became attached to the immobilized antibodies when the immunosensor was incubated in liquid samples. The sandwich immunoassay was performed with three antibodies conjugated with specific nanocrystal ( -E. coli-CdS, -campylobacter-PbS and -salmonella-CuS) which has releasable metal ions for electrochemical measurements. The square wave anodic stripping voltammetry (SWASV) was employed to measure released metal ions from bound antibody nanocrystal conjugates. The calibration curves for three selected bacteria were found in the range of 1 × 103 – 5 × 105 cells mL−1 with the limit of detection (LOD) 400 cells mL−1 for salmonella, 400 cells mL−1 for campylobacter and 800 cells mL−1 for E. coli. The precision and sensitivity of this method show the feasibility of multiplexed determination of bacteria in milk samples.

Avaliação de compostos halogenados em água e ar de piscinas

A procura de piscinas para a prática de atividades desportivas, recreativas e/ou terapêuticas tem sofrido um aumento gradual ao longo do tempo. No entanto, nas piscinas existem vários perigos associados à sua utilização. Relativamente aos perigos químicos, a utilização de desinfetantes à base de cloro, bromo ou compostos derivados vai, por um lado, inativar microrganismos patogénicos mas, por outro, dar origem a subprodutos ao reagir com compostos orgânicos presentes na água. Os trihalometanos são um exemplo de subprodutos que se podem formar e, entre os compostos principais, estão o clorofórmio (TCM), bromodiclorometano (BDCM), clorodibromometano (CDBM) e bromofórmio (TBM). Este trabalho teve como objetivo o desenvolvimento de uma metodologia analítica para a determinação de trihalometanos em água e ar de piscinas e a sua aplicação a um conjunto de amostras. Para a análise dos compostos, foi utilizada a microextração em fase sólida no espaço de cabeça (HS-SPME) com posterior quantificação dos compostos por cromatografia gasosa com detetor de captura eletrónica (GC-ECD). Foi realizada uma otimização das condições de extração dos compostos em estudo em amostras de água, através da realização de dois planeamentos experimentais. As condições ótimas são assim obtidas para uma temperatura de extração de 45ºC, um tempo de extração de 25 min e um tempo de dessorção de 5 min. Foram analisadas amostras de águas de piscina cedidas pelo Centro de Estudos de Águas, sendo avaliada a aplicação da técnica HS-SPME e o efeito de matriz. O modo como se manuseiam as soluções que contêm os compostos em estudo influencia os resultados devido ao facto destes serem bastante voláteis. Concluiu-se também que existe efeito de matriz, logo a concentração das amostras deverá ser determinada através do método de adição de padrão. A caraterização da água de piscinas interiores permitiu conhecer a concentração de trihalometanos (THMs). Foram obtidas concentrações de TCM entre 4,5 e 406,5 μg/L sendo que apenas 4 das 27 amostras analisadas ultrapassam o valor limite imposto pelo Decreto-Lei nº306/2007 (100 μg/L) no que diz respeito a águas de consumo humano e que é normalmente utilizado como valor indicativo para a qualidade das águas de piscina. Relativamente à concentração obtida no ar de uma piscina interior, foi detetada uma concentração média de 224 μg/m3 de TCM, valor muito abaixo dos 10000 μg/m3 impostos pelo Decreto-lei nº24/2012, como valor limite para exposição profissional a agentes químicos.

Resolução do problema do escalonamento da produção de energia eléctrica usando programação lógica por restrições

A operação dos Mercados de Energia Eléctrica passa, actualmente, por uma profunda reestruturação, com o principal foco nas transacções do sistema de transmissão entre os diferentes agentes. Tendo isso em conta, o serviço de transmissão neste novo esquema de funcionamento do Mercado de Energia Eléctrica deve ser provido de máxima eficiência económica, atendendo sempre às restrições de segurança do sistema. Com esta reorganização do sector eléctrico da última década surgiu também a necessidade de rever os modelos tradicionais de optimização económica do Sistema Eléctrico de Energia, como por exemplo o despacho e prédespacho (unit commitment). A reestruturação e liberalização dos mercados de energia eléctrica trouxeram novas restrições a alguns dos problemas tradicionais associados aos Sistemas Eléctricos de Energia. Um desses problemas é o Escalonamento da Produção de Energia Eléctrica, que no contexto actual, implica quase sempre negociação entre os diferentes agentes do mercado e consequentemente reescalonamento. A maioria dos métodos usados para a resolução do problema não permitem reformular o prédespacho, algo para que a Programação Lógica por Restrições é extremamente adequada. O trabalho desenvolvido nesta dissertação visa criar uma aplicação computacional com base na Programação Lógica por Restrições, através da plataforma ECLiPSe, para resolver o problema do Escalonamento da Produção de Energia Eléctrica dos grupos térmicos, demonstrando assim a versatilidade e flexibilidade deste tipo de programação aplicada a problema combinatoriais deste género.

Fuzzy Monte Carlo model for transmission power systems reliability based decision making

This thesis presents the Fuzzy Monte Carlo Model for Transmission Power Systems Reliability based studies (FMC-TRel) methodology, which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states. This is followed by a remedial action algorithm, based on Optimal Power Flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. For the system states that cause load curtailment, an optimization approach is applied to reduce the probability of occurrence of these states while minimizing the costs to achieve that reduction. This methodology is of most importance for supporting the transmission system operator decision making, namely in the identification of critical components and in the planning of future investments in the transmission power system. A case study based on Reliability Test System (RTS) 1996 IEEE 24 Bus is presented to illustrate with detail the application of the proposed methodology.

Optimização energética de um sistema de climatização industrial

O desenvolvimento deste trabalho teve como objectivo a optimização de um sistema de climatização industrial, constituído por quatro centrais de climatização adiabáticas, que apresentam limitações de capacidade de arrefecimento, controlo e eficiência. Inicialmente foi necessária a pesquisa bibliográfica e recolha de informação relativa à indústria têxtil e ao processo de arrefecimento evaporativo. Numa fase posterior foram recolhidos e analisados os diversos dados essenciais à compreensão do binómio edifício/sistema de climatização, para a obtenção de possíveis hipóteses de optimização. Da fase de recolha de informações e dados, destaca-se, também, a realização de análises à qualidade do ar interior (QAI). As optimizações seleccionadas como passíveis de implementação, foram estudadas e analisadas com o auxílio do software de simulação energética dinâmica DesignBuilder e os resultados obtidos foram devidamente trabalhados e ajustados de modo a permitir uma assimilação amigável e de fácil interpretação das suas vantagens e desvantagens, tendo ainda sido objecto de estudo de viabilidade económica. A optimização proposta reflecte uma melhoria substancial das condições interiores ao nível da temperatura e humidade relativa, resultando, ainda assim, numa redução de consumos energéticos na ordem dos 23 % (490.337 kWh), isto é, uma poupança anual de 42.169 € aos custos de exploração e com um período de retorno de 1 ano e 11 meses.

Host-Guest interaction between herbicide oxadiargyl and hydroxypropyl-β-cyclodextrin

In the face of a growing human population and increased urbanization, the demand for pesticides will simply rise. Farmers must escalate yields on increasingly fewer farm acres. However, the risks of pesticides, whether real or perceived, may force changes in the way these chemicals are used. Scientists are working toward pest control plans that are environmentally sound, effective, and profitable. In this context the development of new pesticide formulations which may improve application effectiveness, safety, handling, and storage can be pointed out as a solution. As a contribution to the area, the microencapsulation of the herbicide oxadiargyl (OXA) in (2-hydroxypropyl)-β-cyclodextrin (HP-β-CD) was performed. The study was conducted in different aqueous media (ultrapure water and in different pH buffer solutions). In all cases an increment of the oxadiargyl solubility as a function of the HP-β-CD concentration that has been related to the formation of an inclusion complex was verified. UV-Vis and NMR experiments allowed concluding that the stoichiometry of the OXA/HP-β-CD complex formed is 1 : 1. The gathered results can be regarded as an important step for its removal from industrial effluents and/or to increase the stabilizing action, encapsulation, and adsorption in water treatment plants.

Wine and grape polyphenols — a chemical perspective

Phenolic compounds constitute a diverse group of secondary metabolites which are present in both grapes and wine. The phenolic content and composition of grape processed products (wine) are greatly influenced by the technological practice to which grapes are exposed. During the handling and maturation of the grapes several chemical changes may occur with the appearance of new compounds and/or disappearance of others, and consequent modification of the characteristic ratios of the total phenolic content as well as of their qualitative and quantitative profile. The non-volatile phenolic qualitative composition of grapes and wines, the biosynthetic relationships between these compounds, and the most relevant chemical changes occurring during processing and storage will be highlighted in this review.

Enabling inter-domain transactions in bridge-based hybrid wired/wireless PROFIBUS networks

The marriage of emerging information technologies with control technologies is a major driving force that, in the context of the factory-floor, is creating an enormous eagerness for extending the capabilities of currently available fieldbus networks to cover functionalities not considered up to a recent past. Providing wireless capabilities to such type of communication networks is a big share of that effort. The RFieldbus European project is just one example, where PROFIBUS was provided with suitable extensions for implementing hybrid wired/wireless communication systems. In RFieldbus, interoperability between wired and wireless components is achieved by the use specific intermediate networking systems operating as repeaters, thus creating a single logical ring (SLR) network. The main advantage of the SLR approach is that the effort for protocol extensions is not significant. However, a multiple logical ring (MLR) approach provides traffic and error isolation between different network segments. This concept was introduced in, where an approach for a bridge-based architecture was briefly outlined. This paper will focus on the details of the inter-Domain Protocol (IDP), which is responsible for handling transactions between different network domains (wired or wireless) running the PROFIBUS protocol.

Using a prioritized medium access control protocol for incrementally obtaining an interpolation of sensor readings

This paper addresses sensor network applications which need to obtain an accurate image of physical phenomena and do so with a high sampling rate in both time and space. We present a fast and scalable approach for obtaining an approximate representation of all sensor readings at high sampling rate for quickly reacting to critical events in a physical environment. This approach is an improvement on previous work in that after the new approach has undergone a startup phase then the new approach can use a very small sampling period.