Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Using an ambient intelligent architecture for developing an intelligent tutoring system for training operators of power system control centres

This paper describes an architecture conceived to integrate Power Sys-tems tools in a Power System Control Centre, based on an Ambient Intelligent (AmI) paradigm. This architecture is an instantiation of the generic architecture proposed in [1] for developing systems that interact with AmI environments. This architecture has been proposed as a consequence of a methodology for the inclu-sion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Sys-tems Research for Ambient Intelligence). The architecture presented in the paper will be able to integrate two applications in the control room of a power system transmission network. The first is SPARSE expert system, used to get diagnosis of incidents and to support power restoration. The second application is an Intelligent Tutoring System (ITS) incorporating two training tools. The first tutoring tool is used to train operators to get the diagnosis of incidents. The second one is another tutoring tool used to train operators to perform restoration procedures.

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.

Cyber-ambient intelligent training of operators in power systems control centres

Cyber-Physical Systems and Ambient Intelligence are two of the most important and emerging paradigms of our days. The introduction of renewable sources gave origin to a completely different dimension of the distribution generation problem. On the other hand, Electricity Markets introduced a different dimension in the complexity, the economic dimension. Our goal is to study how to proceed with the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

An intelligent tutoring system for operators’ training in power system control centres

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 Centre 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, taking into account context awareness and the unobtrusive integration in the working environment.

Optimal intelligent supervisory control system in cyber-physical intelligence

This paper studies Optimal Intelligent Supervisory Control System (OISCS) model for the design of control systems which can work in the presence of cyber-physical elements with privacy protection. The development of such architecture has the possibility of providing new ways of integrated control into systems where large amounts of fast computation are not easily available, either due to limitations on power, physical size or choice of computing elements.

Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.

Intelligent training in control centres based on an ambient intelligence paradigm

This article describes a new approach in the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

Intelligent SCADA for load control

A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

A study on the encryption algorithm for RFID tag (SEED : 8 Rounds × 64 bits block)

Although it is always weak between RFID Tag and Terminal in focus of the security, there are no security skills in RFID Tag. Recently there are a lot of studying in order to protect it, but because it has some physical limitation of RFID, that is it should be low electric power and high speed, it is impossible to protect with the skills. At present, the methods of RFID security are using a security server, a security policy and security. One of them the most famous skill is the security module, then they has an authentication skill and an encryption skill. In this paper, we designed and implemented after modification original SEED into 8 Round and 64 bits for Tag.

Practical Quality Control: Comparision of Methods on the Quantification of Stationary Phases in Paper and Thin-Layer Chromatographic Systems

Introduction: Paper and thin layer chromatography methods are frequently used in Classic Nuclear Medicine for the determination of radiochemical purity (RCP) on radiopharmaceutical preparations. An aliquot of the radiopharmaceutical to be tested is spotted at the origin of a chromatographic strip (stationary phase), which in turn is placed in a chromatographic chamber in order to separate and quantify radiochemical species present in the radiopharmaceutical preparation. There are several methods for the RCP measurement, based on the use of equipment as dose calibrators, well scintillation counters, radiochromatografic scanners and gamma cameras. The purpose of this study was to compare these quantification methods for the determination of RCP. Material and Methods: 99mTc-Tetrofosmin and 99mTc-HDP are the radiopharmaceuticals chosen to serve as the basis for this study. For the determination of RCP of 99mTc-Tetrofosmin we used ITLC-SG (2.5 x 10 cm) and 2-butanone (99mTc-tetrofosmin Rf = 0.55, 99mTcO4- Rf = 1.0, other labeled impurities 99mTc-RH RF = 0.0). For the determination of RCP of 99mTc-HDP, Whatman 31ET and acetone was used (99mTc-HDP Rf = 0.0, 99mTcO4- Rf = 1.0, other labeled impurities RF = 0.0). After the development of the solvent front, the strips were allowed to dry and then imaged on the gamma camera (256x256 matrix; zoom 2; LEHR parallel-hole collimator; 5-minute image) and on the radiochromatogram scanner. Then, strips were cut in Rf 0.8 in the case of 99mTc-tetrofosmin and Rf 0.5 in the case of 99mTc-HDP. The resultant pieces were smashed in an assay tube (to minimize the effect of counting geometry) and counted in the dose calibrator and in the well scintillation counter (during 1 minute). The RCP was calculated using the formula: % 99mTc-Complex = [(99mTc-Complex) / (Total amount of 99mTc-labeled species)] x 100. Statistical analysis was done using the test of hypotheses for the difference between means in independent samples. Results:The gamma camera based method demonstrated higher operator-dependency (especially concerning the drawing of the ROIs) and the measures obtained using the dose calibrator are very sensitive to the amount of activity spotted in the chromatographic strip, so the use of a minimum of 3.7 MBq activity is essential to minimize quantification errors. Radiochromatographic scanner and well scintillation counter showed concordant results and demonstrated the higher level of precision. Conclusions: Radiochromatographic scanners and well scintillation counters based methods demonstrate to be the most accurate and less operator-dependant methods.

Validação da versão portuguesa do método 'Internacional Chemical Control Toolkit'

Em Portugal, como em outros países, podem ser encontrados milhares de trabalhadores com doenças e outros problemas resultantes da exposição aos compostos orgânicos voláteis (COV’s). No entanto são poucos os estudos aplicados à actividade industrial. Neste trabalho validou-se/estimou-se a exposição ocupacional a COV´s dos trabalhadores que executam a tarefa de ‘aplicação de revestimento do mobiliário’, mais conhecida por ‘acabamento de móveis’ na secção de acabamentos do sector de mobiliário de madeira, que se situa nos concelhos de Paços de Ferreira e Paredes, concelhos do Norte de Portugal. A amostra foi constituída por 17 empresas e foram avaliados 34 tarefas que corresponde ao mesmo número de trabalhadores, uma vez que eles executam essa tarefa durante as oito horas diárias de trabalho. Para avaliar a exposição dos trabalhadores foram utilizadas duas abordagens da higiene do trabalho: a pragmática, através da aplicação do método Toolkit e a tradicional com recurso a amostragens de ar e análises laboratoriais. Os resultados obtidos sugerem que o Toolkit é uma boa ferramenta para ser utilizada pelas Pequenas e Médias Empresas (PME’s), que trabalhem com substâncias em pó ou líquidas. É um método expedito e que não acarreta grandes esforços financeiros. Verificou-se ainda que a maioria dos trabalhadores estão em risco de exposição a COV’s. Sendo necessário tomar medidas de controlo.

Transacção de componentes multimédia suportada por agentes

O objectivo do projecto descrito nesta dissertação é o desenvolvimento da interface entre as empresas e a plataforma Business-to-Business (B2B) de negociação automática de anúncios em construção. A plataforma, no seu todo, deve garantir que os intervalos da programação são preenchidos com um alinhamento de anúncios compatível com os interesses expressos e o perfil construído dos espectadores. A plataforma funciona como um mercado electrónico de negociação automática destinado a agências de publicidade (empresas produtoras) e empresas provedoras de conteúdos e serviços multimédia aos consumidores finais (empresas distribuidoras). As empresas, uma vez registadas na plataforma, passam a ser representadas por agentes que negoceiam automaticamente os itens submetidos com o comportamento especificado. Do ponto de vista da arquitectura, a plataforma consiste num sistema multiagente organizado em três camadas compostas por: (i) agentes de interface com as empresas; (ii) agentes de modelação das empresas; e (iii) agentes delegados, de duração efémera, exclusivamente criados para participar em negociações específicas de conteúdos multimédia. Cada empresa representada na plataforma possui, para além de um número indeterminado de delegados envolvidos em negociações específicas, dois agentes: (i) o agente de interface com a empresa, que expõe um conjunto de operações de interface ao exterior através de um serviço Web, localizado na primeira camada; e (ii) o agente que modela a empresa na plataforma, que expõe através de um serviço Web um conjunto de operações aos agentes das restantes camadas da plataforma, residente na camada intermédia. Este projecto focou-se no desenvolvimento da camada superior de interface da plataforma com as empresas e no enriquecimento da camada intermédia. A realização da camada superior incluiu a especificação da parte da ontologia da plataforma que dá suporte às operações de interface com o exterior, à sua exposição como serviços Web e à criação e controlo dos agentes de interface. Esta camada superior deve permitir às empresas carregar e descarregar toda informação relevante de e para a plataforma, através de uma interface gráfica ou de forma automática, e apresentar de forma gráfica e intuitiva os resultados alcançados, nomeadamente, através da apresentação da evolução das transacções. Em relação à camada intermédia, adicionou-se à ontologia da plataforma a representação do conhecimento de suporte às operações de interface com a camada superior, adoptaram-se taxonomias de classificação de espectadores, anúncios e programas, desenvolveu-se um algoritmo de emparelhamento entre os espectadores, programas e anúncios disponíveis e, por fim, procedeu-se ao armazenamento persistente dos resultados das negociações. Do ponto de vista da plataforma, testou-se o seu funcionamento numa única plataforma física e assegurou-se a segurança e privacidade da comunicação entre empresa e plataforma e entre agentes que representam uma mesma empresa.