Aging based maintenance and reinvestment scheduling of electric distribution

The maintenance of electric distribution network is a topical question for distribution system operators because of increasing significance of failure costs. In this dissertation the maintenance practices of the distribution system operators are analyzed and a theory for scheduling maintenance activities and reinvestment of distribution components is created. The scheduling is based on the deterioration of components and the increasing failure rates due to aging. The dynamic programming algorithm is used as a solving method to maintenance problem which is caused by the increasing failure rates of the network. The other impacts of network maintenance like environmental and regulation reasons are not included to the scope of this thesis. Further the tree trimming of the corridors and the major disturbance of the network are not included to the problem optimized in this thesis. For optimizing, four dynamic programming models are presented and the models are tested. Programming is made in VBA-language to the computer. For testing two different kinds of test networks are used. Because electric distribution system operators want to operate with bigger component groups, optimal timing for component groups is also analyzed. A maintenance software package is created to apply the presented theories in practice. An overview of the program is presented.

Sensor communication in Smart cities and regions: An efficient IoT-based remote health monitoring system

Recent advances in Information and Communication Technology (ICT), especially those related to the Internet of Things (IoT), are facilitating smart regions. Among many services that a smart region can offer, remote health monitoring is a typical application of IoT paradigm. It offers the ability to continuously monitor and collect health-related data from a person, and transmit the data to a remote entity (for example, a healthcare service provider) for further processing and knowledge extraction. An IoT-based remote health monitoring system can be beneficial in rural areas belonging to the smart region where people have limited access to regular healthcare services. The same system can be beneficial in urban areas where hospitals can be overcrowded and where it may take substantial time to avail healthcare. However, this system may generate a large amount of data. In order to realize an efficient IoT-based remote health monitoring system, it is imperative to study the network communication needs of such a system; in particular the bandwidth requirements and the volume of generated data. The thesis studies a commercial product for remote health monitoring in Skellefteå, Sweden. Based on the results obtained via the commercial product, the thesis identified the key network-related requirements of a typical remote health monitoring system in terms of real-time event update, bandwidth requirements and data generation. Furthermore, the thesis has proposed an architecture called IReHMo - an IoT-based remote health monitoring architecture. This architecture allows users to incorporate several types of IoT devices to extend the sensing capabilities of the system. Using IReHMo, several IoT communication protocols such as HTTP, MQTT and CoAP has been evaluated and compared against each other. Results showed that CoAP is the most efficient protocol to transmit small size healthcare data to the remote servers. The combination of IReHMo and CoAP significantly reduced the required bandwidth as well as the volume of generated data (up to 56 percent) compared to the commercial product. Finally, the thesis conducted a scalability analysis, to determine the feasibility of deploying the combination of IReHMo and CoAP in large numbers in regions in north Sweden.

Time-domain analysis of piezoelectric impedance-based structural health monitoring using multilevel wavelet decomposition

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A New Impedance Measurement System for PZT-Based Structural Health Monitoring

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Influence of Excitation Signal on Impedance-based Structural Health Monitoring

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sizing PZT Transducers in Impedance-Based Structural Health Monitoring

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Real-time multi-sensors measurement system with temperature effects compensation for impedance-based structural health monitoring

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Impedance-based structural health monitoring with artificial neural networks

This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically >30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, multiple sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with experimental examples, investigations on a massive quarter scale model of a steel bridge section and a space truss structure, in order to verify the performance of this proposed methodology.

Chronological Monte Carlo-based assessment of distribution system reliability

Regulatory authorities in many countries, in order to maintain an acceptable balance between appropriate customer service qualities and costs, are introducing a performance-based regulation. These regulations impose penalties, and in some cases rewards, which introduce a component of financial risk to an electric power utility due to the uncertainty associated with preserving a specific level of system reliability. In Brazil, for instance, one of the reliability indices receiving special attention by the utilities is the Maximum Continuous Interruption Duration per customer (MCID). This paper describes a chronological Monte Carlo simulation approach to evaluate probability distributions of reliability indices, including the MCID, and the corresponding penalties. In order to get the desired efficiency, modern computational techniques are used for modeling (UML -Unified Modeling Language) as well as for programming (Object- Oriented Programming). Case studies on a simple distribution network and on real Brazilian distribution systems are presented and discussed. © Copyright KTH 2006.

An Experimental Study on the Effect of Temperature on Piezoelectric Sensors for Impedance-Based Structural Health Monitoring

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Design and implementation of wireless sensor networks for impedance-based structural health monitoring using ZigBee and Global System for Mobile Communications

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Piezoelectric transducers assessed by the pencil lead break for impedance-based structural health monitoring

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evaluation of p24-based antiretroviral treatment monitoring in pediatric HIV-1 infection: prediction of the CD4+ T-cell changes between consecutive visits

Worldwide, 700,000 infants are infected annually by HIV-1, most of them in resource-limited settings. Care for these children requires simple, inexpensive tests. We have evaluated HIV-1 p24 antigen for antiretroviral treatment (ART) monitoring in children. p24 by boosted enzyme-linked immunosorbent assay of heated plasma and HIV-1 RNA were measured prospectively in 24 HIV-1-infected children receiving ART. p24 and HIV-1 RNA concentrations and their changes between consecutive visits were related to the respective CD4+ changes. Age at study entry was 7.6 years; follow-up was 47.2 months, yielding 18 visits at an interval of 2.8 months (medians). There were 399 complete visit data sets and 375 interval data sets. Controlling for variation between individuals, there was a positive relationship between concentrations of HIV-1 RNA and p24 (P < 0.0001). While controlling for initial CD4+ count, age, sex, days since start of ART, and days between visits, the relative change in CD4+ count between 2 successive visits was negatively related to the corresponding relative change in HIV-1 RNA (P = 0.009), but not to the initial HIV-1 RNA concentration (P = 0.94). Similarly, we found a negative relationship with the relative change in p24 over the interval (P < 0.0001), whereas the initial p24 concentration showed a trend (P = 0.08). Statistical support for the p24 model and the HIV-1 RNA model was similar. p24 may be an accurate low-cost alternative to monitor ART in pediatric HIV-1 infection.