Implementation of an IoT-based Sensor Network Integrating IoT-based Sensor Networks with Large-Scale Message Distribution

As technology advances not only do new standards and programming styles appear but also some of the previously established ones gain relevance. In a new Internet paradigm where interconnection between small devices is key to the development of new businesses and scientific advancement there is the need to find simple solutions that anyone can implement in order to allow ideas to become more than that, ideas. Open-source software is still alive and well, especially in the area of the Internet of Things. This opens windows for many low capital entrepreneurs to experiment with their ideas and actually develop prototypes, which can help identify problems with a project or shine light on possible new features and interactions. As programming becomes more and more popular between people of fields not related to software there is the need for guidance in developing something other than basic algorithms, which is where this thesis comes in: A comprehensive document explaining the challenges and available choices of developing a sensor data and message delivery system, which scales well and implements the delivery of critical messages. Modularity and extensibility were also given much importance, making this an affordable tool for anyone that wants to build a sensor network of the kind.

Study of distribution network demand response events in the Portuguese system

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. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A 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. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

Residential property loans and performance during property price booms: evidence from European banks

Understanding the performance of banks is of the utmost relevance, because of the impact of this sector on economic growth and financial stability. Of all the different assets that make up a bank portfolio, the residential mortgage loans constitute one of its main. Using the dynamic panel data method, we analyse the influence of residential mortgage loans on bank profitability and risk, using a sample of 555 banks in the European Union (EU-15), over the period from 1995 to 2008. We find that banks with larger weights of residential mortgage loans show lower credit risk in good times. This result explains why banks rush to lend on property during booms due to the positive effects it has on credit risk. The results show further that credit risk and profitability are lower during the upturn in the residential property price cycle. The results also reveal the existence of a non-linear relationship (U-shaped marginal effect), as a function of bank’s risk, between profitability and the residential mortgage loans exposure. For those banks that have high credit risk, a large exposure of residential mortgage loans is associated with higher risk-adjusted profitability, through lower risk. For banks with a moderate/low credit risk, the effects of higher residential mortgage loan exposure on its risk-adjusted profitability are also positive or marginally positive.

Semantic social network analysis

Mestrado em Engenharia Informática

On the use of IEEE 802.15.4/Zigbee for time-sensitive wireless sensor network applications

Mestrado em Engenharia Electrotécnica e de Computadores

Development and validation of a novel method for the analysis of chlorinated pesticides in soils using microwave-assisted extraction–headspace solid phase microextraction and gas chromatography–tandem mass spectrometry

A new procedure for determining eleven organochlorine pesticides in soils using microwave-assisted extraction (MAE) and headspace solid phase microextraction (HS-SPME) is described. The studied pesticides consisted of mirex, α- and γ-chlordane, p,p’-DDT, heptachlor, heptachlor epoxide isomer A, γ-hexachlorocyclohexane, dieldrin, endrin, aldrine and hexachlorobenzene. The HS-SPME was optimized for the most important parameters such as extraction time, sample volume and temperature. The present analytical procedure requires a reduced volume of organic solvents and avoids the need for extract clean-up steps. For optimized conditions the limits of detection for the method ranged from 0.02 to 3.6 ng/g, intermediate precision ranged from 14 to 36% (as CV%), and the recovery from 8 up to 51%. The proposed methodology can be used in the rapid screening of soil for the presence of the selected pesticides, and was applied to landfill soil samples.

Development of a simple analytical method for the simultaneousdetermination of paracetamol, paracetamol-glucuronide andp-aminophenol in river water

Paracetamol is among the most worldwide consumed pharmaceuticals. Although its occurrence in the environment is well documented, data about the presence of its metabolites and transformation products is very scarce. The present work describes the development of an analytical method for the simultaneous determination of paracetamol, its principal metabolite (paracetamol-glucuronide) and its main transformation product (p-aminophenol) based on solid phase extraction (SPE) and high performance liquid chromatography coupled to diode array detection (HPLC-DAD). The method was applied to analysis of river waters, showing to be suitable to be used in routine analysis. Different SPE sorbents were compared and the use of two Oasis WAX cartridges in tandem proved to be the most adequate approach for sample clean up and pre-concentration. Under optimized conditions, limits of detection in the range 40–67 ng/L were obtained, as well as mean recoveries between 60 and 110% with relative standard deviations (RSD) below 6%. Finally, the developed SPE-HPLC/DAD method was successfully applied to the analysis of the selected compounds in samples from seven rivers located in the north of Portugal. Nevertheless all the compounds were detected, it was the first time that paracetamol-glucuronide was found in river water at concentrations up to 3.57 μg/L.

Tensile behaviour of a structural adhesive at high temperatures by the extended finite element method

Component joining is typically performed by welding, fastening, or adhesive-bonding. For bonded aerospace applications, adhesives must withstand high-temperatures (200°C or above, depending on the application), which implies their mechanical characterization under identical conditions. The extended finite element method (XFEM) is an enhancement of the finite element method (FEM) that can be used for the strength prediction of bonded structures. This work proposes and validates damage laws for a thin layer of an epoxy adhesive at room temperature (RT), 100, 150, and 200°C using the XFEM. The fracture toughness (G Ic ) and maximum load ( ); in pure tensile loading were defined by testing double-cantilever beam (DCB) and bulk tensile specimens, respectively, which permitted building the damage laws for each temperature. The bulk test results revealed that decreased gradually with the temperature. On the other hand, the value of G Ic of the adhesive, extracted from the DCB data, was shown to be relatively insensitive to temperature up to the glass transition temperature (T g ), while above T g (at 200°C) a great reduction took place. The output of the DCB numerical simulations for the various temperatures showed a good agreement with the experimental results, which validated the obtained data for strength prediction of bonded joints in tension. By the obtained results, the XFEM proved to be an alternative for the accurate strength prediction of bonded structures.

QoS of IP services in a fieldbus network: on the limitations and possible improvements

This paper focuses on the problem of providing efficient scheduling mechanisms for IP packets encapsulated in the frames of a real-time fieldbus network - the PROFIBUS. The approach described consists on a dual-stack approach encompassing both the controlrelated traffic ("native" fieldbus traffic) and the IPrelated traffic. The overall goal is to maintain the hard real-time guarantees of the control-related traffic, while at the same time providing the desired quality of service (QoS) to the coexistent IP applications. We start to describe the work which have been up to now carried out in the framework of the European project RFieldbus (High Performance Wireless Fieldbus in Industrial Multimedia-Related Environments - IST-1999-11316). Then we identify its limitations and point out solutions that are now being addressed out of the framework of the above-mentioned European project.

A power line communication stack for metering, SCADA and large-scale domotic applications

This paper describes the communication stack of the REMPLI system: a structure using power-lines and IPbased networks for communication, for data acquisition and control of energy distribution and consumption. It is furthermore prepared to use alternative communication media like GSM or analog modem connections. The REMPLI system provides communication service for existing applications, namely automated meter reading, energy billing and domotic applications. The communication stack, consisting of physical, network, transport, and application layer is described as well as the communication services provided by the system. We show how the peculiarities of the power-line communication influence the design of the communication stack, by introducing requirements to efficiently use the limited bandwidth, optimize traffic and implement fair use of the communication medium for the extensive communication partners.