Control in distribution networks with demand side management

The way in which electricity networks operate is going through a period of significant change. Renewable generation technologies are having a growing presence and increasing penetrations of generation that are being connected at distribution level. Unfortunately, a renewable energy source is most of the time intermittent and needs to be forecasted. Current trends in Smart grids foresee the accommodation of a variety of distributed generation sources including intermittent renewable sources. It is also expected that smart grids will include demand management resources, widespread communications and control technologies required to use demand response are needed to help the maintenance in supply-demand balance in electricity systems. Consequently, smart household appliances with controllable loads will be likely a common presence in our homes. Thus, new control techniques are requested to manage the loads and achieve all the potential energy present in intermittent energy sources. This thesis is focused on the development of a demand side management control method in a distributed network, aiming the creation of greater flexibility in demand and better ease the integration of renewable technologies. In particular, this work presents a novel multi-agent model-based predictive control method to manage distributed energy systems from the demand side, in presence of limited energy sources with fluctuating output and with energy storage in house-hold or car batteries. Specifically, here is presented a solution for thermal comfort which manages a limited shared energy resource via a demand side management perspective, using an integrated approach which also involves a power price auction and an appliance loads allocation scheme. The control is applied individually to a set of Thermal Control Areas, demand units, where the objective is to minimize the energy usage and not exceed the limited and shared energy resource, while simultaneously indoor temperatures are maintained within a comfort frame. Thermal Control Areas are overall thermodynamically connected in the distributed environment and also coupled by energy related constraints. The energy split is performed based on a fixed sequential order established from a previous completed auction wherein the bids are made by each Thermal Control Area, acting as demand side management agents, based on the daily energy price. The developed solutions are explained with algorithms and are applied to different scenarios, being the results explanatory of the benefits of the proposed approaches.

Medium access control design for distributed opportunistic radio networks

Existing wireless networks are characterized by a fixed spectrum assignment policy. However, the scarcity of available spectrum and its inefficient usage demands for a new communication paradigm to exploit the existing spectrum opportunistically. Future Cognitive Radio (CR) devices should be able to sense unoccupied spectrum and will allow the deployment of real opportunistic networks. Still, traditional Physical (PHY) and Medium Access Control (MAC) protocols are not suitable for this new type of networks because they are optimized to operate over fixed assigned frequency bands. Therefore, novel PHY-MAC cross-layer protocols should be developed to cope with the specific features of opportunistic networks. This thesis is mainly focused on the design and evaluation of MAC protocols for Decentralized Cognitive Radio Networks (DCRNs). It starts with a characterization of the spectrum sensing framework based on the Energy-Based Sensing (EBS) technique considering multiple scenarios. Then, guided by the sensing results obtained by the aforementioned technique, we present two novel decentralized CR MAC schemes: the first one designed to operate in single-channel scenarios and the second one to be used in multichannel scenarios. Analytical models for the network goodput, packet service time and individual transmission probability are derived and used to compute the performance of both protocols. Simulation results assess the accuracy of the analytical models as well as the benefits of the proposed CR MAC schemes.

A systematic methodology to analyse the performance and design configurations of business interoperability in cooperative industrial networks

This thesis proposes a methodology for modelling business interoperability in a context of cooperative industrial networks. The purpose is to develop a methodology that enables the design of cooperative industrial network platforms that are able to deliver business interoperability and the analysis of its impact on the performance of these platforms. To achieve the proposed objective, two modelling tools have been employed: the Axiomatic Design Theory for the design of interoperable platforms; and Agent-Based Simulation for the analysis of the impact of business interoperability. The sequence of the application of the two modelling tools depends on the scenario under analysis, i.e. whether the cooperative industrial network platform exists or not. If the cooperative industrial network platform does not exist, the methodology suggests first the application of the Axiomatic Design Theory to design different configurations of interoperable cooperative industrial network platforms, and then the use of Agent-Based Simulation to analyse or predict the business interoperability and operational performance of the designed configurations. Otherwise, one should start by analysing the performance of the existing platform and based on the achieved results, decide whether it is necessary to redesign it or not. If the redesign is needed, simulation is once again used to predict the performance of the redesigned platform. To explain how those two modelling tools can be applied in practice, a theoretical modelling framework, a theoretical Axiomatic Design model and a theoretical Agent-Based Simulation model are proposed. To demonstrate the applicability of the proposed methodology and/or to validate the proposed theoretical models, a case study regarding a Portuguese Reverse Logistics cooperative network (Valorpneu network) and a case study regarding a Portuguese construction project (Dam Baixo Sabor network) are presented. The findings of the application of the proposed methodology to these two case studies suggest that indeed the Axiomatic Design Theory can effectively contribute in the design of interoperable cooperative industrial network platforms and that Agent-Based Simulation provides an effective set of tools for analysing the impact of business interoperability on the performance of those platforms. However, these conclusions cannot be generalised as only two case studies have been carried out. In terms of relevance to theory, this is the first time that the network effect is addressed in the analysis of the impact of business interoperability on the performance of networked companies and also the first time that a holistic approach is proposed to design interoperable cooperative industrial network platforms. Regarding the practical implications, the proposed methodology is intended to provide industrial managers a management tool that can guide them easily, and in practical and systematic way, in the design of configurations of interoperable cooperative industrial network platforms and/or in the analysis of the impact of business interoperability on the performance of their companies and the networks where their companies operate.

Migrant networks and migrant intentions to return

Social ties are potentially an important determinant of migrants’ intention to return to their home country, and yet this topic has not been addressed in the existing economics literature on international migration. This study examines the absolute and relative importance of migrant social networks both at destination and at origin. We base our research on experimental data from Batista and Narciso (2013)1. By defining networks according to different characteristics of their members and migrant return intentions with respect to three different time horizons, we are able to dissect the network effect into its components. After controlling for unobserved heterogeneity and reverse causality biases we find that network at home seems to be the most important determinant of the migrant’s intention to return home within five and ten years.

Assessing the role of social networks on migrant labor market outcomes: Evidence from a representative immigrant survey

What role do social networks play in determining migrant labor market outcomes? We examine this question using data from a random sample of 1500 immigrants living in Ireland. We propose a theoretical model formally predicting that immigrants with more contacts have additional access to job offers, and are therefore better able to become employed and choose higher paid jobs. Our empirical analysis confirms these findings, while focusing more generally on the relationship between migrants’ social networks and a variety of labor market outcomes (namely wages, employment, occupational choice and job security), contrary to the literature. We find evidence that having one more contact in the network is associated with an increase of 11pp in the probability of being employed and with an increase of about 100 euros in the average salary. However, our data is not suggestive of a network size effect on occupational choice and job security. Our findings are robust to sample selection and other endogeneity concerns.

Predicting market movement with Artificial Neural Networks

This paper presents an application of an Artificial Neural Network (ANN) to the prediction of stock market direction in the US. Using a multilayer perceptron neural network and a backpropagation algorithm for the training process, the model aims at learning the hidden patterns in the daily movement of the S&P500 to correctly identify if the market will be in a Trend Following or Mean Reversion behavior. The ANN is able to produce a successful investment strategy which outperforms the buy and hold strategy, but presents instability in its overall results which compromises its practical application in real life investment decisions.

Using artificial neural networks to generate trading signals for crude oil, copper and gold futures

In this thesis, a feed-forward, back-propagating Artificial Neural Network using the gradient descent algorithm is developed to forecast the directional movement of daily returns for WTI, gold and copper futures. Out-of-sample back-test results vary, with some predictive abilities for copper futures but none for either WTI or gold. The best statistically significant hit rate achieved was 57% for copper with an absolute return Sharpe Ratio of 1.25 and a benchmarked Information Ratio of 2.11.

Assessing the role of social networks on migrant labor market outcomes: Evidence from a representative immigrant survey

What role do social networks play in determining migrant labor market outcomes? We examine this question using data from a random sample of 1500 immigrants living in Ireland. We propose a theoretical model formally predicting that immigrants with more contacts have additional access to job offers, and are therefore better able to become employed and choose higher paid jobs. Our empirical analysis confirms these findings, while focusing more generally on the relationship between migrants’ social networks and a variety of labor market outcomes (namely wages, employment, occupational choice and job security), contrary to the literature. We find evidence that having one more contact in the network is associated with an increase of 11pp in the probability of being employed and with an increase of about 100 euros in the average salary. However, our data is not suggestive of a network size effect on occupational choice and job security. Our findings are robust to sample selection and other endogeneity concerns.

A new credit monitoring framework for agents' networks

The purpose of this work is to develop a practicable approach for Telecom firms to manage the credit risk exposition to their commercial agents’ network. Particularly it will try to approach the problem of credit concession to clients’ from a corporation perspective and explore the particular scenario of agents that are part of the commercial chain of the corporation and therefore are not end-users. The agents’ network that served as a model for the presented study is composed by companies that, at the same time, are both clients and suppliers of the Telecommunication Company. In that sense the credit exposition analysis must took into consideration all financial fluxes, both inbound and outbound. The current strain on the Financial Sector in Portugal, and other peripheral European economies, combined with the high leverage situation of most companies, generates an environment prone to credit default risk. Due to these circumstances managing credit risk exposure is becoming increasingly a critical function for every company Financial Department. The approach designed in the current study combined two traditional risk monitoring tools: credit risk scoring and credit limitation policies. The objective was to design a new credit monitoring framework that is more flexible, uses both external and internal relationship history to assess risk and takes into consideration commercial objectives inside the agents’ network. Although not explored at length, the blueprint of a Credit Governance model was created for implementing the new credit monitoring framework inside the telecom firm. The Telecom Company that served as a model for the present work decided to implement the new Credit Monitoring framework after this was presented to its Executive Commission.

Exploring chemical conversions in metabolic networks by tracing atoms transitions

Dissertação de mestrado em Bioinformática

Poly-N-acetyl glucosamine expression in Staphylococcus epidermidis biofilm cells affects the immune response and promotes tissue pathology in infected hosts

Staphylococcus epidermidis is a biofilm - forming bacterium and a leading etiological agent of nosocomial infections. The ability to establish biofilms on indwelling medical devices is a key virulence factor for this bacterium. Still, the influence of poly - N - acetyl glucosamine (PNAG), the major component of the extracellular biofilm matrix, in the host immune response has been scarcely studied. Here, t h is influence was assessed in mice challenged i.p. with PNAG - p roducing (WT) and isogenic - mutant lacking PNAG (M10) bacteria grown in biofilm - inducing conditions. Faster bacterial clearance was observed in the mice infected with WT bacteria than in M10 - infected counterparts , which w as accompanied by earlier neutrophil recruitment and higher IL - 6 production. Interestingly, in the WT - infected mice, but not in those infected with M10 , elevated serum IL - 10 was detected . To further study the effe ct of PNAG in the immune response, mice were primed with WT or M10 biofilm bacteria and subsequently infected with WT biofilm - released cells. WT - primed mice presented a higher frequency of splenic IFN - γ + and IL - 17 + CD4 + T cells, and more severe liver patho logy than M10 - primed counterparts. Nevertheless, T reg cells obtained from the WT - primed mice presented a higher suppressive function than those obtained from M10 - primed mice. This effect was abrogated when IL - 10 - deficient mice were similarly primed and infected indicating that PNAG promotes the differentiati on of highly suppressive T reg cells by a mechanism dependent on IL - 10. Altogether, these results provide evidence help ing explain ing the coexistence of inflammation and bacterial persistence often observed in biofilm - originated S. epidermidis infections

Thermal characterization of polyhydroxyalkanoates and poly(lactic acid) blends obtained by injection molding

In this work we present the thermal characterization of the full scope of polyhydroxyalcanoate and poly(lactic acid) blends obtain by injection molding. Blends of polyhydroxyalcanoate and poly(lactic acid) (PHA/PLA) were prepared in different compositions ranging from 0–100% in steps of 10%. The blends were injection molded and then characterized by differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and wide angle X-ray diffraction (WAXD). The increment of PHA fraction increased the degree of crystallinity of the blend and the miscibility of the base polymers as verified by the Fox model. The WAXD analysis indicates that the presence of PHA hindered the PLA crystallization. The crystallization evolution trough PHA weight fraction (wf) shows a phase inversion around 50-60%. SEM analyses confirmed that the miscibility of PHA/PLA blends increased with the incorporation of PHA and became total for values of PHA higher that 50%.

Nonsolvent induced phase separation preparation of poly(vinylidene fluoride-co-chlorotrifluoroethylene) membranes with tailored morphology, piezoelectric phase content and mechanical properties

Poly(vinylidene fluoride-co-chlorotrifluoroethylene) – P(VDF-CTFE) membranes are increasingly interesting for a wide range of applications, including battery separators, filtration membranes and biomedical applications. This work reports on the morphology, hydrophobicity, thermal and mechanical properties variation of P(VDF-CTFE) membranes processed by nonsolvent induced phase separation technique (NIPS) as a function of the main processing parameters. All membranes show a porous structure composed of large spherulites, (interconnected) micropores and/or microvoids depending on the processing conditions used that in turn affect their hydrophobicity and mechanical properties. The degree of crystallinity of the membranes remains approximately constant with a value of about 15 %, except for the membranes immediately immersed in ethanol, which is of about 23 %. In turn, the crystalline phases present in the copolymer is mainly affected by the temperature and nonsolvent characteristics of the coagulation bath, the β-phase content ranging from 33 to 100 %, depending on those processing parameters. It was show that the temperature of water-based coagulation bath plays an important role in order to produce structurally uniform and homogeneous porous membranes, which is particularly important from the point of view of technological applications.

High performance electromechanical actuators based on ionic liquid/poly(vinylidene fluoride)

Due to the increasing need of low voltage actuators, independent from electrochemical processes, electroactive actuators based on poly(vinylidene fluoride) composites with 10, 25 and 40 % of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, [C2mim] [NTf2], ionic liquid are prepared by solvent casting and melting. We show that the charge structure of [C2mim] [NTf2] induces the complete piezoelectric -phase crystallization of the PVDF within the composite and decreases its crystallinity fraction significantly. [C2mim] [NTf2] also works as a plasticizer of PVDF, reducing the elastic modulus down to 12 % of the initial value. Moreover, the composites show significant displacement and bending under applied voltages of 2, 5 and 10 Vpp. The displacement and bending of the composite membranes are also evaluated as a function of [C2mim] [NTf2] content and sample thickness. Increasing amounts of ionic liquid result in larger deformations independently of the applied voltage.

Gd2O3: Eu Nanoparticle-Based Poly(vinylidene fluoride) Composites for Indirect X-ray Detection

Polymer based scintillator composites have been fabricated by combining poly(vinylidene fluoride) (PVDF) and Gd2O3:Eu nanoparticles (50nm). PVDF has been used since it is a flexible and stable binder matrix and highly resistance to thermal and light deterioration. Gd2O3:Eu has been selected as scintillator material due to its wide band gap, high density and suitable visible light yield. The structural, mechanical, thermal and electrical characteristics of the composites were studied as a function of filler content, together with their performance as scintillator material. The introduction of Gd2O3:Eu nanoparticles into the PVDF matrix does not influence the morphology of the polymer or the degree of crystallinity. On the other hand, an increase of the Young´s modulus with respect to PVDF matrix is observed for filler contents of 0.1-0.75 wt.%. The introduction of Gd2O3:Eu into the PVDF matrix increases dielectric constant and DC electrical conductivity as well as the visible light yield in the nanocomposite, being this increase dependent upon Gd2O3:Eu content and X-ray input power. In this way, Gd2O3:Eu/PVDF composites shows suitable characteristics to be used as X-ray radiation transducers, in particular for large area applications.