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.

Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

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.

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

Towards an Academic Social Network for Bologna Process

The Bologna Process aimed to build a European Higher Education Area promoting student's mobility. The adoption of Bologna Declaration directives requires a self management distributed approach to deal with student's mobility, allowing frequent updates in institutions rules or legislation. This paper suggests a computational system architecture, which follows a social network design. A set of structured annotations is proposed in order to organize the user's information. For instance, when the user is a student its annotations are organized into an academic record. The academic record data is used to discover interests, namely mobility interests, among students that belongs the academic network. These ideas have been applied into a demonstrator that includes a mobility simulator to compare and show the student's academic evolution.

Academic social network in EHES

This paper presents the foundations of an Academic Social Network (ASN) focusing the Bologna Declaration and the Bologna Process (BP) mobility issues using ontological support. An ASN will permit students to share commons academic interests, preferences and mobility paths in the European Higher Education Space (EHES). The description of the conceptual support is ontology based allowing knowledge sharing and reuse. An approach is presented by merging Academic Ontology to Support the Bologna Mobility Process with Friend of a Friend ontology. The resulting ontology supports the student mobility profile in the ASN. The strategies to make available, in the network, knowledge about mobility issues, are presented including knowledge discovery and simulation approaches to cover student's mobility scenarios for BP.

Outermost european regions of the atlantic area network

This paper is part of the results from the project "Implementation Strategies and Development of an Open and Distance Education System for the University of the Azores" funded by the European Social Fund. http://hdl.handle.net/10400.3/2327

Application of wetland systems in the treatment of acid rock mine drainage

The presented work was conducted within the Dissertation / Internship, branch of Environmental Protection Technology, associated to the Master thesis in Chemical Engineering by the Instituto Superior de Engenharia do Porto and it was developed in the Aquatest a.s, headquartered in Prague, in Czech Republic. The ore mining exploitation in the Czech Republic began in the thirteenth century, and has been extended until the twentieth century, being now evident the consequences of the intensive extraction which includes contamination of soil and sub-soil by high concentrations of heavy metals. The mountain region of Zlaté Hory was chosen for the implementation of the remediation project, which consisted in the construction of three cells (tanks), the first to raise the pH, the second for the sedimentation of the formed precipitates and a third to increase the process efficiency in order to reduce high concentrations of metals, with special emphasis on iron, manganese and sulfates. This project was initiated in 2005, being pioneer in this country and is still ongoing due to the complex chemical and biological phenomenon’s inherent to the system. At the site where the project was implemented, there is a natural lagoon, thereby enabling a comparative study of the two systems (natural and artificial) regarding the efficiency of both in the reduction/ removal of the referred pollutants. The study aimed to assist and cooperate in the ongoing investigation at the company Aquatest, in terms of field work conducted in Zlaté Hory and in terms of research methodologies used in it. Thereby, it was carried out a survey and analysis of available data from 2005 to 2008, being complemented by the treatment of new data from 2009 to 2010. Moreover, a theoretical study of the chemical and biological processes that occurs in both systems was performed. Regarding the field work, an active participation in the collection and in situ sample analyzing of water and soil from the natural pond has been attained, with the supervision of Engineer, Irena Šupiková. Laboratory analysis of water and soil were carried out by laboratory technicians. It was found that the natural lagoon is more efficient in reducing iron and manganese, being obtained removal percentages of 100%. The artificial lagoon had a removal percentage of 90% and 33% for iron and manganese respectively. Despite the minor efficiency of the constructed wetland, it must be pointed out that this system was designed for the treatment and consequent reduction of iron. In this context, it can conclude that the main goal has been achieved. In the case of sulphates, the removal optimization is yet a goal to be achieved not only in the Czech Republic but also in other places where this type of contamination persists. In fact, in the natural lagoon and in the constructed wetland, removal efficiencies of 45% and 7% were obtained respectively. It has been speculated that the water at the entrance of both systems has different sources. The analysis of the collected data shows at the entrance of the natural pond, a concentration of 4.6 mg/L of total iron, 14.6 mg/L of manganese and 951 mg/L of sulphates. In the artificial pond, the concentrations are 27.7 mg/L, 8.1 mg/L and 382 mg/L respectively for iron, manganese and sulphates. During 2010 the investigation has been expanded. The study of soil samples has started in order to observe and evaluate the contribution of bacteria in the removal of heavy metals being in its early phase. Summarizing, this technology has revealed to be an interesting solution, since in addition to substantially reduce the mentioned contaminants, mostly iron, it combines the low cost of implementation with an reduced maintenance, and it can also be installed in recreation parks, providing habitats for plants and birds.

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Influence of network effects on the diffusion of information systems: the case of open source

Doutoramento em Gestão

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

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.

From task scheduling in single processor environments to message scheduling in a PROFIBUS fieldbus network

In this paper we survey the most relevant results for the prioritybased schedulability analysis of real-time tasks, both for the fixed and dynamic priority assignment schemes. We give emphasis to the worst-case response time analysis in non-preemptive contexts, which is fundamental for the communication schedulability analysis. We define an architecture to support priority-based scheduling of messages at the application process level of a specific fieldbus communication network, the PROFIBUS. The proposed architecture improves the worst-case messages’ response time, overcoming the limitation of the first-come-first-served (FCFS) PROFIBUS queue implementations.