Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

Analysis and Visualisation of Crowd-sourced Tourism Data

C3S2E '16 Proceedings of the Ninth International C* Conference on Computer Science & Software Engineering

POSTDATA – Towards publishing European poetry as linked open data

POSTDATA is a 5 year's European Research Council (ERC) Starting Grant Project that started in May 2016 and is hosted by the Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain. The context of the project is the corpora of European Poetry (EP), with a special focus on poetic materials from different languages and literary traditions. POSTDATA aims to offer a standardized model in the philological field and a metadata application profile (MAP) for EP in order to build a common classification of all these poetic materials. The information of Spanish, Italian and French repertoires will be published in the Linked Open Data (LOD) ecosystem. Later we expect to extend the model to include additional corpora. There are a number of Web Based Information Systems in Europe with repertoires of poems available to human consumption but not in an appropriate condition to be accessible and reusable by the Semantic Web. These systems are not interoperable; they are in fact locked in their databases and proprietary software, not suitable to be linked in the Semantic Web. A way to make this data interoperable is to develop a MAP in order to be able to publish this data available in the LOD ecosystem, and also to publish new data that will be created and modeled based on this MAP. To create a common data model for EP is not simple since the existent data models are based on conceptualizations and terminology belonging to their own poetical traditions and each tradition has developed an idiosyncratic analytical terminology in a different and independent way for years. The result of this uncoordinated evolution is a set of varied terminologies to explain analogous metrical phenomena through the different poetic systems whose correspondences have been hardly studied – see examples in González-Blanco & Rodríguez (2014a and b). This work has to be done by domain experts before the modeling actually starts. On the other hand, the development of a MAP is a complex task though it is imperative to follow a method for this development. The last years Curado Malta & Baptista (2012, 2013a, 2013b) have been studying the development of MAP's in a Design Science Research (DSR) methodological process in order to define a method for the development of MAPs (see Curado Malta (2014)). The output of this DSR process was a first version of a method for the development of Metadata Application Profiles (Me4MAP) (paper to be published). The DSR process is now in the validation phase of the Relevance Cycle to validate Me4MAP. The development of this MAP for poetry will follow the guidelines of Me4MAP and this development will be used to do the validation of Me4MAP. The final goal of the POSTDATA project is: i) to be able to publish all the data locked in the WIS, in LOD, where any agent interested will be able to build applications over the data in order to serve final users; ii) to build a Web platform where: a) researchers, students and other final users interested in EP will be able to access poems (and their analyses) of all databases; b) researchers, students and other final users will be able to upload poems, the digitalized images of manuscripts, and fill in the information concerning the analysis of the poem, collaboratively contributing to a LOD dataset of poetry.

A DCAP for the social and solidarity economy

This article presents a work-in-progress version of a Dublin Core Application Profile (DCAP) developed to serve the Social and Solidarity Economy (SSE). Studies revealed that this community is interested in implementing both internal interoperability between their Web platforms to build a global SSE e-marketplace, and external interoperability among their Web platforms and external ones. The Dublin Core Application Profile for Social and Solidarity Economy (DCAP-SSE) serves this purpose. SSE organisations are submerged in the market economy but they have specificities not taken into account in this economy. The DCAP-SSE integrates terms from well-known metadata schemas, Resource Description Framework (RDF) vocabularies or ontologies, in order to enhance interoperability and take advantage of the benefits of the Linked Open Data ecosystem. It also integrates terms from the new essglobal RDF vocabulary which was created with the goal to respond to the SSE-specific needs. The DCAP-SSE also integrates five new Vocabulary Encoding Schemes to be used with DCAP-SSE properties. The DCAP development was based on a method for the development of application profiles (Me4MAP). We believe that this article has an educational value since it presents the idea that it is important to base DCAP developments on a method. This article shows the main results of applying such a method.

A Data Mining Framework for Electric Load Profiling

This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.

A Data-mining-based Methodology to support MV Electricity Customers' Characterization

This paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.

Load Profiling Tool to Support Smart Grid Operation Scenarios

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.

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.

Amostragem Adaptativa em Redes de Sensores

Uma nova área tecnológica está em crescente desenvolvimento. Esta área, denominada de internet das coisas, surge na necessidade de interligar vários objetos para uma melhoria a nível de serviços ou necessidades por parte dos utilizadores. Esta dissertação concentra-se numa área específica da tecnologia internet das coisas que é a sensorização. Esta rede de sensorização é implementada pelo projeto europeu denominado de Future Cities [1] onde se cria uma infraestrutura de investigação e validação de projetos e serviços inteligentes na cidade do Porto. O trabalho realizado nesta dissertação insere-se numa das plataformas existentes nessa rede de sensorização: a plataforma de sensores ambientais intitulada de UrbanSense. Estes sensores ambientais que estão incorporados em Data Collect Unit (DCU), também denominados por nós, medem variáveis ambientais tais como a temperatura, humidade, ozono e monóxido de carbono. No entanto, os nós têm recursos limitados em termos de energia, processamento e memória. Apesar das grandes evoluções a nível de armazenamento e de processamento, a nível energético, nomeadamente nas baterias, não existe ainda uma evolução tão notável, limitando a sua operacionalidade [2]. Esta tese foca-se, essencialmente, na melhoria do desempenho energético da rede de sensores UrbanSense. A principal contribuição é uma adaptação do protocolo de redes Ad Hoc OLSR (Optimized Link State Routing Protocol) para ser usado por nós alimentados a energia renovável, de forma a aumentar a vida útil dos nós da rede de sensorização. Com esta contribuição é possível obter um maior número de dados durante períodos de tempo mais longos, aproximadamente 10 horas relativamente às 7 horas anteriores, resultando numa maior recolha e envio dos mesmos com uma taxa superior, cerca de 500 KB/s. Existindo deste modo uma aproximação analítica dos vários parâmetros existentes na rede de sensorização. Contudo, o aumento do tempo de vida útil dos nós sensores com recurso à energia renovável, nomeadamente, energia solar, incrementa o seu peso e tamanho que limita a sua mobilidade. Com o referido acréscimo a determinar e a limitar a sua mobilidade exigindo, por isso, um planeamento prévio da sua localização. Numa primeira fase do trabalho analisou-se o consumo da DCU, visto serem estes a base na infraestrutura e comunicando entre si por WiFi ou 3G. Após uma análise dos protocolos de routing com iv suporte para parametrização energética, a escolha recaiu sobre o protocolo OLSR devido à maturidade e compatibilidade com o sistema atual da DCU, pois apesar de existirem outros protocolos, a implementação dos mesmos, não se encontram disponível como software aberto. Para a validação do trabalho realizado na presente dissertação, é realizado um ensaio prévio sem a energia renovável, para permitir caracterização de limitações do sistema. Com este ensaio, tornou-se possível verificar a compatibilidade entre os vários materiais e ajustamento de estratégias. Num segundo teste de validação é concretizado um ensaio real do sistema com 4 nós a comunicar, usando o protocolo com eficiência energética. O protocolo é avaliado em termos de aumento do tempo de vida útil do nó e da taxa de transferência. O desenvolvimento da análise e da adaptação do protocolo de rede Ad Hoc oferece uma maior longevidade em termos de tempo de vida útil, comparando ao que existe durante o processamento de envio de dados. Apesar do tempo de longevidade ser inferior, quando o parâmetro energético se encontra por omissão com o fator 3, a realização da adaptação do sistema conforme a energia, oferece uma taxa de transferência maior num período mais longo. Este é um fator favorável para a abertura de novos serviços de envio de dados em tempo real ou envio de ficheiros com um tamanho mais elevado.

Laboratório de criação digital

O projeto aqui apresentado consiste no desenvolvimento de um plano estratégico de marketing digital para o projeto Laboratório de Criação Digital (LCDPorto). O LCDPorto tem sete anos de existência, sem nunca ter definido uma estratégia de comunicação. O principal objetivo passa por aprofundar os vários temas que integram Marketing Digital, e desenvolver um plano que permita ao LCDPorto ganhar mais notoriedade pelas atividades que desenvolve e, também, obter mais público para participar nas atividades. Áreas como email marketing, contente marketing, SEO, social media e outras, não são áreas que funcionam de forma independente, mas sim, parte de um plano estratégico. Neste relatório serão apresentados alguns dos passos deste plano, nomeadamente Análise de Concorrência Online, estratégia de SEO, com o objetivo de obter dados prévios essenciais ao desenvolvimento desta estratégia de Marketing Digital.