Perspectives of the Internal Public in a Cultural Event: the Case of Noc Noc, Guimarães - Portugal

Given the significant impact that cultural events may have in local communities and the inherent organization complexity, it is important to understand their specificities. Most of the times cultural events disregard marketing and often marketing is distant from art. Thus an analysis of an inside perspective might bring significant returns to the organization of such an event. This paper considers the three editions (2011, 2012 and 2013) of a cultural event – Noc Noc – organized by a local association in the city of Guimarães, Portugal. Its format is based in analogous events, as Noc Noc intends to convert everyday spaces (homes, commercial outlets and a number of other buildings) into cultural spaces, processed and transformed by artists, hosts and audiences. By interviewing a sample of people (20) who have hosted this cultural event, sometimes doubling as artists, and by experiencing the three editions of the event, this paper illustrates how the internal public understands this particular cultural event, analyzing specifically their motivations, ways of acting and participating, as well as their relationship with the public, with the organization of the event and with art in general. Results support that artists and hosts motivations must be identified in a timely and appropriate moment, as well as their views of this particular cultural event, in order to keep them participating, since low budget cultural events such as this one may have a key role in small scale cities.

Auditory event-related potentials in children with benign epilepsy with centro-temporal spikes

Benign focal epilepsy in childhood with centro-temporal spikes (BECTS) is one of the most common forms of idiopathic epilepsy, with onset from age 3 to 14 years. Although the prognosis for children with BECTS is excellent, some studies have revealed neuropsychological deficits in many domains, including language. Auditory event-related potentials (AERPs) reflect activation of different neuronal populations and are suggested to contribute to the evaluation of auditory discrimination (N1), attention allocation and phonological categorization (N2), and echoic memory (mismatch negativity – MMN). The scarce existing literature about this theme motivated the present study, which aims to investigate and document the existing AERP changes in a group of children with BECTS. AERPs were recorded, during the day, to pure and vocal tones and in a conventional auditory oddball paradigm in five children with BECTS (aged 8–12; mean = 10 years; male = 5) and in six gender and age-matched controls. Results revealed high amplitude of AERPs for the group of children with BECTS with a slight latency delay more pronounced in fronto-central electrodes. Children with BECTS may have abnormal central auditory processing, reflected by electrophysiological measures such as AERPs. In advance, AERPs seem a good tool to detect and reliably reveal cortical excitability in children with typical BECTS.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Real-Time Simulation of energy Management in a Domestic Consumer

Recent and future changes in power systems, mainly in the smart grid operation context, are related to a high complexity of power networks operation. This leads to more complex communications and to higher network elements monitoring and control levels, both from network’s and consumers’ standpoint. The present work focuses on a real scenario of the LASIE laboratory, located at the Polytechnic of Porto. Laboratory systems are managed by the SCADA House Intelligent Management (SHIM), already developed by the authors based on a SCADA system. The SHIM capacities have been recently improved by including real-time simulation from Opal RT. This makes possible the integration of Matlab®/Simulink® real-time simulation models. The main goal of the present paper is to compare the advantages of the resulting improved system, while managing the energy consumption of a domestic consumer.

Load Control Timescales Simulation in a Multi-Agent Smart Grid Platform

Environmental concerns and the shortage in the fossil fuel reserves have been potentiating the growth and globalization of distributed generation. Another resource that has been increasing its importance is the demand response, which is used to change consumers’ consumption profile, helping to reduce peak demand. Aiming to support small players’ participation in demand response events, the Curtailment Service Provider emerged. This player works as an aggregator for demand response events. The control of small and medium players which act in smart grid and micro grid environments is enhanced with a multi-agent system with artificial intelligence techniques – the MASGriP (Multi-Agent Smart Grid Platform). Using strategic behaviours in each player, this system simulates the profile of real players by using software agents. This paper shows the importance of modeling these behaviours for studying this type of scenarios. A case study with three examples shows the differences between each player and the best behaviour in order to achieve the higher profit in each situation.

Domestic Consumption Simulation and Management Using a Continuous Consumption Management and Optimization Algorithm

The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

Towards a unified European electricity market: The contribution of data-mining to support realistic simulation studies

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European Electricity Market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. The continuous transformations electricity markets have been experiencing over the years create the need to use simulation platforms to support operators, regulators, and involved players for understanding and dealing with this complex environment. This paper focuses on demonstrating the advantage that real electricity markets data has for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations will bring to the participant countries. A case study using MASCEM (Multi-Agent System for Competitive Electricity Markets) is presented, with a scenario based on real data, simulating the European Electricity Market environment, and comparing its performance when using several different market mechanisms.

Dynamic Approach and Testbed for Small and Medium Players Simulation in Smart Grid Environments

The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff.

Realistic Multi-Agent Simulation of Competitive Electricity Markets

The dynamism and ongoing changes that the electricity markets sector is constantly suffering, enhanced by the huge increase in competitiveness, create the need of using simulation platforms to support operators, regulators, and the involved players in understanding and dealing with this complex environment. This paper presents an enhanced electricity market simulator, based on multi-agent technology, which provides an advanced simulation framework for the study of real electricity markets operation, and the interactions between the involved players. MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) uses real data for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations bring to different countries. Also, the development of an upper-ontology to support the communication between participating agents, provides the means for the integration of this simulator with other frameworks, such as MAN-REM (Multi-Agent Negotiation and Risk Management in Electricity Markets). A case study using the enhanced simulation platform that results from the integration of several systems and different tools is presented, with a scenario based on real data, simulating the MIBEL electricity market environment, and comparing the simulation performance with the real electricity market results.

Real-Time Simulation of Real-Time Pricing Demand Response to Meet Wind Variations

Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.

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.

Optimização energética das estufas de secagem de uma indústria de cerâmica

A gestão de energia é um dos factores chave do sucesso de uma empresa e como qualquer outro factor de produção deve ser gerido continuamente e eficazmente. A gestão correcta do consumo de energia assume-se como crucial nas empresas do sector cerâmico pois exigem grande consumo de gás natural. Também a tendência de aumento do custo do gás natural tem induzido a necessidade de minimização do consumo de combustível nas indústrias e favorecido o desenvolvimento de novas abordagens para a optimização deste recurso natural. O trabalho apresentado nesta tese teve como objectivo a optimização da energia nas estufas de secagem na Fábrica de Cerâmica de Valadares S.A. A actividade desta empresa consiste na produção de louça sanitária envolvendo um consumo elevado de energia. Realizou-se um levantamento das condições técnicas/operacionais dos equipamentos em estudo e elaborou-se uma ferramenta de simulação que foi aplicada para realizar um balanço energético detalhado e diagnóstico da situação existente. No seguimento, foi efectuada uma análise de mercado, para elaboração do estudo económico da implementação das medidas sugeridas, nomeadamente, a recuperação dos gases de combustão que saem das três estufas que secam os moldes para as estufas de louça cerâmica. Optou-se por esta medida uma vez que reduzirá significativamente, em cerca de 50%, o consumo de combustível (gás natural) nas estufas de secagem. O tempo de retorno do investimento necessário para adquirir o equipamento é de, aproximadamente, 10 meses.