Encenação e interpretação de Ella de Herbert Achternbusch

Foi Jean-Pierre Sarrazac quem me deu o texto, aí por volta de 1985, depois de eu ter encenado o seu Lázaro também ele sonhava com o Eldorado, nas instalações dos Modestos, encenação que ele viera ver aquando da sua primeira viagem ao Porto. Disse-me que era um texto para mim. Na primeira leitura, o desejo de fazer a peça colou-se-me ao corpo. Não que pudesse antever uma experiência que me marcaria profundamente de tanto procurar dar corpo a esse ser galináceo que de ora em diante me habitaria. Ler Ella foi, na altura, a descoberta das possibilidades de um teatro que fazia do que era pobre, da infra-língua, dos neurónios desaparafusados e do corpo deficiente, a matéria de uma teatralidade insuspeitada, de um teatro ainda por fazer. Na realidade a primeira abordagem foi difícil, o francês estropiado da tradução não era de leitura imediata e a percepção que tive da relevância da peça foi mais intuitiva, mais sensação do que compreensão. O texto tornou-se mais claro pouco tempo depois ao ler Théâtres Intimes do Sarrazac, a sua tese sobre a simbiose entre o íntimo e o político como futuro do teatro e ainda as suas considerações sobre o récit de vie, “relato de uma vida” à falta de melhor tradução, no teatro de Beckett e de Achternbush. A vontade de fazer a peça foi ficando, mas a oportunidade não surgia. Tinha saído de Évora em confronto com o teatro que lá se fazia e procurava justamente essa dimensão subjectiva que me parecia necessária a um teatro da história que continuava a defender e querer praticar – Ella era para mim a revelação desse teatro, uma palavra dita na primeira pessoa, mas dita como negação do sujeito, palavra tomada de empréstimo desde logo pelo autor. Herbert Achternbusch fala de um familiar próximo: «Ella é minha tia, eu sou o seu tutor», de uma realidade em que quotidiano e história se reencontram num contínuo fluxo e refluxo de causas e consequências. Ele escutou a palavra de Ella e transpô-la para cena, fazendo do filho, Joseph, o seu fiel depositário. Duplo empréstimo, portanto, que sinaliza o mutismo e a inacção do verdadeiro sujeito do relato de vida. Se é o nome da mãe, Ella, que dá título à peça, a sua história de vida só nos chega regurgitada pelo filho que lhe está para sempre umbilicalmente ligado. A oportunidade surgiu quando a companhia de Coimbra Escola da Noite, que pretendia fazer Susn do mesmo autor, me possibilitou realizar a encenação com produção sua. Foi nesse contexto e já em 1992 que decidi fazer o espectáculo com a equipa do Teatro da Rainha, que entretanto começava a refazer-se autonomamente. A essa equipa juntava-se agora a Amélia Varejão, nome histórico do teatro português, vinda do longínquo TEP de António Pedro, mestra de costura e figura excepcional em cena que fizera connosco muitos guarda-roupas e com quem tinha uma relação de grande proximidade, amizade e respeito profissional. Pela minha parte, decidi encenar Ella e também interpretar Joseph, tarefa que teria sido impossível sem a orientação, assumida como direcção de ensaios, da Isabel Lopes, que vinha de Évora no intervalo das suas tarefas de actriz no CENDREV. O que foi esta experiência de encenação feita no corpo do Joseph? Foi fundamentalmente descobrir duas coisas: uma, o modo feminino do comportamento gestual de uma criatura que toda a vida fez trabalhos forçados, violentos, outra, a descoberta das etapas sincopadas, desfazendo as brancas mentais de uma cabeça fundida e incapaz de lógica, de raciocínio, através da memória imediata do que é gestual e físico, realizando a única acção concebida por Achternbusch para a execução da peça, fazer um café. Essa acção única, partida em mil e um fragmentos e dispersões, foi realmente construída no trabalho de ensaios como pura descoberta de jogo apoiada pela definição do espaço e pela manipulação dos objectos. Poderei dizer que encenar Ella foi descobrir a teatralidade de um corpo bloqueado por uma cabeça limitada pela deficiência desde o nascimento, deficiência essa acrescentada pela experiência de vida e pelas circunstâncias históricas. Pela sua rebeldia, a sua não conformação às soluções de aniquilamento do eu, Ella foi submetida durante toda a vida a uma tortura constante e se há uma descoberta que tenha feito com esta peça é a de que a vitalidade de uma sobrevivente não morre diante da maior repressão e a de que a rebeldia salutar pode expressar alegria vital na condição mais inumana. Nenhum ódio, nenhuma raiva e uma capacidade de surpresa perante o mais acessível e irrelevante face à biografia trágica, um moinho de café estimado e tratado como um objecto de altar, o pouco que se tem como um céu alcançado, o café, extraordinária nova possibilidade e prazer – a peça desenrola-se já a partir da sociedade de consumo e a sua retrospectiva elabora-se a partir desse presente. Um outro aspecto decisivo foi descobrir a comicidade como uma via paradoxal do trágico contemporâneo, de uma infra-tragédia que oscila entre a incontinência verbal e a afasia. Em Ella, a comicidade da palavra e do gesto não são uma via menor em termos dramáticos, pelo contrário, amplificam as possibilidades autenticamente populares da expressão linguística. E é importante referir nesta introdução a extraordinária tradução da Profª Idalina Aguiar e Melo cujo trabalho de procura dos equivalentes linguísticos do bávaro alemão de Achternbusch e da palavra deficiente, estropiada, foi notável revelando um profundo conhecimento de falares e expressões regionais e uma capacidade inventiva extraordinária da palavra agramatical e falha de lógica vinda de uma cabeça muito particular.

MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Multilevel negotiation in smart grids for VPP management of distributed resources

A multilevel negotiation mechanism for operating smart grids and negotiating in electricity markets considers the advantages of virtual power player management.

Ancillary services market clearing simulation: a comparison between deterministic and heuristic methods

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

AI in power systems and energy markets

In a world increasingly conscientious about environmental effects, power and energy systems are undergoing huge transformations. Electric energy produced from power plants is transmitted and distributed to end users through a power grid. The power industry performs the engineering design, installation, operation, and maintenance tasks to provide a high-quality, secure energy supply while accounting for its systems’ abilities to withstand uncertain events, such as weather-related outages. Competitive, deregulated electricity markets and new renewable energy sources, however, have further complicated this already complex infrastructure.Sustainable development has also been a challenge for power systems. Recently, there has been a signifi cant increase in the installation of distributed generations, mainly based on renewable resources such as wind and solar. Integrating these new generation systems leads to more complexity. Indeed, the number of generation sources greatly increases as the grid embraces numerous smaller and distributed resources. In addition, the inherent uncertainties of wind and solar energy lead to technical challenges such as forecasting, scheduling, operation, control, and risk management. In this special issue introductory article, we analyze the key areas in this field that can benefi t most from AI and intelligent systems now and in the future.We also identify new opportunities for cross-fertilization between power systems and energy markets and intelligent systems researchers.

Personality, emotion, and mood in agent-based group decision making

Group decision making plays an important role in organizations, especially in the present-day economy that demands high-quality, yet quick decisions. Group decision-support systems (GDSSs) are interactive computer-based environments that support concerted, coordinated team efforts toward the completion of joint tasks. The need for collaborative work in organizations has led to the development of a set of general collaborative computer-supported technologies and specific GDSSs that support distributed groups (in time and space) in various domains. However, each person is unique and has different reactions to various arguments. Many times a disagreement arises because of the way we began arguing, not because of the content itself. Nevertheless, emotion, mood, and personality factors have not yet been addressed in GDSSs, despite how strongly they influence results. Our group’s previous work considered the roles that emotion and mood play in decision making. In this article, we reformulate these factors and include personality as well. Thus, this work incorporates personality, emotion, and mood in the negotiation process of an argumentbased group decision-making process. Our main goal in this work is to improve the negotiation process through argumentation using the affective characteristics of the involved participants. Each participant agent represents a group decision member. This representation lets us simulate people with different personalities. The discussion process between group members (agents) is made through the exchange of persuasive arguments. Although our multiagent architecture model4 includes two types of agents—the facilitator and the participant— this article focuses on the emotional, personality, and argumentation components of the participant agent.

Context-aware emotion-based model for group decision making

Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.

An emotional and context-aware model for adapting RSS news to users and groups

The exhibition of information does not always attend to the preferences and characteristics of the users, nor the context that involves the user. With the aim of overcoming this gap, we propose an emotional context-aware model for adapting information contents to users and groups. The proposed model is based on OCC and Big Five models to handle emotion and personality respectively. The idea is to adapt the representation of the information in order to maximize the positive emotional valences and minimize the negatives. To evaluate the proposed model it was developed a prototype for adapting RSS news to users and group of users.

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.

Analysis of PCBs in soils and sediments by microwave-assisted extraction, headspace-SPME and high resolution gas chromatography with ion-trap tandem mass spectrometry

A procedure for the determination of seven indicator PCBs in soils and sediments using microwave-assisted extraction (MAE) and headspace solid-phase microextraction (HS-SPME) prior to GC-MS/MS is described. Optimization of the HS-SPME was carried out for the most important parameters such as extraction time, sample volume and temperature. The adopted methodology has reduced consumption of organic solvents and analysis runtime. Under the optimized conditions, the method detection limit ranged from 0.6 to 1 ng/g when 5 g of sample was extracted, the precision on real samples ranged from 4 to 21% and the recovery from 69 to 104%. The proposed method, which included the analysis of a certified reference material in its validation procedure, can be extended to several other PCBs and used in the monitoring of soil or sediments for the presence of PCBs.

Screening of grapes and wine for azoxystrobin, kresoxim-methyl and trifloxystrobin fungicides by HPLC with diode array detection

The Quinone outside Inhibitors (QoI) are one of the most important and recent fungicide groups used in viticulture and also allowed by Integrated Pest Management. Azoxystrobin, kresoxim-methyl and trifloxystrobin are the main active ingredients for treating downy and powdery mildews that can be present in grapes and wines. In this paper, a method is reported for the analysis of these three QoI-fungicides in grapes and wine. After liquid–liquid extraction and a clean-up on commercial silica cartridges, analysis was by isocratic HPLC with diode array detection (DAD) with a run time of 13 min. Confirmation was by solid-phase micro-extraction (SPME), followed by GC/MS determination. The main validation parameters for the three compounds in grapes and wine were a limit of detection up to 0.073mg kg-1, a precision not exceeding 10.0% and an average recovery of 93% ±38.

Demand response management in power systems using a particle swarm optimization approach

Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.

Distributed, Agent-Based Intelligent System for Demand Response Program Simulation in Smart Grids

A distributed, agent-based intelligent system models and simulates a smart grid using physical players and computationally simulated agents. The proposed system can assess the impact of demand response programs.

A Multiple Criteria Utility-based Approa h for the Unit Commitment with Wind Power and Pumped Storage Hydro

The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.