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.

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.

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.

Levantamento de práticas ambientais e energéticas de PMEs em Portugal

Para qualquer empresa o seu maior objetivo passa pela produção de lucro e, atualmente, esse aspeto está diretamente relacionado com a sua capacidade de manter uma gestão que incorpore a responsabilidade social, ambiental e económica, em prol de um desenvolvimento global mais sustentável. As grandes empresas já iniciaram e continuam este processo de mudança, desenvolvendo medidas e estratégias neste sentido. Porém, apesar de representarem o grosso do tecido empresarial, as Pequenas e Médias Empresas só agora começam a dar os primeiros passos em direção a uma gestão mais ponderada ambiental e energeticamente. Com este trabalho pretende-se reunir informação relativa às Pequenas e Médias Empresas portuguesas de forma a compreender quais as principais áreas de atuação, as medidas que poderão ser implementadas e, consolidar o ponto de situação deste sector acerca dos vários temas ao nível do meio ambiente e da energia. Para tal, foram realizados levantamentos energéticos e aplicado um questionário acerca dos comportamentos e práticas ambientais. Verificou-se que apesar da grande maioria das empresas analisadas já terem ponderado a importância e as vantagens da eficiência energética, ainda são poucas as organizações que têm implementados planos, estratégias ou instrumentos para melhoria do seu desempenho ambiental e energético.

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.

Analysis of the mismatch between school furniture and children

The characteristics of school furniture are strongly associated with back and neck pain, referred by school-aged children. In Portugal, about 60% of the adolescents involved in a recent study reported having felt back pain at least once in the last three months. The aim of this study was to compare furniture sizes of the 2 types indicated for primary schools, within 9 schools, with the anthropometric characteristics of Portuguese students, in order to evaluate the mismatch between them. The sample consisted of 432 volunteer students. Regarding the methodology, 5 anthropometric measures were gathered, as well as 5 dimensions from the school furniture. For the evaluation of classroom furniture, a (mis)match criterion equation was defined. Results indicated that there is a significant mismatch between furniture dimensions and the anthropometric characteristics of the students.

La littérature selon Roland Barthes

Para obter o Grau de Mestre em Tradução e Interpretação Especializadas apresento este projecto de tradução do ensaio de Vincent Jouve “La Littérature selon Roland Barthes” e análise crítica das dificuldades tradutórias encontradas. Para a tradutora é uma actividade inovadora e aliciante. A selecção da obra reveste-se de argumentos tanto pessoais como profissionais sendo particularmente oportuna, pois coincide com o centenário de nascimento de Barthes. Roland Barthes é um autor rico, complexo e desconcertante que, embora pouco estudado à época, levanta emoções extremas: adorado por uns e detestado por outros. O ensaio de Vincent Jouve reflecte essa riqueza quer de forma quer de conteúdo. Participar na divulgação, mesmo que só académica, destes autores é muito gratificante. O ensaio literário tem características próprias, que o tornam semelhante a uma manifestação artística, privilegia-se o sentido traduzindo a obra sem recorrer a progamas de tradução. Este relatório é composto por três partes fundamentais: a preparação prévia, a tradução e a análise das dificuldades. O apêndice é constituido pela obra traduzida e pelos capítulos analizados (I e IV), en Francês.