Electricity Markets Simulation: MASCEM Contributions to the Challenging Reality

Electricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in sophisticated tools very helpful under this context. Some simulation tools have already been developed, some of them very interesting. However, at the present state it is important to go a step forward in Electricity Markets simulators as this is crucial for facing changes in Power Systems. This paper explains the context and needs of electricity market simulation, describing the most important characteristics of available simulators. We present our work concerning MASCEM simulator, presenting its features as well as the improvements being made to accomplish the change and challenging reality of Electricity Markets.

Optimal location of gas supply units in natural gas system network

Natural gas industry has been confronted with big challenges: great growth in demand, investments on new GSUs – gas supply units, and efficient technical system management. The right number of GSUs, their best location on networks and the optimal allocation to loads is a decision problem that can be formulated as a combinatorial programming problem, with the objective of minimizing system expenses. Our emphasis is on the formulation, interpretation and development of a solution algorithm that will analyze the trade-off between infrastructure investment expenditure and operating system costs. The location model was applied to a 12 node natural gas network, and its effectiveness was tested in five different operating scenarios.

Metalearning in ALBidS: A Strategic Bidding System for electricity markets

Metalearning is a subfield of machine learning with special pro-pensity for dynamic and complex environments, from which it is difficult to extract predictable knowledge. The field of study of this work is the electricity market, which due to the restructuring that recently took place, became an especially complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotia-tion entities. The proposed metalearner takes advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that pro-vides decision support to electricity markets’ participating players. Using the outputs of each different strategy as inputs, the metalearner creates its own output, considering each strategy with a different weight, depending on its individual quality of performance. The results of the proposed meth-od are studied and analyzed using MASCEM - a multi-agent electricity market simulator that models market players and simulates their operation in the market. This simulator provides the chance to test the metalearner in scenarios based on real electricity market´s data.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Bid definition method for electricity markets based on an adaptive multiagent system

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.

Using an ambient intelligent architecture for developing an intelligent tutoring system for training operators of power system control centres

This paper describes an architecture conceived to integrate Power Sys-tems tools in a Power System Control Centre, based on an Ambient Intelligent (AmI) paradigm. This architecture is an instantiation of the generic architecture proposed in [1] for developing systems that interact with AmI environments. This architecture has been proposed as a consequence of a methodology for the inclu-sion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Sys-tems Research for Ambient Intelligence). The architecture presented in the paper will be able to integrate two applications in the control room of a power system transmission network. The first is SPARSE expert system, used to get diagnosis of incidents and to support power restoration. The second application is an Intelligent Tutoring System (ITS) incorporating two training tools. The first tutoring tool is used to train operators to get the diagnosis of incidents. The second one is another tutoring tool used to train operators to perform restoration procedures.

Orientation system for people with cognitive disabilities

In health care there has been a growing interest and investment in new tools to have a constant monitoring of patients. The increasing of average life ex-pectation and, consequently, the costs in health care due to elderly population are the motivation for this investment. However, healthmonitoring is not only important to elderly people, it can be also applied to people with cognitive disabilities. In this article we present some systems, which try to support these persons on doing their day-to-day activities and how it can improve their life quality. Also, we present an idea to a project that tries to help the persons with cognitive disabilities by providing assistance in geo-guidance and keep their caregivers aware of their location.

Shopping center tracking and recommendation systems

Shopping centers present a rich and heterogeneous environment, where IT systems can be implemented in order to support the needs of its actors. However, due to the environment complexity, several feasibility issues emerge when designing both the logical and physical architecture of such systems. Additionally, the system must be able to cope with the individual needs of each actor, and provide services that are easily adopted by them, taking into account several sociological and economical aspects. In this sense, we present an overview of current support systems for shopping center environments. From this overview, a high-level model of the domain (involving actors and services) is described along with challenges and possible features in the context of current Semantic Web, mobile device and sensor technologies.

Recommendation and planning through mobile devices in tourism context

In this paper we present a mobile recommendation and planning system, named PSiS Mobile. It is designed to provide effective support during a tourist visit through context-aware information and recommendations about points of interest, exploiting tourist preferences and context. Designing a tool like this brings several challenges that must be addressed. We discuss how these challenges have been overcame, present the overall system architecture, since this mobile application extends the PSiS project website, and the mobile application architecture.

Lightweight user modeling – a case study

In the context of previous publications, we propose a new lightweight UM process, intended to work as a tourism recommender system in a commercial environment. The new process tackles issues like cold start, gray sheep and over specialization through a rich user model and the application of a gradual forgetting function to the collected user action history. Also, significant performance improvements were achieved regarding the previously proposed UM process.

Adaptation model for PCMAT – Mathematics collaborative learning platform

The aim of this paper is to present an adaptation model for an Adaptive Educational Hypermedia System, PCMAT. The adaptation of the application is based on progressive self-assessment (exercises, tasks, and so on) and applies the constructivist learning theory and the learning styles theory. Our objective is the creation of a better, more adequate adaptation model that takes into account the complexities of different users.

New ionic liquids and salts derived from β-Lactam antibiotics

In recent years ionic liquids (ILs) have been increasing the popularity and the number of applications. Ionic liquids were used mainly as solvent in organic synthesis, but in recent years they are also used in analytical chemistry, separation chemistry and material science. Additional to significant developments in their chemical properties and applications, ionic liquids are now bringing unexpected opportunities at the interface of chemistry with the life sciences. Ionic liquids (ILs) are currently defined as salts that are composed solely of cations and anions which melt below 100ºC. Our goal in this work is to explore the dual activity of the ionic liquids, due to the presence of two different ions, an anion with bacterial activity as β-lactam antibiotics and different kinds of cations. In this work the anions of ILs and salts were derived from three different antibiotics: ampicillin, penicillin and amoxicillin. The cations were derived from substituted ammonium, phosphonium pyridinium and methylimidazolium salts, such as: tetraethyl ammonium, trihexiltetradecilphosphonium, cetylpyridinium, choline (an essential nutrient), 1-ethyl-3-methylimidazolium, and 1-ethanol-3-methyl imidazolium structures. Commercial ammonium and phosponium halogen salts were first transformed into hydroxides on ionic exchange column (Amberlite IRA-400) in methanol. The prepared hydroxides were then neutralized with β-lactam antibiotics. After crystallization we obtained pure ILs and salts containing β-lactam antibiotics. This work presents a novel method for preparation of new salts of antibiotics with low melting point and their chemistry and microbiological characterization.

Preparation and characterization of beta-lactam antibiotic as Ionic liquids and salts

With the increase of bacterial resistance a large number of therapeutic strategies have been used to fight different kind of infections. In recent years ionic liquids (ILs) have been increasing the popularity and the number of applications. First ionic liquids were used mainly as solvent in organic synthesis, but now they are used in analytical chemistry, separation chemistry and material science among others. Additional to significant developments in their chemical properties and applications, ionic liquids are now bringing unexpected opportunities at the interface of chemistry with the life sciences Ionic liquids (ILs) are currently defined as salts that are composed solely of cations and anions which melt below 100ºC. Our goal in this work is to explore the dual activity of the ionic liquids, due to the presence of two different ions, an ion with bacterial activity as a beta-lactam antibiotic and different kinds of cations. In this work the anions of ILs and salts were derived from three different antibiotics: ampicillin, penicillin and amoxicillin. The cations were derived from substituted ammonium, phosphonium pyridinium and methylimidazolium salts, such as: tetraethyl ammonium, trihexiltetradecilphosphonium, cetylpyridinium, choline (an essential nutrient), 1-ethyl-3-methylimidazolium, and 1-ethanol-3-methyl imidazolium structures. Commercial ammonium and phosponium halogen salts were first transformed into hydroxides. on ionic exchange column (Amberlite IRA-400) in methanol. The prepared hydroxides were then neutralized with beta-lactam antibiotics. After crystallization we obtained pure ILs and salts containing beta-lactam antibiotics. This work presents a novel method for preparation of new salts of antibiotics with low melting point and their characterization.

Natural organic matter fractionation along the treatment of water for human consumption

The main objective of this study was to characterize the organic matter present in raw water and along the treatment process, as well as its seasonal variation. A natural organic matter fractionation approach has been applied to Lever water treatment plant located in Douro River, in Oporto (Portugal). The process used was based on the sorption of dissolved organic matter in different types of ion exchange resins, DAX-8, DAX-4 and IRA-958, allowing its separation into four fractions: very hydrophobic acids (VHA), slightly hydrophobic acids (SHA), charged hydrophilic (CHA) and hydrophilic neutral (NEU). The dissolved organic carbon (DOC) determination was used to quantify dissolved organic matter. Samples were collected monthly, during approximately one year, from raw water captured at the surface and under the bed of the river, and after each step of the treatment: pre-filtration in sand/anthracite filters, ozonation, coagulation/flocculation, counter current dissolved air flotation and filtration (CoCoDAFF) and chlorination. The NEU fraction showed a seasonal variation, with maximum values in autumn for the sampling points corresponding to raw water captured at the surface and under the bed of the river. It was usually the predominating fraction and did not show a significant decrease throughout the treatment. Nevertheless their low concentration, the same occurred for the CHA and VHA fractions. There was an overall decrease in the SHA fraction throughout the water treatment (especially after CoCoDAFF and ozonation) as well as in the DOC. The TSUVA254 values obtained for raw water generally varied between 2.0 and 4.0 L mgC-1 m-1 and between 0.75 and 1.78 L mgC-1 m-1 for treated water. It was observed a decrease of TSUVA values along the treatment, especially after ozonation. These results may contribute to a further optimization in the process of treating water for human consumption.

Caracterização da matéria orgânica natural em águas para consumo humano

O tratamento de água para consumo humano tem por objectivos não só a sua qualidade em termos de parâmetros químicos e físicos, como também microbiológicos. Considerando que a MON pode afectar os sistemas de tratamento, a sua redução minimiza a formação de subprodutos de desinfecção, como por exemplo os trihalometanos e diminui o crescimento de microrganismos ao longo do sistema de distribuição. Nesse sentido tem havido recentemente uma grande evolução na investigação relativamente à remoção de matéria orgânica natural. O principal objectivo deste trabalho foi o de caracterizar a matéria orgânica presente na água bruta e ao longo do processo de tratamento, assim como a sua evolução sazonal. Os dados obtidos a partir desta caracterização poderão contribuir para uma futura optimização no processo de tratamento de águas de consumo. O processo utilizado baseou-se na sorção da matéria orgânica dissolvida em diferentes tipos de resinas de permuta iónica, DAX-8, DAX-4 e IRA-958, permitindo a sua separação em várias fracções: ácidos muito hidrofóbicos (VHA), ácidos ligeiramente hidrofóbicos (SHA), compostos hidrofílicos carregados (CHA) e hidrofílicos neutros (NEU). De acordo com os resultados obtidos apenas a fracção NEU demonstrou ter uma tendência sazonal, apresentando valores máximos no Verão, nos pontos de amostragem referentes à água bruta superficial (PA802) e água bruta superficial após pré-tratamento por filtração (PA800). Os valores de COD não mostraram uma variação sazonal para as amostras de água bruta superficial que rondaram os 2 mg C/L ao longo do período de amostragem (Julho a Outubro), durante o qual se verificou uma baixa pluviosidade e temperaturas médias muito semelhantes. Os compostos NEU predominam em todos os pontos de amostragem não apresentando uma tendência definida ao longo do tratamento. Observou-se uma diminuição das fracções SHA e CHA ao longo do tratamento. Não se pode indicar uma tendência definida relativamente à fracção VHA. Verifica-se globalmente uma diminuição do teor de MON ao longo do tratamento. Este trabalho demonstrou que na água bruta superficial existe uma predominância dos compostos NEU, seguidos dos SHA, dos VHA e finalmente dos compostos CHA. Na água bruta captada no sub-leito do rio, verifica-se apenas a existência dos compostos NEU, sendo as restantes fracções praticamente nulas. Os valores mais elevados de TSUVA254nm foram obtidos para as amostras que não sofreram qualquer tratamento, água bruta do sub-leito (PA903) e superficial (PA802), e água bruta após pré-filtração (PA800). Nos restantes pontos de amostragem, apesar de se verificarem valores inferiores, não se observa uma diminuição deste parâmetro ao longo do tratamento, nem uma variação sazonal. Os valores de TSUVA254nm obtidos são geralmente inferiores a 3 L.mgC-1.m-1, correspondendo a materiais não húmicos, que são considerados biodegradáveis. Para as amostras de água tratada os valores oscilam entre os 1,23 e 1,58 L.mgC-1.m-1, valores inferiores a 2 L.mgC-1.m-1, o que é considerado um valor de referência ao nível do tratamento, segundo a USEPA.