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.

From antimicrobial agents to health promotion

A emergência de multiresistência apresentada por microrganismos é um dos grandes desafios que enfrentam actualmente os profissionais de Saúde e a população em geral. Os factores que contribuem para o desenvolvimento de resistência a antibióticos na comunidade podem ser categorizados como comportamentais ou ambientais/políticas. O objectivo deste trabalho foi caracterizar a situação actual na visão dos Pais de alunos do pré-escolar e 1º ciclo. De modo a avaliar as necessidades de intervenção e as actividades a serem desenvolvidas, um instrumento para estudar os hábitos e comportamentos adoptados na utilização de antibióticos, foi adaptado, validado e aplicado numa amostra piloto.

Seller, buyer and VPP agents behavior on a simulated electricity market

Competitive 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 an electricity market simulator able to model market players and simulate their operation in the market. As market players are complex entities, having their characteristics and objectives, making their decisions and interacting with other players, a multi-agent architecture is used and proved to be adequate. MASCEM players have learning capabilities and different risk preferences. They are able to refine their strategies according to their past experience (both real and simulated) and considering other agents’ behavior. Agents’ behavior is also subject to its risk preferences.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

Self-managing agents for dynamic scheduling in manufacturing

The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.

Estratégias de oferta em leilões simétricos no âmbito dos mercados liberalizados de electricidade

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Intra- and interspecific mineral composition variability of commercial instant coffees and coffee substitutes: contribution to mineral intake

The present paper reports the amount and estimated daily mineral intake of nine elements (Ca, Mg, K, Na, P, Fe, Mn, Cr and Ni) in commercial instant coffees and coffee substitutes (n = 49). Elements were quantified by high-resolution continuum source flame (HR-CS-FAAS) and graphite furnace (HR-CS-GFAAS) atomic absorption spectrometry, while phosphorous was evaluated by a standard vanadomolybdophosphoric acid colorimetric method. Instant coffees and coffee substitutes are rich in K, Mg and P (>100 mg/100 g dw), contain Na, Ca and Fe in moderate amounts (>1 mg/100 g), and trace levels of Cr and Ni. Among the samples analysed, plain instant coffees are richer in minerals (p < 0.001), except for Na and Cr. Blends of coffee substitutes (barley, malt, chicory and rye) with coffee (20–66%) present intermediate amounts, while lower quantities are found in substitutes without coffee, particularly in barley. From a nutritional point of view the results indicate that the mean ingestion of two instant beverages per day (total of 4 g instant powder), either with or without coffee, cannot be regarded as important sources of minerals to the human diet, although providing a supplementation of some minerals, particularly Mg and Mn in instant coffees. Additionally, and for authentication purposes, the correlations observed between some elements and the coffee percentage in the blends, with particular significance for Mg amounts, provides a potential tool for the estimation of coffee in substitute blends.

EDI e a fatura eletrónica redes colaborativas e desmaterialização

O Electronic Data Interchange (EDI) oferece um vasto leque de oportunidades para as empresas se tornarem mais competitivas. Não só na ótica dos processos de negócio de bens e serviços, como nas práticas organizacionais e de gestão. A adoção de tecnologias de informação e comunicação do comércio eletrónico B2B, visando o aumento da eficácia e eficiência na troca de documentos de negócio, possibilita a melhoria da colaboração entre agentes económicos de uma cadeia produtiva de bens ou serviços. O comércio eletrónico permitiu uma profunda transformação das práticas comerciais tradicionais, onde o EDI influenciou positivamente na forma de conduzir o negócio. Um conceito atualmente emergente é o de fatura eletrónica, essencial para o desenvolvimento da relação entre entidades (B2B). A desmaterialização da fatura acarreta inúmeros benefícios para as entidades envolvidas, tais como: a redução de custos, a redução do impacto ambiental e o aumento da produtividade e da transparência nos processos de negócio. Esta dissertação pretende abordar em detalhe as temáticas referentes ao EDI e à fatura eletrónica, no que concerne ao conceito, às mensagens, aos standards utilizados, aos benefícios e custos envolvidos, e a toda a sua envolvência ao longo de uma cadeia de abastecimento. Com base nestes conceitos, é apresentado um caso de estudo de sucesso na empresa nacional Sonae®, que pretende abordar todo o programa EDI da empresa. O esforço despendido na implementação do programa e na adoção da fatura eletrónica legal na Sonae® supera em larga escala os objetivos pretendidos, devido aos benefícios inerentes à utilização do EDI. A fatura eletrónica representa não só o conceito de troca de documentos via eletrónica, como também uma nova forma de conduzir os negócios.

Adaptive learning in agents behaviour: a framework for electricity markets simulation

Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

Processos de purificação/ valorização do glicerol proveniente da produção de biodiesel

Mestrado em Engenharia Química - Ramo optimização energética na indústria química

Amperometric and spectrophotometric determination of carbaryl in natural waters and commercial formulations

The work presented describes the development and evaluation of two flow-injection analysis (FIA) systems for the automated determination of carbaryl in spiked natural waters and commercial formulations. Samples are injected directly into the system where they are subjected to alkaline hydrolysis thus forming 1-naphthol. This product is readily oxidised at a glassy carbon electrode. The electrochemical behaviour of 1-naphthol allows the development of an FIA system with an amperometric detector in which 1-naphthol determination, and thus measurement of carbaryl concentration, can be performed. Linear response over the range 1.0×10–7 to 1.0×10–5 mol L–1, with a sampling rate of 80 samples h–1, was recorded. The detection limit was 1.0×10–8 mol L–1. Another FIA manifold was constructed but this used a colorimetric detector. The methodology was based on the coupling of 1-naphthol with phenylhydrazine hydrochloride to produce a red complex which has maximum absorbance at 495 nm. The response was linear from 1.0×10–5 to 1.5×10–3 mol L–1 with a detection limit of 1.0×10–6 mol L–1. Sample-throughput was about 60 samples h–1. Validation of the results provided by the two FIA methodologies was performed by comparing them with results from a standard HPLC–UV technique. The relative deviation was <5%. Recovery trials were also carried out and the values obtained ranged from 97.0 to 102.0% for both methods. The repeatability (RSD, %) of 12 consecutive injections of one sample was 0.8% and 1.6% for the amperometric and colorimetric systems, respectively.

FIA potentiometric system based on periodate polymeric membrane sensors for the assessment of ascorbic acid in commercial drinks

Ascorbic acid is found in many food samples. Its clinical and technological importance demands an easyto- use, rapid, robust and inexpensive method of analysis. For this purpose, this work proposes a new flow procedure based on the oxidation of ascorbic acid by periodate. A new potentiometric periodate sensor was constructed to monitor this reaction. The selective membranes were of PVC with porphyrin-based sensing systems and a lipophilic cation as additive. The sensor displayed a near-Nernstian response for periodate over 1.0x10-2–6.0x10-6 M, with an anionic slope of 73.9 ± 0.9 mV decade-1. It was pH independent in acidic media and presented good selectivity features towards several inorganic anions. The flow set-up operated in double-channel, carrying a 5.0x10-4 M IO- 4 solution and a suitable buffer; these were mixed in a 50-cm reaction coil. The overall flow rate was 7 ml min-1 and the injection volume 70 µl. Under these conditions, a linear behaviour against concentration was observed for 17.7–194.0 µg ml-1, presenting slopes of 0.169 mV (mg/l)-1, a reproducibility of ±1.1 mV (n = 5), and a sampling rate of ~96 samples h-1. The proposed method was applied to the analysis of beverages and pharmaceuticals.

Polycyclic aromatic hydrocarbons in commercial squids from different geographical origins: levels and risks for human consumption

The concentrations of 18 polycyclic aromatic hydrocarbons (PAHs) were determined in five commercially valuable squid species from different geographical origins (Atlantic, Indic and Pacific Oceans). Out of the 18 quantified PAHs (the 16 PAHs considered by US EPA as priority pollutants, dibenzo(a,l)pyrene and benzo(j)fluoranthene) only dibenz(a,h)anthracene was not detected. The total concentrations of PAHs varied by a factor of more than 100-fold, from 0.22 (Loligo gahi) to 60.9 lg/kg ww (Loligo reynaudii). Intraand inter-specific variability of PAH levels was statistically assessed. Nine carcinogenic (probable/possible) PAHs accounted for 1% (L. reynaudii) to 26% (Loligo opalescens) of the total PAHs content being the main contributors naphthalene (in Loligo duvaucelii, L. reynaudii and Loligo vulgaris species), chrysene (in L. opalescens) and indeno(1,2,3-cd)pyrene (in L. gahi). PAHs source analysis indicated that four of the five zones of capture of the different squid species are significantly affected by both petrogenic and pyrolytic sources. Assessment of the target carcinogenic risks, established by the US EPA, suggested that L. gahi (Atlantic Ocean) and L. opalescens (from Pacific Ocean) may pose additional risks for consumers, if not eaten in moderation, derived from benzo(a)pyrene ingestion.

A proposal for media component brokerage

This paper describes how MPEG-4 object based video (obv) can be used to allow selected objects to be inserted into the play-out stream to a specific user based on a profile derived for that user. The application scenario described here is for personalized product placement, and considers the value of this application in the current and evolving commercial media distribution market given the huge emphasis media distributors are currently placing on targeted advertising. This level of application of video content requires a sophisticated content description and metadata system (e.g., MPEG-7). The scenario considers the requirement for global libraries to provide the objects to be inserted into the streams. The paper then considers the commercial trading of objects between the libraries, video service providers, advertising agencies and other parties involved in the service. Consequently a brokerage of video objects is proposed based on negotiation and trading using intelligent agents representing the various parties. The proposed Media Brokerage Platform is a multi-agent system structured in two layers. In the top layer, there is a collection of coarse grain agents representing the real world players – the providers and deliverers of media contents and the market regulator profiler – and, in the bottom layer, there is a set of finer grain agents constituting the marketplace – the delegate agents and the market agent. For knowledge representation (domain, strategic and negotiation protocols) we propose a Semantic Web approach based on ontologies. The media components contents should be represented in MPEG-7 and the metadata describing the objects to be traded should follow a specific ontology. The top layer content providers and deliverers are modelled by intelligent autonomous agents that express their will to transact – buy or sell – media components by registering at a service registry. The market regulator profiler creates, according to the selected profile, a market agent, which, in turn, checks the service registry for potential trading partners for a given component and invites them for the marketplace. The subsequent negotiation and actual transaction is performed by delegate agents in accordance with their profiles and the predefined rules of the market.

Personalised Advertising Supported by Agents

This paper reports the development of a B2B platform for the personalization of the publicity transmitted during the program intervals. The platform as a whole must ensure that the intervals are filled with ads compatible with the profile, context and expressed interests of the viewers. The platform acts as an electronic marketplace for advertising agencies (content producer companies) and multimedia content providers (content distribution companies). The companies, once registered at the platform, are represented by agents who negotiate automatically the price of the interval timeslots according to the specified price range and adaptation behaviour. The candidate ads for a given viewer interval are selected through a matching mechanism between ad, viewer and the current context (program being watched) profiles. The overall architecture of the platform consists of a multiagent system organized into three layers consisting of: (i) interface agents that interact with companies; (ii) enterprise agents that model the companies, and (iii) delegate agents that negotiate a specific ad or interval. The negotiation follows a variant of the Iterated Contract Net Interaction Protocol (ICNIP) and is based on the price/s offered by the advertising agencies to occupy the viewer’s interval.