Adaptive Learning in Games: Defining Profiles of Competitor Players

Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

MASCEM Restructuring: Ontologies For Scenarios Generation in Power Systems Simulators

The electricity market restructuring, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in an rising complexity in power systems operation. Various power system simulators have been introduced in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex environment. This paper focuses on the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The restructuring of MASCEM (Multi-Agent System for Competitive Electricity Markets), and this system’s integration with MASGriP (Multi-Agent Smart Grid Platform), and ALBidS (Adaptive Learning Strategic Bidding System) provide the means for the exemplification of the usefulness of this ontology. A practical example is presented, showing how common simulation scenarios for different simulators, directed to very distinct environments, can be created departing from the proposed ontology.

Smart Grid Communication Technologies in the Brazilian Electrical Sector

Intelligent electrical grids can be considered as the next generation of electrical energy transportation. The enormous potential leads to worldwide focus of research on the technology of smart grids. This paper aims to present a review of the Brazilian electricity sector in context with the integration of communication technologies for smart grids. The work gives an overview of the generation, transmission and distribution of electrical energy in the Brazil and a brief summary of the current electricity market. Smart grid technologies are introduced and the requirements for the Brazilian power system are pointed out. Various technologies for communication within an intelligent network are presented and their characteristics, advantages and disadvantages are compared to the Brazilian conditions. In addition, a summary is given of current pilot projects for Smart Grid technologies within Brazil, as well as a presentation of individual selected projects.

Multiagent System Architecture for Short-term Operation of Integrated Microgrids

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

Inserção de todos os consumidores no mercado liberalizado de energia elétrica: oportunidades e desafios

O processo de liberalização do setor elétrico em Portugal Continental seguiu uma metodologia idêntica à da maior parte dos países europeus, tendo a abertura de mercado sido efetuada de forma progressiva. Assim, no âmbito do acompanhamento do setor elétrico nacional, reveste-se de particular interesse caracterizar a evolução mais recente do mercado liberalizado, nomeadamente em relação ao preço da energia elétrica. A previsão do preço da energia elétrica é uma questão muito importante para todos os participantes do mercado de energia elétrica. Como se trata de um assunto de grande importância, a previsão do preço da energia elétrica tem sido alvo de diversos estudos e diversas metodologias têm sido propostas. Esta questão é abordada na presente dissertação recorrendo a técnicas de previsão, nomeadamente a métodos baseados no histórico da variável em estudo. As previsões são, segundo alguns especialistas, um dos inputs essenciais que os gestores desenvolvem para ajudar no processo de decisão. Virtualmente cada decisão relevante ao nível das operações depende de uma previsão. Para a realização do modelo de previsão de preço da energia elétrica foram utilizados os modelos Autorregressivos Integrados de Médias Móveis, Autoregressive / Integrated / Moving Average (ARIMA), que geram previsões através da informação contida na própria série temporal. Como se pretende avaliar a estrutura do preço da energia elétrica do mercado de energia, é importante identificar, deste conjunto de variáveis, quais as que estão mais relacionados com o preço. Neste sentido, é realizada em paralelo uma análise exploratória, através da correlação entre o preço da energia elétrica e outras variáveis de estudo, utilizando para esse efeito o coeficiente de correlação de Pearson. O coeficiente de correlação de Pearson é uma medida do grau e da direção de relação linear entre duas variáveis quantitativas. O modelo desenvolvido foi aplicado tendo por base o histórico de preço da eletricidade desde o inicio do mercado liberalizado e de modo a obter as previsões diária, mensal e anual do preço da eletricidade. A metodologia desenvolvida demonstrou ser eficiente na obtenção das soluções e ser suficientemente rápida para prever o valor do preço da energia elétrica em poucos segundos, servindo de apoio à decisão em ambiente de mercado.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

A negociação no mercado a prazo do MIBEL

This master thesis has been developed during the internship in the Supervision Department of Supervision of the Intermediation and Market Structures of CMVM. My collaboration in such department was mainly focused on the derivatives market of the Iberian Electricity Market (MIBEL). MIBEL embodies two organized markets – the derivatives market in Portugal and the spot market in Spain The trading activity in the derivatives market of MIBEL is processed through the trading platform of the regulated market managed by OMIP, however, much of the negotiation is over-the-counter. The aim of this work is to describe the market from a legal and economic perspective and to analyse the evolution of the negotiation, namely the impact of OTC in the regulated market trading. To achieve this, I propose to analyse also MiFID and EMIR rules over derivative contracts and the role of central counterparties, as they both are important to the discussion. In parallel, we found that OTC transactions are considerably higher than those traded in the regulated market managed by OMIP, those findings can be justified by the contractual relationships based on trust already established between the partiesarties. Nevertheless, since 2011 this trend changed by an increase of the registered OTC. Thereafter, although the parties continued to trade bilaterally, these transactions were registered in a central counterparty in order to eliminate the inherent risks related to the OTC derivatives transactions. This change in the negotiation pattern may also be influenced by the mandatory reporting of transactions imposed by EMIR, that requires for some classes of derivatives the centralized clearing and for all other requires the implementation of risk mitigation techniques.

Vehicle-to-anything application (v2anything app) for electric vehicles

This paper presents a mobile information system denominated as Vehicle-to-Anything Application (V2Anything App), and explains its conceptual aspects. This application is aimed at giving relevant information to Full Electric Vehicle (FEV) drivers, by supporting the integration of several sources of data in a mobile application, thus contributing to the deployment of the electric mobility process. The V2Anything App provides recommendations to the drivers about the FEV range autonomy, location of battery charging stations, information of the electricity market, and also a route planner taking into account public transportations and car or bike sharing systems. The main contributions of this application are related with the creation of an Information and Communication Technology (ICT) platform, recommender systems, data integration systems, driver profile, and personalized range prediction. Thus, it is possible to deliver relevant information to the FEV drivers related with the electric mobility process, electricity market, public transportation, and the FEV performance.

The importance and accuracy of wind power forecasts

Due to the global crisis o f climate change many countries throughout the world are installing the renewable energy o f wind power into their electricity system. Wind energy causes complications when it is being integrated into the electricity system due its intermittent nature. Additionally winds intennittency can result in penalties being enforced due to the deregulation in the electricity market. Wind power forecasting can play a pivotal role to ease the integration o f wind energy. Wind power forecasts at 24 and 48 hours ahead of time are deemed the most crucial for determining an appropriate balance on the power system. In the electricity market wind power forecasts can also assist market participants in terms o f applying a suitable bidding strategy, unit commitment or have an impact on the value o f the spot price. For these reasons this study investigates the importance o f wind power forecasts for such players as the Transmission System Operators (TSOs) and Independent Power Producers (IPPs). Investigation in this study is also conducted into the impacts that wind power forecasts can have on the electricity market in relation to bidding strategies, spot price and unit commitment by examining various case studies. The results o f these case studies portray a clear and insightful indication o f the significance o f availing from the information available from wind power forecasts. The accuracy o f a particular wind power forecast is also explored. Data from a wind power forecast is examined in the circumstances o f both 24 and 48 hour forecasts. The accuracy o f the wind power forecasts are displayed through a variety o f statistical approaches. The results o f the investigation can assist market participants taking part in the electricity pool and also provides a platform that can be applied to any forecast when attempting to define its accuracy. This study contributes significantly to the knowledge in the area o f wind power forecasts by explaining the importance o f wind power forecasting within the energy sector. It innovativeness and uniqueness lies in determining the accuracy o f a particular wind power forecast that was previously unknown.

Returns to Foreign Language Skills in a Developing Country: The Case of Turkey

Foreign language skills represent a form of human capital that can be rewarded in the labor market. Drawing on data from the Adult Education Survey of 2007, this is the first study estimating returns to foreign language skills in Turkey. We contribute to the literature on the economic value of language knowledge, with a special focus on a country characterized by fast economic and social development. Although English is the most widely spoken foreign language in Turkey, we initially consider the economic value of different foreign languages among the employed males aged 25 to 65. We find positive and significant returns to proficiency in English and Russian, which increase with the level of competence. Knowledge of French and German also appears to be positively rewarded in the Turkish labor market, although their economic value seems mostly linked to an increased likelihood to hold specific occupations rather than increased earnings within occupations. Focusing on English, we also explore the heterogeneity in returns to different levels of proficiency by frequency of English use at work, birth-cohort, education, occupation and rural/urban location. The results are also robust to the endogenous specification of English language skills.

Putting the Special Case in Its Place: Switzerland and Small-N Comparison in Policy Research

This research note presents a set of strategies to conduct small-N comparisons in policy research including the Swiss case. Even though every country can be considered "special" to some extent, the Swiss political system is often viewed as a particularly difficult case for comparison because of the impact of its idiosyncratic institutional features (most notably direct democracy). In order to deal with this problem, our note sets out two possible strategies - the use of functional equivalents and of counterfactual reasoning - and explains how to implement them empirically through process tracing and the establishment of causal chains. As an illustration, these strategies are used for a comparison of the process of electricity market liberalisation in Switzerland and Belgium.

Convergence withEU environmental legislation in Russia and Kyoto Protocol effects on certain power plants in Russia

Venäjällä uudistetaan sähkömarkkinoita. Uudistamisella pyritään vapauttamaan sähkömarkkinat ja lisäämään kilpailua energiasektorilla. Sähkömarkkinoiden vapauttamisen tarkoitus on energiasektorin hyötysuhteen nostaminen ja investointien houkutteleminen sektorille. Venäjä on ratifioinut Kioton protokollan, mikä energiasektorin kannalta on tärkeää, koska protokollan yhteistoteutusmekanismin kautta saadaan houkuteltua investointeja sektorille. Venäjän sähkömarkkinoiden vapauttamisen pitkäaikainen tähtäin on Venäjän ja Euroopan sähkömarkkinoiden integroituminen, joka tarkoittaa myös ympäristölainsäädännönyhtenäistämistä. Tämä tutkimus on osa Fortum Oyj:n tarjoamaa teknistä katselmusta Venäjällä toimivalle sähköyhtiölle, TGC-9:lle. Tässä työssä keskitytään TGC-9:n omistamien energiatuotantolaitoksien happamoitumista aiheuttaviin ilmapäästöihin ja pölypäästöihin. Tutkimuksessa pyritään myös löytämään Kioton protokollan yhteistoteutusmekanismi hyödyntämiskohteita. NOx -päästöt tulevat olemaan suurin haaste TGC-9:lle, jos ympäristöstandardit yhdenmukaistetaan. Yhteistoteutusmekanismin hyödyntämiskohteita löydettiin neljä: koksaamokaasun hyödyntäminen, maakaasun korvaaminen kuoren poltolla ja kaksi tapausta liittyen laitoksien hyötysuhteen nostamiseen.

Sähkökaupan riskit ja riskienhallinta

Diplomityön tavoitteena on luoda kokonaisvaltainen kuva sähkökaupassa esiintyvistä riskeistä ja niiden analysointi- sekä hallintamenetelmistä. Toinen päätavoitteista on lisätä ymmärrystä markkinoiden erikoispiirteistä, kuten siirtokapasiteettirajoituksista, kysynnän hintajouston puutteesta ja markkinoiden keskittyneisyydestä, sekä arvioida niiden merkitystä sähkökaupan riskienhallinnan näkökulmasta. Markkinoiden erikoispiirteet ja sähkön tuotantoon ja kulutukseen vaikuttavat fundamentaaliset tekijät aiheuttavat suuria muutoksia pörssisähkön hintatasossa. Sähkön volatiliteetti yhdessä useiden muiden riskitekijöiden kanssa aiheuttaa sähkökaupantoimijoille todellisen tarpeen riskienhallinnalle. Sähkökauppa tarjoaa haasteellisen toimintaympäristön riskienhallinnan näkökulmasta. Sähkökaupassa esiintyvien riskien täydellinen hallitseminen on miltei mahdoton tehtävä, mutta sähkökaupan toimintaympäristön tunteminen ja järjestelmällisesti toteutettu riskienhallinta luovat hyvät edellytykset menestyksekkäälle toiminnalle sähkökaupassa. Diplomityössä käsitellään sähkökaupassa esiintyviä riskejä ja niidensyntyyn vaikuttavia tekijöitä. Näiden asioiden ymmärtäminen luo pohjan sähkökaupan onnistuneelle riskienhallinnalle. Työssä käydään myös läpi yleisimmät sähkökaupassa käytetyt riskianalyysin menetelmät. Diplomityössä esitellään sähköpörssin tarjoamat johdannaistuotteet ja havainnollistetaan niiden käyttöä osana sähkökaupan riskienhallintaa. Työn lopussa käsitellään profiiliriskin muodostumista jasen vaikutuksia sähkön hankintakustannuksiin.

Investment Determinants and Future Shape of Russia's Power Generation

The reformation of power sector is still in the process of development. The present day situation in Russian electricity power market ischaracterized as transitional period: competitive electricity market is forming, new companies are being created and the power of government regulation is decreasing. The main aim of the reformation is to attract much-needed private investments to the power sector. The electricity consumption increases very rapidly and power sector has to cope with high demand. The goal of this master's thesis is to analyze the nowadays situation in Russian power sector, such as generation structure, condition of electricity networks, electricity price formation for end-users, shape of fuel sector and investments risks and attraction.The final result of this work is creation of scenario of Russian power sector future shape and analysis of the present day situation.

Short-term Hydropower Planning System

The Thesis gives a decision support framework that has significant impact on the economic performance and viability of a hydropower company. The studyaddresses the short-term hydropower planning problem in the Nordic deregulated electricity market. The basics of the Nordic electricity market, trading mechanisms, hydropower system characteristics and production planning are presented in the Thesis. The related modelling theory and optimization methods are covered aswell. The Thesis provides a mixed integer linear programming model applied in asuccessive linearization method for optimal bidding and scheduling decisions inthe hydropower system operation within short-term horizon. A scenario based deterministic approach is exploited for modelling uncertainty in market price and inflow. The Thesis proposes a calibration framework to examine the physical accuracy and economic optimality of the decisions suggested by the model. A calibration example is provided with data from a real hydropower system using a commercial modelling application with the mixed integer linear programming solver CPLEX.