With the deregulation of power industry and the market competition, reliable power supply and secured system operation are major concerns of the independent system operator (ISO) or decision-maker (DM). Power dispatch under deregulated environment is complicated with various possibilities of decisions involved. Without the assistance of Energy Management System (EMS), it is not easy for ISO or DM to operate with pure experiences. To enhance the operational efficiency, EMS involves the state-of-the-art control technology, and the fast and effective computer assisted decision support system will help dispatch the power. A conventional EMS has a few major tasks, among them, the ¡§network analysis¡¨ task and the ¡§forecast and scheduling¡¨ task are the most important in assisting the on-line power dispatch. In dealing with the new deregulated environment, an ¡§operational planning¡¨ has to be added to aid the EMS for more security. There are significant changes on EMS after deregulation. This dissertation will focus on the changes and new functions, in the ¡§network analysis¡¨ and the ¡§forecast and scheduling¡¨ tasks of an EMS, which supports the operation in the competitive environment. In the ¡§network analysis¡¨ task, we discuss the real and reactive power dispatch and congestion management with AC optimal power flow (OPF). In this task, the formulation of AC OPF with deregulation issues and the effect of flexible AC transmission systems (FACTS) devices are presented. A predictor-corrector interior-point nonlinear-programming (PCIPNLP) algorithm has been developed to solve the problem. The model involves only slight modification to the present OPF for social welfare maximization to obtain the optimized bid-based dispatch and nodal spot prices. The incorporation of FACTS devices for system operations can ease the difficulties caused by transmission congestion. It is found that PCIPNLP technique is very effective for the modified OPF solution for congestion relief under deregulation. In the ¡§forecast and scheduling¡¨ task, we discuss the resource scheduling for bid-based dynamic economic dispatch and spot dispatch for power and reserve. They can be formulated for social welfare maximizing problem that is solved by using an efficient interior point method. And the optimal resource allocation and nodal spot price can be given from the various test results. We have also proposed a fuzzy based strategic gaming method to determine the GenCo¡¦s bidding strategy. Based on fuzzy set theory, a multi-criteria decision-making method is used to obtain the optimal strategy combination, bids and expected payoffs. Decision maker can find the optimal strategy combination by using weight vector to represent his subjective attitude about the structure of multi-objectives. The advantages have also been demonstrated through the numerical examples. Compared with the classical (¡§nonfuzzy¡¨) game theory, the proposed approach could help the decision maker to obtain higher expected payoffs, and make his choices easily. Possible applications of the proposed fuzzy method can be suggested for other decision-making problems in the power systems

The growing need of grid stability derived from the current energy transition is favouring the expansion of the ancillary services markets. Thanks to their fast response, this situation can be exploited by different kinds of batteries, even by those that were initially designed for a different application. However, each regulation product presents different market rules that are also country dependent. For this reason, it is important to ensure that the batteries in question count on the right characteristics. This project is focused on an energy storage system conceived for a number of applications not including ancillary services. With the aim of determining if that battery could find a new revenue stream in balancing markets, a study of the most relevant frequency markets has been conducted. After identifying those in which the battery could take part according to its technical features, a mathematical model has been developed. The model provides the optimal bidding strategy for the day ahead auctions of the selected markets and the most convenient operational planning for the day of delivery. Thanks to the model, the battery has been proved to be able to make profits from participating in the Swedish Frequency Containment Reserve (FCR) markets while it is not being occupied in its main intended applications. Furthermore, it will be possible to increase those profits by competing in the Swedish Fast Frequency Reserve (FFR) market, once the daily auctions are implemented. / Balanstjänster är en växande marknad i de utvecklade länderna på grund av det växande behovet av nätstabilitet orsakat av den nuvarande energiomställningen. Denna situation kan utnyttjas av olika batterier även de som från början var designade för en annan applikation. Dess natur tillåter en snabb respons som är väsentlig i vissa av de reglerande produkterna och inte lätt att hitta i andra teknologier. Varje regleringsprodukt har dock olika marknadsregler som också är landsberoende. Av denna anledning är det viktigt att säkerställa att batterierna i fråga har rätt egenskaper. Detta projekt är fokuserat på ett energilagringssystem som utvecklats för ett antal applikationer som inte inkluderar balansjänster. I syfte att ta reda på om batteriet kan hitta en ny intäktsström på balansmarknaden har en studie av de mest relevanta frekvensmarknaderna genomförts. Efter att ha identifierat de som batteriet kan delta i enligt dess tekniska egenskaper, har en matematisk modell utvecklats. Modellen ger den optimala budgivningsstrategin för auktionerna för dagen före på de utvalda marknaderna och den mest bekväma operativa planeringen för leveransdagen. Tack vare modellen har batteriet visat sig kunna tjäna pengar på att delta på de svenska FCR-marknaderna medan den inte är sysselsatt med sina huvudsakliga avsedda tillämpningar. Dessutom kommer det att kunna öka dessa vinster i framtiden genom att delta på den svenska FFR-marknaden när de dagen-före auktionerna är genomförda.

Comparison of double auction bidding strategies for automated trading agents Bc. Daniel Vach Absctract In this work, ZIP, GDX, and AA automated bidding strategies are compared in symmetric agent-agent experiments with a variable composition of agent population. ZIPOJA, a novel strategy based on ZIP with Oja's rule extension for updating its optimal price, is introduced. Then it is showed that ZIPOJA underperforms in competition against other strategies and that it underperforms even against the original ZIP. Dominance of AA over GDX and ZIP is questioned and it is showed that it is not robust to composition changes of agent population and that the experimental setup strongly affects the results. GDX is a dominant strategy over AA in many experiments in this work in contrast to the previous literature. Some mixed strategy Nash equilibria are found and their basins of attraction are shown by dynamic analysis.

Made available in DSpace on 2016-08-17T14:53:21Z (GMT). No. of bitstreams: 1 Sergio Augusto.pdf: 2350058 bytes, checksum: 7c3c67925b0b27a77105c3cb0799c4e6 (MD5) Previous issue date: 2012-05-04 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / This work provides a framework to obtain the optimal bidding strategy for a GENCO in long-term electricity auction. The tool is based on intelligent techniques for optimizing the proposed Utility Function. The goal is to find the optimal strategy that maximizes the expected payoff of GENCO and simultaneously minimize the risks. The risks are modeled by two classical metrics: the Variance (Portfolio Theory) and Value at Risk (VaR). The proposed methodology is applied to auctions for long-term forward contracts, such that used in the Brazilian power system for buying and selling energy in the regulated market. The Bidding Strategy is formed through a Supply Curve which relates the optimal amount of energy to different offer prices. Thus, it allows the GENCO define the best bid (offer) for a given offer price. The proposed approach is validated for three test cases: First, concerning the variation of generation and price of energy scenarios for evaluation of the bidding strategy and the GENCOS risk perception; The second, consider a cascade hydro-term system for evaluation of MRE; and The third, considers the northeastern Brazilian subsystem where the supply curve is formed for the CHESF company's power plants portfolio. The results show how the offer may be changed according the variation of the spot prices and physical generation and demonstrate the efficacy of meta-heuristics proposed to optimize the supply model. / Este trabalho apresenta uma ferramenta de auxílio e suporte à tomada de decisões na formação de estratégias de oferta para agentes geradores (GENCOS) participantes de leilões de eletricidade de longo-prazo. A ferramenta é baseada em técnicas inteligentes para a otimização da Função de Utilidade proposta média-risco . O objetivo é encontrar a Estratégia Ótima que maximize o retorno esperado da GENCO e, simultaneamente, minimize os riscos relacionados às incertezas no montante de energia produzida e no preço spot, modelados por duas métricas clássicas de risco: a Variância (teoria dos portfólios) e o Valor em Risco (VaR). A abordagem proposta é aplicada ao mercado brasileiro de eletricidade, especificamente, ao ambiente de Leilões de Energia Existente na categoria Quantidade de Energia, tais quais os leilões aplicados pelo órgão regulador brasileiro para compra e venda de energia no mercado regulado. Sugere-se aqui a formação de uma Curva de Oferta que relacione a quantidade de energia ótima para diferentes preços de oferta. E, deste modo, permita a GENCO definir qual o melhor lance (oferta) para dado preço de oferta durante o processo do leilão. Para a avaliação da abordagem foram utilizados três casos testes: O primeiro considera cenários de geração física e preço de energia a fim de avaliar a estratégia de oferta e a percepção ao risco de contratação da GENCO quanto à variação de tais cenários; o segundo, considera um sistema em cascata onde é possível observar o efeito do Mecanismo de Realocação de Energia (MRE) sobre a oferta das GENCOS; e o terceiro considera o subsistema nordeste brasileiro onde a curva de oferta é formada para o portfólio de usinas pertencentes à empresa CHESF. Os resultados demonstram como a oferta de energia pode ser alterada de acordo com cenários de oferta gerados e comprovam a eficiência da meta-heurística proposta para otimização do modelo de oferta.