Leilão de direitos de transmissão financeiros de energia eléctrica em ambiente de mercado

Os direitos de transmissão (Transmission Rigths – TRs) correspondem, na sua essência, a contratos que conferem aos seus proprietários o direito de transmitir energia eléctrica, por um determinado caminho, a um preço fixo. Na actualidade vive-se uma era de liberalização dos mercados de energia eléctrica nos quais, no caso concreto dos mercados de TRs, os diversos agentes podem ceder os TRs que possuem a outros agentes desde que cumpram certos requisitos impostos pelo sistema na figura do seu operador de sistema (Independent System Operator – ISO). Neste sentido, o ISO oferece, aos diversos agentes do mercado, algumas ferramentas que lhes permite transaccionar, sob sua orientação, os seus respectivos TRs fazendo-se cumprir todos os requisitos indispensáveis para o efeito. A mais popular dessas ferramentas, nos principais mercados energético da actualidade, é o leilão. Com o presente trabalho de dissertação é pretendido apresentar-se um modelo para a resolução do problema inerente a um leilão de TRs em ambiente de mercado, neste caso concreto de direitos de transmissão financeiros de energia eléctrica (Financial Transmission Rigths – FTRs). Neste sentido foi desenvolvido um simulador informático (SIM_AuctFTR) que implementa um modelo para este tipo de problemas. Este trabalho foi estruturado essencialmente em três etapas com objectivos inerentes. Assim, numa primeira fase da realização deste trabalho, foi realizado um estudo de diversos conceitos e metodologias inerentes ao problema de leilão de FTRs em ambiente de mercado, suportado por uma sólida base bibliográfica. A segunda fase tratou-se do desenvolvimento do algoritmo da aplicação computacional que solucione um problema de um leilão de FTRs. O SIM_AuctFTR foi desenvolvido sobre o pressuposto da maximização dos rendimentos financeiros provenientes da atribuição dos FTRs propostos a leilão, tendo estes últimos de coabitar no sistema respeitando as restrições técnicas a que este são inerentes, mesmo na eventualidade da ocorrência de contingências de nível ‘n-1’. Por último, numa terceira fase, partindo da aplicação desenvolvida, foram realizados 4 casos de estudos com outras tantas redes eléctricas de forma a testar a robustez da ferramenta desenvolvida.Transmission Rights (TRs) essentially correspond to contracts that grant the owner the right to transmit electric energy on a given path according to a fixed price. Currently, one is witnessing an era of liberalization of electric energy markets on which, particularly TRs markets, several agents may pass the TRs they own to other agents as long as certain regulations imposed by the system, through the figure of its Independent System Operator (ISO), are fulfilled. In that sense, the ISO provides the various market agents with some tools that allow them to negotiate, under its supervisions, their TRs, while still ensuring that all indispensable requirements to this effect are met. The most popular of such tools in the current main energetic markets is the auction. With the present dissertation, one wants to present a model to solve the inherent problem of a TRs auction in a market environment; in this concrete case, financial transmission rights (FTRs) of electric energy. Bearing this in mind, one developed a computer simulation software (SIM_AuctFTR) that implements a model for such problems. This work was essentially structured into three stages, each with inherent objectives. Thus, on the first stage of this work, several concepts and methodologies were studied regarding the problem of auctioning FTRs in market environments, using a solid bibliographical basis as a support. The second stage of this work was occupied by the development of the algorithm of the computational application able to solve the problem of a FTRs auction. SIM_AuctFTR was developed according to the assumption that the financial income originated by the attribution of the FTRs being auctioned should be maximized. The FTRs should also be able to cohabit in the system and respect the inherent technical restrictions, even if level ‘n-1’ contingencies were to occur. Finally, on the third stage and having the application developed as a starting point, 4 case studies were performed in as many electric networks in order to test the robustness of the developed tool

Financial Engineering for Energy System Capital Budgeting

The United State energy industry is experiencing a major paradigm shift. This conventional vertically integrated energy industry is gradually transformed to a competitive market environment—a deregulated energy market. The market and regulatory frameworks are expected to continue to evolve in the future. Market participants are emphasizing more on profit maximization as returns on investment are no longer guaranteed. Therefore, risk management and capital budgeting play critical roles in energy system planning. Planning always involves uncertainties. When there are uncertainties, there are risks involve. This dissertation concentrates on the application of Real Options Analysis, ROA, especially lattice method, to energy system capital budgeting. Lattice method has one major weakness: massive bush of lattice. This dissertation proposes a method known as Binomial Lattice-Value at Risk approach to solve the curse of lattice dimensionality. Due to deregulation, market participants\u27 incentives have changed. Generation companies, GENCOs, are no longer willing to release their cost information or strategic plans. Thus, this dissertation introduces the implementation of Profit at Risk ideology into decision analysis, which created an efficient approach known as Binomial Lattice-Profit at Risk, BL-PaR. With the price of fuels soaring and environmental concerns growing larger, the expansion of ROA into renewable energy sector is desirable. Renewable energy has significant advantages as it does not contribute to greenhouse gases. This research focuses on wind energy, which is uncontrollable and unpredictable. A decision based solution of incorporating wind energy with pump storage hydro, PSH, and financial contract hedging is introduced. This energy technology integration is capable of increasing the available-capability of wind energy to be as effective as thermal unit. A physical asset hedging known as the Look Ahead Optimization, LAO, method is then applied to both wind unit and PSH system. This optimization method minimizes the size of hedging and maximizes profit by obtaining the optimal energy storage. The combination of the LAO method with BL-PaR approach achieves several critical goals. Together with the inclusion of financial contract hedging via financial transmission rights, FTRs, a double-protections mechanism is established. The evaluation of FTRs portfolio using ROA enables the risk management process to run efficiently

Risk Minimization in Power System Expansion and Power Pool Electricity Markets

Centralized power system planning covers time windows that range from ten to thirty years. Consequently, it is the longest and most uncertain part of power system economics. One of the challenges that power system planning faces is the inability to accurately predict random events; these random events introduce risk in the planning process. Another challenge stems from the fact that, despite having a centralized planning scheme, generation plans are set first and then transmission expansion plans are carried out. This thesis addresses these problems. A joint model for generation and transmission expansion for the vertically integrated industry is proposed. Randomness is considered in demand, equivalent availability factors of the generators, and transmission capacity factors of the transmission lines. The system expansion model is formulated as a two-stage stochastic program with fixed recourse and probabilistic constraints. The transmission network is included via a DC approximation. The mean variance Markowitz theory is used as a risk minimization technique in order to minimize the variance of the annualized estimated generating cost. This system expansion model is capable of considering the locations of new generation and transmission and also of choosing the right mixture of generating technologies. The global tendency is to move from regulated power systems to deregulated power systems. Power pool electricity markets, assuming that the independent system operator is concerned with the social cost minimization, face great uncertainties from supply and demand bids submitted by market participants. In power pool electricity markets, randomness in the cost and benefit functions through random demand and supply functions has never been considered before. This thesis considers as random all the coefficients of the quadratic cost and benefit functions and uses the mean variance Markowitz theory to minimize the social cost variance. The impacts that this risk minimization technique has on nodal prices and on the elasticities of the supply and demand curves are studied. All the mathematical models in this thesis are exemplified by the six-node network proposed by Garver in 1970, by the 21-node network proposed by the IEEE Reliability Test System Task Force in 1979, and by the IEEE 57- and 118-node systems