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This work presents a binary expansion (BE) solution approach to the problem of strategic bidding under uncertainty in short-term electricity markets. The BE scheme is used to transform the products of variables in the nonlinear bidding problem into a mixed integer linear programming formulation, which can be solved by commercially available computational systems. The BE scheme is applicable to pure price, pure quantity, or joint price/quantity bidding models. It is also possible to represents transmission networks, uncertainties (scenarios for price, quantity, plant availability, and load), financial instruments, capacity reinforcement decisions, and unit commitment. The application of the methodology is illustrated in case studies, with configurations derived from the 80-GW Brazilian system. [ABSTRACT FROM AUTHOR]

Presents information on a study regarding a Benders decomposition model to solve electric power transmission network expansion planning problems. Details on the mathematical model for the design problem; Application of Benders decomposition model; Information on Gomory cuts and Benders decomposition; Results and discussion.

This article aims to analyze agents' behavior in a competitive hydrothermal energy market. The idea is to investigate how much the day-to-day behavior of the market can be different from the predictions presented by cost-based models because of the risk perception of each agent (hydroelectric energy producer, in this case) as a participant of the market. The main contribution is in determining the impact on the agents' revenue in the short-term market due to the variation in the amount of energy generated and the market price, which other methodologies may not be able to capture. For this reason, a case study was made using daily simulations in a given month, observing the strategy and bids of eight hydroelectric agents for a central market operator emulated by an energy price offer simulator called SOPEE. The study reflected qualitative and quantitative examples of how the risk perception and the behavior of each agent can influence market behavior due to the variation in their perceptions of the parameters that form the energy price. [ABSTRACT FROM AUTHOR]

This work develops a stochastic optimization model for the creation of a bidding strategy for a generator in an energy call option auction similar to Brazil's, i.e., where the bidder can offer both the premium and the strike price. The objective of the model is to maximize the bidder's competitiveness while ensuring that the project's target rate of return is achieved with a given probability, for example 95%. The problem's complexity is compounded by uncertainties in fuel supply and the need to switch between fuels. The generators face the conundrum of bidding a single strike price to cover the expenses generated by using multiple types of fuels. We address the problem of finding bidding strategies which, taking into account uncertainty in fuel supply and risk constraints, set the combination of strike price and option premium that ensure a desired risk-adjusted return for greenfield dual-fuel thermal plants. [ABSTRACT FROM PUBLISHER]

Deals with a study which investigated the market power issues in bid-based hydrothermal scheduling. Modeling market power; Market power in hydrothermal systems; Mitigatory measures analysis.

The objective of this work is threefold. We firstly present an optimization model for a price-taker hydrothermal generation company (Genco) to devise bidding strategies in multi-item iterative auctions of long-term contracts. The bidding model calculates a bidder's best-response function, which takes into account the key issues on the auctioned contracts, such as its time horizon, the risk factors that affect the future contract outcomes, interdependence between auctioned products, and the agents' risk profile. The risk profile of the Gencos are represented as piecewise linear utility functions and a practical specification approach is proposed. We finally present a simulator of a uniform-pricing and iterative multi-item contract auction, where the set of auction rules is implemented and the optimization model developed is used to determine the Gencos's best responses at each auction round. The simulator enables auctioneers and generators to estimate the auction's competitive equilibrium price and to study the auction dynamics. A real multiproduct descending clock auction is simulated for the Brazilian power system under the proposed bidding scheme. [ABSTRACT FROM PUBLISHER]

Renewable sources have recently emerged as a generation option for many countries in order to promote clean energy development. In the case of Brazil, small hydro plants and cogeneration from sugarcane waste (bagasse) have been attractive alternatives during the past years, with hundreds of MW installed since 2004. Despite their advantages, both alternatives are hindered by seasonal yet complementary availability. This forces producers to discount (or price) the risks faced when selling firm energy contracts and may ultimately lead to projects being commercially unattractive. We propose a stochastic optimization model that defines the optimal composition of a portfolio based on these two renewable sources in order to maximize the revenue of an energy trading company. At the same time, this model mitigates hydrological and fuel unavailability risks, thus allowing the participation of both sources in the forward market environment in a competitive manner. A case study is presented, based on data from the Brazilian system. [ABSTRACT FROM AUTHOR]

The firm energy of generation plants is a critical component in some electricity markets. It is usually calculated by the regulator and sets a cap to the amount a plant can trade in capacity markets (or auctions), in order to avoid free-riding behaviors. Firm energy is a systemic property and, in case of hydro plants, a synergy is observed whenever a cooperative operation occurs, i.e., the firm energy of a system is greater than the sum of the individual plants. This immediately raises the question of how to divide the system's firm energy among the individual hydro plants. The objective of this work is to investigate the application of different allocation methods of firm energy rights among hydro plants using a game-theoretic framework. It is shown that there is not an optimal and unique approach to make this allocation. The paper investigates the advantages and disadvantages of different methods, such as marginal allocation, average production during the critical period, incremental allocation, finally recommending the Aumann-Shapley as the allocation method. This method is tested for the Brazilian power system, which has around 100 hydro plants. The results obtained are compared with the current allocation adopted by the electricity regulatory agency of Brazil. [ABSTRACT FROM AUTHOR]

This work presents a new methodology for the allocation of transmission service cost among network users in energy markets. The proposed method is based on an optimization/game-theoretic framework (Aumann-Shapley) that retains the desirable properties of other existing methodologies such as the Average Participations Factors (APF) and Long Run Marginal Costs (LRMC). The approach is shown to be computationally feasible and presents desirable characteristics in terms of economic coherence and isonomy. Computational results are presented for the Brazilian power system and compared with those obtained by three other methodologies: LRMC, APF, and the current method adopted in Brazil. [ABSTRACT FROM AUTHOR]