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Power systems are subject to a great variety of uncertainties. Restructuring and competition in electricity systems are definitely contingent on the available means to overcome the difficulties brought by these uncertainties. In the case of electricity trade, holding a competitive framework constitutes a task tougher than for other commodities due to the particularities of the electricity transactions. As a key example, the transmission of electrical energy is such that the production and consumption at a given bus of the system do affect the entire system. Therefore, the actions to be carried out in order to accommodate these uncertainties without compromising the consistency of the tradecall for a global management able to involve, if required, the participation of every agent in the system. [ABSTRACT FROM AUTHOR]

Electricity markets generally comprise a great variety of mechanisms allowing market agents to carry out energy transactions in accordance with their market strategy. For instance, in futures markets, agents can engage in longterm energy transactions seeking to reduce the risk level on profit/utility variability by hedging against the financial losses derived from pool price uncertainty. [ABSTRACT FROM AUTHOR]

We study in this chapter the electricity procurement problem faced by a large consumer. Such a consumer refers to an entity with a significant electricity consumption that participates in the electricity market, and has the capability of signing bilateral contracts with suppliers. Petrochemical industries, aluminum production complexes, or vehicle-assembling facilities are examples of large consumers. Supply sources available for the consumer include forward contracts, bilateral contracts, the pool, and self-production. [ABSTRACT FROM AUTHOR]

In this chapter we discuss the problem faced by a retailer of electrical energy in a medium-term horizon. A retailer (also called marketer) can be seen as an intermediary between producers and consumers (or retailers) that supplies energy to those consumers (or other retailers) not participating in the electricity markets. In general, retailers are not supposed to own generating units or to consume electricity. [ABSTRACT FROM AUTHOR]

This chapter considers the problem of an electric energy producer that sells its production of energy in both the futures market and the pool. The futures market allows the producer to sell its energy production at fixed prices through forward contracts, which span a pre-specified time period, e.g., one month. On the other hand, the pool allows the power producer to sell energy on a short-term basis taking advantage of periods of high price, but at the cost of suffering high price volatility. [ABSTRACT FROM AUTHOR]

The amount of wind generation is rapidly increasing in many electric energy systems across the world. The large-scale electricity production based on the exploitation of wind energy resources is currently feasible and is gradually becoming a profitable business attracting the attention of investors. Two main driving forces are responsible for the growing relevance of wind generation: the increasing trend of fossil fuel prices (natural gas, oil, and coal) as less and less reserves are available, and the need to curb carbon emissions to preserve a functioning atmosphere. [ABSTRACT FROM AUTHOR]

In this chapter we discuss the problem faced by a producer participating in a pool. This pool is assumed to be comprised of three markets that are sequentially cleared, namely, day-ahead, regulation, and adjustment markets. We consider that the producer owns a set of thermal units. [ABSTRACT FROM AUTHOR]

In Chapter 2 we study the basic formulation of decision-making problems using stochastic programming. In these problems we consider that the objective of the decision-making agents is either maximizing profit (e.g., the financial profit of an electricity producer) or minimizing cost (e.g., the electricity procurement cost of an industrial consumer). In stochastic programming, where uncertain data are modeled as stochastic processes, the profit or cost is a random variable that can be characterized by a probability distribution. In an optimization problem involving a random objective function it is necessary to optimize a function characterizing the distribution of this random variable, for instance, its expected value. This is the criterion that is generally used in stochastic programming problems. Therefore, the problem consisting in maximizing ˵the profit″ obtained by a decision-making agent results in maximizing the expected profit achieved by this agent. [ABSTRACT FROM AUTHOR]

Many engineering and science problems are subject to uncertainty due to the inherent randomness of natural phenomena and/or to the imperfect knowledge of the variables determining the functional state of the human-created structures. In this context, computational methods that tackle uncertainty allow engineers and scientists to propose solutions less sensitive to environmental influences, while achieving simultaneously cost reduction, profit gains, and/or reliability improvement. [ABSTRACT FROM AUTHOR]

Unknown data abound in decision-making problems in the real world. This lack of perfect information is common in problems belonging to different knowledge areas such as engineering, economics, finances, etc. [ABSTRACT FROM AUTHOR]

This chapter provides an overview of the organization and agents of a typical fully-fledged electricity market, and outlines the decision-making problems faced by these agents. The time framework and the uncertainty of these decision-making processes are also discussed. [ABSTRACT FROM AUTHOR]