Pricing Transmission Congestion

Transmission of electric power is the ability to move large volumes of energy from where it is generated to where is needed. Even though the quantity of power traded in the wholesale market in the United States went from almost nothing in 1994 to over 800 terrawatthours in 2000, there has been relatively little money put into the transmission system. Consequently, the transmission infrastructure is aged, resulting in "congested lines" such as increased instances of constrained systems, reduced import capability, heavily loaded lines, and stability problems. Therefore, any effort to reduce transmission congestion may provide substantial benefits in customer choice and economic efficiency in power operation. A popular type of congestion-management pricing is known as locational marginal pricing (LMP). Although LMP should be an effective long-term strategy, there has not been a concerted effort to use LMP to alleviate stability concerns. The intellectual merit of this project lies in extending the LMP concept to include stability-limited regions of bulk power systems. The proposed work focuses on defining the stability constraints based on the underlying physics of power systems, the inclusion of these constraints into suitable optimization models, and the evaluation of the economic implications produced by such optimizations.

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Modeling Market Price of Electricity

The purpose of this research project is to determine suitable approaches for finding the statistical distributions of real-time electricity prices in a deregulated market. It use a bottoms-up systems based approach in which the market is represented via a production-costing model. The components of this model are the capacity, reliability, and cost characteristics of the generators that comprise the market, fuel prices, demand, and the meteorological influences that affect it. As a first approximation, the price at every hour is equated to the marginal cost of the last generating unit used to supply each hour’s demand. The initial effort concentrates on finding the statistical distribution of the marginal unit at each hour via the production-costing model from the available information on the supply and demand sides of the market. Empirical data suggest, however, that when the supply approaches demand and under an oligopoly market, the spot price exceeds the marginal cost of production. This phenomenon is investigated using different economic models under a stochastic framework based on a production-costing representation of the market. Attempts at modeling the entire statistical distributions require that the stochastic processes associated with the generator outages and chronological load are accounted for. The project develops approximate analytical procedures that are applicable to large systems and evaluates the accuracy of these approximations using Monte Carlo simulation. The computations are validated by comparing the results predicted by these models with historical data.

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Decision Making under Uncertainty

Most engineering economic decisions involve parameters whose values are uncertain because they require information that will be known only in the future. For example, decisions on the capacity expansion of a manufacturing facility depend among other factors on future demands and prices. Although the exact future demands may be unknown, their values may be known to follow a certain probability distribution function. One of the best ways to gain a real understanding of the concepts involved in decision-making under risk is by direct experimentation, i.e., making decisions and observing the result. In this website you can find   a virtual laboratory where you can get hands-on experience in dealing with risk.   You will gain cognitive skills by interacting with a simulated environment, which will help you to understand the fundamental concepts of decision-making under uncertainty. The virtual lab consists of a set of experiments in which you have an interactive participation in simulations of design situations. Currently, only one experiment (experiment 1) is available. Experiment 1 consists of a game that simulates the dynamics of a real life situation in which a textile manufacturing company needs to determine the level of production of a seasonal garment to be manufactured before the season starts. This problem is known in the operations research literature as the newsvendor problem and is a classic in operations research partly because its framework can be applied to many problems from different fields such as health care, financing and insurance purchasing.

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