Multifactor optimization of electrical power plants

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The recent trend toward electricity market deregulation that has occurred in jurisdictions around the world has led to a fundamental shift in the role of individual power producers. In this new paradigm, individual market participants must bear the sole financial risks of market price and cost uncertainties. In addition, innovations in financial energy contracts are rapidly becoming more popular as a means of managing risk. No longer can operational decisions be separated from financial market realities. Similarly however, the operational constraints of electrical generators do not disappear when markets are deregulated. The operational restrictions of electrical power plants often force companies to continuously make decisions that will have highly uncertain future financial consequences. One simple example would be a hydro plant with a limited reserve of water or a coal plant with a limited inventory of coal that must decide at what price to produce power given that whatever resources are consumed today will no longer be available in the future. Determining the size of this opportunity cost is complicated by the high degree of uncertainty in power prices as well as the number of different factors which may influence these prices. As coal inventory decisions in Ontario alone can involve hundreds of millions of dollars, this problem is far from trivial. Dozens of other operational constraints give rise to similar such decision making problems in the face of uncertainty. For individual participants to operate and manage risk efficiently, powerful computer models and mathematical solution algorithms are required. Currently however, most such financially based methods are limited in the number of variables they can consider. This proposal aims at developing a new set of mathematical algorithms that will enable industry practitioners to take into account more factors and variables than is currently computationally feasible, thereby leading to a more efficient use of the nation's scarce energy resources.