Uncertainty and Investment in Electricity Generation: the Case of Hydro-Québec
World wide the electricity industry is undergoing a substantial process of restructuring, with an emphasis on the introduction of competition in the generation sector. Competition is ostensibly going to lead to better incentives, both in the use of existing resources and in future investment decisions. One of the main drivers of this new environment will be the increased opportunity for energy sales between what had been, before the introduction of competition, fairly closed markets. These new opportunities may lead to new investments in generation and transmission capacity which will occur in order to take advantage of cost differentials between regions, one of the driving factors in the call for restructuring. Accounting for some of the underlying complexity of electricity systems, specifically equipment availability and load duration curves, this paper illustrates how uncertainty affects investment in generation. We offer a simple 2-region model to analyse this problem, based on the linear programming model of Chaton (1997). Specifically, we analyse the case where one region has access to four generation technologies, differentiated by cost characteristics as well as construction lead times. A second (neighbouring) region has access to only one of the generation technologies, hence the necessary asymmetry between producing regions. Uncertainty is present in the demand for energy in the first market, as well as in the input fuel prices. Given this uncertainty, and the possibility of electricity sales between regions, we investigate and characterise optimal generation investment in the first market as a function of the problem parameters. The model is calibrated with data from Hydro-Québec and the northeastern United States. This application is particularly interesting and relevant, given the abundance of relatively cheap hydroelectric power in Québec, and Hydro-Québec’s self-proclaimed strategic interests in increasing its exports to the northeastern markets. The numerical example illustrates the importance of appropriately modelling the complexity of the electrical system when considering the impacts of restructuring.
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