Estimation of aggregate miles of EHV transmission line needs
Author(s)Markel, Lawrence Craig
Regression analysis is used to develop models for the total number of miles of EHV line needed in a power system. These models are not meant to be used to design a transmission system but to examine existing EHV systems to see if general patterns or relationships exist on a system- wide basis. The U.S. was divided into regions and data on regional load and generation characteristics was obtained for the years 1960, 1970, 1980, and 1990. Regressions were performed on this combination cross-sectional and time-series data to develop equations for circuit miles of EHV line and for gigawatt-miles (miles of line X power-carrying capability) of EHV line. t- and F-tests were used to determine the statistical significance of the model parameters. The independent variables (system characteristics) found to be most significant in determining the miles of EHV line include the generating capacity of the system, the area (square miles) of the region, the percent of area that is metropolitan, the number of generating plants in the system, the percent of energy used for industrial purposes, the percent of generating capacity which is hydro- electric, and the average distance between plants and load centers. -The equations developed are multiplicative, of the form miles of line = K7Xf i4' where the Xi's are system characteristics. "Expansion" models attempting to determine the additions to the existing grid in a 10 year period were also postulated. However, they are not as statistically significant as the "static" models. Methods of using the models to investigate new plant siting strategies, such as power parks or offshore nuclear plants, are discussed. Analysis of the effect of trends in plant siting and construction, such as the growing scarcity of potential plant sites near load centers, is also mentioned. The limitations, uses, and possible extensions of this type of model are also described.
Essentially constitutes a M.S. thesis in the Dept. of Electrical Engineering
MIT Energy Lab
Electric power distribution -- High tension, Regression analysis
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