{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/40081"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/40081","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"An interval mathematics approach to economic evaluation of power distribution systems","abstract":"Electric utilities are constantly seeking ways to reduce costs, and one way is to defer the construction of major new facilities. Such a deferal can be instituted by automating the power distribution system in an effort to make the system operate more efficiently and effectively. Increased efficiency on the distribution level improves the use of existing facilities on the distribution, transmission, and generation levels. The stumbling block for justifying distribution automation is often at the economic evaluation stage. This is due to the difficulty of incorporating the effects of technologies which have not been implemented in the past. In this research, a new method of economic analysis of utility distribution systems is proposed. The method will utilize interval analysis to determine the effects of uncertainty in data in utility revenue requirement studies. One of the frequently encountered problems in applying interval analysis is the resulting overly large bounds which in turn reduce the usefulness of results. Therefore, a method of obtaining sharp bounds is presented. The economic calculations will incorporate results from reliability analysis as well as reconfiguration studies. Thus, an explicit consideration of engineering design aspects is included. In addition, a cost/effectiveness analysis of distribution automation is presented in terms of several proposed economic indices associated with system cost, reliability, efficiency, and peak. A method of incorporating value of service considerations into revenue requirement studies is also presented. The capability to analyze automation expansion plans as well as conventional expansion plans will be discussed. Accordingly, utility distribution planning can be more precise with regard to potential economic benefits.","abstract_html":"Electric utilities are constantly seeking ways to reduce costs, and one way is to defer the construction of major new facilities. Such a deferal can be instituted by automating the power distribution system in an effort to make the system operate more efficiently and effectively. Increased efficiency on the distribution level improves the use of existing facilities on the distribution, transmission, and generation levels. The stumbling block for justifying distribution automation is often at the economic evaluation stage. This is due to the difficulty of incorporating the effects of technologies which have not been implemented in the past. In this research, a new method of economic analysis of utility distribution systems is proposed. The method will utilize interval analysis to determine the effects of uncertainty in data in utility revenue requirement studies. One of the frequently encountered problems in applying interval analysis is the resulting overly large bounds which in turn reduce the usefulness of results. Therefore, a method of obtaining sharp bounds is presented. The economic calculations will incorporate results from reliability analysis as well as reconfiguration studies. Thus, an explicit consideration of engineering design aspects is included. In addition, a cost/effectiveness analysis of distribution automation is presented in terms of several proposed economic indices associated with system cost, reliability, efficiency, and peak. A method of incorporating value of service considerations into revenue requirement studies is also presented. The capability to analyze automation expansion plans as well as conventional expansion plans will be discussed. Accordingly, utility distribution planning can be more precise with regard to potential economic benefits.","abstract_has_math":false,"creators":["Shaalan, Hesham Ezzat"],"institution":"Virginia Tech","degree_name":"Ph. 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